A Dissertation. entitled. Flexible and Redundant Supply Chain Practices to Build Strategic Supply Chain

Transcription

1 A Dissertation entitled Flexible and Redundant Supply Chain Practices to Build Strategic Supply Chain Resilience: Contingent and Resource-based Perspectives by Kihyun Park Submitted to the Graduate Faculty as partial fulfillment of the requirements for the Doctor of Philosophy Degree in Manufacturing and Technology Management Dr. Dale Dwyer, Committee Chair Dr. Paul Hong, Committee Member Dr. Hokey Min, Committee Member Dr. Gene Chang, Committee Member Dr. Sachin Modi, Committee Member Dr. Ratricia R. Komuniecki, Dean College of Graduate Studies The University of Toledo December 2011

2 Copyright 2011, Kihyun Park This document is copyrighted material. Under copyright law, no parts of this document may be reproduced without the expressed permission of the author.

3 An Abstract of Flexible and Redundant Supply Chain Practices to Build Strategic Supply Chain Resilience: Contingent and Resource-based Perspectives by Kihyun Park Submitted to the Graduate Faculty as partial fulfillment of the requirements for the Doctor of Philosophy Degree in Manufacturing and Technology Management The University of Toledo December 2011 Supply chain risk management (SCRM) has become an emerging research issue during recent years (Christopher & Peck, 2004; Sheffi, 2005; Tang, 2006). Defining supply chain risk and identifying its sources have been essential tasks in determining how to manage supply chain risk. As firms face uncertain demands and supplier failures, they should be able to manage supply chain risks adequately, not only in order to maintain normal levels of operation but also to gain sustainable competitive advantages in the current business environment. By examining existing theories and conducting an extensive literature review, the researcher has identified two research gaps. One gap consists of a lack of available research on firm-level practices that make supply chains resilient in responding appropriately to supply chain disruptions and factors that lead firms to adopt and implement these practices. A second gap is the lack of a comprehensive and integrated resilient supply chain framework and methods to measure its development. Having iii

4 identified research gaps, this study addresses three research questions: (1) What are the antecedents of resilient supply chain management practices? (2) What are the dimensions of resilient supply chain management practices, and how can each component be measured? (3) How do resilient supply chain management practices result in resilient supply chain capabilities? Drawing upon contingency theory (CT), this study identifies four types of risk and risk taking propensity as antecedents, or enablers, which result in firms implementing risk-related activities. A resource-based view (RBV) provides this study with the theoretical rationale to explain how firms resources and routines not only reduce the detrimental effects of supply chain disruptions but also formulate external-facing capabilities that lead to a competitive advantage. The large-scale survey data was collected from the U.S. and South Korea, and analyzed by Structural Equation Modeling using AMOS 6.0. Out of eight hypotheses, five are supported. The results of this study suggest that a higher perception of internal risk and firms willingness to take risk facilitate the implementation of flexible and redundant practices and formulate capabilities. Resilient supply chain capabilities enable firms to prepare to respond to supply chain disruptions and recover from them. Theoretical and managerial implications, limitations, and recommendation for future research are discussed. iv

5 Dedicated to God the Father, Jesus the Son, and the Holy Spirit

6 Acknowledgements It is my firm belief that God has guided and enabled this research thus far. He has not only given me needed wisdom and strength but sent me many people who served and endured me with much love, support and prayer in the right place at the right time. First of all, my special thanks go to my advisor, Dr. Dale Dwyer. He is my boss, mentor, and champion upon this research. Without his leading and contribution, I would not be able to get it done. I would like to give many thanks to my committee members, Drs. Paul Hong, Hokey Min, Gene Chang, and Sachin Modi. They have provided me with much insightful feedback and practical support. My appreciation also goes to the COBI faculties and other doctoral students including class of 2007, Mark Yang, David Dobrzykowski, Oanh Tran, and Abdullah Aldakhil. I thank them all. Second, I am very thankful for my dear friends and coworkers in Toledo and Hanyang UBF. Their love, friendship, and prayer supports have been and will be a source of my joy, encouragement, and strength. Given a page requirement, I will thank them personally. Third, I would like to express my deepest gratitude to my beloved wife, Hyunhee Kim and my son, Andrew Park. Because of you, I am what I am now and the happiest man in the world. Lastly, I cannot forget to mention how much I love and thank my wonderful parents, Mr. Byungtae Park and Mrs. Soony Kim and two lovely sisters, Yoojeong and Yoonjeong for their love and support over the years. Thank you all. vi

7 Table of Contents Abstract...iii Acknowledgements... vi Table of Contents... vii List of Tables... xi List of Figures... xiii Chapter 1 Introduction Problem Statement Research Objectives and Expected Contribution... 6 Chapter 2 Theory Development Literature Review Supply Chain Managment Supply Chain Risk Sources Supply Chain Risk Management (SCRM) Supply Chain Resilience Theory Base Resource-based View (RBV) Contingency Theory (CT) Research Model Research Framework vii

8 2.3.2 Research Model Antecedents of Resilient Supply Chain Practices Organizational Level Internal Risk Network Level Supply-related Risk Customer-related Risk Environment Level External Risk Risk Taking Propensity Resilient Supply Chain Practices (RSCP) Flexible Approach Information Sharing Security Compliance Extent of Postponement Extent of Collaboration Contingency Planning Redundant Approach Safety Stock Slack Capacity Resilient Supply Chain Capability Hypothesis Development Research Hypothesis viii

9 2.7.2 Research Hypothesis Research Hypothesis Chapter 3 Research Methodology (Item Generation and Pilot Study) Item Generation Pre-test and Structured Interviews Pilot Study using Q-sort Method First round Q-sort Second round Q-sort Sampling Plan Sample Characteristics Non-response Bias Test Chapter 4 Large-scale Instrument Validation Instrument Assessment Methodology Large-scale Measurement Model Initial First-order Measurment Model Final First-order Measurment Model Second-order CFA Measuremnt model Chapter 5 Path Analysis and Hypotheses Testing Structural Modeling Results Discussion of Path Analysis and Hypotheses Testing Results Summary of Results Chapter 6 Conclusion Summary ix

10 6.2 Theoretical Implications Managerial Implications Limitations Future Research References Appendix A Initial Items Based on Literature Reviews Appendix B Online Survey Questionnaire Appendix C Online Survey Questionnaire (Korean) Appendix D Summary of Measuremnt Constructs x

11 List of Tables 2.1 Supply Chain Strategy Classification The Definitions of Supply Chain Risk Management The Components of Supply Chain Resilience Definition of Constructs of Antecedents of Resilient Supply Chain Practices Definition of Constructs of Resilient Supply Chain Practices Definition of Constructs of Resilient Supply Chain Capabilities Inter-judge Agreement Raw Score (Round 1) Inter-judge Agreement Raw Score (Round 2) Inter-judge Agreement Raw Score Summary Final Itmes for Large-scale Survey Data Collection and Response Rate Sample Characteristics Reliability and Convergent Validity for Antecedents of Resilient Supply Chain Practices Reliability and Convergent Validity for Flexible Resilient Supply Chain Practices Reliability and Convergent Validity for Redundant Resilient Supply Chain Practices Reliability and Convergent Validity for Resilient Supply Chain Capabilities Corrected Item-total Statistics for Antecedents xi

12 4.6 Corrected Item-total Statistics for Flexible Practices Corrected Item-total Statistics for Redundant Practices Corrected Item-total Statistics for Capabilities Final Measurement Model for Antecedents Final Measurement Model for Flexible Practices Final Measurement Model for Redundant Practices Final Measurement Model for Resilient Supply Chain Capabilities Inter-construct Correlation and Discriminant Validity Validation of Second order Construct for Flexible Practices Validation of Second order Construct for Redundant Practices and Capabilities Path Analysis and Hypotheses Testing Results xii

13 List of Figures 2-1 Supply Chain Risk Sources Research Model Hypothesized Model Second-order CFA Measurment Model Structural Model Results xiii

14 Chapter 1 Introduction Supply chain risk management (SCRM) has become an emerging research issue during recent years (Christopher & Peck, 2004; Sheffi, 2005; Tang, 2006). Defining supply chain risk and identifying its sources have been essential tasks in determining how to manage supply chain risk. As firms face uncertain demands and supplier failures, they should be able to manage supply chain risks adequately, not only in order to maintain normal levels of operation but also to gain sustainable competitive advantages in the current business environment. Lean supply chain strategies formerly have been the dominant approach used to manage supply chains in the global economy; however, research has shown that as supply chains become leaner, the more likely it is that the supply chain process will become vulnerable and that risk will be incurred (Christopher & Peck 2004; Juttner et al., 2003; Lee & Wolfe, 2003). Supply chain disruptions occur due to many different reasons, such as global and single sourcing, supplier failure, complex and irregular demands, natural disasters, and other factors. These disruptions sometimes occur frequently, and when they do, they often inhibit product, process, information, and financial flow. The concept of risk has emerged from constructing investment portfolios. Rao and Goldsby (2009) have explained two ways of defining risk: First, risk includes not only a 1

15 downside but also the possibility that performance might be higher than expected. In other words, risk is the manifestation of uncontrollability that may result both in positive or negative outcomes (Arrow, 1970). Second, risk refers to some form of negative effect in terms of performance. Juttner et al. (2003) have defined supply chain vulnerability as an exposure to serious disturbance arising from supply chain risks and affecting the supply chain s ability to effectively serve the end customer market (p. 202). Johnson (2001) has divided the concept of supply chain risk into product supply (supply disruption and capacity limit) and product demand (volatility and seasonality). Svensson (2000) has introduced categories (quantitative and qualitative) and sources (atomistic or holistic) of business disturbance. In a follow-up paper, Sevensson (2002) identified an additional set of four disturbance scenarios concerning the degree (high or low) of inbound and outbound logistics vulnerability. Jüttner et al. (2003) have developed four important constructs when managing supply chain vulnerability: sources of risk, adverse consequences of risk, drivers of risk, and mitigation strategies. Chopra and Sodi (2004) have introduced supply chain risk categories, including delays, disruptions, forecasts, systems, inventories, intellectual property, and capacity. Tang (2006) has classified supply chain risk into operational risks and disruption risks. Operational risk refers to inherent uncertainties, and disruption risk refers to major disruption in the form of natural and man-made disasters. Paulson (2004) has explained that the number of papers focusing on supply chain risk amounted to 23 in 2002, but in 1995, only one paper in the area of supply chain 2

16 management. Studies on supply chain risk management have received much attention and have been a recent topic of interest during the past few years (Juttner, 2005; Wagner & Bode 2008). The existing body of supply chain risk management research pertains to risk identification, assessment, mitigation, and treatment. Juttner et al. (2003) has introduced four elements of SCRM: (1) assessing risk, (2) identifying risk by defining risk consequences, (3) tracking risk drivers, and (4) mitigating risk in the supply chain. Tang (2006) has divided tactical and strategic plans for managing supply chain risk into four categories based on the following management processes: (1) supply management, (2) demand management, (3) production management, and (4) information management. Ritche and Brindly (2000) have analyzed the emergence of risk from within the supply chain and throughout the supply chain network and explored the relationship between supply chain risk management and performance. Enterprise risk management practices are presented in the supply chain context (Shi, 2004). Several researchers have begun to adapt the concept of resilience to explain how to deal with supply chain risks and make the supply chain process more secure and resilient (Christopher & Peck, 2004; Rice & Caniato 2003; Sheffi, 2002; Tang 2006). Supply chain resilience is quite a new concept in the domain of SCRM and remains in the infancy stage of its development (Ponomarov & Holcomb, 2009). Christopher and Peck (2004) have defined resilience as the capacity of a system to return to its original (or desired) state after disruptions. Resilience can be defined as the ability to bounce back from a detrimental event that results in damage to a firm s operation in terms of services, production, and fill rate and is achieved by increasing redundancy and flexibility (Sheffi 3

17 & Rice, Jr., 2005). Sheffi and Rice, Jr. have argued that organizational resilience can be developed by conducting specific training, educating stakeholders, and generating contingency planning. The concept of resilience has been adapted from the fields of psychology, sociology, and economics as a way of approaching and overcoming vulnerabilities that each entity across the supply chain needs to exploit. The overarching characteristics of resilience are adaptability, preparedness, proper response, maintenance, and recovery from supply characteristics. These characteristics overlap from discipline to discipline in terms of explaining resilience. Adaptability has been regarded as a core element of a resilient ecosystem (Ponomarov & Holcomb, 2009). Response and recovery are two common components of resilience as defined within the fields of psychology, economics, health, and education. The notion of maintaining normal levels of operation and business continuity derives from ecology. Drawing from the previous papers and adopting Ponomarov and Holcomb s (2009) definition, this study defines resilient supply chain capability as the adaptive capability of the supply chain to prepare for unexpected events, respond to disruptions, and recover from them by maintaining continuity of operations at the desired level of connectedness and control over structure and function (p. 131). 1.1 Problem Statement By examining existing theories and conducting an extensive literature review, the researcher has identified two research gaps. One gap consists of a lack of available 4

18 research on firm-level practices that make supply chains resilient in responding appropriately to supply chain disruptions and factors that lead firms to adopt and implement these practices. Although a large number of studies have been conducted focusing on supply chain risk and its impact on business performance, the research on the enablers of resilient supply chain practices is very limited. Many studies in the area of logistics and operations management have been conducted in an attempt to measure and mitigate supply chain risk. However, in order to capture the importance and impact of resilient supply chain practices more precisely, researchers need to consider these practices at the antecedent level. A second gap is the lack of a comprehensive and integrated resilient supply chain framework and methods to measure its development. Many studies have defined SCRM, but most of them have done so using a fragmented approach. In addition, most studies focusing on supply chain risk management have been conducted using conceptual models, anecdotal evidence, case studies, and secondary datasets. These two gaps reveal specific areas where additional research is needed and suggest that a resilient supply chain practice framework requires a more holistic view in order to assess accurately the impact of these gaps on each entity across the supply chain. Having identified research gaps, this study addresses three research questions: (1) What are the antecedents of resilient supply chain management practices? (2) What are the dimensions of resilient supply chain management practices, and how can each component be measured? (3) How do resilient supply chain management practices result in resilient supply chain capabilities? 5

19 Drawing upon contingency theory (CT), this study identifies four types of risk and risk taking propensity as antecedents, or enablers, which result in firms implementing risk-related activities. A resource-based view (RBV) provides this study with the theoretical rationale to explain how firms resources and routines not only reduce the detrimental effect of supply chain disruptions but also formulate external-facing capabilities that lead to a competitive advantage. 1.2 Research Objectives and Expected Contribution In a general sense, this study aims to clarify and define what it means to develop and maintain supply chain resilience and the type of firm-level practices that characterize supply chain processes as more secure and resilient. To accomplish this aim, one of the purposes of this study is to examine the following factors: (1) antecedents that lead a focal firm to adopt and implement resilient supply chain practices that, in turn, enable supply chain processes to be more resilient; (2) flexible resilient supply chain practices (contingency planning, information sharing, collaboration, postponement, and security compliance) and redundant resilient supply chain practices (safety stock and slack capacity); and (3) resilient supply chain capabilities that exhibit readiness, response, and recovery capabilities. More specifically, the purpose of this study is to explore the following factors: (1) the direct effect of internal risk on risk taking propensity; (2) the direct effect of supplier risk on risk taking propensity; (3) the direct effect of customer risk on risk taking 6

20 propensity; (4) the direct effect of external risk on risk taking propensity; (5) the direct effect of risk taking propensity on flexible resilient supply chain practices; (6) the direct effect of risk taking propensity on redundant resilient supply chain practices; (7) the direct effect of flexible resilient supply chain practices on resilient supply chain capabilities; (8) the direct effect of flexible resilient supply chain practices on resilient supply chain capabilities. The expected academic contribution of this study is to provide a theoretical framework for resilient supply chain framework and empirical validation of supply chain risk as well as processes used to manage it effectively. This study identifies coordination mechanisms within supply chain practices, including risk perceptions, assessment, management, and outcomes, drawing upon contingency theory and a resource-based perspective. Few studies have explained these comprehensive interrelationships. The anticipated managerial implications include (1) providing focal firms with guidelines for making supply chain processes more secure and resilient based on perceived risk, risk taking propensity, and resource commitment, and (2) identifying bundles of routines and resources that enable firms to be ready, respond to, and recover from both expected and unexpected perceived risk. The set of activities and routines inside firms leads to being proactively prepared and responding to disruptive events quickly. Firms need to maintain redundancy because resilient supply chain practices cannot prevent detrimental events across the supply chain entirely. This study sheds 7

21 lights upon the processes that each firm uses to manage supply chain risk and to gain sustainable competitive advantage without sacrificing quality and cost. The organization of this study is as follows: Chapter 2 introduces theoretical grounds that characterize a resilient supply chain, defines resilient supply chain practices and capabilities, and develops hypotheses. Chapter 3 describes the processes used for item generation and purification using the Q-sort method. Chapter 4 assesses measurement practices employed in this study and analyzes large-scale survey data using structural equation modeling (SEM). Chapter 5 discusses the results of path analysis and hypotheses testing. Chapter 6 includes theoretical and managerial implications, limitations, and suggestions for future research. 8

22 Chapter 2 Theory Development 2.1 Literature Review Supply Chain Management In the industrial age, manufacturing focused on increasing mass production, maximizing existing resource utilization and efficiency, and minimizing inventory levels and system variety. Also, market segmentation and positioning were restricted to examining stand-alone firms. However, meeting market needs and customers diverse requests became important factors in winning business and gaining a competitive edge in the post-industrial age (Doll & Vonderembse, 1991). Customers began to demand individually customized products and fast delivery. The firms that could not meet customer requirements quickly and deservedly ran the risk of losing market share and profitability. As markets expanded globally, the supply chain approach to managing business emerged. Since the concept of the supply chain was introduced in the early 1980s, managing supply chains has been one of the dominant issues and research streams for both academicians and practitioners. Business activities and competition among firms have been shifting steadily from a company-versus-company approach to a supply-chainversus-supply-chain approach. Competition in the global economy has expanded beyond 9

23 the scope of local and national levels through rapidly changing technologies and uncertainty surrounding customer demand (Lambert & Cooper 2000; Vonderembse et al., 2006; Li et al., 2005). The most important goal in supply chain management is to deliver products and services to customers in a timely manner and at a lower cost than global competitors. Interrelated network capabilities across the supply chain are required because a single firm alone cannot successfully manage these challenges. A supply chain approach has the dual purpose of earning profit for individual firms as well as for the entire supply chain (Li et al., 2005). Thus, supply chain management is an overarching paradigm that covers design management, planning processes, manufacturing processes, delivery, logistics, suppliers, and customers. Over the decades, many research articles have drawn attention to the link between different patterns of supply chain strategies and product/market uncertainty. Fisher (1997) was the first scholar to introduce dichotomy matching that is, matching two product types (functional and innovative) with supply chain strategies (efficient and responsive). Lee (2002) added one more dimension supply uncertainty to Fisher s typology. According to Lee, functional product types correspond with low demand uncertainty while innovative product types correspond with high demand uncertainty. Building on Fisher s typology, Lee has suggested that low supply uncertainty corresponds with stable processes while high supply uncertainty corresponds with evolving processes. As a result, firms must consider the risk involved with their supply chain strategies. Table 2.1 portrays a supply chain strategy classification system based on product type and product life cycle (PLC). Vonderembse et al. (2006) have introduced the notion that hybrid 10

24 products combine functional and innovative products. They have referred to hybrid products as complex products that feature mixed characteristics both of standard and innovative products (e.g., automotive or assembled products). They have argued that the hybrid supply chain strategy better matches hybrid products and innovative products with a long PLC. In the next section, this study briefly reviews the sources of supply chain risk and the elements of supply chain risk management. Table 2.1 Supply Chain Strategy Classification (sourced from Fisher, 1997; Lee, 2003; Vonderembse et al., 2006) Product Type Product Life Cycle Standard Innovative Hybrid Introduction Growth Maturity Decline Lean Supply Chain Agile Supply Chain Hybrid/Lean Supply Chain Hybrid Supply Chain Supply Chain Risk Sources Figure 2-1 describes different sources of supply chain risk. Supply chain risk sources are characterized by three primary factors: environmental factors, network factors, and organizational risk factors. Environmental risk is regarded as external, while demand and supply risk are considered internal. Environmental risk is comprised of external uncertainties caused by natural, political, and social uncertainties. Network risk includes demand- and supply-side risk. Demand risk pertains to any uncertainty regarding product demand, product life cycle, and outbound logistics flows (Svensson, 2002; Johnson, 11

25 2001). Supply risk pertains to supplier relationships and activities. Juttner et al. (2005) have suggested separating control and process mechanisms as risk absorbers or amplifiers from other sources of risk. Process mechanisms refer to process designs and implementation practices among supply chain entities. Control mechanisms involve decision making regarding rules and policies, such as batch size, order quantity, and safety stock. Both mechanisms play a role in absorbing and amplifying the impact of risk in the supply chain. Figure 2-1 Supply Chain Risk Sources (Sourced from Juttner et al., 2003; Juttner et al, 2005) Ritchie and Marshall (1993) have stressed the importance of five factors related to business and organizational risk: (1) decision-maker-related factors, (2) problem-specific 12

26 factors, (3) organizational factors, (4) industry factors, and (5) environmental factors. These authors have identified the broad category of framework based on organizational, industry, and environmental factors. Drawing upon these factors, Rao and Goldsby (2009) devised a tool to identify different risks and introduced typology of risk to explain how overall supply chain risk is formulated. According to these researchers, organizational risk is comprised of agency, credit, liability, and operating uncertainty. Industry risk is comprised of input, product, and competitive uncertainty. Environmental risk is comprised of political, policy, macroeconomic, and social uncertainty. Johnson (2001) has argued that the majority of supply chain risk is experienced on the supplier side. Firms should decide between off-shoring and relying on internal suppliers for their materials selection and sourcing. Because of the sheer number of suppliers and the complexities associated with their interdependence, there are many opportunities for supplier failure, including those related to cultural differences, geographic region, and social norms (Choi & Krause, 2003). Occasionally, suppliers possibly may be unable to meet firms requirements and expectations, so the ability to respond immediately to customers needs may be compromised. Peck (2005) has identified the drivers of supply chain vulnerability at four interlinked levels: (1) workflows and information flows, (2) fixed and mobile assets, (3) contractual and trading relationships, and (4) natural and social environments. Peck has emphasized the dynamic and constantly evolving nature of vulnerability in assessing supply chain risk. Based on the above-mentioned research, this study defines supply chain risk as any disruptions that 13

27 occur at the environmental, network, and organizational levels and that hamper normal and planned levels of operation Supply Chain Risk Management (SCRM) Table 2.2 describes the elements of SCRM and provides their definitions. SCRM seeks to identify the possible sources of supply chain risk and implement proper actions to avoid or cushion supply chain disruption (Juttner et al., 2003). Kleindorfer and Saad (2005) have suggested nine principles for managing disruption risk in supply chains; these principles have been adapted from supply chain and industrial risk management literatures. Christopher (2005) has listed six steps in developing a risk identification and mitigating strategy: (1) prioritize earnings drivers; (2) identify critical infrastructures that affect the earnings drivers; (3) locate vulnerabilities in the critical infrastructure; (4) model scenarios for the vulnerabilities; (5) develop responses to the scenarios; and (6) monitor, detect, and respond to potential disruptions. Hendricks and Singnal (2005) have observed abnormal stock returns among firms who experienced disruptions and found that they were unable to recover from negative effects of disruptions quickly. Tang (2006) has suggested nine strategies to develop a robust supply chain and mitigate supply chain risk related to product, supply, and demand: (1) postponement, (2) strategic stock, (3) flexible supply base, (4) make and buy, (5) economic supply incentives, (6) flexible transportation, (7) dynamic pricing and promotion, (8) assortment planning, and (9) silent product rollover. According to Tomlin (2006), supply chain risk management is 14

28 characterized by contingency strategies and mitigation actions. In this study, supply chain risk management refers to the management of supply chain risk through collaboration and coordination among supply chain entities to reduce the likelihood of any disruptions and ensure business continuity and profitability. Table 2.2 The Definitions of Supply Chain Risk Management (Sourced from Rao and Goldsby, 2009) Authors Definition Christopher (2002) SCRM is the management of external risks and supply chain risks through a coordinated approach among supply chain members to reduce supply chain vulnerability as a whole Norrman and Lindroth (2002) SCRM is to, collaboratively with partners in a supply chain, apply risk management process tools to deal with risks and uncertainties caused by or impacting logistics-related activities or resources Tang (2006) SCRM is the management of supply chain risks through coordination or collaboration amongst the supply chain partners so as to ensure profitability and continuity Manuj and Mentzer (2008a, b) (Global) SCRM is the identification and evaluation of risks and consequent losses in the global supply chain and implementation of appropriate strategies through a coordinated approach among supply chain members with the objective of reducing one or more of the following losses, probability, speed of event, speed of losses, the time for detection of the events, frequency, or exposure for supply chain outcomes that, in turn, lead to close matching of actual cost savings and profitability with those desired Juttner et al. (2003) The identification and management of risks for the supply chain, through a coordinated approach amongst supply chain members, to reduce supply chain vulnerability as a whole 15

29 2.1.4 Supply Chain Resilience This study reviews the notion of resilience in general in contrast to other disciplinary perspectives, and then describes what it means for a supply chain to be resilient. The Latin root of the word resilience, resilire, means to rebound or leap back (Simmie & Martin, 2010). The concept of resilience has been developed and researched concurrently in diverse disciplines, such as psychology and ecology. In this study, the concept of resilience is adapted from psychology, ecology, economics, health, and education in approaching and overcoming vulnerabilities that each entity across the supply chain faces. Resilience emerged within psychology literatures first. For example, psychological researchers have attempted to discover why some children become more immune to negative factors whereas others show the opposite tendency (Kinght 2007). Garmezy (1971), Garmezy and Rutter (1983), and Werner and Smith (1989, 1992) made important early contributions to the scholarly literature base regarding resilience in this area of psychology. From the mid-1990s, empirical research has been conducted by many researchers on resilience (Doll & Lyon, 1998; Luthar 2000; Masten & Coastworth, 1998). According to Garmezy and Neuchterlein (1972), resilience is the ability to bounce back despite significant adversity or stress. Resilience requires a balance between stress (i.e., risk factors) and the capacity to manage (i.e., protective factors) (Rutter, 1993). If risk factors transcend protective factors, individuals become less resilient (Garmezy, 1993). Polk (1997) has categorized the main factors associated with resiliency into four categories: relational, dispositional, philosophical, and situational. Among these four categories are 16

30 factors that include intelligence, sociability, confidence, self-efficacy, optimism, good health, easy-going temperament, internal locus of control, flexibility in goal setting, problem-solving ability, hope, the ability to utilize available resources, and social support. Table 2.3 The Components of Supply Chain Resilience (sourced from Ponomarov and Holcomb, 2009) Discussed aspects Agility, responsiveness Visibility Flexibility/redundancy Structure and knowledge Reduction of uncertainty, complexity, reengineering Collaboration Integration, operational capabilities, transparency Relevant research summary Christopher (2004) describes agility as one of the most powerful ways of achieving resilience in the supply chain. Agile supply networks are capable of more rapid response to changed conditions Increasing the visibility of demand information across the supply chain reduces the risks (Chopra and Sodhi, 2004) Christopher (2005) states that resilient processes are flexible and agile and are able to change quickly. Flexibility enables a manufacturer to respond quickly and efficiently to dynamic market changes (Swamidass and Newell, 1987). Rice and Caniato (2003) suggested a hybrid flexibility/redundancy approach for increasing supply chain resilience Knowledge and understanding of supply chain structures-both physical and informational-are important elements of supply chain resilience (Choi and Hong, 2002) van der Vorst and Beulens (2002) view reduction of uncertainty as the way to improve supply chain resilience Christopher (2000) adds reduction of complexity through business process reengineering initiatives Collaborative partnerships help to manage risks effectively (Lee, 2004) In describing the operational capabilities of resilient supply chains, Smith (2004) emphasized the importance of integrated environment that provides end-to-end interaction of orders, inventory, transportation and distribution to facilitate supply chain transparency 17

31 Rice and Caniato (2003) have discussed how to build a resilient and secure supply network. Actions to develop security can be divided into three categories: freight, information, and physical security. Increasing resiliency requires flexibility and redundancy. Sheffi (2006) has explained that a small number of commodities, multiple suppliers, close supplier relationships, postponement and built-to-order operations, and corporate culture lead to supply chain resilience. McManus et al. (2007) have introduced ways to enhance supply chain resilience through relying on (1) keystone vulnerabilities, criticality, and preparedness; (2) adaptive capacity; and (3) situation awareness. Asbjørnslett (2008) has defined resilience as the ability to sustain and survive in spite of a severe and harmful impact. By drawing multidisciplinary perspectives into the supply chain context, Ponomarov and Holcomb (2009) have combined elements of supply chain resilience from existing literature (see Table 2.3). 2.2 Theory Base Resource-based View (RBV) The resource-based view (RBV) has been an important theoretical framework when explaining how and why competitive advantages can be sustainable for particular companies. RBV advances the notion that a firm s competitive advantage is achieved from its unique resources and capabilities. The RBV perspective emerged from within the field of strategic management. RBV theorizes that a firm creates value by combining heterogeneous and immobile resources that are valuable, rare, inimitable, or nonsubstitutable against competitors (Barney, 1991). Many authors have discussed these four 18

32 characteristics of resources that enable firms to gain a sustainable competitive advantage against their competitors (Barney, 1991; Peteraf, 1993; Rungtusananatham et al., 2003). Rungtusantham et al. (2003) have identified four important types of resources: those that are (1) valuable, (2) rare, (3) inimitable, and (4) non-substitutable (VRIN). They have been defined and described within the literature as follows: 1. Resources should be valuable by enabling firms either to reduce their weaknesses or outperform their competitors. Valuable resources lead firms to enhance their efficiency and effectiveness (Barratt & Oke, 2007). Firms investment in resources should not be higher than the discounted future rent fee (Mahoney & Prahalad, 1992). 2. Rare resources offer firms increased opportunities to gain a competitive edge. Purchasable resources, including computer software and web-based applications, such as EDI and ERP, may not be rare, but implementing them in unique ways can enhance the capabilities of firms. 3. In order for an advantage to be sustainable, resources should not be perfectly inimitable so that competitors cannot duplicate them (Barney 1991; Peteraf, 1993). Peteraf (1993) has argued that this inimitable quality underlies a casual ambiguity of resources, which brings about competitive advantage and is sometimes unknown, idiosyncratic, and embedded in a firm s specific assets. In particular, resources, including knowledge and network dependency, are more likely to be inimitable (Conner & Prahalad, 1996). 19

33 4. Finally, resources should not be easily substitutable to prevent competitors from marshalling similar valuable but more cost-efficient resources. They would be able to come up with strategically equivalent but somewhat different resources that can be used for the same purpose (Barratt & Oke, 2007). In the information systems (IS) literature, RBV has been used to analyze information technology (IT) capabilities (Mata et al., 1995) and to explain how business value resides more in a firm s ability to utilize IT than in the technology itself because IT business value is derived from the degree to which IT is used in the key activities in the firm s value chain. The greater the use, the more likely the firm is to develop unique capabilities from its core IT infrastructure (Zhu et al., 2005). IT-enhanced capabilities that integrate various resources cannot be easily imitated and or substituted. In order to understand routine-based capabilities correctly, the concepts of resource and routine need to be clarified. According to Peng et al. (2008), resource is defined as a firm s tangible and intangible assets that can be productively utilized. Resources are more likely to support a firm s sustained competitive advantage when they are protected by isolating mechanisms (Rumelt and Lamb, 1984) such as timecompression diseconomies, historical uniqueness, embeddedness, and causal ambiguity (Barney, 1991). Routine refers to regular and expected patterns of behavior providing firms with the means to implement their value creation strategies (Grant 1991; Teece et al., 1997). Routines are organizational processes that enable firms to achieve desired outcomes using a set of resource. Many researchers have conceptualized capabilities as bundles of routines or high-level routines (Collis, 1994; Winter, 2003). Routines have 20

34 been regarded as the foundation of capabilities (Eisenhardt & Martin 2000). Peng et al. (2008) have suggested that routines from internally consistent bundles and play a crucial role in shaping operations capabilities and creating competitive advantage. These authors have conceptualized operations capabilities as a bundle of routines and identified two capabilities such as improvement and innovation. These capabilities are regarded as higher-level bundles of routines Contingency Theory (CT) Contingency theory stems from behavioral theory and claims that optimal decisions and actions are dependent on internal and external factors. Burns and Stalker (1961) are two researchers who introduced the contingency approach by making a distinction between mechanistic and organic forms of management and organization. The mechanistic form is related to routine technology and stable environments whereas the organic form is related to changing technology and turbulent and uncertain environments. Different types of technical systems and the size of firms explain many of their characteristics (Woodward, 1965; Pugh et al., 1968). Organizational structure and management styles are influenced by many contingencies and environmental influences. Scott (1992) has mentioned that the best way to organize depends on the nature of the environment to which the organization relates (p. 89). Contingency theory posits that the more organizational structures and processes fit into environments characterized by uncertainty, the more successful these firms will be (Miller, 1992). Sousa and Voss (2008) have argued that the contributions of 21

35 contingency theory are achieved by (1) identifying important contingency variables that distinguish between contexts, (2) grouping different contexts based on these contingency variables, and (3) determining the most effective internal organization designs or responses in each major group. The internal and external contingency factors that help establish these groupings have been identified in many studies (Gupta et al., 1994; Homburg et al., 1999; Mintzberg, 1979; Sousa & Voss, 2008; Wagner et al., 2001). Size, age, environment, and technology are regarded as major contingency factors. Contingency studies have identified three primary types of variables: (1) contextual variables, which represent situational characteristics exogenous to the focal firm and manager; (2) response variables, which are the organizational or managerial actions taken in response to current or anticipated contingency factors; and (3) performance variables, which are dependent measures and represent specific aspects of effectiveness i.e., criteria that are appropriate in evaluating the fit between the above two variables (Sousa & Voss, 2008). Gupta et al. (1994) have identified common dimensions among these variables, such as task difficulty, task variability, and task interdependence. Mintzberg (1979) has identified stability, complexity, diversity, environment, and hostility as contingency variables and the design of the superstructure, positions, decision making, and lateral linkage as structural design parameters. Homburg et al. (1999) have introduced internal factors, such as cost-leadership strategy, differentiation, distribution, and customer base, as well as external factors, such as market-related uncertainty, technological turbulence, 22

36 and market growth. Wagner et al. (2001) have identified formalization of regulations, centralization of decision-making processes, and organizational size as contingency factors. 2.3 Research Model Research Framework Drawing upon CT and RBV, Figure 2-2 presents the research framework for this study. CT suggests that a series of optimal decisions within a firm are contingent upon internal and external factors and that the fit between organizational structure and process will lead to better performance. The ability to adopt and implement practices that reduce the effects of harmful events depends on the extent to which firms perceive and react correctly to current and unexpected risks. This study identifies three types of risk and risk taking propensity as antecedents, or enablers that allow firms to initiate and implement risk-related activities. RBV serves as a theoretical lens through which to view important connections that link internal resources and bundles of routines with external-facing capabilities links that enable firms not only to respond to and recover from any disruptions properly but also to maintain or gain a sustainable advantage to win new business. According to RBV, the availability of resources leads firms to shape operational capabilities and performance improvements (Peng et al., 2008). For instance, Ericsson lost $400 million dollars in sales and ultimately left the cell-phone market because of water and smoke 23

37 damage from a fire in a mobile chip supplier s plant. In essence, Ericsson underestimated the effects of the incident. In contrast, Nokia took over a leadership position and boosted its sales growth rate by quickly facilitating safety stock and re-engineering its phones according to the capabilities of available suppliers (Juttner et al., 2003) Research Model Figure 2-2 displays the research model for resilient supply chain practices (RSCP) and resilient supply chain capabilities (RSCC). There are three stages that capture the holistic view of resilient supply chain management in terms of enablers, practices, and capabilities. This framework can be interpreted from a CT and RBV perspective as a theoretical lens. CT indentifies three levels of supply chain risk (i.e., organizational-level risk, network-level risk, and environmental-level risk). At the organizational level, firms encounter disruptions that hamper their ongoing internal operations. Inter-organizationallevel risk refers to network risk, which includes risk on the supply side as well as the customer side. This category belongs to the risk that occurs within respective supply chain networks. Environmental-level risk refers to risk that occurs outside a firm s network, and in many cases, firms are unable to control this type of risk. As another factor leading to RSCP, this study introduces risk taking propensity. The attitudes and tendencies within organizations to approach and view perceived risk differently certainly affect the manner in which firms respond to and deal with this risk. This study conceptualizes RSCP as having flexible and redundant approaches. RBV provides a theoretical rationale that explains how internal routines enable firms to 24

38 Antecedent Resilient SC Practices RSC Capabilities Organization Internal Risk Network Supply related Risk Customer related Risk Risk Taking Propensity Flexible RSCP Information Sharing Security Compliance Extent of Postponement Extent of Collaboration Contingency Planning Redundant RSCP Resilient SCM Capabilities Readiness Response Recovery Environment External Risk Safety Stock Slack Capacity Figure 2-2 Research Model 25

39 form capabilities that allow them to outperform their competitors and gain sustainable advantage. The concept of flexible resilient supply chain practices refers to risk reduction and avoidance related to information sharing, security initiatives, and the extent to which postponement occurs, the extent to which collaboration is present and contingency planning. This set of activities and routines leads firms to prepare for and respond to disruptive events proactively and quickly. The concept of redundant resilient supply chain practices, which pertains to hedging risk, primarily refers to safety stock and slack capacity. Firms need to maintain redundancy because flexible resilient supply chain practices cannot prevent detrimental events across the supply chain entirely. The definitions of each constructs are shown in Tables 2.4 through Antecedents of Resilient Supply Chain Practices In this section, several factors that lead to adopting resilient supply chain practices are introduced. Chopra and Sodhi (2004) have identified major risks that require special attention, such as disruptions, delays, procurement risk, capacity risk, forecast risk, and inventory risk. As an alternative to a framework based on internal and external factors, Christopher and Lee (2004) have introduced a different approach to classifying supply chain risk. According to Christopher and Lee, supply chain risks are related to (1) financial risks: inventory overstocking, stock-out, and obsolescence; (2) decision risks: uncertainty about making decisions; (3) chaos risks: second guessing, mistrust, 26

40 overreactions, unnecessary interventions, and distorted information; and (4) market risks: changes in customer requirements and global trends. Finch (2004) has noted that there are three levels of risk: (1) application-level risk, which affects local functions and technical failures; (2) organizational-level risk, which is associated with strategic failure; and (3) inter-organizational-level risk, which refers to network failures that impact customers and suppliers. These authors have further specified and provided examples of typical risks that are related to these three levels, such as natural disasters (e.g., floods and earthquakes), deliberate acts (e.g., sabotage, theft, terrorism, and vandalism), legal risks (e.g., disclosure and counterfeit of intellectual property), accidents (e.g., poor management resulting in human error), information security (e.g., viruses and hacking), and knowledge management (e.g., failure to hire and retain skilled personnel). Manju et al. (2008) have identified and classified four types of supply chain risk (supply, operational, demand, and security risks) and four types of environmental risk (macro, policy, competitive, and resource risks). This study examines risk more closely at three levels: the organizational level, the network level, and the environmental level. Internal risk, supplier-related risk, customerrelated risk, and external risk are proposed as their sub-categories. This study adopts the classification system endorsed by Juttner et al. (2003), Christopher (2005), and Trkman and McCormack (2009). This breakdown is regarded as classic in categorizing different types of risk because it is straightforward and easy to conceptualize. It allows researchers to establish a division between risk within the supply chain and risk that may emerge from the outside environment. Some studies have employed only two categories of risk, 27

41 e.g., risk that is internal and risk that is external to the focal firm, but this approach represents an oversimplification of risk because most companies engage in more than two supply chains. Potential risks in upstream and downstream supply chains that firms belong to are different in their characteristics and in their effects Organizational Level Internal Risk Internal risk refers to risks related to any disruptions and failures of resources (i.e., production, labor, and system) to maintain a normal level of operation within an individual company (Juttner et al., 2003; Kiser and Cantrell, 2006). Internal risk at the organizational level arises from the direct and indirect adverse impact of any events associated with services and operations that are underperforming compared to expectations. Internal risk involves uncertainties regarding production, labor, and systems (Juttner et al., 2003; Chopra & Sohdi, 2004). These uncertainties can manifest themselves in the form of strikes, product obsolescence, machine failure, outage, and IT-system breakdowns. Particularly, IT-system breakdowns can devastate normal business activities in a highly integrated network environment. For example, the virus infection which occurred at NASA, the Pentagon, and Ford caused billions of dollars in estimated damages (Chopra & Codhi, 2004). Other sources of internal risk include employee strikes, lead-time variation, manufacturing capacity reduction, incorrect order forecasting, equipment breakdowns, lack of financial control and stability, errors in product design, and the failure to establish 28

42 reliable business relationships (Viswanadham & Gaonkar, 2008; Kiser & Cantrell, 2006). The mismatch between actual demand and projected demand causes forecasting inaccuracy, which results from short product life cycles, high product variety, and information distortion (Chopra & Codhi, 2004). Table 2.4 Definition of Constructs of Antecedents of Resilient Supply Chain Practices Construct Definition References Internal Risk Supply-related Risk Customer-related Risk External Risk Risk Taking Propensity Risks related to any disruptions and failures of resources (i.e., production, labor, and system) to maintain a normal level of operation within an individual company Risks related to any disruptions and failures of product and/or service flow from suppliers Risks related to unpredictable or misunderstood customer demand (i.e., complex preference, forecasting error, and customers bankruptcy) Risks that arise from any disruptions and failures outside the supply chain (i.e., natural disasters, political instability, and international terror attacks) Company s willingness to make resource commitments to deal with risks Chopra and Codhi, 2004; Juttner et al., 2003; Kiser and Cantrell, 2006 Choi and Krause, 2006; Manju et al., 2008; Rao and Goldsby, 2009; Wagner and Neshat, 2009; Zsidisin, 2003 Bartezzaghi and Verganti, 1995; Chopra and Sohdi, 2004; Trkman and McCormack, 2009; Wagner and Neshat, 2009 Juttner et al. 2003; Manju et al., 2008; Rao and Goldsby 2009 Cho and Lee, 2006; Das and Joshi, 2007; Miller and Friesen,

43 2.4.2 Network Level Supply-related Risk Supply related risk is defined as risks related to any disruptions and failures of product and/or service flow from suppliers. As market competition becomes intense and expands globally, firms have been outsourcing their manufacturing to diverse suppliers as a means of gaining cost advantages. Supply networks and bases are becoming more complex and integrated. Choi and Krause (2006) have conceptualized supply base complexity as having three dimensions, which include the number of suppliers in the supply base, the degree of differentiation among suppliers, and the level of interrelationships among the suppliers. These researchers have suggested that supply base complexity and supply risk are positively co-related, which means that a higher level of supply base complexity equates to a higher level of supply risk. Supply-related risk is associated with suppliers financial stability and the condition of their physical facilities (Kiser & Grantrell, 2006). Manju et al. (2008) have identified and introduced several supplier risks: (1) business disruptions caused by the sudden inability of suppliers to meet orders, (2) delays from suppliers suppliers, (3) market survival in the case of core suppliers who are going bankrupt, (4) conflict with suppliers due to confusion regarding inventory ownership and intellectual property, and (5) opportunistic behavior of suppliers due to information asymmetry. Quality fluctuations in inputs, raw materials shortages, and spare parts restrictions are example of input supply uncertainties (Rao & Goldsby, 2009). Increasingly, innovative intellectual property that belongs to international companies is provided to suppliers in developing 30

44 countries without proper legal protection. There is the possibility of foreign venders redesigning components and making and selling products under their own brand names, thus becoming potential competitors. However, strategies exist to mitigate these potential problems. For example, to prevent problems related to disputes about ownership, Motorola owns some of the testing equipment located at suppliers facilities (Chopra & Sohdi, 2004). Another risk on the side of suppliers is caused by a sudden increase in prices of key components from suppliers. In these cases, firms may experience an unexpected increase in acquisition cost Customer-related Risk Customer related risk is defined as risks related to unpredictable or misunderstood customer demand (i.e., complex preference, forecasting error, and customers bankruptcy). The requirements and demands of customers are becoming increasingly complex and volatile in terms of volume and mix of products and services. The more firms recognize and meet customers needs with fast delivery and low cost, the more likely they are to gain competitive advantage. Bartezzaghi and Verganti (1995) have suggested that demand uncertainty is characterized by heterogeneity, undispersion, and erraticness. According to these researchers, heterogeneity occurs when offering products and services with different kinds of demands within different markets. Undispersion occurs when demand is characterized by a high degree of personalization. Erraticness occurs when high demand alternates with low demand in a rapidly cycling process. Trkman and McCormack (2009) have suggested that market heterogeneity results in rapid changes in customer preferences and composition. 31

45 Tang (2006) has explained the nature of uncertain and shifting demands across time, markets, and products. Firms face demand uncertainties related to seasonality, such as peak and off-peak seasons. Demand uncertainty is found when firms sell multiple products with different life cycles in different markets. Similar to supplier-related risk, demand-related risk is also affected by system breakdowns related to processing customer information, such as theft of credit card numbers or other financial information. In 2002, Sears, Roebuck and Co. experienced an abrupt 30% stock price decrease in one day because of losses incurred by criminal cardholders (Chopra & Sohdi, 2004). Financial instability can make key customers withhold their payments, which damages the revenue of firms. Forecasting errors in demand predictions have been found to lead to a shortage of excess stocks, which can result in financial loss (Manju et al., 2008). Demand risk resides in downstream supply chain operations, customer dependence, customers financial circumstances, the product and its characteristics (life cycle and complexity), the outbound supply chain (physical distribution of products to the end customer), and the distribution and transportation operations required to serve customers (Wagner & Neshat, 2009) Environment Level External Risk External risk refers to risks that arise from any disruptions and failures outside the supply chain (i.e., natural disasters, political instability, and international terror attacks). External risk occurs when external events occur over which each entity in the supply 32

46 chain has little control, e.g., weather hazards or financial collapse (Tapierco & Grando, 2008). Aldrich (1979) has identified five subcategories of environmental uncertainty: (1) capacity, (2) stability-instability, (3) turbulence, (4) homogeneity-heterogeneity, and (5) concentration-dispersion. Gupta and Wilemon (1990) have suggested that the sources of environmental uncertainty include global competition; irregular demand; continuous development of new technologies; and the involvement of external organizations, including suppliers and customers. Manju et al. (2008) have classified external risk into three dimensions: (1) macro-economic risk, which includes recessions, economic shifts, and variations in exchange rates; (2) competitive risk, which refers to uncertainty about competitors, (3) policy risk, which includes shifts in legislation and government policy; and (4) resource risk, which refers to uncertainty about resource availability. Adopting Miller s (1991) framework, Rao and Goldsby (2009) have proposed five variables that comprise environment risk: political, policy, macro-economic, social, and natural uncertainty. According to these researchers, political stability is required for firms to maintain normal operations and to conduct business with foreign supply chain partners. Policy uncertainty can be defined as changes in government policy that affect business organization, e.g., price controls, fiscal and monetary reforms, nationalization/privatization, and minimum wage agreements. Macroeconomic uncertainty includes inflation, fluctuations in currency exchange rates, and fluctuations in oil prices. Terrorist activities serve as a primary example of social uncertainty. Ford had to idle several facilities when the components supplied from Canada and Mexico were delayed at the border following the terrorist attacks of 9/11. Natural risk refers to various 33

47 phenomena that hamper planned business activity and decrease production capacity. Earthquakes, fires, hurricanes, floods, and other natural disasters are examples of natural risk Risk Taking Propensity In this study, risk taking propensity refers to a company s willingness to make resource commitments to deal with risks (Miller & Friesen, 1978). Risk propensity has been defined in many studies. Sitkin and Pablo (1992) have defined individual risk propensity as the general willingness of a person to engage in risky behaviors and accept uncertain outcomes in decision-making (p. 15). Risk propensity ranges from riskaversion tendencies to actively avoiding risk to risk-seeking tendencies to actively exploiting uncertainty (Weber et al., 2002). Risk propensity has been found to be highly situation dependent, which suggests that there is no general personal attribute that demonstrates consistent risk-avoiding or risk-seeking tendencies (Keil et al., 2000). Sharma et al. (2009) have suggested that the risk propensity of consumers is a higher-order trait that is comprised of three factors: perceived risk, risk-taking attitude, and price consciousness. Studies on risk propensity predominantly have emphasized the individual components. By extending the study of risk propensity to an organizational level by examining the supply chain, Kocabasoglu et al. (2007) have defined organizational risk propensity as the likelihood of a firm s acceptance of less or more risky behavior over time (p. 23). Risk taking is a firm s propensity to proceed into unknown territory. The more firms are willing to take risk by engaging in risky business 34

48 activities to achieve goals, the more likely they are to take bold actions that lead to launching cutting-edge products and services (Gilley et al., 2002; Das & Joshi, 2007). 2.5 Resilient Supply Chain Practices (RSCP) Fisher (1997) has suggested three ways to deal with demand uncertainty: (1) risk reduction, (2) risk avoidance, and (3) risk hedging. Whereas reducing or avoiding risk is related to maintaining a flexible approach, risk hedging is related to shield failures because simply it is not possible to eliminate risk entirely. Fisher has argued that firms can reduce uncertainty by finding sources of new data and increasing the number of different products with common components. Risk avoidance can be achieved by cutting lead times and improving flexibility, which leads to accurate forecasts. Risk hedging involves managing the remaining residual uncertainty using principles of redundancy, such as safety stock and excess capacity. Zsidisin and Ellram (2003) have examined supply risk from the standpoint of efforts of purchasing firms to manage their suppliers. Zsidisin and Ellram have introduced (1) behavior-based management efforts and (2) outcome-based management efforts. Behavior-based management emphasizes the business processes of suppliers that lead to risk reduction in the form of improved production processes, information sharing, and close long-term partnerships. Outcome-based management reduces not only the probability that harmful events may occur but also the detrimental effects of supply risk events through multiple sourcing and buffer stock. 35

49 Wagner and Bode (2008) has proposed a cause-oriented focus and an effectoriented focus when managing supply chain risk. A cause-oriented focus refers to a decrease in the likelihood that a disruptive event will occur and the avoidance of possible risk through switching and relocating existing facilities and launching preventive safety and security systems. An effect-oriented focus refers to minimizing the disruption and employing principles of redundancy, such as providing organizational slack, employing a buffering strategy, increasing capacity, and using multiple sourcing. Based on the above-mentioned studies, resilient supply chain practice refers to the set of activities undertaken in a firm to promote effective management of its supply chain risk to ensure risk mitigation and a quick return to normal operation. In the next section, this study details and categorizes resilient supply chain practice into a flexible approach and a redundant approach. The flexible approach encompasses information sharing, security initiatives, extent of postponement, extent of collaboration, and contingency planning. The redundant approach encompasses safety stock and slack capacity Flexible Approach Information Sharing Information sharing has been defined as the extent to which critical and proprietary information is communicated to supply chain partners (Li et al., 2005 p. 625). Uncertainties arise when each member within a supply chain cannot obtain information about the other members (Yu et al., 2001). Each firm should be able to manage risks that arise within its own organization. At the same time, firms need to communicate with one 36

50 another when managing complex and diverse risks. Therefore, effective information sharing among partners is a key determinant in reducing internal and external risk in the supply chain environment (Hallikas et al., 2004). Many researchers have recommended sharing information as a preferred way to diminish supply chain risk. Tang (2004) has suggested that more accurate future demand forecasting and more efficient coordination can be achieved by sharing information among entities through the Internet, exchange data interfaces (EDI), and enterprise resource planning (ERP) processes. Information sharing regarding demand, supply, inventory, production schedules, and purchasing schedules enables firms to generate higher levels of supply intelligence and greater visibility of risk profiles (Christopher & Peck, 2004). Skipper and Hanna (2009) have defined information sharing as the ability to integrate and connect different systems and facilitate a seamless data exchange. Other researchers have found that information sharing can eliminate or mitigate the negative impact of the bullwhip effect caused by demand uncertainty and amplification (Srinivasan et al., 1994; Yu et al., 2001). Barratt and Oke (2007) have introduced multiple industry initiatives that have been used in sharing information: (1) Collaborative planning, forecasting, and replenishing (CPFR); (2) vendor-managed inventory (VMI); (3) efficient consumer response (ECR); and (4) quick response. Zhu and Benton Jr. (2007) have argued that information sharing has three sub-dimensions, including information content, information quality, and information sharing support technology. 37

51 Security Compliance Security compliance refers to the application of policies, procedures, and technology to protect supply chain assets (product, facilities, equipment, information and personnel) from theft, damage, or terrorism and to prevent the introduction of unauthorized contraband, people or weapons of mass destruction into the supply chain. Following the 9/11 tragedy, securing supply chain business activities became an important agenda for practitioners and academicians. The annual amount US businesses invested in securing logistics and supply chain security has been estimated to be approximately $65 billion (Bernasek, 2002; William et al., 2009). Typical government and non-government security initiatives include the Customer-Trade Partnership against Terrorism (C-TPAT), the Container Security Initiative (CSI), Fast and Security Trade (FAST), the Emergency Planning and Community Right to Know Act (EPCRA), the Advanced Manifest Rule (AMR), Antitamper Seals, X-Ray and Gamma-Ray Scanning, Safe and Secure Tradelanes (SST), and ISO/PAS 28000:2005 (Williams et al., 2009; Willis & Ortiz, 2004). After completing a comprehensive review of the literature, Williams et al. (2008) proposed four perspectives through which supply chain security can be viewed: (1) an intra-organizational perspective, (2) an inter-organizational perspective, (3) a combination of intra- and inter-organizational perspectives, and 4) the perspective of no security efforts. 38

52 Table 2.5 Definition of Constructs of Resilient Supply Chain Practices Construct Definition References Resilient Supply Chain Practices Flexible Redund ant Information Sharing Security Compliance Extent of postponement Extent of Collaboration Contingency Planning Safety Stock Slack Capacity The set of activities undertaken in an individual firm, aimed to achieve resilience and ensure risk mitigation The extent to which critical and proprietary information is exchanged with supply chain partners The application of policies, procedures, and technology to protect the destruction of supply chain assets (i.e., product, facilities, equipment, information and personnel) from theft, damage, or terrorism The ability of a company to move forward one or more operations or activities (making, sourcing and delivering) to a much later point in the supply chain to recognize and meet customers needs The extent to which supply chain entities are collaborating to cope with supply chain risks The series of specified business activities that are designed to deal with supply chain risks before they occur The extent to which a company is maintaining redundant stock (i.e., added inventory and extra components/parts) to absorb or cushion the detrimental effect of supply chain disruptions The extent to which a company is maintaining redundant capacity (i.e., extra production line, multiple sourcing, and alternative manufacturing facilities) to absorb or cushion the detrimental effect of supply chain disruptions Fisher, 1997; Wagner and Bode, 2008; Zsidisin, 2003; Li et al., 2005 Barratt and Oke, 2007; Hallikas et al., 2004; Li et al., 2005; Monczka et al., 1998; Paulraj et al., 2008; Tang, 2004 Bernasek, 2002; Lee and Wolfe, 2003; Ritter et al., 2007; Williams et al. 2008;William et al., 2009 Li et al., 2005; Beamon, 1998; Tang, 2006; Naylor et al., 1999; Van Hoek et al., 1999; Sheffi et al., 2003 Simatupang and Sridharan, 2002; Swink, 2006; Christopher and Peck, 2004; Mishra and Shah, 2009; Zsidisin and Smith, 2005; Lee, 2004; Svensson, 2004; Tomlin, 2006; Skipper and Hanna, 2009; Sheffi et al., 2003; Sheffi and Rice, 2005; Tang, 2008; Sheffi et al., 2003; Rice and Canatio, 2003; Chopra and Sodhi, 2004; Tomlin, 2006 Sheffi and Rice, 2005; Tang, 2008; Sheffi et al., 2003; Rice and Canatio, 2003; Chopra and Sodhi, 2004; Tomlin,

53 Ritter et al. (2007) have separated security issues within organizations into five categories, including shipping and storage, transportation, personnel, facility maintenance, and information security. Process flow, checklists, agreements for critical materials, backup communication with suppliers, maps, a formalized hierarchy, and clear documentation are intra-organizational elements that can be used to reduce supply chain security breaches (Helferich & Cook, 2002). The inter-organizational approach emphasizes organizational relationships among supply chain partners, public entities, and competitors (William et al., 2008). Moreover, Speckman and Davis (2004) has identified three major factors in establishing supply chain security: (1) management strategies, (2) government initiatives, and (3) operative routines and technical systems. Management strategies include managing supply chain risk and mitigating its negative impact, e.g. risk sharing contracts, operations decentralization, management training, and implementing total quality management (TQM) principles (Lee & Whang, 2005). Operative routines have been defined as the totality of procedures included in a firm s attempts to improve security against adverse disruptions. Technical systems also play an important role in implementing strategies and operative routines to enhance security. Operative routines may include restricting access to a facility, controlling carriers and drivers, providing personnel for security monitoring, educating employees regarding security issues, screening cargo, conducting inspections, and using mechanical or electronic seals. Technical systems include firewalls, closed-circuit television (CCTV), perimeter alarms, 40

54 application authentication devices, tracking devices, electronic seal systems, and other technical deterrents (Speckman and Davis, 2004). Lee and Wolfe (2003) have defined six strategies for mitigating the adverse effects of an insecure supply chain: (1) total supply network visibility, (2) comprehensive tracking and monitoring, (3) flexible sourcing projects, (4) product and process redesign, (5) balanced inventory management, and (6) demand-based management. In order to implement these strategies, an infrastructure that includes knowledge transfer and information visibility, a well-prepared workforce, agile logistics systems, readiness for rapid execution, and financial resources is necessary Extent of Postponement Extent of postponement refers to the ability of a company to move forward one or more operations or activities (making, sourcing and delivering) to a much later point in the supply chain to recognize and meet customers needs (Li et al., 2005; Beamon 1998; Lee and Billington, 1995; Naylor et al., 1999). Van Hoek et al. (1999) have categorized postponement into three types: (1) time postponement, (2) form postponement, and (3) place postponement. Time postponement refers to delaying the forward movement of goods. Form postponement refers to determining the form and function of products. Place postponement refers to positioning upstream inventories in the manufacturing process. Postponement strategies are appropriate to use with finished goods only after obtaining accurate information about customer preferences by differentiating them at the 41

55 end of the production stage (Lee, 2004). These conditions allow firms to execute reengineering changes to products and to adapt to sudden demand fluctuations and unexpected disruptions. Postponement is considered to be an important strategy that enables supply chains to become more resilient by increasing component commonality, standardizing manufacturing processes, and identifying demand differentiation (Sheffi et al., 2003; Sheffi, 2006). Tang (2006) has argued that postponement is a robust demand management strategy that leads to supply chain efficiency and supply resilience. According to Lee (1996), postponement is an effective strategy in enhancing supply chain efficiency when facing uncertain demands for diverse products. At the same time, postponement enables firms to better manage both internal and external risk by deferring a measure of the demand to a much later point in time (Tang, 2006). On March 17, 2000, a small fire broke out in a Philips semiconductor plant located in Albuquerque, New Mexico. After the fire, the water and smoke damage contaminated almost the entire stock of semiconductor chips that had been scheduled to ship to Ericsson and Nokia. Despite this destructive incident, Nokia was able to postpone the insertion of these chips into the final assembly process owing to their modular design concept. This strategy enabled Nokia to reconfigure its standardized phone design and adapt slightly different chips from other suppliers (Hopkins, 2005; Norrman & Jansson, 2004; Tang, 2006). In comparison, Ericsson, which not only had eliminated its supply bases and used a single supplier in an attempt to simplify its supply chain but also failed to quickly recognize the severity of the negative impact from the fire, had to face $400 million in lost sales and was driven out of 42

56 its mobile business (Norrman & Jansson, 2004). In addition, postponement offers Hewlett-Packard (HP) the highest level of flexibility and demand-risk mitigation (Tang & Tomlin, 2008) Extent of Collaboration Extent of collaboration is defined as the extent to which supply chain entities are collaborating to cope with supply chain risks. Extent of collaboration refers to the activities that create the conditions in which collaborative working becomes possible among entities in the supply chain to deal with supply chain disruptions. Simatupang and Sridharan (2002) have suggested that collaboration occurs when two or more independent companies work jointly to plan and execute supply chain operations with greater success than when acting in isolation (p. 19). Swink (2006) has argued that a firm s ability to collaborate with partners is a key element in achieving innovative success. Managing risk across supply chains is a network-wide task, and it is possible only with a high level of collaboration (Christopher & Peck, 2004). According to Mishra and Shah (2009), firms need to develop routines and practices that lead to collaboration among partners so they can achieve new product development (NPD) success. These authors have identified three types of collaborative activities that involve internal cross-functional employee teams, customers, and suppliers. They further found that supplier and customer involvement and inter-functional cooperation efforts are positively associated with enhancing organizational performance (Itter & Larcker, 1997; Langerak & Hultink, 2005). 43

57 In view of agency theory, Zsidisin and Smith (2005) have suggested that early supplier involvement reduces risk from product and supplier failures by managing outcome uncertainty, programming supplier tasks and accomplishments, creating goal congruence, avoiding adverse selection and moral hazards, and monitoring supplier activities. Involving customers in NPD processes enables design teams to respond quickly to evolving customer needs and preferences, thereby leading to reduced uncertainty in demand (Mishra & Shah, 2009). Christopher and Peck (2004) have suggested that visibility through collaborative planning with suppliers and customers prevents intervening inventory, the bullwhip effect, and supply disruptions by means of clear communication. Collaboration with suppliers and customers when responding to risk as well as redesigning products and processes gives firms that have experienced a disaster a head start over their competitors (Lee, 2004). Collaboration can provide a bond that unites the combined efforts of firms across the supply chain network and prevents disruption and crisis (Richey, 2009). Sheffi and Rice (2005) have argued that empowering those at the lowest level in the decision-making process to respond to disruptions quickly is an important tenet of organizational resilience. When front-line employees are empowered to take corrective actions quickly, firms are able to respond to disruptions more effectively. They can find out what kinds of decisions need to be made better than anyone in the organization. Supply chain partnership increases information flow and knowledge formation, reduces uncertainty, and enhances profitability by delivering low-cost, highquality products more quickly (Fiala, 2005). Supply chain collaboration leads to 44

58 minimum risk related to forecasting, better coordination of demand fulfillment, and cohesive market focus (Faisal et al., 2007; Fisher 1997) Contingency Planning Contingency planning is a key to achieving flexibility in that it is impossible to predict any disruptive event with 100% accuracy (LaLond, 2005). Contingency planning involves a series of events that are designed to take full advantage of a business opportunity or to reduce the impact of an event that generally would be disastrous to a firm. (Svensson, 2004, p. 729). At its core, contingency planning is designed to reduce supply chain vulnerabilities. There are two types of contingency planning: (1) contingency planning that is framed to assure business continuity in response to any form of disaster and (2) contingency planning that is uncertain and considers only various risks to a strategic plan (Simpkins, 2009). Contingency planning is effective only when disruptions occur. Tomlin (2006) has noted that rerouting and demand management are tactics of operational contingency. In response to disruptions, contingent-rerouting plans include increasing production at alternative locations, temporarily switching transportation, and shifting customer demand to alternative products. According to Skipper and Hanna (2009), contingency planning is a special type of planning that provides firms with a blueprint for managing risk related to unknown events. The contingency plan document must specify a timely and complete response to 45

59 diverse risks. The process components of the plan include risk assessment, risk evaluation and management, collaborative management, first response, security, operations, stability, subsequent stages of response, and performance evaluation (Skipper & Hanna, 2009). Sheffi et al. (2003) have suggested that organizational resilience is enabled by developing contingency planning that describes and defines the roles, procedures, duties, and responsibilities of key players in a firm in case of unexpected disruptions. All entities across the supply chain are required to have contingency plans and tools to take corrective actions when out-of-control conditions are detected (Lee & Christopher, 2004) Redundant Approach Safety Stock Safety stock refers to the extent to which a company is maintaining redundant stock (i.e., added inventory and extra components/parts) to absorb or cushion the detrimental effect of supply chain disruptions. Creating redundancy and enhancing flexibility enable firms to reduce the likelihood of disruptions and increase resilience. Safety stocks, extra inventory, multiple sourcing, extra capacity, and backup sites are examples of redundancy. Sheffi and Rice (2005) have argued that redundancy represents sheer cost with limited benefit and provides emergency cover. However, redundancy resources are needed only in the case of disruptions, causing unutilized capacity, idle inventory, reduced quality, and increased costs. Thus, redundancy disguises inefficiencies by inhibiting the advantages of a lean supply chain (Tang, 2008). 46

60 Sheffi et al. (2003) have noted that the goal of redundancy is to apply buffering practices by duplicating facilities and components, increasing inventories, and increasing the number of suppliers to ensure backup solutions are available and to reduce risk. Organizational resilience is achieved by both flexibility and redundancy, which consists of safety stock and underutilized capacity (Sheffi, 2006). Chopra and Sodhi (2004) have suggested a risk mitigation strategy that includes adding inventory and capacity, relying on multiple sources, increasing responsiveness and flexibility, and aggregating demand. Rice and Canatio (2003) have suggested that redundancy is a key factor in creating resilience. They refer to redundancy as additional capacity that can be utilized to substitute the capacity loss caused by disruptions. Tomlin (2006) has emphasized redundancy as a mitigation action. According to Tomlin, redundancy, which consists of multiple supplier sourcing, added inventory, and increased production capacity, refers to actions taken in response to disruptions that incur additional cost. Tang (2008) has introduced several types of potential redundancy, including extra back-up production capacity, extra inventory, and extra back-up suppliers. Sheffi (2005) has categorized redundancy into two elements: safety stock and slack capacity. According to Sheffi, safety stock, which includes extra inventory of raw materials, parts, and finished goods, prevents disruptions in demand and supply patterns by stockpiling extra supplies, parts, and products. As mentioned above, safety stock is detrimental to quality, cost, and delivery and prevents corrective actions to identify the source of problems by tapping into the parts inventory and replacing defective ones. 47

61 However, safety stock allows firms time to prepare a response and recover when faced with unexpected disruptions Slack Capacity Slack capacity refers to the extent to which a company is maintaining redundant capacity (i.e., extra production line, multiple sourcing, and alternative manufacturing facilities) to absorb or cushion the detrimental effect of supply chain disruptions. The second form of redundancy is slack capacity. When preparing for disruptions, firms build redundant production lines to produce components for their most important products and keep alternative facilities ready to respond. Some companies do not maintain full utilization rates of their production facilities because underutilized capacity serves as a cushion to absorb uncertainties on the demand side, and others require their suppliers to provide extra capacity. Examples of slack capacity include shadow flight, extra IT systems, redundant employee training, and alternative manufacturing facilities. Complete redundant capacity should be maintained for information technologies, especially within service industries, because service firms cannot have extra inventory and because service failures are costly. 2.6 Resilient Supply Chain Capability This study examines three types of resilient supply chain capabilities: readiness, response, and recovery. Ponomarov and Holcomb (2009) have identified three phases of a resilient supply chain: readiness, response, and recovery. These researchers have 48

62 suggested that event readiness (disaster preparedness), effective and efficient response (emergency response), and the ability to recover to an original or improved state (disaster recovery) comprise the essence of supply chain resilience. Reich (2006) also identified implications of the 3Cs for disaster planning and management. Control is meant to enable people to cope with disastrous circumstances by enabling them to set their own goals and make their own decisions. In this regard, excessive external help can lead to lack of control and long-term dependency. Coherence pertains to generating cognitive clarity by reducing uncertainty and creating processes and procedures. To provide increased understanding, knowledge, and information is critical in establishing order and structure related to coherence. Interconnectivity characterizes a resilient community (Allenby & Fink, 2005). Connectedness is a collective effort in dealing with disasters. This integral part of resilience plays an important role in establishing and maintaining supportive relationships as well as expanding and combining individual capacities. By matching the phases of the 3Rs with the 3Cs, Ponomarov and Holcomb (2009) have introduced elements that characterize resiliency within the supply chain within each phase: (1) readiness: logistic quality, efficiency, cost minimization, riskhedging capabilities, backups of systems and processes, effectiveness of logistical processes, systematic contingency planning, information technology upgrades, and supply chain relationship building; (2) response: timeliness, postponement, flexibility, agility, risk sharing, and information sharing; and (3) recovery: cycle-time reduction, delivery competency, customer service, efficiency of warehouse operations, knowledge management, and highly integrated systems and processes. 49

63 Lee (2003) has suggested that top-performing supply chain processes require agility, adaptability, and alignment to achieve sustainable competitive advantage over competitors. Agility refers primarily to the ability of firms to quickly manage short-term changes in supply and demand. Adaptability refers to the ability to redesign supply chain processes in response to market changes. Alignment refers to the process of building a network that is able to respond cooperatively to any change or disruption and establishing incentives for supply chain entities to maximize their own performance. Table 2.6 Definition of Constructs of Resilient Supply Chain Capabilities Construct Definition References Resilient Supply Chain Capabilities RSC Readiness Capability RSC Response Capability RSC Recover Capability The adaptive capability of the supply chain to prepare for unexpected events, respond to disruptions, and recover from them by maintaining continuity of operations at the desired level of connectedness and control over structure and function The ability to detect and prevent the source of possible disruptions to maintain the planned level of operations The ability to cope with the realized disruption by reorganizing supply chain resources quickly The ability of supply chain resources to return to the original or better state of operations by redesigning supply chain process Craighead et al., 2007; Lee, 2003; Ponomarov and Holcomb, 2009; Reich, 2006 Craighead et al., 2007; Lee, 2003; Ponomarov and Holcomb, 2009; Reich, 2006 Craighead et al., 2007; Lee, 2003; Ponomarov and Holcomb, 2009; Reich, 2006 Craighead et al., 2007; Lee, 2003; Ponomarov and Holcomb, 2009; Reich, 2006 Handfield (2007) has identified a supply chain triad, which includes three components of disruption management: disruption discovery, disruption recovery, and 50

64 supply chain redesign. Disruption detection involves the ability to detect and discover potential risks and disruptions that already have occurred because the more quickly that the problem is discovered, the more quickly detrimental effects can be reduced. In this regard, firms need to understand that various types of possible disruptions exist, develop systems to trace their sources, and improve their understanding of risk exposure. Disruption recovery involves reconfiguring the supply chain and controlling damage in order to mitigate the effects of disruptions that have been discovered. It involves responding to supply chain disruptions and identifying alternative resources. Redesigning the supply chain refers to re-optimizing supply chain processes to eliminate or reduce the likelihood of future disruptions. It requires a specific set of tools and systems to keep track of potential disruptions, and it requires collaboration among supply chain partners. Craighead et al. (2007) have categorized supply chain risk mitigation capabilities into two groups: recovery capability and warning capability. These mitigation capabilities have been proposed to moderate the relationship between supply chain design characteristics in terms of density, complexity, and node criticality and supply chain disruption severity. They define recovery capability as the interaction of supply chain entities and the corresponding coordination of supply chain resources to return the supply chain to a normal and planned level of product flow (p. 144). Warning capability refers to the ability to detect disruptions and disseminate pertinent information to relevant supply chain entities. 51

65 Drawing upon the above-mentioned research, this current study refers to resilient supply chain capability as the adaptive capability of the supply chain to prepare for unexpected events, respond to disruptions, and recover from these disruptions by maintaining continuity of operations at the desired level of connectedness and control over the supply chain structure and function. Readiness capability refers to the interaction and coordination of supply chain resources to detect and prevent sources of possible disruptions so that normal and planned levels of operation can be achieved and maintained. Response capability refers to the interaction and coordination of supply chain resources that enable firms to respond to and manage pending or realized disruptions and subsequently to disseminate pertinent information about the disruption to relevant entities within the supply chain. Recovery capability refers to interactions among supply chain entities and the corresponding coordination of supply chain resources to return the supply chain to the normal and planned level of product and process production. 2.7 Hypothesis Development Research Hypothesis 1 Figure 2-3 portrays the hypothesized model. In this study, four types of perceived risk are identified: internal, supplier, customer, and environmental. Management literature reflects three approaches when managing business risk: the classical approach, the transitional approach, and the process approach (Jauch & Kraft, 1986; Zhang 2001). The classical approach suggests that objective attributes of the business environment affect organizational structure, decision-making processes, and performance. The 52

66 transitional approach emphasizes that decision makers have choices and influence. The process approach suggests that the relationship between risk and system characteristics is mediated not by objective properties but rather by the perceptions of decision makers. More research has been conducted on perceptions of uncertainty rather than objective measures because perception is the basis on which decisions are most frequently made (Sitikin & Weingart, 1995; Kocabasoglu et al., 2007). Internal Risk H1a Flexible RSCPs Supply related Risk Customer related Risk External Risk H1b H1c H1d Risk Taking Propensity H2a H2b Redundant RSCPs H3a H3b RSC Capabilities Figure 2-3 Hypothesized Model Many researchers have studied the interrelationships among risk perception, risk propensity, and decision making. Risk perception and risk propensity are thought to have an impact on the selection of risk-reducing strategies and behavioral decisions (Cho & Lee, 2006; Sitkin & Weingart, 1995). By connecting risk perception to risk propensity, Petrakis (2005) has illustrated that entrepreneurs risk propensity plays a role in transforming environmental impacts and business cycles. He found that risk propensity 53

67 affects demographics, venture investments, and firm performance. Folani and Mullins (2000) conducted a regression analysis of risk propensity and risk perception and found no significant relationship between them. These researchers subsequently concluded that risk propensity does not necessarily affect risk perception but rather new venture choice. These results are consistent with studies of consumers choice indicating that tasks involving judgment require different cognitive processes. Kocabasoglu et al. (2007) have argued that the level of risk perception is related to the extent to which executives discourage or support managers from making risky decisions. Perceived risk consists of four sub-dimensions: dynamism, munificence, heterogeneity, and hostility (Aldrich, 1979; Hitt et al., 1998; Kocabasoglu et al., 2007). According to Kocabasoglu et al. (2007), dynamism refers to how rapidly change occurs in product design, customer requirements, and technology. Munificence refers to the extent to which organizational external factors support the growth of a firm. Heterogeneity refers to the characteristics that differentiate firms from each other, which means that the more heterogeneous markets and industries are, the more complex and uncertain they are. Hostility refers to the degree of competition and regulation within an industry, which suggests that strong competition and strict regulations lead to a high level of hostility. Based on four aspects of uncertainty, Kocabasoglu et al. (2007) have related uncertainty to risk propensity. These researchers have suggested that firms within a growing industry would be more willing to engage in risky actions than to take advantage 54

68 of growth opportunities. In order to reduce uncertainty and deal with risk, firms frequently collect information about the external environment in dynamic business climates and are willing to accept risk in order to establish trust and collaboration with dependable partners in terms of information sharing (Daft & Lengel, 1986; Das and Joshi, 2007; Kocabasoglu et al., 2007). If firms need to face a wide range of various customer preferences and requirements, they are more likely to seek risks by regarding these customer preferences as opportunities. Miller and Friesen (1983) have concluded that successful firms in a dynamic business climate and various demands are likely to have higher risk-taking tendencies compared to unsuccessful firms. They argue that the more competitive that the business climate becomes, the less likely it is that firms will take risks. Makhija and Stewart (2002) have argued that the more uncomfortable firms feel in dealing with risk, the fewer level of risk propensity they show. On the contrary, firms that are exposed to constant uncertain situations tend to develop skills to make decisions under uncertainty. They are likely to face risk with a higher level of comfort and have a greater risk taking propensity. Miller (1983) have also argued that the more risk taking firms are, the more likely they engage in risky behavior and show bold acts to accomplish their goals. Firms that reward managers who make more programmed decisions tend to have more risk taking propensity (Sitkin and Pablo, 1992; Makhija & Stewart, 2002). Therefore, it is hypothesized that: 55

69 Hypothesis 1a: The higher level of internal risk that a firm perceives, the higher level of risk taking propensity that a firm will exhibit. Hypothesis 1b: The higher level of supply-related risk that a firm perceives, the higher level of risk taking propensity that a firm will exhibit. Hypothesis 1c: The higher level of demand-related risk that a firm perceives, the higher level of risk taking propensity that a firm will exhibit. Hypothesis 1d: The higher level of external risk that a firm perceives, the higher level of risk taking propensity that a firm will exhibit Research Hypothesis 2 Willingness to deal with risks impacts whether risky decisions occur or not (MacCrimmon & Wehrung, 1986). Risk propensity has been regarded as one of the main determinants of actions taken under risky circumstances. Kocabasoglu et al. (2007) have argued that higher risk propensity increases the likelihood that organizations will engage in risky behaviors. Keil et al. (2000) have suggested that there is a significant positive relationship between risk propensity and decision-making behavior. Tabak and Barr (1999) and Forlani et al. (2002) have noted that risk taking propensity affects intentions to adopt technological innovations and risk-taking action in the decision-making process. Since high risk propensity is likely to outweigh potential return, it will lead to risk-taking behavior by means of increasing the involvement in risky environments. Fellner and Maciejovsky (2002) have indicated that risk-seeking investors are more likely to exercise aggressive investment strategies and engage in more frequent turnover of their 56

70 asset portfolio than risk-avoiding investors. Wood and Zaichkowsky (2004) have suggested that there is a significant relationship between investment risk and stock trading frequency. Organizational risk-taking propensity is characterized by a tendency to engage in risky projects, a preference for taking bold actions when dealing with risk, and a willingness to commit to resource investment (Miller & Friesen, 1983; Miller, 1983). Researchers have suggested that the more willing firms are to deal with risks, the more likely they are to become innovative and creative (Nystrom, 1990; Shalley & Gilson, 2004). Calntone et al. (2003) have shown that risk-taking propensity is positively associated with the level of new product development. Gilley et al. (2002) have argued that the more risk-averse a management team is, the less likely it is to commit resources to new products and technologies. According to Gilley at al., risk-taking firms tend to exhibit behaviors that result in launching new products, providing new services, and using innovative technologies. Thus, risk taking propensity is also expected to influence risk-related behavioral practices and outcomes. The willingness of firms to deal with risks and make their resource commitments influences the development of routines in the presence of supply chain risks. This study formulates the following hypothesis predicting the positive effect of risk taking propensity both on the flexible and redundant approaches to managing risk. Therefore, it is hypothesized that: 57

71 Hypothesis 2a: The higher level of risk taking propensity that a firm exhibits, the higher level of flexible RSC practices that a firm will implement. Hypothesis 2b: The higher level of risk taking propensity that a firm exhibits, the higher level of redundant RSC practices that a firm will implement Research Hypothesis 3 Information sharing has been found to reduce substantially the bullwhip effect across the supply chain (Dejonckheere et al., 2004; Barratt & Oke, 2007). Many researchers have reported that information sharing leads to better coordination of price, improved decision making and physical movement, and optimal inventory holding policies (Closs et al., 1997; Whang, 1995; Corbett & Tang, 1999; Garvirneni et al., 1999; Barratt & Oke, 2007). Information sharing concerning product design and procurement is likely to reduce the cost of protecting opportunistic behavior and improve product quality (Carr & Pearson, 1999; Paulraj et al., 2008). Many supply chain disruptions could be alleviated by true and real-time demand information sharing among supply chain partners (Mason-Jones, 1998; Barratt & Oke, 2007). Through information sharing and tight integration of information systems across supply chain entities, Cisco s ehub connects multiple suppliers and provides them with a complete picture of capacity crunches, supply failures, and problem resolution paths (Lee & Wolfe, 2003). Van Hoek et al. (1999) have suggested that those who adopt postponement strategies in their operation improve their supply chain flexibility and balance customer requirements with global efficiency (Lee, 2002). Postponement and build-to-order 58

72 operations enable firms to deal with supply shortages using diversified parts and semifinished materials (Sheffi, 2006). Accordingly, Hewlett-Packard (HP) was able to respond to supply and demand mismatches with a postponement strategy that increased resilience, and Intel s Systems Group reduced its product mix of 2,000 types to 35 types of capacitors, resistors, and diodes. Using commodity parts and modular design allows firms to simplify operations and generate flexibility, in turn reducing time to market and time to recover from disruptions. Postponement is regarded as an acceptable and preferred way to manage demand uncertainties due to the imprecise information about customer preference (Lee, 2004). Sheu et al. (2006) have found that Customer-Trade Partnership against Terrorism (C-TPAT) certification impacts international supply chain collaboration. Firms that implement C-TPAT are expected to benefit through lower costs, border inspections, and customer satisfaction. Thibault et al. (2006) have suggested that security initiatives foster cooperative relationships between industry and government. Sarathy (2006) has concluded that supply chain security efforts are likely to raise visibility, lower total cost, and enhance tracking and shipping data. Peleg-Gillai et al. (2006) have found that security efforts lead to improved relationships and profitability. Rice and Spayd (2005) have shown that efforts to maintain and increase security lead to collateral benefits, such as reducing theft, minimizing delays in shipping, decreasing equipment damage, and lowering inspection costs. Rice and Caniato (2003) have suggested that security-related activities lead to supply chain security and resilience. 59

73 Developing collaborative relationships with customers and suppliers enables firms to work together in designing and redesigning supply chain processes; these relationships can also facilitate and promote effective contingency planning in case of disruptions (Lee, 2004). Christopher and Peck (2004) have suggested that higher levels of collaboration among supply chain entities increase the likelihood that supply chain risks can be mitigated. Collaborative activities can prevent opportunism and postproduction problems (Srinvasan & Brush, 2006). Sheffi and Rice, Jr. (2005) have suggested that empowerment is one of the most important aspects of supply chain resilience. Firms can respond to disruptions quickly and properly by empowering front-line employees to initiate corrective actions because front-line employees often are more capable than top management is in taking immediate and effective corrective action. Zsidisin and Smith (2005) have shown that early supplier involvement is effective in managing supply risk by reducing product failure and supplier failure. Sheffi et al. (2003) have emphasized the importance of contingency planning in achieving organizational resilience. They have explained that contingency planning consists of describing precise procedures to follow and defining the respective roles associated with those procedures in times of disruptions. When these plans are implemented, they become significant ingredients within a resilient organization. Through war gaming, simulations, drills, and mock exercises, firms can improve plans and indentify unaddressed issues. Giunipero and Eltantawy (2004) have reported that contingency planning for transportation risk provides firms with alternative transportation modes, which guards against supply disruption. Tomlin (2006) has suggested that 60

74 operational contingencies, such as rerouting, are the key components of any disruptionmanagement strategy. Responding to perceived supply risk, purchasing firms create contingency planning and implement buffer strategies that result in process improvement (Zsidisin et al., 2000). Therefore, it is hypothesized that: Hypothesis 3a: The higher level of flexible RSC practices that a firm implements, the higher level of RSC capabilities that a firm will achieve. Bourgeois (1981) has stressed the importance of organizational slack when managing a variety of different risks. Hendricks et al. (2009) have reported that the more operational slack that exists in the supply chain, the less likely it is that a negative stock market reaction will occur, using cash-to-cash cycle, days of inventory, and sales over assets as proxies of operational slack. Many researchers have argued that safety stock and excessive capacity can mitigate the negative impact of supply chain disruptions because they provide the components of resilience, such as flexibility and redundancy (Christopher & Peck, 2004; Tomlin, 2006; Tang, 2008; Sheffi, 2006). It has been suggested that multiple suppliers, backup systems, excess capacity, and buffer practices can lower the likelihood of disruptions and reduce their detrimental effect (Kleindorfer & Sadd, 2005; Lee, 2004). Firms need to identify areas where a lack of safety stock and slack capacity can disrupt their normal operations and thereby convince investors that building organizational slack is an effective practice. Sheffi (2005) has suggested that firms employ dual inventory systems, which requires adding some 61

75 inventory as a strategic emergency stock apart from normal inventory (Williams et al., 2008). Instead of seeking various suppliers to produce the same component, firms are required to create multiple supply sources with appropriate and adequate manufacturing capacity so that they are able to choose alternative suppliers that can produce the same product quality and supplier dependability when both of these qualities are needed. Therefore, it is hypothesized that: Hypothesis 3b: The higher level of redundant RSC practices that a firm implements, the higher level of RSC capabilities that a firm will achieve. 62

76 Chapter 3 Research Methodology (Item Generation and Pilot Study) To empirically test hypothesized relationships between the constructs defined in Chapter 2, valid and reliable scales need to be developed. This chapter describes the instruments used to measure the following constructs: (1) internal risks, (2) supplierrelated risks, (3) customer-related risks, (4) environmental risks, (5) risk taking propensity, (6) resilient supply chain practices, and (7) resilient supply chain capabilities. According to Nunnally (1978) and Churchill (1979), constructing valid and reliable measures requires four stages. To verify and refine the validity and reliability of this instrument, a four-step process is taken. First, a broad and comprehensive literature review enables clear construct definition, the generation of initial items, and solid theory development. Second, a pretest based on structured interviews with academicians and practitioners clarifies the meaning and definition of each item and provides a clear path for following instructions about response options. Academicians and practitioners are asked to provide feedback and comments on the drafts of the initial items. Accommodating their feedback, items are changed, revised, and or omitted to ensure content validity. Third, a pilot study is conducted by sending a questionnaire to a relatively small number of respondents who accurately represent target samples. The purpose of the pilot study is to pre-assess reliability and construct validity of each scale and to finalize the development of the 63

77 instrument with refined items prior to conducting a large-scale survey (Li, 2002). Fourth, a large-scale survey is distributed and data is collected and analyzed using the AMOS 6.0 structural equation modeling (SEM) to test the proposed hypotheses and report the statistical results. 3.1 Item Generation Content validity is a basic and important requirement when generating an effective instrument that captures the main domain of each construct (Churchill, 1979; Li, 2002). One method used to achieve content validity is to conduct a comprehensive literature review as well as structured interviews with academicians and practitioners who are experts in the research area under investigation. Through an extensive literature review, this study generated a preliminary pool of items and assigned each item to a specific construct category. Out of 15 constructs, 9 constructs were adopted and changed based on existing studies: (1) internal risk, (2) supplier-related risk, (3) customer-related risk, (4) environmental risk, (5) risk taking propensity, (6) postponement, (7) information sharing, (8) collaborative activity, and (9) contingency planning. Six constructs were defined and developed: (1) security initiatives, (2) safety stock, (3) extra capacity, (4) readiness capability, (5) response capability, and (6) recovery capability. In formulating the research framework, this study presents three levels of supply chain resilience: (1) the antecedent level, (2) the practice level, and (3) 64

78 the capability level. A five-point Likert scale was used to measure respondents perceived risk and their attitudes about risk. The items that measure perceived risk were generated by adopting and revising items from previous studies in the area of supply chain management, logistics, and operations management (Juttner et al., 2003; Kiser & Cantrell, 2006; Tapierco; Chopra & Sohdi, 2004; Viswanadham & Gaonkar, 2008; Choi & Krause, 2006; Manju et al., 2008; Rao & Goldsby, 2009; Bartezzaghi & Verganti, 1995; Trkman & McCormack, 2009; Tang, 2006, 2008; Wagner & Neshat, 2009; Manju et al., 2008; Gupta & Wilemon, 1990; Rao & Goldsby, 2009). Following Juttner et al. s (2003) framework, this study identifies perceived risk within a company, within the supply chain network, and outside the respective supply chain. Items were classified into four subscales to measure each domain of risk perception: (1) internal, (2) supply, (3) customer, and (4) external. The items designed to measure risk taking propensity were generated by conducting literature reviews within the following domains: consumer behavior, management, marketing, and supply chain management (Sitkin & Pablo, 1992; Weber et al., 2002; Sharma et al., 2009; Keil et al., 2000; Kocabasoglu et al., 2007; Gilley et al., 2002; Das & Joshi, 2007; Zsidisin et al., 2000; Cho & Lee, 2006). The items related to risk taking propensity were measured at the organizational level. Resilient supply chain practices are based on two approaches: a flexible approach and a redundant approach. A five-point Likert scale was used to measure managers 65

79 perceptions of the extent to which different types of resources and activities achieve supply chain resilience. Items were generated in seven dimensions at the practice level. A flexible approach includes information sharing, postponement, contingency planning, security compliance, and collaboration. The items for a flexible approach were generated by reviewing relevant research literature in the following areas: supply chain management, risk management, ecology, psychology, and economics (Barratt & Oke, 2007; Hallikas et al., 2004; Li et al., 2005; Monczka et al., 1998; Paulraj et al., 2008; Tang, 2004; Zhu & Benton, Jr., 2007; Ritter et al., 2007; Williams et al., 2008; William et al., 2009; Van Hoek et al., 1999; Sheffi et al., 2003; Swink, 2006; Christopher & Peck, 2004; Zsidisin & Smith, 2005; Svensson, 2004; Tomlin, 2006). A redundant approach consists of safety stock and slack capacity to allow firms to obtain slack and redundancy in absorbing the detrimental effect of supply chain risks. Items designed to measure perceptions about a redundant approach were generated by reviewing research literature in the following areas: strategic management, logistics, and supply chain management (Sheffi & Rice, 2005; Tang, 2008; Sheffi et al., 2003; Rice & Canatio, 2003; Chopra & Sodhi; 2004; Tomlin, 2006). This study identifies three dimensions of resilient supply chain capabilities: readiness, response, and recovery. New definitions were created for the constructs used in this study to measure resilient supply chain capabilities, including external-facing capabilities, which enable firms to maintain normal levels of operation regardless of supply chain risk. The items were created by adapting the concepts of risk mitigation 66

80 capability and redesigning capability (Craighead et al., 2007; Handfield, 2007; Lee, 2003). 3.2 Pre-test and Structured Interviews After the initial items were generated, the questionnaire was sent to content experts, including six professors and four practitioners. The purpose of the pre-pilot test was to assess whether each item measures the domain of the corresponding construct and to check the clarity and consistency of each item in terms of wording, length, and concept. These professors and practitioners were asked to review the questionnaire and point out any items they believed needed to be changed, dropped, or added (Zhang, 2001). After receiving their feedback and comments, the items were modified accordingly and included in the pilot study. The questionnaire was pretested by two practitioners and two academicians each for both the English version and the Korean version. The definitions of each construct were explained to them in advance. After consulting with these professionals for one to two hours during face-to-face meetings and one day s review on their own, each of the eight participants was asked to provide feedback and comments on the questionnaire to improve content validity. The rationale for selecting these participants was that all the practitioners each had more than eight years of experience in the manufacturing sector and academicians each had published more than five articles in the area of operations and supply chain management. If they believed that any items were unable to capture the 67

81 main domain of each respective construct, they were also asked to suggest new items. Incorporating their corrections, suggestions, and feedback, this study modified and revised the instrument as needed. After the pre-test and structured interviews, the second version of the questionnaire was ready for pilot testing using the Q-sort method. 3.3 Pilot Study Using the Q-sort Method Four practitioners who were not involved in the pre-test were chosen and asked to participate in the Q-sort. Two rounds of Q-sort were conducted, and each round was completed by two practitioners Judge 1 and Judge 2. After they were provided the definitions, both were asked to decide which item best described one of 15 constructs to the best of their knowledge. In case they found an item that they could not categorize, a not available category was provided, and when an item was placed into this category, each judge was asked to provide the reason for doing so and an appropriate name for this potentially new category. To analyze the results of the Q-sort and measure the reliability of the instrument, this study used (1) the inter-judge agreement raw score and (2) Cohen s Kappa (Cohen, 1960). The inter-judge agreement raw score was calculated by adding up the number of items that both judges agreed to put into the same category and dividing it by the total number of items. Cohen s Kappa coefficient is a statistical measure of inter-judge reliability. It measures the agreement between two judges who classify X items into Y mutually exclusive categories separately (Selart et al., 2008). Since Cohen s Kappa 68

82 considers the agreement occurring by chance, it is regarded as a more robust measure than the simple agreement score (Selart et al., 2008) First-round Q-sort The results of the first and second rounds of Q-sort are reported in Table 3.1 and 3.2 The inter-judge raw score was 66.66%, and Cohen s Kappa coefficient was Fleiss (1981) indicated that Kappa coefficients below 0.4 are considered poor, coefficients between 0.4 and 0.75 are considered fair to good, and coefficients higher than 0.75 are considered excellent. According to Fleiss scale, Cohen s Kappa coefficient (0.642) reached an acceptable level but could be improved. The items in the off-diagonal needed to be reexamined and reworded. By analyzing them and incorporating the feedback of the judges, this study reworded several items, omitted three items and added five items. The total number of items was increased to 98 for the second-round Q-sort Second-round Q-sort For the second-round Q-sort, as shown in Table 3.3, the inter-judge raw score was 77.55% and Cohen s Kappa coefficient was Since the Kappa coefficient reached the excellent level (i.e., higher than 0.75) after conducting the second round Q-sort, the stability of the instrument was established, and the large-scale survey questionnaire was ready to be distributed. The number of final items for each construct and its subdimensions for the large-scale survey is listed in Table

83 Judge 2 Table 3.1 Inter-judge Agreement Raw Score (Round 1) Judge N/A N/A Total Number of Placement: 96 Number of Agreement: 64 Raw Agreement: 66% 1. Internal Risk; 2. Supply Risk; 3. Customer Risk; 4. External Risk; 5. Risk Taking Propensity; 6. Extent of Postponement; 7. Information Sharing; 8. Security Compliance; 9. Extent of Collaboration; 10. Contingency Planning; 11. Safety Stock; 12. Slack Capacity; 13. Resilient Readiness Capacity; 14. Resilient Response Capacity; 15. Resilient Recovery Capacity 70

84 Judge 2 Table 3.2 Inter-judge Agreement Raw Score (Round 2) Judge N/A N/A 0 Number of Agreement: Total Number of Placement: 98 Raw Agreement: 77% Internal Risk; 2. Supply Risk; 3. Customer Risk; 4. External Risk; 5. Risk Taking Propensity; 6. Extent of Postponement; 7. Information Sharing; 8. Security Compliance; 9. Extent of Collaboration; 10. Contingency Planning; 11. Safety Stock; 12. Slack Capacity; 13. Resilient Readiness Capacity; 14. Resilient Response Capacity; 15. Resilient Recovery Capacity 71

85 Table 3.3 Inter-judge Agreement Raw Score Summary Agreement Measures Round 1 % Round 2 % Summary Cohen s Kappa Placement Ratio Summary 66.66% (64/96) 77.55% (76/98) Internal Risk 7 88% 4 50% Supply-related Risk 7 100% 6 86% Demand-related Risk 7 100% 6 86% External Risk 6 75% 8 100% Risk Taking Propensity 6 100% 5 83% Extent of Postponement 4 67% 5 83% Information Sharing 6 100% 3 50% Security Compliance 4 67% 5 83% Extent of Collaboration 1 14% 3 43% Contingency Planning 2 28% 5 71% Safety Stock 1 100% 5 83% Slack Capacity 2 33% 6 100% RSC Readiness Capability RSC Response Capability 2 40% 4 67% 3 50% 5 83% RSC Recover Capability 5 83% 6 100% Average 72

86 Table 3.4 Final Items for Large-scale Survey Construct Sub Dimension Number of Items Organizational risks Internal Risks 8 Network risks Supply-related Risk 7 Demand-related Risk 7 Environmental risk External Risks 8 Risk Taking Propensity 6 Information Sharing 6 Security Compliance 6 Flexible Resilient Supply Chain Practices Extent of Postponement 6 Extent of Collaboration 7 Contingency Planning 7 Redundant Resilient Supply Chain Practices Safety Stock 6 Slack Capacity 6 RSC Readiness Capability 6 Resilient Supply Chain Capabilities RSC Response Capability 6 RSC Recover Capability 6 Total Sampling Plan The final items are related to sourcing, manufacturing, and logistics activities, and they focus on product and information flow along the supply chain. The selection of 73

87 respondents and their respective industries was enabled by a series of structured interviews and a pilot test to suit the needs and purposes of this study. Before large-scale data collection was conducted, respondents were chosen among supply chain managers, plant managers, manufacturing managers, purchasing managers, vice presidents, and presidents of organizations from industries within six Standard Industrial Classification (SIC) codes: 28 (Chemicals and Allied Products), 33 (Primary Metal Products), 34 (Fabricated Metal Products), 35 (Industrial and Commercial Machinery and Computer Equipment), 36 (Electronic, Electric Equipment and Components), and 37(Transportation Equipment). Table 3.5 Data Collection and Response Rate Country Sample Questionnaire Sent Total Received Response Rate Missing Value USA % 14 Korea % 9 Total % 23 The -based survey was conducted both in the U.S. and in South Korea. In the U.S., mailing lists from Orbitinternationalgroup.com, Specialdatabases.com, and the APICS the Association for Operations Management (American Production and Inventory Control Society) were obtained. To obtain the Korean data, the top 500 firms were selected from the Korea Composite Stock Price Index (KOSPI) and the Korean Securities 74

88 Dealers Automated Quotations (KOSDA) as an initial target sample. For both countries, each respondent s company fell within one of the above-mentioned six target industries. Table 3.5 shows the results of the data collection process as well as the response rate. Data was collected for four months (from mid-january to mid-may 2011). For the data collection in the U.S., the first , which included a brief overview of the survey questionnaire, was sent to the initial respondents. In the , the survey link that directs them to the actual online survey questionnaire was also included. If they agreed to participate, they were then asked to click on the link and begin completing the questionnaire. A reminder was sent out every two or three weeks. For the Korean data, an initial phone call was made to 500 respondents explaining the purpose of this study and requesting their participation. The link to the online survey questionnaires was sent to those who expressed their interest via . A reminder was sent those who did not complete the survey questionnaire within two weeks. A follow-up telephone was conducted as a final reminder. A total of 71 respondents from the U.S. and 115 respondents from Korea completed surveys, which resulted in a response rate of 4.7% and 22.8%, respectively Sample Characteristics Table 3.6 shows the sample characteristics of the respondents who completed surveys regarding their respective business units; characteristics included the number of employees, sales volume, job titles, and number of years of experience. All of the characteristics show that no single category accounts for more than 50% of the total 75

89 Table 3.6 Sample Characteristics Variables (n=163) Frequency Percentage (%) Business Unit Company 79 48% Division 21 13% Plant 59 36% Others 4 2% Number of Employee % % % % 1000 and over 52 32% Unidentified 3 2% Sales Volume < % % % % Over % Unidentified 3 2% Job Title CEO / Present 2 1% Vice Director 7 4% Director 5 3% Manager % Others 41 32% Years Under 2 years 8 5% % % % Over 20 years 20 12% Unidentified 2 1% 76

90 response, which demonstrates that the sample data is well dispersed and that coverage is good for each category. The majority of respondents (66%) were comprised of middle managers, who tended to be more available to complete the questionnaire than executive managers Non-response Bias Test Armstrong and Overton (1977) have suggested that the late return of surveys from slow responders represents the opinions of non-respondents, also referred to as nonresponse bias. Non-responses lower the validity of a measurement; however, a common method of testing non-response bias is to check for statistically significant differences between participants who responded quickly and those whose responses were delayed (Krause, 1999; Prahinski & Benton, 2004). After dividing the 163 survey responses into two groups (80 for the early response and 83 for the delayed response), half of the total items (49 out of 98) were randomly selected and a t-test between the two groups was conducted. The results indicate that there are no statistically significant differences between these two groups of 49 items. Therefore, it is concluded that the data set is an unbiased sample. 77

91 Chapter 4 Large-Scale Instrument Validation After large-scale data collection has been completed, a data set is ready for instrument validation, statistical analysis, and hypotheses testing. The instrument validation consists of first-order and second-order confirmatory factor analysis (CFA) to test reliability, validity, and validation of the second-order constructs. Chapter 4 discusses instrument assessment methodology and instrument validation. Chapter 5 focuses on path analysis using structural equation modeling (SEM). 4.1 Instrument Assessment Methodology Using 163 responses, this study assessed the large-scale measurement instrument by testing its reliability and validity. The general concept of validity refers to content validity, convergent validity, and discriminant validity. Hair et al. (2006) has defined reliability as an assessment of the degree of consistency between multiple measurements of a variable (p. 137). Reliability is an important concept that concerns the repeatability of a measurement. Measurement is regarded as reliable if the results of a questionnaire are identical after respondents complete it a second time under the same conditions. The most commonly used measure for reliability is Cronbach s alpha (Cronbach, 1951). If the value of alpha of any measurement is 0.7 or above, it indicates a good measurement (Nunally, 1978). Bagozzi and Yi (1998) have suggested that item-factor loadings of

92 are also considered adequate and indicate reliable measures. Another measure of reliability is the Correlated Item-Total Correlation (CITC). This formula measures how well each item belongs to the domain of each construct and contributes to the internal consistency of the instrument (Kerlinger, 1978). If a CITC coefficient for any item is below 0.5 and increases the alpha value if deleted, the item is not measuring what other items are measuring and needs to be omitted (Torkzadeh & Dhillon, 2003). Content validity determines whether measures represent the domain of the construct. Content validity exists when there is a general agreement among practitioners and academicians that measurement items accurately define and measure important aspects of the construct under investigation (Kaynak & Hartley, 2006; Li et al., 2005). Content validity is evaluated by one of the procedures listed below rather than statistical testing: (1) a comprehensive literature review, (2) measurement evaluation by practitioners and academicians, and (3) a pilot study or Q-sort procedure. This study implemented all three procedures to check the content validity of the instrument. Hair et al. (2006) has defined convergent validity as the extent to which indicators of a specific construct converge or share a high proportion of variance in common (p. 771) and discriminant validity as the extent to which a construct is truly distinct from other constructs (p. 771). Convergent validity is the degree to which measured variables actually represent the latent construct that they have been designed to measure. If the standardized factor loadings on their respective constructs are greater than 79

93 twice their standard errors and statistically significant, convergent validity is considered acceptable (Anderson & Gerbing, 1988; Kaynak & Hartley, 2006). Discriminant validity assesses how distinct constructs are from one another. The average variance extracted (AVE) is used to evaluate the discriminant validity. There are two ways to verify discriminant validity using the AVE value: First, if the AVE value for each construct is greater than the squared correlation between that construct and other constructs in the model, discriminant validity can be assessed. The recommended threshold value is 0.5 or above (Ewing & Napoli, 2005). Second, discriminant validity is assessed if the square root of the construct s AVE is greater than the correlations of the construct with all other constructs (Fornell & Larcker, 1981). Validation of the second-order constructs determines whether the second-order model exits. The validation process follows three steps: 1) compute χ2 value of a firstorder CFA model of a construct; 2) compute χ2 value of a second-order CFA model of a construct; 3) compute the T-coefficient (χ2 value of a first-order CFA model of a construct over χ2 value of a second-order CFA model of a construct). If the value of T- coefficient is 0.80 or above, the existence of the second-order construct is validated (Doll et al., 1995). The T-coefficient value cannot be validated for any second-order construct with less than four first-order constructs. In that case, the existence of the second-order construct is validated if the factor loading of each dimension is 0.5 or above (Liao, 2009). 80

94 4.2 Large-scale Measurement Model The results of instrument assessment and measurement models are reported in Tables 4.1 through 4.4. Reliability, validity, and validation of the second-order constructs are assessed in subsections 4.1 through 4.4. Table 4.1 Reliability and Convergent Validity for Antecedents of Resilient Supply Chain Practices Label Items Standardized loading Internal Risk (IR) Our business is adversely affected by our internal: IR1 machine breakdowns IR2 labor problems (e.g., strike) IR3 operational accidents (e.g., fires or truck accident) IR4 utility outages 0.41 IR5 IT system breakdowns (e.g., virus attack and network delays) IR6 equipment operating out of specifications IR7 financial instability (e.g., late payment) IR8 lack of highly skilled employees Supply-related Risk (SR) Our business is adversely affected by our suppliers : SR 1 abrupt capacity fluctuations SR 2 inconsistent product quality SR 3 poor delivery performance (i.e., delivery dependability) SR 4 financial instability (e.g., late payment) SR 5 inability to adapt to required product design or technological changes SR 6 conflict with us regarding intellectual property ownership (e.g., counterfeit and forgery) SR 7 alliance with our direct competitor Customer-related Risk (CR) Our business is adversely affected by our customers : CR 1 inaccurate information about order quantities CR 2 sudden demand increases which often go beyond our capacity CR 3 financial instability (e.g., late payment) CR 4 high variation in their demand that affects our master production plan (e.g., rescheduling) CR 5 unpredictable requirements for product features CR 6 frequently changing product preferences CR 7 orders for different product combinations External Risk (ER) Our business is adversely affected by following problems outside our organization: Cronbach s alpha

95 ER 1 Political instability (e.g., new laws, stipulations, war, civil unrest) ER 2 Diseases or epidemics (e.g., SARS, Foot and Mouth Disease, H1N1) 0.57 ER 3 Natural disasters (e.g., earthquake, flooding, extreme climate change, tsunami, ash cloud) 0.68 ER 4 International terror attacks ER 5 Macroeconomic uncertainties (e.g., currency fluctuation, inflation) ER 6 Regulatory barriers for supply chain operations (e.g., customs, tariffs) ER 7 Legislation or international standards changes for supply chain operations (e.g., ISO9000, transportation laws) 0.63 ER 8 Fast and frequently changing technology in our industry Risk Taking Propensity (RP) Our company : RP 1 has a tendency to take on high-risk projects with chances of above average rates of return on our investment RP 2 provides rewards for innovative suggestions (e.g., bonuses, time off) RP 3 has a tendency to take the first mover s advantage by leading the competition RP 4 is willing to put some proportion of savings in uninsured investments for the sake of higher return RP 5 makes quick decisions if we believe high-risk projects will provide a new competitive advantage RP 6 is willing to take substantial risks to realize significant financial gains from investments Table 4.2 Reliability and Convergent Validity for Flexible Resilient Supply Chain Label EP 1 EP 2 EP 3 EP 4 EP 5 EP 6 Items Practices Extent of Postponement (EP) Our products are designed to use standard sub-assemblies for modularity Our company delays final product assembly activities until the last possible position (or nearest to customers) in the supply chain Our goods are stored at appropriate distribution points close to the customers in the supply Our production process modules can be re-arranged so that customization can be carried out later at distribution centers Our company delays final product assembly activities until customer orders have actually been received (e.g., assemblyto-order) Our product designs enable us to accommodate several generations of products Standardized loading Cronbach s alpha Information Sharing (IS) IS 1 Our company shares our business units proprietary

96 information (e.g., production, financial, design, and risk) with supply chain partners IS 2 Our company informs our supply chain partners of changing needs of customers in advance IS 3 Our supply chain partners share their proprietary information with us IS 4 Our supply chain partners share their business knowledge of core business processes with us Our company and supply chain partners keep each other IS 5 informed frequently and in a timely manner about events or changes that may affect other partners IS 6 Our company and supply chain partners exchange information that helps in the establishment of business planning Security Compliance (SC) Our company: SC 1 includes supply chain partners in our goal-setting activities and planning SC 2 regularly solves problems jointly with our supply chain partners SC 3 involves supply chain partners early in the new product design and development effort SC 4 works jointly with supply chain partners to plan and execute supply chain operations SC 5 is jointly responsible with supply chain partners for making sure that disruptions are properly handled SC 6 collaborates with supply chain partners in managing disruptions Extent of Collaboration (EC) Our company: EC 1 includes supply chain partners in our goal-setting activities and planning EC 2 regularly solves problems jointly with our supply chain partners EC 3 involves supply chain partners early in the new product design and development effort EC 4 works jointly with supply chain partners to plan and execute supply chain operations EC 5 is jointly responsible with supply chain partners for making sure that disruptions are properly handled EC 6 collaborates with supply chain partners in managing disruptions EC 7 regards the collaboration with supply chain partners as important in risk management Contingency Planning (CP) Our company: CP 1 prepares a set of contingency action plans for unexpected disruptions CP 2 assigns roles and responsibilities for particular types of disruptions CP 3 involves our supply chain partners in developing contingency plans CP 4 jointly develops contingency plans along with our supply chain partners CP 5 can count on supply chain partners for implementing contingency plans

97 CP 6 defines specific processes in case of unexpected disruptions CP 7 keeps our supply chain partners informed of updated contingency plans Table 4.3 Reliability and Convergent Validity for Redundant Resilient Supply Chain Practices Label Our company: Items Safety Stock (SS) Standardized loading SS 1 maintains safety stock in case of supply chain disruptions SS 2 SS 3 SS 4 SS 5 keeps extra inventory of strategic items (e.g., raw materials, parts, and finished goods) uses safety stock to have time to prepare response and recovery in case of disruption holds safety stock to deal with variable demand rate or lead time maintains safety stock to reduce the likelihood of supply chain disruptions (e.g., supplier failure, machine breakdown) SS 6 holds buffer stock to mitigate the risk of stock-out Our company: SLC 1 Slack Capacity (SLC) maintains slack capacity (e.g., additional production lines and IT backup systems) in case of supply chain disruptions Cronbach s alpha.950 SLC 2 cross-trains employees SLC 3 keeps multi-use assets SLC 4 SLC 5 SLC 6 holds underutilized capacity which serves as a cushion to absorb the detrimental effect of any disruptions seeks alternative solutions by adding additional capacity to prevent and cushion risks sources from multiple suppliers to minimize the likelihood of supply chain disruptions

98 Table 4.4 Reliability and Convergent Validity for Resilient Supply Chain Capabilities Label Items Standardized loading Readiness Capability (RDC) Our company (prior to disruptions): RDC1 can eliminate the source of potential disruptions before they occur RDC2 is able to reduce the likelihood of disruptions beforehand through joint supply chain resources RDC3 monitors supply chain processes in advance to prevent potential disruptions RDC4 is prepared to manage expected disruptions RDC5 has inspection plans or preventive maintenance programs to minimize the risks in supply chain RDC6 collaborates with supply chain partners in detecting the sources of possible disruptions Response Capability (RPC) Our company (immediately after disruptions): RPC 1 can rapidly respond to actual disruptions RPC 2 involves supply chain partners in responding to actual disruptions RPC 3 can quickly reorganize supply chain resources immediately after an actual disruption breaks out RPC 4 is able to mitigate the effect of actual disruptions in the supply chain RPC 5 is able to detect the root causes of disruptions in the supply chain RPC 6 can suspend supply chain operations until root causes of disruptions are eliminated Recovery Capability (RCC) Our company (afterward until recovery): RCC 1 can recover from disruptions in the supply chain RCC 2 involves supply chain partners in recovering to a normal or planned level of operations after disruptions in the supply chain RCC 3 can reconfigure supply chain resources after responding to disruptions in the supply chain RCC 4 implements proper recovery plans/measures to recover from supply chain disruptions RCC 5 can resume essential business operations after responding to disruptions in the supply chain RCC 6 can design new plans to prevent the same supply chain disruptions from occurring in the future 0.79 Cronbach s alpha

99 4.2.1 Initial First-order Measurement Model The results of the first-order CFA measurement model, which includes 15 constructs with 98 items. SEM using AMOS 6 was conducted to assess the measurement models. Multiple fit indices (χ2, CFI, IFI, RMSEA, and SRMR) are reported to assess the model fit. The results suggest that most of the fit indices are not good or acceptable. Tables 4.1 through 4.4 shows standardized factor loadings and Cronbach s alpha. Although the reliability values of 14 constructs are 0.7 and above, with the exception of one construct (Internal Risk=0.696), there are many items whose inter-item factor loadings are less than 0.6. This does not indicate adequate convergent validity for each dimension. In order to improve model fit and assess convergent validity while maintaining content validity, items are deleted sequentially according to the following criteria: (1) low item loading, (2) low corrected item-total correlation, and (3) modification index. According to these criteria, items with the lowest factor loadings from each construct, i.e., those less than 0.4, should be eliminated. Thus, 14 items (IR2, IR5, SR4, CR3, ER8, EP5, IS1, SC1, EC1, CP1, SS1, SLC2, RPC6, RCC2) were eliminated. Using CITC statistics, items with correlation coefficients less than 0.4 are eliminated. An item with less than 0.5 for CITC is kept if it is considered important for maintaining content validity. Therefore, another 14 items (IR2, IR3, IR4, IR7, SR5, SR6, SR7, ER2, ER3, ER4, ER5, RP1, EP6, SLC 6) were eliminated because their CITC statistics were below 0.5 (see Tables 4.5 through 4.8). Three items with CITC scores lower than 0.5 were retained because two of 86

100 these items were very close to the 0.5 threshold (SR1 = and RP3=0.498). RP2 was kept in order to maintain content validity. Table 4.5 Corrected Item-Total Statistics for Antecedents Item-Total Statistics Scale Mean if Item Deleted Scale Variance if Item Deleted Corrected Item-Total Correlation Cronbach's Alpha if Item Deleted IR IR IR IR IR IR IR IR Scale Mean if Item Deleted Scale Variance if Item Deleted Corrected Item-Total Correlation Cronbach's Alpha if Item Deleted SR SR SR SR SR SR SR Scale Mean if Item Deleted Scale Variance if Item Deleted Corrected Item-Total Correlation Cronbach's Alpha if Item Deleted CR CR CR CR CR CR CR Scale Mean if Item Deleted Scale Variance if Item Deleted Corrected Item-Total Correlation Cronbach's Alpha if Item Deleted ER ER ER ER

101 ER ER ER ER Scale Mean if Item Deleted Scale Variance if Item Deleted Corrected Item-Total Correlation Cronbach's Alpha if Item Deleted RP RP RP RP RP RP Table 4.6 Corrected Item-Total Statistics for Flexible Practices Scale Mean if Item Deleted Item-Total Statistics Scale Variance if Item Deleted Corrected Item-Total Correlation Cronbach's Alpha if Item Deleted EP EP EP EP EP EP Scale Mean if Item Deleted Scale Variance if Item Deleted Corrected Item-Total Correlation Cronbach's Alpha if Item Deleted IS IS IS IS IS IS Scale Mean if Item Deleted Scale Variance if Item Deleted Corrected Item-Total Correlation Cronbach's Alpha if Item Deleted SC SC SC SC SC SC Scale Mean if Item Deleted Scale Variance if Item Deleted Corrected Item-Total Correlation Cronbach's Alpha if Item Deleted 88

102 EC EC EC EC EC EC EC Scale Mean if Item Deleted Scale Variance if Item Deleted Corrected Item-Total Correlation Cronbach's Alpha if Item Deleted CP CP CP CP CP CP CP Table 4.7 Corrected Item-Total Statistics for Redundant Practices Scale Mean if Item Deleted Item-Total Statistics Scale Variance if Item Deleted Corrected Item-Total Correlation Cronbach's Alpha if Item Deleted SS SS SS SS SS SS Scale Mean if Item Deleted Scale Variance if Item Deleted Corrected Item-Total Correlation Cronbach's Alpha if Item Deleted SLC SLC SLC SLC SLC SLC

103 Table 4.8 Corrected Item-Total Statistics for Capabilities Scale Mean if Item Deleted Item-Total Statistics Scale Variance if Item Deleted Corrected Item-Total Correlation Cronbach's Alpha if Item Deleted RDC RDC RDC RDC RDC RDC Scale Mean if Item Deleted Scale Variance if Item Deleted Corrected Item-Total Correlation Cronbach's Alpha if Item Deleted RPC RPC RPC RPC RPC RPC Scale Mean if Item Deleted Scale Variance if Item Deleted Corrected Item-Total Correlation Cronbach's Alpha if Item Deleted RRC RRC RRC RRC RRC RRC Using the modification index in the AMOS output, items are deleted if there are error covariances and cross-loadings. If the error covariance between two items from different constructs is high, the items are measuring a similar concept. Thus, eight items (CR1, IS2, SC6, EC2, CP7, RDC2, RDC6, RRC3) were eliminated. The chi-square index is a fundamental measure for model fit and sensitive to sample size. The appropriate value for chi-square/df should exceed 1 but be less than 5 (Tarafdar et al., 2007). Values of CFI and IFI above 0.8 indicate a reasonable fit, and values above 0.9 represent a good model fit (Joreskog & Sorbom, 1989). If the value of RMSEA is less than 0.8, it is 90

104 regarded as an acceptable fit and less than 0.5 as a good model fit (Hu & Bentler, 1998; Modi and Mabert, 2007). If the value of SRMR is below 0.09 it is regarded as a good model fit. The process of dropping items continued until all model fit indices exceeded the cutoff values. Thus, the six items (CR7, RP5, RP5, RP6, EP4, SLC3) with low factor loadings were additionally eliminated Final First-order Measurement Model Final items are listed in Tables 4.9 through In total, 45 items were eliminated. Compared to the initial model fit, revised fit indices met the criteria for a good model fit. The model fit indices of the initial CFA measurement were as follows: CFI = 0.686, IFI = 0.691, RMSEA = 0.069, and SRMR = After purification and modification, the model fit indices were improved: CFI = 0.905, IFI = 0.908, RMSEA = and SRMR = Cronbach s alpha values of the 15 constructs are shown in Tables 4.9 through Alpha values for all 14 constructs are greater than 0.7, with the exception of one construct (Risk Taking Propensity: 0.66). Although it is below 0.7, a minimum threshold alpha value of 0.6 is often used considering the nature of the international data set (Bagozzi & Yi, 1998; Cagliano et al. 2006; Nunnally, 1967). The results indicate that the instrument items are reliable measures. Standardized factor loadings for 15 constructs are also listed in Tables 4.9 through They are all statistically significant at the level of 0.01 and greater than twice their standard errors. Significant factor loadings on the respective constructs indicate evidence of convergent validity. 91

105 Table 4.9 Final Measurement Model for Antecedents Label Items Standardized loading Internal Risk (IR) Our business is adversely affected by our internal: IR1 machine breakdowns IR6 equipment operating out of specifications IR8 lack of highly skilled employees Supply-related Risk (SR) Our business is adversely affected by our suppliers : SR 1 abrupt capacity fluctuations SR 2 inconsistent product quality SR 3 poor delivery performance (i.e., delivery dependability) Customer-related Risk (CR) Our business is adversely affected by our customers : CR 2 sudden demand increases which often go beyond our capacity CR 4 high variation in their demand that affects our master production plan (e.g., rescheduling) CR 5 unpredictable requirements for product features CR 6 frequently changing product preferences External Risk (ER) Our business is adversely affected by following problems outside our organization: ER 1 Political instability (e.g., new laws, stipulations, war, civil unrest) ER 6 Regulatory barriers for supply chain operations (e.g., customs, tariffs) ER 7 Legislation or international standards changes for supply chain operations (e.g., ISO9000, transportation laws) Risk Taking Propensity (RP) Our company : RP 2 provides rewards for innovative suggestions (e.g., bonuses, time off) RP 3 has a tendency to take the first mover s advantage by leading the competition RP 4 is willing to put some proportion of savings in uninsured investments for the sake of higher return Cronbach s alpha AVE Table 4.10 Final Measurement Model for Flexible Practices Label Items Standardized loading Cronbach s alpha AVE EP 1 EP 2 EP 3 Extent of Postponement (EP) Our products are designed to use standard sub-assemblies for modularity Our company delays final product assembly activities until the last possible position (or nearest to customers) in the supply chain Our goods are stored at appropriate distribution points close to the customers in the supply

106 IS 3 IS 4 IS 5 Information Sharing (IS) Our supply chain partners share their proprietary information with us Our supply chain partners share their business knowledge of core business processes with us Our company and supply chain partners keep each other informed frequently and in a timely manner about events or changes that may affect other partners Our company and supply chain partners exchange information IS 6 that helps in the establishment of business planning Security Compliance (SC) Our company: regularly solves problems jointly with our supply chain SC 2 partners involves supply chain partners early in the new product SC 3 design and development effort works jointly with supply chain partners to plan and execute SC 4 supply chain operations is jointly responsible with supply chain partners for making SC 5 sure that disruptions are properly handled Extent of Collaboration (EC) Our company: EC 4 works jointly with supply chain partners to plan and execute supply chain operations EC 5 is jointly responsible with supply chain partners for making sure that disruptions are properly handled EC 6 collaborates with supply chain partners in managing disruptions EC 7 regards the collaboration with supply chain partners as important in risk management Contingency Planning (CP) Our company: CP 3 involves our supply chain partners in developing contingency plans CP 4 jointly develops contingency plans along with our supply chain partners CP 5 can count on supply chain partners for implementing contingency plans Table 4.11 Final Measurement Model for Redundant Practices Label Items Safety Stock (SS) Our company: uses safety stock to have time to prepare response and SS 3 recovery in case of disruption holds safety stock to deal with variable demand rate or lead SS 4 time Standardized loading Cronbach s alpha AVE

107 SS 5 maintains safety stock to reduce the likelihood of supply chain disruptions (e.g., supplier failure, machine breakdown) SS 6 holds buffer stock to mitigate the risk of stock-out Slack Capacity (SLC) Our company: SLC 1 maintains slack capacity (e.g., additional production lines and IT backup systems) in case of supply chain disruptions SLC 4 holds underutilized capacity which serves as a cushion to absorb the detrimental effect of any disruptions SLC 5 seeks alternative solutions by adding additional capacity to prevent and cushion risks Table 4.12 Final Measurement Model for Resilient Supply Chain Capabilities Label Items Readiness Capability (RDC) Our company (prior to disruptions): can eliminate the source of potential disruptions before they RDC1 occur monitors supply chain processes in advance to prevent RDC3 potential disruptions Standardized loading RDC4 is prepared to manage expected disruptions has inspection plans or preventive maintenance programs to RDC5 minimize the risks in supply chain Response Capability (RPC) Our company (immediately after disruptions): RPC 1 can rapidly respond to actual disruptions RPC 2 involves supply chain partners in responding to actual disruptions RPC 3 can quickly reorganize supply chain resources immediately after an actual disruption breaks out RPC 4 is able to mitigate the effect of actual disruptions in the supply chain Recovery Capability (RCC) Our company (afterward until recovery): RCC 1 can recover from disruptions in the supply chain RCC 4 implements proper recovery plans/measures to recover from supply chain disruptions RCC 5 can resume essential business operations after responding to disruptions in the supply chain RCC 6 can design new plans to prevent the same supply chain disruptions from occurring in the future Cronbach s alpha AVE

108 Table 4.13 Inter-construct Correlation and Discriminant validity (n=163) IR SR CR ER RP EP IS SC EC CP SS SLC RDC RPC RRC IR [0.700] a SR 0.517*** [0.735] CR 0.627*** 0.571*** [0.692] ER 0.235** 0.362*** 0.381*** [0.698] RP * [0.632] EP [0.676] IS * 0.347*** [0.783] SC ** 0.363*** 0.258** 0.342*** [0.854] EC *** 0.495*** 0.447*** [0.818] CP *** 0.431*** 0.645*** 0.593*** [0.875] SS ** 0.357*** 0.205** 0.225** 0.182** 0.146* [0.885] SLC ** 0.24** 0.223** 0.431*** 0.355*** 0.414*** 0.541*** [0.735] RDC ** ** 0.283*** 0.416*** 0.453*** 0.531*** 0.561*** 0.334*** 0.495*** [0.787] RPC ** 0.268** 0.362*** 0.415*** 0.578*** 0.464*** 0.371*** 0.401*** 0.707*** [0.821] - RRC ** *** 0.272** 0.309*** 0.454*** 0.394*** 0.34*** 0.292*** 0.371*** 0.582*** 0.726*** [0.802] 0.286*** Correlation coefficients are *** significant at p <0.01, ** significant at p <0.05, and * significant at p <0.1 a Squared root of average variances extracted (AVEs) are on the diagonal in brackets. Note: IR (Internal Risk), SR (Supplier Risk), CR (Customer Risk), ER (External Risk), RP (Risk Taking Propensity), EP (Extent of Postponement), IS (Information Sharing), SC (Security Compliance), CP (Contingency Planning), SS (Safety Stock), Slack (Slack Capacity), RDC (Resilient Supply Chain Readiness Capacity), RPC (Resilient Supply Chain Response Capacity), RRC (Resilient Supply Chain Recovery Capacity) 95

109 Table 4.13 shows inter-construct correlations and discriminant validity. Squared root of average variances extracted (AVEs) are on the diagonal in brackets. The square root of average variance extracted of each construct is greater than the correlations of the construct with all other constructs (Fornell and Larcker, 1981). The results show that the discriminant validity for 15 constructs is assessed, which means each construct is measuring a distinct concept among each other Second-order CFA Measurement Model Figure 4-1 shows model fit indices for the second-order CFA measurement model (χ 2 = , d.f. = 1287, CFI = 0.893, IFI = 0.895, RMSEA = 0.051, and SRMR = 0.075). The results indicate that they all achieve an acceptable level to assess the measurement model. The results of the model fit indices for the first-order CFA and the second-order CFA for Resilient Supply Chain Practices and Capabilities are reported in Tables 4.14 through 4.15 to validate the existence of the second-order constructs. In Table 4.14, the T-coefficient of indicates that the second-order construct exits. Table 4.14 Validation of Second Order Construct for Flexible Practices χ 2 df CFI IFI RMSEA SRMR First-order CFA Second-order CFA T-coefficient (χ 2 of First-order / χ 2 of Second-order) 92.7% 96

110 e_ir1 1 IR1 e_ir6 1 IR61 IR e_ir8 e_sr1 e_sr2 e_sr IR8 SR1 SR2 SR3 SR e_cr2 e_cr4 e_cr5 e_cr CR2 CR4 CR5 CR6 CR e_er1 1 ER1 e_er6 e_er ER6 ER7 ER e_rp2 e_rp3 e_rp RP2 RP3 RP4 RP EP IS SC FRSCP EC CP SS RRSCP SLC RDC RPC RRC RRSCC Model fit: χ 2 = , d.f. = 1287, CFI = 0.893, IFI= 0.895, RMSEA =0.051, and SRMR= Figure 4-1 Second-Order CFA Measurement Model 97

111 The T-coefficient cannot be validated for the second-order constructs with less than four sub-dimensions. So the factor loadings on the respective second-order constructs are reported. If all the loadings are 0.5 or above on the second-order constructs, it is evidence of a second-order construct. According to Table 4.15, the existence of the second-order constructs for Redundant Practices and Resilient Supply Chain Capabilities is validated. Table 4.15 Validation of Second Order Construct for Redundant Practices and Capabilities First-Order construct Second-Order Construct Estimate Significant Safety Stock (SS) Redundant Resilient n/a Slack Capacity (SLC) Supply Chain Practices (RRSCP) p < 0.01 Readiness Capability n/a Response Capability Resilient Supply Chain Capabilities p < 0.01 (RSCC) Recovery Capability p < 0.01 In sum, all of 15 constructs in this study show that they are reliable and valid measures to capture the main domain of each construct. In Chapter 4, reliability, convergent validity, discriminant validity, and validation of the second-order construct are assessed. 98

112 Chapter 5 Path Analysis and Hypotheses Testing This chapter analyzes path coefficients among the eight hypotheses using structural equation modeling (SEM). SEM has flexibility in the following areas: (1) modeling relationships among multiple predictor and criterion variables, (2) constructing unobservable latent variables, (3) statistically testing a priori substantive/theoretical and measurement assumptions against empirical data (i.e., confirmatory analysis), and (4) modeling errors in measurements for observed variables (Chin, 1998). If hypotheses consist of a series of simultaneous interrelationships between dependent and independent variables, the SEM technique is regarded as more advantageous than the regression method. Using AMOS 6.0, this study follows a two-step process: (1) measurement model development with the assessment of reliability and validity; (2) path coefficient analysis with structural modeling (Anderson & Gerbing, 1988). Since the first step already has been covered in Chapter 4, this chapter discusses the results of the structural model, including the model fit indices and significance of the path coefficient in Section 5.1. A discussion of path analysis and hypotheses testing results is presented in Section 5.2. Chapter 5 ends with a summary of the results in Section

113 5.1 Structural Modeling Results Figure 5-1 illustrates the standardized structural coefficients (1) between four types of supply chain risk perceptions as independent variables (IV) and risk taking propensity as a dependent variable (DV); (2) between risk taking propensity (IV) and resilient supply chain practices (DV); (3) between resilient supply chain practices (IV) and resilient supply chain capabilities (DV). Figure 5-1 also shows fit indices for validating the structural model. Fit indices reflect an acceptable model fit: χ2 /df = 1.419, CFI = 0.89, IFI = 0.892, RMSEA = 0.051, and SRMR = CFI and IFI are higher than the recommended minimum value of 0.8; RMSEA is lower than the recommended minimum value of 0.8; SRMR is also lower than the recommended minimum value of 0.09 for a reasonable model fit (Hu & Bentler, 1998; Modi and Mabert, 2007). Table 5.1 reports hypotheses testing results. Four (H1a, H2b, H3a, and H3b) out of 10 hypotheses are supported at the level of 0.01, one hypothesis (H2a) is supported at the level of 0.05, and three hypotheses (H1b, H1c, and H1d) are not supported. For the two hypotheses related to risk perception (H1a and H1b), the standardized coefficients from internal risk and supplier risk to risk taking propensity are statistically significant at the level of 0.01: H1a (β 11 = 0.481, t = 2.679, p<0.01) and H2a (β 12 = -0.44, t = , p<0.01). Although the coefficient (β 12 ) is statistically significant at the level of 0.01, it shows a negative relationship with risk taking propensity, which is the opposite of the proposed hypothesis (H1b). 100

114 Internal Risk (ξ 1 ) H1a β 11=0.481*** Supplier Risk (ξ 2 ) Customer Risk (ξ 3 ) External Risk (ξ 4 ) H1b β 12= *** H1c β 13= H1d β 14=0.15 Risk Taking Propensity (ξ 5) H2a β 21=0.32** H2b β 22=0.487*** Flexible RSCP (ξ 6 ) Redundant RSCP (ξ 7 ) H3a β 31=0.672*** H5a β 32=0.34*** RSC Capabilities (ξ 8) Model fit: χ 2 =1846.5, d.f. = 1301, CFI = 0.89, IFI= 0.892, RMSEA =0.051, and SRMR= Coefficients are significant at ** p < 0.05, *** p < 0.01 Figure 5-1 Structural Model Results Table 5.1 Path Analysis and Hypotheses Testing Results Hypotheses Relationship Path Coefficient Critical Ratio Significant H1a IR RP p < 0.01 H1b SR RP p < 0.01 H1c CR RP p > 0.1 H1d ER RP p > 0.1 H2a RP FRSCP p < 0.05 H2b RP RRSCP p < 0.01 H3a FRSCP RSCC p < 0.01 H3b RRSCP RSCC p < 0.01 Note: IR (Internal Risk), SR (Supplier Risk), CR (Customer Risk), ER (External Risk), RP (Risk Taking Propensity), FRSCP (Flexible Resilient Supply Chain Practice), RRSCP (Redundant Resilient Supply Chain Practice) 101

115 The path coefficients from customer risk and external risk to risk taking propensity (H1c and H1d) are not statistically significant (p>0.1). H2a (β 21 = 0.32, t = 2.343, p<0.05) and H2b (β 22 = 0.487, t = 3.633, p<0.01) are strongly supported. The path coefficients from resilient supply chain risk practices to resilient supply chain capabilities are all statistically significant (β 31 = 0.672, t = 3.469, p<0.01; β 32 = 0.34, t = 3.125, p<0.01), and hypotheses H3a and H3b are strongly supported. 5.2 Discussion of Path Analysis and Hypotheses Testing Results First, Risk perception (mutual trust, organizational compatibility, and top management support) and risk taking propensity are discussed (H1a, H1b, H1c, and H1d). One hypothesis (H1a) is supported at the level of 0.01, while three other hypotheses (H1b, H1c, and H1d) are not supported. These empirical results suggest that there are positive direct effects of internal risk (IR) on risk taking propensity (RP) and negative effects of supplier risk on risk taking propensity. Ongoing business activities in a company are adversely affected by internal risk sources, such as machine breakdowns, equipment operating out of specifications, and lack of highly skilled employees. The internal level of operational accidents pertains to uncertainties in production, labor, and systems. The path coefficient from internal risk to risk taking propensity is 0.48, which means that internal risk explains the variance of risk taking propensity by 48%. A firm that perceives increased internal risk tends to have a higher risk-taking propensity to manage or exploit the risk. 102

116 Hypothesis 1b is significant but not supported. The results indicate that supplier risk has a negative impact on risk taking propensity, which means that the more firms perceive risk from the supplier side, the more like they are to become risk averse. Suppliers inconsistent product quality, abrupt capacity fluctuations, and unreliable delivery performance can adversely affect business activity across the supply chain and, ultimately, final customers (Zsidisinet al., 2000). The buyer-supplier relationship can be interrupted or terminated by supplier-related risks (Wagner & Bode, 2008). In response to consistent supplier disruptions, firms would seek alternative suppliers instead of managing supplier risk. Thus, supplier risk is negatively related to risk taking propensity. Hypotheses H1c and H1d are not supported. From a statistical standpoint, the correlation between H1a and H1d might dominate that between H1c and H1d resulting in hiding the significance of H1c and H1d. Customer-related risk results from (1) disruptions in downstream supply chain operations (e.g., disruptions of transportation and distribution network to final customer) and (2) uncertain customer demand (e.g., frequently changing product preferences and sudden demand increases) (Wagner & Bode, 2008). The questions for customer risk inquire primarily about uncertain customer demand. However, two out of four questions also inquire about how uncertain demand affects production capacity and master production plans. It might cause confusion among respondents and offset the causal relationship between customer risk and risk taking propensity. 103

117 Two interviews were conducted on the topic of external risk with one plant manager of a first-tier supplier and one manufacturing manager with a Six-Sigma Black Belt electronic manufacturer. They thought that if external risk (i.e., natural disaster, political instability, and regulation change) occurs even more than once a year, they could not keep operating their businesses. Miller and Friesen (1983) also found that there is no statistically significant relationship between hostile business climates (high regulation) and risk taking propensity. Thus, this may explain and support the reasons why the results of H1c and H1d were not significant. Second, Risk taking propensity and flexible and redundant resilient supply chain practices (H2a and H2b) are discussed. Hypotheses H2a and H2b are supported at the level of 0.05 and 0.01, respectively. These results indicate that risk taking propensity (RP) has a positive impact on both flexible and redundant resilient supply chain practices (RSCP). As proposed, to the degree that firms are willing to take risks, the more likely they are to become creative and innovative, while risk-averse firms tend to commit fewer resources to new technologies and products (Miller, 1983; Gilley et al., 2004). Flexible RSCP (FRSCP) consists of five sub-dimensions (postponement, collaboration, security compliance, information sharing, and contingency planning), and redundant RSCP (RRSCP) consists of two sub-dimensions (safety stock and slack capacity). Their effect sizes are β 21 = 0.32 (H2a; t=2.34) and β 22 = (H2b, t=3.63), 104

118 respectively. The effect size of H2a is a little lower than that of H2b. Managing perceived risk and engaging in five different practices (FRSCP) by committing to resource investment and establishing organizational routines require much more time and effort than RRSCP. Thus, the lower effect size of H2a is understandable. With a path coefficient of 0.48, risk taking propensity explains the variance of RRSCP by 48%. If firms are willing to take risk and absorb the detrimental effect of supply chain disruption, securing extra inventory and slack capacity (e.g., multi-use assets, additional production lines, IT backup systems, and multiple sourcing) provide a starting point for mitigating risk. Third, FRSCP, RRSCP and resilient supply chain capabilities (RSCC) (H3a and H3b) are discussed. One of the main objectives of this study is to empirically examine the relationships between two RSCPs and RSCC. The two hypotheses (H3a and H3b) are supported at the level of These results show that both RSCPs are positively associated with RSCC. As proposed, the more firms implement RSCPs, the more likely they are to formulate RSCC. RSCC consists of three sub-dimensions (resilient supply chain readiness capability, resilient supply chain response capability, and resilient supply chain recovery capability). The path coefficient of (H3a) explains the variance of RSCC by 67%, whereas that of 0.34 (H3b) explains the variance of RSCC by 34%. These indicate that both FRSCP and RRSCP contribute to RSCC formation. 105

119 Even though the relationship between RRSCP and RSCC is positive and statistically significant, FRSCP plays a more crucial role for firms in achieving readiness, response, and recovery capability in case of supply chain disruptions. If firms implement postponement, collaboration, security compliance, information sharing, and contingency planning, they are more likely to become ready for and responsive to unexpected disruptions and reestablish normal levels of business operation. The results also suggest that RRSCP (e.g., backup systems, multiple sourcing, extra capacity, and buffer practices) lower the likelihood of disruptions and achieve RSCC. 5.3 Summary of Results Overall, the empirical results in Table 5.1 shows six out of eight path coefficients are statistically significant. There are positive effects of internal risk and negative effects of supplier risk on risk taking propensity. The higher level of risk taking propensity will lead to increased implementation of RSCPs. RSCPs have positive relationships with RSCC. Five (H1a, H2a, H2b, H3a, and H3b) of eight hypotheses are supported. The opposite effect of H1b and the fact that H1c and H1d did not achieve statistical significance compared to the initial hypotheses were discussed in Section

120 Chapter 6 Conclusion 6.1 Summary As the competition in global business markets has expanded beyond the local or even national scope, supply chain networks have become even wider and more complex. They involve suppliers from all over the world and meet diverse needs and requirements of customers. For example, in the automotive industry, to manufacturer a car involves hundreds of suppliers and thousands of parts and components. Several supply chain strategies have been introduced to deal with different types of product and market uncertainty (Fisher, 1997; Lee, 2002; Vonderembse et al, 2006). One of these strategies is the lean supply chain strategy. Lean philosophy used to be a dominant approach in exploiting problematic issues across supply chains by eliminating waste and maximizing efficiency because what matters most in winning business in the context of supply chains is to deliver what customers need when they need it with the lowest cost against global competitors. But as firms eliminate organizational slack and extra inventory and maintain single sourcing, if any problems occur among supply chain entities, their business is interrupted or adversely affected. Christopher and Peck (2004) have argued that the leaner the supply chain network is, the more vulnerable the supply chain process becomes and the more often supply chain 107

121 disruptions occur. That is why supply chain risk management has drawn attention from both academicians and practitioners. The research agenda in risk management centers on risk identification, assessment, mitigation, and treatment. Since the early 2000s, several studies have adopted the concept of resilience from many disciplines, including ecology, psychology, and economics, in order to distinguish between business practices that make firms more secure and resilient and those that do not (Rice & Caniato, 2003; Sheffi, 2002; Tang, 2006). The resilient supply chain framework provides an alternative paradigm that allows firms to handle the issues of vulnerability and disruption across the global supply chain. Different from the lean supply chain strategy, the resilient supply chain strategy emphasizes firms capacity to prepare for expected and unexpected risk factors, respond to actual disruptions in a timely manner, and bounce back from a detrimental event quickly and return to a normal or improved state of business operations. The resilient supply chain strategy aims to improve firms business continuity, enhance their business performance, and eventually gain sustainable advantages against competitors. Through a comprehensive literature review, this study identifies two important research gaps: (1) the lack of a comprehensive and integrated resilient supply chain framework; (2) the lack of a valid and reliable measurement instrument and empirical study of supply chain risk management. Keeping in mind the need to fill these gaps and the need for a new theoretical framework to explicate supply chain disruptions, this study proposes three research questions: (1) What are the antecedents of resilient supply chain 108

122 management practices? (2) What are the dimensions of resilient supply chain management practices, and how can each component be measured? (3) How do resilient supply chain management practices form resilient supply chain capability? The first question is answered, in part, in the literature review in Chapter 2. This study identifies the antecedents of resilient supply chain practices as the perception of different levels of supply chain risk and risk taking propensity. Based on Juttner et al. s (2003) breakdowns, this study introduces several sources of supply chain risk: (1) organizational risk, (2) network risk (i.e., supplier and customer risk), and (3) environmental risk. Risk taking propensity refers to the connection between risk perceptions and the implementation of resilient supply chain practices. To address the second question, this study delineates seven resilient supply chain practices within two categories. The two categories include (1) the flexible approach (information sharing, postponement, collaboration, security compliance, and contingency planning) and (2) the redundant approach (safety stock and slack capacity). The last research question is addressed in the theory development section of this dissertation (Section 2.6). Resilient supply chain capability can be defined as the adaptive capability of the supply chain when preparing for unexpected events, responding to disruptions, and recovering from disruptive events by maintaining continuity of operations at the desired level of connectedness and control over structure and function. Resilient supply chain capability features three sub-dimensions (readiness, response, and 109

123 recovery, also referred to as 3R ). Firms need to form 3R capabilities not only to reduce the likelihood of supply chain disruptions and minimize their adverse effect but also to generate market profitability consistently. This study tested eight hypotheses to examine the interrelationship among resilient supply chain antecedents, practices, and capabilities using data from 163 respondents. Five out of eight hypotheses are supported, and their coefficients are statistically significant at the level of 0.01, including one at the level of 0.05 (between risk taking propensity and flexible practices). The results for one hypothesis (between supplier risk and risk taking propensity) are significant but reveal an opposite effect than what was initially anticipated. Two hypotheses are not supported, and their coefficients are insignificant. A detailed discussion of the results is presented in Chapter 4. The results of this study suggest that a higher perception of internal risk and firms willingness to take risk facilitate the implementation of flexible and redundant practices and formulate capabilities. Resilient supply chain capabilities enable firms to prepare to respond to supply chain disruptions and recover from them. 6.2 Theoretical Implications This study is one of the first large-scale empirical studies that defines supply chain resilience and indentifies resilient supply chain practices in the area of supply chain risk management. The research model is comprised of three stages: (1) the antecedents of 110

124 resilient supply chain practices, (2) resilient supply chain practices, and (3) resilient supply chain capabilities. This study also describes the process of resilient supply chain capabilities formation. Several theoretical implications are described as follows. First, a comprehensive and integrated resilient supply chain framework is established by examining three stages of a resilient supply chain. Supply chain risk management requires an increasingly holistic view in order to assess its impact on each entity and each business across the supply chain. Prior studies conducted on supply chain risk are somewhat fragmented in that each focuses on either supply chain risk sources, the control of supply chain risk, or outcomes of supply chain management. They also exhibit limited casual relationships among the variables under investigation. In order to capture the effect of resilient supply chain practices more precisely, enablers of these practices and their outcomes need to be taken into account. A resilient supply chain framework is grounded in two theoretical bases: contingency theory (CT) and resourcebased view (RBV). Organizational structure and management styles are influenced by many environmental aspects. CT suggests that the optimal set of decisions and actions depends on internal and external factors. It also suggests that the fit between organizational structure and environment will enhance business performance. Risk perceptions can range from those on an internal level (inside a firm) to those on a network level (both the supplier side and customer side) to those on an environmental level (outside the supply chain network). Given the variety and types of risk possible, firms reactions will vary 111

125 depending on their tendencies when managing a crisis. The role of CT is to identify the driving forces that enable firms to adopt and implement resilient supply chain practices. The degree to which firms adopt resources and implement bundles of routines is determined by how they perceive and respond to the expected and unexpected risk sources properly. CT confirms that if firms perceive a high level of internal and external risk and are willing to exploit those, they tend to launch more resources and engage in the investment of business practices that enable them to deal with supply chain disruptions. Although many papers have examined the effect of supply chain risk management practices upon firms operational and financial performance, the perceptions and actions that reside between these two outcomes is unclear. RBV conceptualizes capabilities as a combination of tangible and intangible assets and organizational processes. RBV plays a critical role in connecting internal firm-level resources and routines to 3R (readiness, response, and recovery) capabilities. RBV confirms the formulation process of resilient supply chain capabilities. The process begins with the perception of and propensity for various risks through business practices that enhance flexibility and redundancy and result in the formulation of resilient supply chain capabilities. This study offers empirical support for RBV by showing that internal levels of resources and bundles of routines formulate external capabilities that allow firms to gain a competitive advantage. As stated above, the research model in this study reflects a holistic view of resilient supply chain framework through CT and RBV. Through the lens of CT, risk perceptions and risk taking propensity are able to identify the fit between uncertainty and 112

126 organizational structures, and thereby lead to proper responses related to supply chain risks. According to Sousa and Voss (2008), CT involves three types of variables: (1) contingency variables, (2) response variables, and (3) performance variables. Contingency variables are related to contextual and situational characteristics in which firms operate. Response variables consist of managerial actions and responses to the contingency variables. Performance variables consist of outcome measures that help evaluate the relative effectiveness of organizational actions taken. Many studies within operations management literature have used different types of response variables (e.g., quality management, lean/just-in-time production, and employee involvement) and performance variables (e.g., customer satisfaction, financial and market performance, and employee satisfaction) (Ahmad and Schroeder, 2003; Das et al., 2000; Lawler, 1988; Shah and Ward, 2003; Sila, 2007). In light of response and performance aspects of risk management, RBV plays a role in devising certain resilient supply chain capabilities that CT cannot explain entirely. CT is used to identify the enablers of RSCP in this study. Instead of listing management and performance measures that already have been developed, RBV specifies bundles of internal resources and routines in response to risk perceptions and propensity and explains the process of supply chain resilience formation. The empirical results of H1a, H1b, H2a, H2b, H3a, and H3b support the complementary and mutually reinforcing roles of both CT and RBV in the resilient supply chain framework. In sum, CT and RBV allow this study to identify routines and resources that enable companies to be ready for, to respond to, and to recover from expected and unexpected supply chain disruptions. 113

127 Second, this study provides reliable and valid measurement scales through a survey questionnaire. Most previous research on supply risk management has taken the form of conceptual studies, anecdotal evidence, case studies, and secondary data analysis. Empirical studies using a survey method are rare although a few empirical studies do exist (Wagner & Bode, 2008). Newly developed measurements include the following: (1) security compliance, (2) safety stock, (3) slack capacity, (4) readiness capability, (5) response capability, and (6) recovery capability. All of the measurement items have undergone a series of rigorous statistical processes (i.e., Q-sort, confirmative factor analysis, reliability testing, convergent and discriminant validity assessment, and the validation of second-order constructs) to confirm the validation of measurement used to assess the resilient supply chain framework. Thus, the measurement instrument in this study offers a new and holistic approach in assessing the impact of supply chain disruptions and risk management on each entity along the supply chain. Also, it can be used in follow-up data collection and future research on supply chain resilience and risk management. This study first uses a five-point Likert scale with frequency measures where 1= not at all, 2 = annually, 3 = quarterly, 4 = monthly, and 5 = weekly in measuring risk perceptions. Most of the studies found in the supply chain risk management literature use agreement measures (where 1 = strongly disagree, 2 = disagree, 3 = neutral, 4 = agree, 5 = strongly agree) or extent measures (where 1 = none, 2 = little extent, 3 = moderate extent, 4 = great extent, 5 = a very great extent). After several structured interviews were 114

128 conducted for this study, many practitioners suggested that frequency measures might be more accurate in measuring risk perceptions. According to their comments on business cycles and the likelihood of risk sources, daily and bi-annual scales were not chosen. Therefore, this study offers an effective way of measuring the perceptions of supply chain risk. 6.3 Managerial Implications The results of this study reveal several implications for managers. First, this study provides focal firms with guidelines for making the supply chain process more secure and resilient. Firms need to consider pursuing supply chain resilience through risk identification and assessment, willingness to exploit risks, and resource commitment. Keeping extra inventory and buffer stock is not enough to ensure supply chain resilience. Rather, supply chain resilience is achieved when firms are ready for even unexpected accidents, able to respond quickly to disruptions, able to recover from disruptions quickly, and able to return to normal levels of business operation quickly. The establishment of resilient supply chain capabilities is enabled by (1) readiness capability, which includes monitoring and eliminating sources of potential disruptions ahead of their occurrence; (2) response capability, which includes reorganizing supply chain resources immediately after disruptions have occurred; and (3) recovery capability, which includes implementing recovery action programs and designing new plans to prevent the same problems. 115

129 Second, the perceptions of internal risk by managers influence their risk taking propensity. The more frequently that managers experience internal risks, the more willing they are to assume and manage internal risks. Internal risks are more predictable and controllable than network or environmental risks. When the production and system flow of firms are interrupted by internal risks due to machine breakdowns and equipment operating out of specifications, firms are more likely to fix the problems immediately to maintain ongoing business. A lack of highly skilled employees combined with higher risk taking propensity requires developing slack capacity by cross-training employees. Toyota Motor Corp. placed employees who were capable of working at any station on its assembly lines. In that way, daily production goals were met even when minor problems occurred on their assembly lines (Chopra and Sodhi, 2004; Mishina, 1992). Third, supplier risks have a negative impact on risk taking propensity. This result suggests a relationship that is opposite to the one expected in H1b. High supplier risks caused by abrupt capacity fluctuations, inconsistent product quality, and poor delivery performance can adversely affect firms business activities. Zsidisin (2003) introduced inability to meet customer requirements and threats to customer life and safety as two outcomes of supply risk. Zsidisin and Ellram (2003) listed eight types of supply risk management from the standpoint of purchasing companies. The relationship between supplier risks and risk taking propensity can be affected by the role (either buyer-supplier or principal-agent) of survey respondents, their particular markets, and industry characteristics. If the respondents assume the role of primary buyer (or agent) in their respective market, it is obvious that they attempt to eliminate the sources of supply chain 116

130 risks and reduce the detrimental effects of such risks. If they are second- or third-tier suppliers, they are more likely to terminate the business relationship and find alternative suppliers when their suppliers cause chronically persistent problems. There is a need for further study of the relationship between supplier risks and risk taking propensity. Forth, collaboration is the key to uniting supply chain partners combined efforts to overcome disruption and crises. A focal firm is often unable to detect the root cause of disruptions, mitigate the effect of actual problems, and resume business operations by reconfiguring supply chain resources alone. Collaboration is required during all phases of supply chain resilience formulation. Sharing proprietary business information, establishing specific education programs for security procedures, and developing contingency plans with supply chain partners are aligned with collaboration practices, which also enhance supply chain resilience. Fifth, the results from testing H2 suggest that firms willingness to assume and manage supply chain risk has a greater effect on redundancy than on flexibility. One of the reasons is that the flexible approach to establishing a resilient supply chain consists of five sub-dimensions compared to the redundant approach, which consists of only two sub-dimensions. Another reason is that building flexibility into the process of supply chain risk management takes more time and requires the coordinated effort of the entire organization along with its partners (e.g., setting up technologies and systems for information sharing, adopting the build-to-order method, and observing international security compliance and procedures). 117

131 Although maintaining safety stock, cross-training employees, and employing multi-use assets is easier, these processes can cause unnecessary slack and extra cost, according to lean philosophy. As mentioned in Chapter 5, securing extra inventory and slack capacity (e.g., multi-use assets, additional production lines, IT backup systems, and multiple sourcing) is a more accessible approach for risk management. Sixth, the results of H3 also provide meaningful insight and options for practical application to managers. Although risk taking propensity has a greater impact on redundancy, flexibility is more important for establishing supply chain resilience. The coefficient of the flexible approach (β 31 =0.672) on RSCC is twice that of the redundant approach (β 32 =0.34), which means that increasing safety stock and slack capacity is not a complete solution when managing supply chain disruptions. To achieve a higher level of supply chain resilience, firms need to focus more on the development of information sharing, postponement, collaboration, security compliance, and contingency planning. However, information sharing, postponement, and collaboration in the flexible approach are typical examples of general supply chain practices, and many firms are already implementing these practices. Even so, their instruments aim to measure the domain of resilience in the supply chain context in this study. Seventh, the results from the SEM indicate that security compliance, contingency planning, and collaboration in the flexible approach and safety stock in the redundant approach contribute more to the formulation of supply chain resilience than other practices. Their effects on increased readiness, response, and recovery capabilities are 118

132 consistently shown. These results suggest that defining and delineating appropriate business practices related to risk management are keys to establishing a resilient supply chain framework. In sum, this study sheds light upon how each company not only deals with supply chain risks but gains a competitive advantage ensuring supply chain continuity. 6.4 Limitations Even though this study makes academic and practical contributions, it is not free from limitations. First, three sub-dimensions (internal risk, supplier risk, and external risk) of risk perception, one sub-dimension (extent of postponement) of FRSCP, and one subdimension (slack capacity) of RRSCP experienced problematic issues related to measurement. At least half of the initial items have a factor loading below 0.7 and do not load on the respective constructs well. That is why three items each remain for the final measurement model. Particularly, many respondents expressed their concern about differences between safety stock and slack capacity. For the second-order measurement model, extent of postponement also exhibits a low factor loading on FRSCP. Since more than half of the respondents are from small and medium-size companies (fewer than 500 employees), the concept or term to describe postponement (e.g., build-to-order or maketo-order) might not have been familiar to them. Thus, it is necessary to redefine these five constructs and to develop new measurements for them. 119

133 Second, the responses from Korea (106) consisted of more than 65 percent of the total number of responses (163). The reason for this imbalance in response rates is not only that the data collection process involving Korean companies tends to proceed more smoothly but also 14 responses from the U.S. were omitted because they contained too many missing values. In order to claim that this study uses international data and conducts comparative research, more data should be collected from the U.S. Third, the actual survey data was collected from single respondents from either suppliers or focal firms in manufacturing industries. Using reports from only a single respondent has its weakness in accurately representing the entire complex organizational phenomena (Venkatraman & Grant, 1986). Although the characteristics of respondents vary in terms of job function and industries, they cannot represent their respective companies, industries or supply chains, nor can they represent the entire spectrum of issues experienced across the supply chain. Fourth, this study uses cross-sectional data. Although cross-sectional data can offer some insights into firms business activities, it is possible that their risk perception and propensity for risk taking are not affected by unforeseen supply chain disruptions and risk management practices are taking effects at the point of survey. Depending on when and how firms start adopting and implementing these practices, the mechanism of realizing the effects might vary. 120

134 6.5 Future Research There are several recommendations for future research based on sections 6.1 through 6.4. First, future research can be conducted in the form of longitudinal studies to confirm and re-examine the same research model. Unlike cross-sectional studies, longitudinal studies can consider the effects of time and trace changes of the interrelationships within a resilient supply chain framework. Second, the SEM can be tested in different business contexts. Including different contextual variables (e.g., industry, firm size and origin, number of employees, market and product characteristics, etc.) can offer new findings and provide insight into the perspectives of both academicians and practitioners. In order to conduct internal and comparative studies, additional data collection procedures can be implemented from different countries, such as China and Europe. Third, future research can compare resilient supply chain practices to lean supply chain practices. Christopher and Peck (2004) have argued that the leaner a supply chain network becomes, the more likely that supply chain processes become vulnerable to supply chain disruptions. Therefore, the relationship between lean production and resilient supply chain practices can be examined. The expected result is that lean production has a negative or weak impact on supply chain resilience. 121

135 Fourth, although this study identifies FRSCP and RRSCP as sub-dimensions of RSCPs, it is not clear to what extent firms need to adopt and implement those practices. Future research can evaluate the optimization process between FRSCP and RRSCP to maximize resilient supply chain capability using principles of scientific management. Since the perception of three types of risk show insignificant or negative impact on risk taking propensity, measuring likelihood of supply chain risk can be considered an important area for future study. 122

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153 Appendix A Initial Items Based on Literature Reviews 1) Internal risks (8 items) Our business is adversely affected by machine breakdown Our business is adversely affected by labor problems (e.g. strike) Our business is adversely affected by operational accident (e.g. fires or truck accident) Our business is adversely affected by utility outage Our business is adversely affected by IT system breakdown (e.g. virus attack) Our business is adversely affected by equipment operating out of specifications Our business is adversely affected by financial instability (e.g. bankruptcy) Our business is adversely affected by lack of high skilled employee 2) Supplier related risks (8 items) Our business is adversely affected by our suppliers abrupt capacity fluctuations/shortage Our business is adversely affected by our suppliers inconsistent product quality 140

154 Our business is adversely affected by our suppliers poor delivery performance (i.e. delivery dependability) Our business is adversely affected by our suppliers sudden default (e.g. bankruptcy) Our business is adversely affected by our suppliers inability to adapt product design or technological changes Our business is adversely affected by our suppliers conflict with us for intellectual property ownership (e.g. counterfeit and forgery) Our business is adversely affected by our suppliers opportunistic behavior in our ongoing business relationships Our business is adversely affected by our suppliers alliance with our direct competitor 3) Customer related risks (8 items) Our business is adversely affected by our customers unpredictable demand Our business is adversely affected by our customers inaccurate or insufficient order information which result in forecasting error Our business is adversely affected by our customers financial instability (e.g. bankruptcy) Our business is adversely affected by our customers the sudden demand increase which often goes beyond production capacity Our business is adversely affected by our customers volatile demand which affects our master production plan (e.g. rescheduling) 141

155 Our business is adversely affected by our customers changing requirement for product features Our business is adversely affected by our customers unanticipated product preferences Our business is adversely affected by our customers different product combinations 4) External risks (10 items) Our business is adversely affected by political instability (e.g. new laws, stipulations, war, civil unrest, etc.) Our business is adversely affected by diseases or epidemics (e.g. SARS, Foot and Mouth Disease, H1N1) Our business is adversely affected by natural disasters (e.g. earthquake, flooding, extreme climate change, tsunami, ash) Our business is adversely affected by international terror attacks (e.g New York, 2004 Madrid, and 2005 London terror attacks) Our business is adversely affected by currency fluctuation Our business is adversely affected by administrative barriers for supply chain operations (e.g. customs, tariff, red-tape) Our business is adversely affected by legal changes for supply chain operations (e.g. transportation laws) Our business is adversely affected by environmental legislation or requisites for supply chain operations (e.g. ISO9000) 142

156 Our business is adversely affected by competitors who often launch new products unexpectedly Our business is adversely affected by fast and frequently changing technology in our industry 5) Risk taking propensity (6 items) Our company has a tendency to take on high-risk projects with chances of above average rates of return (e.g. ROI) Our company typically adopts a bold posture, which results in increased probability of making profitable decisions Our company is willing to take substantial risks to realize significant financial gains from investments Our company provides rewards for innovative suggestions (e.g. bonuses, time off) Our company has a tendency to take the first mover s advantage by leading the competition Our company is willing to put some proportion of savings in uninsured investments for the sake of higher return 6) Extent of postponement (6 items) Our products are designed to use standard sub-assemblies for modularity Our company delays final product assembly activities until the last possible position (or nearest to customers) in the supply chain 143

157 Our company delays final product assembly activities until customer orders have actually been received Our production process modules can be re-arranged so that customization can be carried out later at distribution centers Our goods are stored at appropriate distribution points close to the customers in the supply chain Our product designs enable us to accommodate several generations of products 7) Information sharing (7 items) Our company shares our business units proprietary information (e.g. production, financial, design, and risk) with supply chain partner Our company informs supply chain partners in advance the of changing needs of customers Our company and supply chain partners keep each other informed about events or changes that may affect other partners Our supply chain partners share their proprietary information with us Our company and supply chain partners exchange information that helps in the establishment of business planning Our supply chain partners share their business knowledge of core business processes with us Our company and our supply chain partners exchange information frequently, informally, and in a timely manner 144

158 8) Security compliance (6 items) Our company has a function that specializes in supply chain security and compliance Our company follows government or industry security guidelines (e.g. C-PAT, CSI, FAST, AMR, etc) Our company audits security procedures of supply chain partners (e.g. employee/driver background checks, origination and ownership, ingredients, and packaging procedures) Our company verifies that supply chain partners follow government or industry security guidelines (e.g. C-PAT, CSI, FAST, AMR, etc) Our company has specific education programs for supply chain partners regarding security procedures Our company has defined consequences for supply chain partners who fail to comply with supply chain security procedures 9) Extent of collaboration (8 items) Our company includes supply chain partners in our goal-setting activities and planning Our company actively involves supply chain partners in new product development processes Our company involves suppliers early in the product design effort 145

159 Our company and supply chain partners work jointly to plan and execute supply chain operations Our company regularly solves problems jointly with our supply chain partners Our company and supply chain partners are jointly responsible for making sure that disruptions are properly handled Our company collaborates with supply chain partners in managing disruptions Our company regards the collaboration with supply chain partners as important in risk management 10) Contingency planning (7 items) Our company prepares a set of contingency action plans for unexpected disruptions Our company defines specific processes in case of unexpected disruptions Our company assigns roles and responsibilities for particular types of disruptions Our company involves our supply chain partners in developing contingency plans Our company jointly develops contingency plans along with our supply chain partners Our company can count on supply chain partners for implementing contingency plans Our company keeps our supply chain partners informed of updated contingency plans 146

160 11) Safety stock (6 items) Our company maintains safety stock in the case of supply chain disruptions Our company keeps extra inventory of strategic items (e.g. raw materials, parts, and finished goods in the event of supply chain disruptions) Safety stock allows us to have time to prepare response and recovery in the case of disruptions Our company holds safety stock to deal with variable demand rate or lead time Safety stock reduces the likelihood of supply chain disruptions (e.g. stock-out) Safety stock mitigates the detrimental effect of supply chain disruptions 12) Slack capacity (6 items) Our company maintains slack capacity (e.g. additional production lines and IT backup systems) for supply chain risks Our company keeps alternative personnel and system provisions Underutilized capacity in our company serves as a cushion to absorb any disruptions In order to prevent and cushion risks, our company seeks alternative solutions by adding additional capacity Our company sources from multiple suppliers to minimize the likelihood of supply chain disruptions Our company has multiple sourcing options for managing potential supply chain disruptions 147

161 13) Resilient supply chain readiness capability (6 items) Our company can eliminate beforehand the source of potential disruptions Our company can reduce in advance the likelihood of disruptions with supply chain partners Our company is able to reduce the likelihood of disruptions through joint supply chain resources Our company monitors supply chain processes to prevent potential disruptions in advance Our company is prepared to manage expected disruptions Our company has inspection plans to minimize the risks in supply chain 14) Resilient supply chain response capability (7 items) Our company can rapidly respond to actual disruptions Our company involves supply chain partners in responding to actual disruptions Our company can quickly reorganize supply chain resources immediately after an actual disruption breaks out Our company can manage supply chain disruptions in a timely manner Our company is able to mitigate the effect of actual disruptions in the supply chain Our company is able to detect the root causes of disruptions in the supply chain Our company can suspend supply chain operations until root causes of disruptions are eliminated 148

162 15) Resilient supply chain recovery capability (6 items) Our company can recover from disruptions in the supply chain Our company involves supply chain partners in recovering to a normal or planned level of operations after disruptions in the supply chain Our company can reconfigure supply chain resources after responding to disruptions in the supply chain Our company implements proper recovery plans/measures to recover from supply chain disruptions Our company can resume essential business operations after responding to disruptions in the supply chain Our company can design new plans to prevent the same supply chain disruptions from occurring in the future 149

163 Appendix B Online Survey Questionnaire Flexible and Redundant Supply Chain Practices to Build Strategic Supply Chain Resilience: Contingent and Resource-based Perspectives As a Ph. D. candidate in Manufacturing and Technology Management at the University of Toledo, I am inviting you to participate in my research project to study how to manage supply chain disruptions. Supply chain disruptions seem to take place very frequently all over the world for a variety of reasons such as production downtime, supplier failure, complex and uncertain demands, and natural disasters. They affect product, process, information, and financial flow. The objective of this research project is to define what it means to have supply chain resilience. As a result of the study, we hope to establish guidelines for making the supply chain process more secure and resilient, as well as to identify routines and resources that enable a company to be ready, to respond to, and to recover from expected and unexpected supply chain disruptions. I would appreciate it if you would complete the questionnaire that follows. It should take you about minutes. Through your participation, I hope to understand how your organization deals with supply chain risks. If you decide to participate, I would be pleased to provide you with a summary of research results. To receive a result of summary, please complete your contact information at the end of the questionnaire. If you have any questions at any time before, during, or after your participation (or you experience any physical or psychological distress as a result of your participation), you should contact a member of the research team (Kihyun Park / and Dr. Dale Dwyer / ). If you have questions beyond those answered by the research team, or you have questions about your rights as a research subject or research-related injuries, please feel free to contact the Chairperson of the SBE Institutional Review Board, Dr. Mary Ellen Edwards, in the Office of Research on the main UT campus at (419) By clicking the Next Page button below, you agree to participate in the study. Respectfully Yours, Kihyun Park 150

164 1) Please indicate the extent to which your company has experienced these problems in your supply chain for the last two years. (QUESTIONS 1-4) Internal risks (inside company) are risks related to any disruptions and failures of resources (i.e., production, labor, and system) to maintain a normal level of operation within an individual company. QUESTION 1: INTERNAL RISKS Our business is adversely affected by our internal: machine breakdowns labor problems (e.g., strike) operational accidents (e.g., fires or truck accident) utility outages IT system breakdowns (e.g., virus attack and network delays) equipment operating out of specifications financial instability (e.g., late payment) lack of highly skilled employees WeeklyMonthlyQuarterlyAnnually Not yet 2) Supplier related risks are risks related to any disruptions and failures of product and/or service flow from suppliers. QUESTION 2: SUPPLIER RELATED RISKS Our business is adversely affected by our suppliers : abrupt capacity fluctuations inconsistent product quality poor delivery performance (i.e., delivery dependability) financial instability (e.g., late payment) inability to adapt to required product design or technological changes conflict with us regarding intellectual property ownership (e.g., counterfeit and forgery) alliance with our direct competitor WeeklyMonthlyQuarterlyAnnually Not yet 3) Customer related risks are risks related to unpredictable or misunderstood customer demand (i.e., complex preference, forecasting error, and customers bankruptcy). QUESTION 3: CUSTOMER RELATED RISKS Our business is adversely affected by our customers : 151

165 inaccurate information about order quantities sudden demand increases which often go beyond our capacity financial instability (e.g., late payment) high variation in their demand that affects our master production plan (e.g., rescheduling) unpredictable requirements for product features frequently changing product preferences orders for different product combinations WeeklyMonthlyQuarterlyAnnually Not yet 4) External risks are risks that arise from any disruptions and failures outside the supply chain (i.e., natural disasters, political instability, and international terror attacks). QUESTION 4: EXTERNAL RISKS Our business is adversely affected by following problems outside our organization: Political instability (e.g., new laws, stipulations, war, civil unrest) Diseases or epidemics (e.g., SARS, Foot and Mouth Disease, H1N1) Natural disasters (e.g., earthquake, flooding, extreme climate change, tsunami, ash cloud) International terror attacks Macroeconomic uncertainties (e.g., currency fluctuation, inflation) Regulatory barriers for supply chain operations (e.g., customs, tariffs) Legislation or international standards changes for supply chain operations (e.g., ISO9000, transportation laws) Fast and frequently changing technology in our industry WeeklyMonthlyQuarterlyAnnually Not yet 5) Please indicate the extent to which following statement describes your company. (QUESTIONS 5-19) Risk taking propensity is a company s willingness to make resource commitments to deal with risks. QUESTION 5: RISK TAKING PROPENSITY Our company: has a tendency to take on high-risk projects with chances of above average rates of return on our To a very great extent great extent moderate extent little extent Not at all 152

166 investment provides rewards for innovative suggestions (e.g., bonuses, time off) has a tendency to take the first mover s advantage by leading the competition is willing to put some proportion of savings in uninsured investments for the sake of higher return makes quick decisions if we believe high-risk projects will provide a new competitive advantage is willing to take substantial risks to realize significant financial gains from investments 6) Extent of postponement is the ability of a company to move forward one or more operations or activities (making, sourcing and delivering) to a much later point in the supply chain to recognize and meet customers needs. QUESTION 6: EXTENT OF POSTPONEMENT Our products are designed to use standard subassemblies for modularity Our company delays final product assembly activities until the last possible position (or nearest to customers) in the supply chain Our goods are stored at appropriate distribution points close to the customers in the supply Our production process modules can be re-arranged so that customization can be carried out later at distribution centers Our company delays final product assembly activities until customer orders have actually been received (e.g., assembly-to-order) Our product designs enable us to accommodate several generations of products To a very great extent great extent moderate extent little extent Not at all 7) Information sharing is the extent to which critical and proprietary information is exchanged with supply chain partners. QUESTION 7: INFORMATION SHARING Our company shares our business units proprietary information (e.g., production, financial, design, and risk) with supply chain partners Our company informs our supply chain partners of changing needs of customers in advance To a very great extent great extent moderate extent little extent Not at all 153

167 Our supply chain partners share their proprietary information with us Our supply chain partners share their business knowledge of core business processes with us Our company and supply chain partners keep each other informed frequently and in a timely manner about events or changes that may affect other partners Our company and supply chain partners exchange information that helps in the establishment of business planning 8) Security compliance is the application of policies, procedures, and technology to protect the destruction of supply chain assets (i.e., product, facilities, equipment, information and personnel) from theft, damage, or terrorism. QUESTION 8: SECURITY COMPLIANCE Our company: has a function that specializes in supply chain security and compliance follows government or industry security guidelines (e.g., C-PAT, CSI, FAST, AMR, etc) audits security procedures of supply chain partners (e.g., employee/driver background checks, origination and ownership, ingredients, and packaging procedures) verifies that supply chain partners follow government or industry security guidelines (e.g., C-PAT, CSI, FAST, AMR, etc) has specific education programs for supply chain partners regarding security procedures has defined consequences for supply chain partners who fail to comply with supply chain security procedures To a very great extent great extent moderate extent little extent Not at all 9) Extent of collaboration is the extent to which supply chain entities are collaborating to cope with supply chain risks. QUESTION 9: EXTENT OF COLLABORATION Our company: includes supply chain partners in our goal-setting activities and planning regularly solves problems jointly with our supply chain partners To a very great extent great extent moderate extent little extent Not at all 154

168 involves supply chain partners early in the new product design and development effort works jointly with supply chain partners to plan and execute supply chain operations is jointly responsible with supply chain partners for making sure that disruptions are properly handled collaborates with supply chain partners in managing disruptions regards the collaboration with supply chain partners as important in risk management 10) Contingency planning is the series of specified business activities that are designed to deal with supply chain risks before they occur. QUESTION 10: CONTINGENCY PLANNING Our company: prepares a set of contingency action plans for unexpected disruptions assigns roles and responsibilities for particular types of disruptions involves our supply chain partners in developing contingency plans jointly develops contingency plans along with our supply chain partners can count on supply chain partners for implementing contingency plans defines specific processes in case of unexpected disruptions keeps our supply chain partners informed of updated contingency plans To a very great extent great extent moderate extent little extent Not at all 11) Safety stock is the extent to which a company is maintaining redundant stock(i.e.,added inventory and extra components/parts) to absorb or cushion the detrimental effect of supply chain disruptions. QUESTION 11: SAFETY STOCK Our company: maintains safety stock in case of supply chain disruptions keeps extra inventory of strategic items (e.g., raw materials, parts, and finished goods) To a very great extent great extent moderate extent little extent Not at all 155

169 uses safety stock to have time to prepare response and recovery in case of disruption holds safety stock to deal with variable demand rate or lead time maintains safety stock to reduce the likelihood of supply chain disruptions (e.g., supplier failure, machine breakdown) holds buffer stock to mitigate the risk of stock-out 12) Slack capacity is the extent to which a company is maintaining redundant capacity (i.e., extra production line, multiple sourcing, and alternative manufacturing facilities) to absorb or cushion the detrimental effect of supply chain disruptions. QUESTION 12: SLACK CAPACITY Our company: maintains slack capacity (e.g., additional production lines and IT backup systems) in case of supply chain disruptions cross-trains employees keeps multi-use assets holds underutilized capacity which serves as a cushion to absorb the detrimental effect of any disruptions seeks alternative solutions by adding additional capacity to prevent and cushion risks sources from multiple suppliers to minimize the likelihood of supply chain disruptions To a very great extent great extent moderate extent little extent Not at all 13) Resilient supply chain readiness capability is the ability to detect and prevent the source of possible disruptions to maintain the planned level of operations. QUESTION 13: READINESS CAPABILITY Our company (prior to disruptions): can eliminate the source of potential disruptions before they occur is able to reduce the likelihood of disruptions beforehand through joint supply chain resources monitors supply chain processes in advance to prevent potential disruptions is prepared to manage expected disruptions To a very great extent great extent moderate extent little extent Not at all 156

170 has inspection plans or preventive maintenance programs to minimize the risks in supply chain collaborates with supply chain partners in detecting the sources of possible disruptions 14) Resilient supply chain response capability is the ability to cope with the realized disruption by reorganizing supply chain resources quickly. QUESTION 14: RESPONSE CAPABILITY Our company (immediately after disruptions): can rapidly respond to actual disruptions involves supply chain partners in responding to actual disruptions can quickly reorganize supply chain resources immediately after an actual disruption breaks out is able to mitigate the effect of actual disruptions in the supply chain is able to detect the root causes of disruptions in the supply chain can suspend supply chain operations until root causes of disruptions are eliminated To a very great extent great extent moderate extent little extent Not at all 15) Resilient supply chain recovery capability is the ability of supply chain resources to return to the original or better state of operations by redesigning supply chain process. QUESTION 15: RECOVERY CAPABILITY Our company (afterward until recovery): can recover from disruptions in the supply chain involves supply chain partners in recovering to a normal or planned level of operations after disruptions in the supply chain can reconfigure supply chain resources after responding to disruptions in the supply chain implements proper recovery plans/measures to recover from supply chain disruptions can resume essential business operations after responding to disruptions in the supply chain can design new plans to prevent the same supply chain disruptions from occurring in the future To a very great extent great extent moderate extent little extent Not at all 157

171 16) General Information about Your Company 1) Headquarters location? 2) What is your company's primary industry SIC or NAICS code (if not know, please note the general industry your company is in)? 17) What is your business unit? Company Division Plant Other (please specify) If you selected other, please specify 18) The number of employees working in your company: less than and over 19) Average annual sales of your company in millions of dollars: under Over 500 millions 20) Your present job title: CEO/President Vice President Director Manager Other (please specify) If you selected other, please specify 158

172 21) The years you have been employed at the current organization: under 2 years over 20 years 22) Thank you for taking the time to participate in this survey. We appreciate your time and insight. The information you provided will make a valuable contribution to uncover the impact of successful resilient supply chain practices on organizational capabilities and performance. If you want to have a copy of the results of this research, please fill in your name, address, phone number, and address below (optional). Name: Address: Phone number: address: 159

173 Appendix C Online Survey Questionnaire (Korean) "탄력적 공급사슬망위험 관리 실행과 역량에 대한 연구" Flexible and Redundant Supply Chain Practices to Build Strategic Supply Chain Resilience: Contingent and Resource-based Perspectives 1. 다음은 지난 2 년간 귀사의 공급사슬망 위험 발생 빈도에 관한 질문입니다. 해당 사항을 클릭하여 체크해 주시기 바랍니다. (QUESTIONS 1-4) Please indicate the extent to which your company has experienced these problems in your supply chain for the last two years. (QUESTIONS 1-4) 1) 내부 위험(성)은 귀사의 정상적인 생산 공정을 (예, 생산 관리) 지연시킬 수 있는 사고나 설비의 고장 (생산, 노동, 시스템)과 관련된 위험을 의미합니다. Internal risks (inside company) are risks related to any disruptions and failures of resources (i.e., production, labor, and system) to maintain a normal level of operation within an individual company. 기계고장 machine breakdowns 노사문제 (예, 파업) labor problems (e.g., strike) 운영 혹은 업무상 사고 (예, 화재 혹은 트럭사고) operational accidents (e.g., fires or truck accident) 정전, 단수 등으로 인한 가동중지 utility outages IT 시스템 고장 (예, 바이러스, 네트워크 지연) IT system breakdowns (e.g., virus attack and network delays) 적정 기준을 벗어나 설비 가동 (예, 불량품, 장비의 오작동) equipment operating out of specifications 금전적인 불안정 (예, 결제 지연) financial instability (e.g., late payment) 숙련된 기술자의 부족 lack of highly skilled employees 주별 월별 분기별 연도별 Weekly MonthlyQuarterly Annually 현재까지 미발생 Not yet 2) 공급업체 위험(성)은 공급업체가 제품이나 서비스 납품하는 과정에서 발생할 수 있는 위험을 의미합니다. Supplier related risks are risks related to any disruptions and failures of product and/or service flow from suppliers. 160

174 공급업체로 인한 다음과 같은 위험 요소들은 우리 회사의 경영에 부정적인 영향을 미친다. Our business is adversely affected by our suppliers : 갑작스런 생산 설비 역량의 변동 abrupt capacity fluctuations 일정치 않은 납품 품질 inconsistent product quality 납품 실적의 저하 (불량한 납품상태) poor delivery performance (i.e., delivery dependability) 금전적인 불안정 (예, 결제 지연) financial instability (e.g., late payment) 제품 디자인 혹은 기술 변화에 필요한 대응 능력 부족 inability to adapt to required product design or technological changes 지적재산권 으로 인한 분쟁 (예, 모조품, 위조) conflict with us regarding intellectual property ownership (e.g., counterfeit and forgery) 경쟁 업체와의 제휴 alliance with our direct competitor 주별 월별 분기별 연도별 Weekly MonthlyQuarterly Annually 현재까지 미발생 Not yet 3) 고객 관련 위험은 고객사의 불확실한 수요나 왜곡된 주문 정보로 발생하는 위험 (예, 다양한 선호도, 수요예측 오류, 고객의 지급불능 상태)을 말합니다. Customer related risks are risks related to unpredictable or misunderstood customer demand (i.e., complex preference, forecasting error, and customers bankruptcy). 다음과 같은 고객 관련 위험은 우리 회사 경영에 부정적인 영향을 미친다. Our business is adversely affected by our customers : 주문량에 대한 고객사의 부정확한 주문정보 inaccurate information about order quantities 생산 설비 역량을 초과하는 갑작스런 수요 증가 sudden demand increases which often go beyond our capacity 금전적인 불안정 (예, 결제 지연) financial instability (e.g., late payment) 귀사의 주 일정 계획의 변동을 초래하는 고객사의 급격한 수요 변화 high variation in their demand that affects our master production plan (e.g., rescheduling) 제품 사양에 대한 예측하기 힘든 요구 unpredictable requirements for product features 제품 선호의 잦은 변화 frequently changing product preferences 상이한 제품 조합의 주문 orders for different product combinations 주별 월별 분기별 연도별 Weekly MonthlyQuarterly Annually 현재까지 미발생 Not yet 161

175 4) 외부 위험(성)은 공급사슬망 외부에서 발생하는 사고나 생산 및 납품 중단과 관련된 위험 (예, 자연 재해, 불안정한 정치 상황, 국제 테러 위협) 을 말합니다. External risks are risks that arise from any disruptions and failures outside the supply chain (i.e., natural disasters, political instability, and international terror attacks). 다음과 같은 외부 위험은 우리 회사 경영에 부정적인 영향을 미친다. Our business is adversely affected by following problems outside our organization: 정치적인 불안정 (예, 새로운 법규, 전쟁) Political instability (e.g., new laws, stipulations, war, civil unrest) 질병 혹은 전염병 (예, 사스, 구제역, H1N1) Diseases or epidemics (e.g., SARS, Foot and Mouth Disease, H1N1) 자연 재해 (예, 지진, 홍수, 기후변화, 쓰나미, 화산재) Natural disasters (e.g., earthquake, flooding, extreme climate change, tsunami, ash cloud) 국제 테러 사건 (예, 9/11, 2004 년 마드리드, 2005 년 런던 폭탄테러) International terror attacks 거시경제 변수의 불확실성 (예, 환율변동, 인플레이션) Macroeconomic uncertainties (e.g., currency fluctuation, inflation) 공급사슬망과 관련된 규제 혹은 장벽 (예, 관료주의, 관세) Regulatory barriers for supply chain operations (e.g., customs, tariffs) 공급사슬망에 대한 국제 규격 혹은 법 조항의 변화 (예; ISO 9000, 운송법) Legislation or international standards changes for supply chain operations (e.g., ISO9000, transportation laws) 산업 내의 급속한 기술 변화 Fast and frequently changing technology in our industry 주별 월별 분기별 연도별 Weekly MonthlyQuarterly Annually 현재까지 미발생 Not yet 2. 각 항목에 대해서 귀사의 위험 성향 및 공급사슬망 실행 방안을 가장 잘 설명하고 있는 응답을 선택하여 주십시오. Please indicate the extent to which following statement describes your company. (QUESTIONS 5-15) 5) 위험 성향 (Risk taking propensity)은 귀사의 위험 선호 혹은 회피적인 성향을 말합니다. Risk taking propensity is a company s willingness to make resource commitments to deal with risks. 우리 회사는 Our company: 위험 부담은 높지만 고수익을 창출할 수 있는 프로젝트를 선호하는 경향이 있다 has a tendency to take on high-risk projects with chances of above average rates of return on our investment 혁신적인 제안에 대한 보상을 제공한다 provides rewards 매우 그렇다 a very great extent 그렇다 great extent 보통이다 moderate extent 약간 그렇다 little extent 전혀 그렇지 않다 Not at all 162

176 for innovative suggestions (e.g., bonuses, time off) 타사와의 경쟁에서 앞서기 위해 시장 선점 우위를 추구하는 경향이 있다 has a tendency to take the first mover s advantage by leading the competition 고수익을 위해 과감히 사내 유보금을 투자금으로 쓸 용의가 있다 is willing to put some proportion of savings in uninsured investments for the sake of higher return 고위험 프로젝트라도 새로운 경쟁 우위를 제공한다면 신속히 투자 결정을 내린다 makes quick decisions if we believe high-risk projects will provide a new competitive advantage 투자 수익률을 높이기 위해 큰 위험이라도 감수한다 is willing to take substantial risks to realize significant financial gains from investments 6) 차별화/지연 전략 (postponement)은 공급사슬 상에서 고객의 실제 수요가 정확히 파악될 때까지 제품 생산을 지연하거나 생산 공정을 재설계할 수 있는 전략을 말합니다. Extent of postponement is the ability of a company to move forward one or more operations or activities (making, sourcing and delivering) to a much later point in the supply chain to recognize and meet customers needs. QUESTION 6: EXTENT OF POSTPONEMENT 매우 그렇다 a very great extent 그렇다 great extent 보통이다 moderate extent 약간 그렇다 little extent 전혀 그렇지 않다 Not at all 우리 회사의 제품 디자인은 모듈 조립 방식을 따른다 Our products are designed to use standard sub-assemblies for modularity 우리 회사는 최종 제품 조립을 공급사슬망의 마지막 (고객사에 가장 근접한) 단계 에서 수행한다 Our company delays final product assembly activities until the last possible position (or nearest to customers) in the supply chain 우리 회사의 제품은 공급사슬망에서 고객사(소비자 포함)에게 가장 근접한 물류 센터에 적재된다 Our goods are stored at appropriate distribution points close to the customers in the supply 우리회사의 물류센터에서는 고객 맞춤형 조립을 위해, 생산공정 모듈을 재배치할 수 있다 Our production process modules can be re-arranged so that customization can be carried out later at distribution centers 우리 회사는 고객사의 실제 수요가 파악될 때까지 최종 제품 조립 과정을 연기한다 Our company delays final product assembly activities until customer orders have actually been received (e.g., assembly-to-order) 우리 회사는 제품 디자인시 다음 신제품 디자인에 대한 고려를 한다 Our product designs enable us to accommodate several generations of products 163

177 7) 정보공유(Information sharing)는 공급사슬 협력업체들과의 중요한 정보교환 정도를 말합니다. Information sharing is the extent to which critical and proprietary information is exchanged with supply chain partners. 우리 회사는 공급사슬 협력업체들과 중요/민감한 정보 (예, 생산, 투자, 디자인 혹은 위험)를 공유한다 Our company shares our business units proprietary information (e.g., production, financial, design, and risk) with supply chain partners 우리 회사는 공급사슬 협력업체들에게 지속적으로 변화하는 고객의 니즈를 사전통보한다 Our company informs our supply chain partners of changing needs of customers in advance 우리의 공급사슬 협력업체들은 중요/민감한 정보들을 우리와 공유한다 Our supply chain partners share their proprietary information with us 우리의 공급사슬 협력업체들은 핵심 비지니스 프로세스에 대한 정보를 우리와 공유한다 Our supply chain partners share their business knowledge of core business processes with us 우리 회사와 공급사슬 협력업체들은 서로에게 영향을 미칠 수 있는 사건이나 변화에 대한 믿을 만한 정보를 자주, 제 때 공유한다 Our company and supply chain partners keep each other informed frequently and in a timely manner about events or changes that may affect other partners 우리 회사와 공급사슬 협력업체들은 경영 계획 수립에 도움이 되는 정보들을 교환한다 Our company and supply chain partners exchange information that helps in the establishment of business planning 매우 그렇다 a very great extent 그렇다 great extent 보통이다 moderate extent 약간 그렇다 little extent 전혀 그렇지 않다 Not at all 8) 안전/보안 규제 준수 (Security compliance)는 공급사슬망 위험으로부터 회사 자산 (예, 제품, 설비, 장비, 정보, 인력)을 보호하기 위한 국제 보안 규격 준수와 관련 제도 및 기술의 도입 정도를 말합니다. (예, Container Security Initiative (CSI), Customer-Trade Partnership Against Terrorism (C-PAT)) Security compliance is the application of policies, procedures, and technology to protect the destruction of supply chain assets (i.e., product, facilities, equipment, information and personnel) from theft, damage, or terrorism. 우리 회사는 Our company: 공급사슬망 보안 담당 부서들을 두고 있다 has a function that specializes in supply chain security and compliance 보안에 대한 국제 표준, 산업 규격 및 정부의 보안 가이드라인을 준수한다 (예, 컨테이너 안전 협정) follows government or industry security guidelines (e.g., C-PAT, CSI, FAST, AMR, etc) 공급사슬망 협력업체들의 안전 및 보안 절차에 대한 감사를 한다 (종업원/운전기사 신원조회, 포장검사) audits security 매우 그렇다 a very great extent 그렇다 great extent 보통이다 moderate extent 약간 그렇다 little extent 전혀 그렇지 않다 Not at all 164

178 procedures of supply chain partners (e.g., employee/driver background checks, origination and ownership, ingredients, and packaging procedures) 공급사슬망 협력업체들이 보안에 대한 산업 규격 및 정부 가이드라인을 준수하고 있는지 점검한다 (예, CSI, C-PAT) verifies that supply chain partners follow government or industry security guidelines (e.g., C-PAT, CSI, FAST, AMR, etc) 공급사슬망 협력업체들을 대상으로 보안 교육 프로그램을 실시하고 있다 has specific education programs for supply chain partners regarding security procedures 협력업체들이 공급사슬망 보안절차를 준수하지 않으면 받게 될 불이익을 명시한다 has defined consequences for supply chain partners who fail to comply with supply chain security procedures 9) 협력 (Collaboration) 이란 공급사슬망 위험에 대처 하기 위한, 우리 회사와 협력업체들 간 공동작업의 정도를 말합니다. Extent of collaboration is the extent to which supply chain entities are collaborating to cope with supply chain risks. 우리 회사는 Our company: 우리 회사의 전략 수립 과정에 협력업체들을 참여시킨다 includes supply chain partners in our goal-setting activities and planning 유사 시 협력업체들과 공동으로 문제 해결을 한다 regularly solves problems jointly with our supply chain partners 제품 디자인 및 개발의 초기 단계 부터 협력업체들을 참여시킨다 involves supply chain partners early in the new product design and development effort 공급사슬망 공정에 대한 계획 및 실행을 협력업체들과 공동으로 한다 works jointly with supply chain partners to plan and execute supply chain operations 협력업체들과 위험 발생시 공동으로 책임을 진다 is jointly responsible with supply chain partners for making sure that disruptions are properly handled 위험을 관리하는 데 있어 협력업체들과 공동으로 공급사슬망 위험을 관리한다 collaborates with supply chain partners in managing disruptions 협력업체들과의 공동 작업 및 협력을 위험 관리의 중요한 필요 조건으로 생각한다 regards the collaboration with supply chain partners as important in risk management 매우 그렇다 a very great extent 그렇다 great extent 보통이다 moderate extent 약간 그렇다 little extent 전혀 그렇지 않다 Not at all 10) 비상계획 (Contingency planning) 이란 공급사슬망 위험 관리 및 사고 발생에 대비하기 위한 일련의 사전 비상/대응 계획을 말합니다. Contingency planning is the series of specified business activities that are designed to deal with supply chain risks before they occur. 165

179 우리 회사는 Our company: 예상치 못한 사고에 대한 사전 비상 계획을 마련한다 prepares a set of contingency action plans for unexpected disruptions 특정 위험요소 및 사건에 대한 책임 부서의 역할을 지정하고 있다 assigns roles and responsibilities for particular types of disruptions 공급사슬망 협력업체들을 비상대책 계획 수립에 참여시킨다 involves our supply chain partners in developing contingency plans 공급사슬망 협력업체과 공동으로 비상 대책 계획을 수립한다 jointly develops contingency plans along with our supply chain partners 비상대책 계획을 수립할 때 공급사슬망 협력업체들의 의견을 신뢰 및 존중한다 can count on supply chain partners for implementing contingency plans 예상치 못한 사고에 대한 구체적인 대응 방안을 구축한다 defines specific processes in case of unexpected disruptions 비상 대책 계획의 변동사항을 공급사슬망 협력업체들에게 통보한다 keeps our supply chain partners informed of updated contingency plans 매우 그렇다 a very great extent 그렇다 great extent 보통이다 moderate extent 약간 그렇다 little extent 전혀 그렇지 않다 Not at all 11) 안전재고 (Safety stock)는 공급사슬망 위험의 부정적인 영향을 완화시키기 위해 우리 회사가 보유하고 있는 여분의 재고 정도 (예, 추가 부품 및 원재료, 임시 재고)를 말합니다. Safety stock is the extent to which a company is maintaining redundant stock (i.e. added inventory and extra components/parts) to absorb or cushion the detrimental effect of supply chain disruptions. 우리 회사는 Our company: 공급사슬망 사고에 대비하여 안전 재고를 보유하고 있다 maintains safety stock in case of supply chain disruptions 전략적인 부품이나 원재료에 대한 추가 재고를 가지고 있다 keeps extra inventory of strategic items (e.g., raw materials, parts, and finished goods) 공급사슬망 사고 발생 시 원상 복구에 필요한 시간 동안 사용할 수 있는 안전재고를 보유하고 있다 uses safety stock to have time to prepare response and recovery in case of disruption 수요변화와 생산지연에대응하기 위해 안전재고를 보유하고 있다 holds safety stock to deal with variable demand rate or lead time 공급사슬망 사고(예, 공급자의 납품기한 미준수,기계고장)의 발생률을 줄이기 위해 안전재고를 보유하고 있다 maintains safety stock to reduce the likelihood of supply chain disruptions (e.g., supplier failure, machine breakdown) 매우 그렇다 a very great extent 그렇다 great extent 보통이다 moderate extent 약간 전혀 그렇지 그렇다 little 않다 Not at extent all 166

180 재고부족의 위험을 줄이기 위해 안전재고를 보유하고 있다 holds buffer stock to mitigate the risk of stock-out 12) 추가 생산 역량 (Slack capacity)은 공급사슬망 위험의 부정적인 영향을 완화시키기 위해 우리 회사가 보유하고 있는 추가적인 생산 역량 (예, 추가 생산라인, 아웃소싱, 대체 생산설비)을 말합니다. Slack capacity is the extent to which a company is maintaining redundant capacity (i.e., extra production line, multiple sourcing, and alternative manufacturing facilities) to absorb or cushion the detrimental effect of supply chain disruptions. 우리 회사는 Our company: 공급사슬 위험에 대비한 잉여자원 (생산라인 추가, IT 백업시스템)을 보유하고 있다 maintains slack capacity (e.g., additional production lines and IT backup systems) in case of supply chain disruptions 종업원들을 여러 부서에 배치하여 훈련한다 (employee cross-training) cross-trains employees 다용도로 쓰일 수 있는 자산 (예, 다기능 기계설비, multi-use assets)을 보유하고 있다. keeps multi-use assets 공급사슬망 사고에 대한 완충 역활을 할 수 있는 미활용 설비를 보유하고 있다 holds underutilized capacity which serves as a cushion to absorb the detrimental effect of any disruptions 위험 방지를 위한 생산 설비를 추가하여 유사 시 대책을 마련한다 seeks alternative solutions by adding additional capacity to prevent and cushion risks 공급사슬망 사고의 발생률을 최소화 시키기위해 여러 공급업체들과 거래한다 sources from multiple suppliers to minimize the likelihood of supply chain disruptions 매우 그렇다 a very great extent 그렇다 great extent 보통이다 moderate extent 약간 그렇다 little extent 전혀 그렇지 않다 Not at all 13) 탄력적 공급사슬망 대비 역량 (Resilient supply chain readiness capability)은 정상 수준의 공정을 유지할 수 있도록 공급사슬 사고의 잠재적인 원인을 추적 및 제거할 수 있는 역량을 말합니다. Resilient supply chain readiness capability is the ability to detect and prevent the source of possible disruptions to maintain the planned level of operations. 우리 회사는 (사고 발생 전) Our company (prior to disruptions): 사고 발생 전에 잠재적인 공급사슬망 사고의 원인을 제거할 수 있다 can eliminate the source of potential disruptions before they occur 협력업체들과 함께 사전에 공급사슬망 사고 발생 가능성을 줄이고 있다 is able to reduce the likelihood of disruptions beforehand through joint supply chain resources 잠재적인 사고 발생의 방지 차원에서 사전에 공급사슬망을 매우 그렇다 a very great extent 그렇다 great extent 보통이다 moderate extent 약간 그렇다 little extent 전혀 그렇지 않다 Not at all 167

181 모니터링 한다 monitors supply chain processes in advance to prevent potential disruptions 예상된 사고들을 관리할 수 있는 준비가 되어 있다 is prepared to manage expected disruptions 공급사슬망 위험을 최소화하는 검열계획이나 사전예방 프로그램을 운용하고 있다 has inspection plans or preventive maintenance programs to minimize the risks in supply chain 가능한 위험원인을 제거하는데 협력업체들과 공동의 노력을 기울인다 collaborates with supply chain partners in detecting the sources of possible disruptions 14) 탄력적 공급사슬망 대응 역량 (Resilient supply chain response capability)은 공급사슬망 자원들을 즉시 재구성함으로써 실제 발생한 사고들에 대처하는 능력을 말합니다. Resilient supply chain response capability is the ability to cope with the realized disruption by reorganizing supply chain resources quickly. 우리 회사는 (사고 발생 직후) Our company (immediately after disruptions): 실제 공급사슬망 사고가 발생했을 때 즉시 대처할 수 있다 can rapidly respond to actual disruptions 실제 발생한 사고에 대해 협력업체들과 공동으로 대처한다 involves supply chain partners in responding to actual disruptions 사고가 발생했을 때 공급사슬망 자원들을 즉각적으로 재구성할 수 있다 can quickly reorganize supply chain resources immediately after an actual disruption breaks out 발생한 사고의 파급 효과를 완충시킬 수 있다 is able to mitigate the effect of actual disruptions in the supply chain 사고 발생 직후 사고의 근본 원인을 발견할 수 있다 is able to detect the root causes of disruptions in the supply chain 사고 발생 직후 사고의 근본 원인이 제거/처리될 때까지 공급사슬망 운영 (예, 생산공정)을 일시 중단할 수 있다 can suspend supply chain operations until root causes of disruptions are eliminated 매우 그렇다 a very great extent 그렇다 great extent 보통이다 moderate extent 약간 그렇다 little extent 전혀 그렇지 않다 Not at all 15) 탄력적 공급사슬망 회복 역량 (Resilient supply chain recovery capability)은 공급사슬망 사고 대처 이후 공급사슬망 프로세스의 재설계를 통해, 정상 혹은 계획된 공정 수준을 회복할 수 있는 역량을 말합니다. Resilient supply chain recovery capability is the ability of supply chain resources to return to the original or better state of operations by redesigning supply chain process. 우리 회사는 (사고 대처 이후 회복까지) Our company (afterward until recovery): 매우 그렇다 a very great extent 그렇다 great extent 보통이다 moderate extent 약간 그렇다 little extent 전혀 그렇지 않다 Not at all 168

182 공급사슬망 사고 발생 이후 제조 공정을 회복할 수 있다 can recover from disruptions in the supply chain 사고 발생 후 정상적인 또는 계획된 공정 수준으로 회복하는 과정에 공급사슬망 협력업체들을 참여시킨다 involves supply chain partners in recovering to a normal or planned level of operations after disruptions in the supply chain 정상적인 혹은 계획된 공정 수준으로 복귀하기 위해 공급사슬망 자원들을 재구성 할 수 있다 can reconfigure supply chain resources after responding to disruptions in the supply chain 사고 발생 후 복구계획 및 조치들을 적절하게 실행하고 있다 implements proper recovery plans/measures to recover from supply chain disruptions 사고처리 이후 핵심적인 사업운영 및 생산공정을 재개할 수 있다 can resume essential business operations after responding to disruptions in the supply chain 향후 동일한 공급사슬망 사고가 발생하지 않도록 새로운 계획안을 수립한다 can design new plans to prevent the same supply chain disruptions from occurring in the future 16) 다음은 귀사의 일반적인 정보를 묻는 질문들입니다. General Information about Your Company 1) 본사 위치 Headquarters location? 2) 귀사의 주요 산업을 나타내는 그룹을 선택하여 주십시오 What is your company's primary industry SIC or NAICS code (if not know, please note the general industry your company is in)? 17) 귀사의 사업 단위는 What is your business unit? 회사 Company 부서 Division 공장 Plant Other (please specify) If you selected other, please specify 18) 귀사에 근무하는 직원의 수는 몇 명입니까 The number of employees working in your company: less than and over 169

183 19) 귀사의 작년도 매출액은 얼마입니까? Average annual sales of your company in hundred millions of Won: under Over ) 귀하의 직위는 Your present job title: 대표이사 혹은 사장 CEO/President 부사장 Vice President 임원 Director 중간관리자 Manager Other (please specify) If you selected other, please specify 21) 귀하께서 현 직장에서 근무하신 기간은 The years you have been employed at the current organization: 2 년 이하 under 2 years 년 이상 over 20 years 22) 지금까지 본 설문에 응답해 주시어 진심으로 감사 드립니다. Thank you for taking the time to participate in this survey. We appreciate your time and insight. 귀하의 설문 응답은 탄력적 공급사슬망 실행 방안들이 조직역량 및 성과에 미치는 영향을 규명하는 데 큰 기여를 할 것입니다. The information you provided will make a valuable contribution to uncover the impact of successful resilient supply chain practices on organizational capabilities and performance. 본 설문의 결과 또한 받아 보시려면 아래의 빈 칸에 이름, 주소, 전화 번호, 이메일 주소를 기입해 주십시오. If you want to have a copy of the results of this research, please fill in your name, address, phone number, and address below (optional). Name: Address: Phone number: address: 170

184 Appendix D Summary of Measurement Constructs Internal risks (IR) Supplier related risks (SR) Customer related risks (CR) External risks (ER) Risk Taking propensity (RP) Extent of Postponement (EP) Information sharing (IS) Security compliance (SC) Risks related to any disruptions and failures of resources (i.e. production, labor, and system) to maintain normal level of operation (problems within an individual company) Risks related to any disruptions and failures of product and/or service flow from suppliers side Risks related to unpredictable or misunderstood customers demand (i.e. complex preference, forecasting error, and customers bankruptcy) (customers side) Risks that arise from any disruptions and failures outside the supply chain (i.e. natural disasters, political instability, and international terror attacks) (outside company) Company s willingness to make resource commitments to deal with risks The ability of a company moving forward one or more operations or activities (making, sourcing and delivering) to a much later point in the supply chain to recognize and meet customers needs The extent to which critical and proprietary information is exchanged with supply chain partners The application of policies, procedures, and technology to protect the destruction of supply chain assets (i.e. product, facilities, equipment, information and personnel) from theft, damage, or terrorism 171

185 Extent of Collaboration (EC) Contingency planning (CP) Safety Stock (SS) Slack Capacity (SLC) Resilient Supply Chain Readiness Capability (RDC) Resilient Supply Chain Response Capability (RPC) Resilient Supply Chain Recovery Capability (RRC) The extent to which supply chain entities are collaborating to cope with supply chain risks The series of specified business activities that are designed to deal with supply chain risks before they occur The extent to which a company is maintaining redundant stocks (i.e. added inventory) to absorb or cushion the detrimental effect of supply chain risks The extent to which a company is maintaining redundant capacity (i.e. extra production line, extra IT systems, and alternative manufacturing facilities) to absorb or cushion the detrimental effect of supply chain risks The ability to detect and prevent the source of possible disruptions to maintain to the planned level of operations in advance (prior to failures and disruptions) The ability to cope with the realized disruption by reorganizing supply chain resources quickly (immediately after failure) The ability of supply chain resources to return to the original or better state of operations by redesigning supply chain process following a disruption (afterwards until recovery) 172