The Effect of Collaborative Demand Planning on Tier 1 Supplier Responsiveness

Transcription

1 Abstract The Effect of Collaborative Demand Planning on Tier 1 Supplier Responsiveness Sang Ho Chae Yonsei School of Business, Yonsei University A204, Parkhouse, 140-1, Daeshin-dong, Seodaemun-gu, Seoul, , South Korea [email protected] +82 (0) POMS 22nd Annual Conference Reno, Nevada, U.S.A. April 29 to May 2, 2011

2 1. Introduction 1.1 Research Context Collaboration and information sharing between companies in supply chains have been one of the major topics for supply chain management professionals and researchers. Since the adoption of electronic data interchange (EDI), information systems for interfirm communication have enabled firms to implement new collaboration processes to increase supply chain performance. In 1992, efficient consumer response (ECR) was initiated by the grocery retail industry to reduce costs in supermarket distribution chain and respond to consumer demand quickly (Lee, 2002). Collaborative Planning, Forecasting, and Replenishment (CPFR) is a second-generation ECR suggested by the Voluntary Interindustry Commerce Standard (VICS) (VICS, 2000; Seifert, 2003). Recently, consumer electronics manufacturers and their customers, including retailers and mobile network operators, have been implementing CPFR to cope with fast changing consumer demand. As consumers require lower price and higher availability of various electronic goods, leading consumer electronics retailers are increasing collaboration with consumer electronics 2 manufacturers to meet consumer demand efficiently. However, Frohlich and Westbrook (2001) argue that supply chain integration

3 between only customers (e.g. electronics retailers) and manufacturers (e.g. electronics manufacturers) without integration with manufacturers suppliers brings little benefit. Considering this indication of Frohlich and Westbrook (2001), this study assumes that a successful implementation of a collaborative demand planning between a manufacturer and a retailer should be also supported by integration with the manufacturer s suppliers. Adopting a single case study of Samsung Electronics a multinational semiconductor and consumer electronics manufacturer, this study investigates the relationships between collaborative demand planning such as CPFR and the manufacturer s integration with suppliers. 1.2 Research Question A recently developed manufacturing paradigm of agile supply chain pursues highly responsive manufacturing and supply chain processes to constantly changing market situations. Therefore, a manufacturer may consider the following underlying problems when it implements collaboration processes with customers and suppliers: 1. Responding efficiently to customer demand 2. Increasing responsiveness of suppliers 3 Within the context of CPFR implementation in the consumer electronics industry, this

4 study aims at understanding the approaches of a consumer electronics manufacturer to solve above problems. These problems are narrowed down to the following research question. How does CPFR implementation affect responsiveness of manufacturer s suppliers? In relation to the research context and research question, the rest of this study is organized into the following sections. The second section reviews the literature to build a theoretical foundation of this study. Based on the discussion in Section 2, the conceptual model to explain the effect of CPFR is developed in the third section. Section 4 justifies the application of the case study method to this research project and explains the methods for data collection and analysis. In Section 5, the conceptual model developed in Section 3 is tested by analyzing the case of Samsung Electronics. Finally, the conclusion in Section 6 provides implications for managers and suggestions for further research. 2. Theoretical Background 2.1 The Resource Based View 4

5 The resource based view of the firm recognizes the firm as a bundle of productive resources (Penrose, 1959). In the strategic management literature, the interchangeably used terms of firm resources and capabilities are defined as tangible and intangible assets that enable firms to develop and implement strategies (Porter, 1981; Daft, 1983). Firm resources can be classified into three categories of physical capital resources (Williamson, 1975), human capital resources (Becker, 1964), and organizational capital resources (Tomer, 1987). The resource based view explains the firm s sustained competitive advantage under two main assumptions. First, this model assumes that resources within firms are heterogeneous and have different levels of efficiency (Peteraf, 1993). Resources with higher level of efficiency enable firms to create higher value to customers or produce at lower cost. Second, the model assumes that these heterogeneous resources may not be easily transferable between firms. Under the assumptions of heterogeneity and immobility of firm resources, Barney (1991) suggests four conditions that a firm resource must have in order to create sustained competitive advantage over rival firms. These conditions are: value, rareness, imperfect imitability, and imperfect substitutability. Firm resources meeting above conditions are often 5 Traditionally, strategic resources have been thought to be restricted to the boundaries termed strategic resources.

6 of the firm and non-tradable (Dierickx and Cool, 1989). It is claimed that if the resources are tradable, they are not inimitable or immobile anymore, thus cannot create sustained competitive advantage. However, recent studies suggest a broader view of strategic resources that they may exist beyond the boundaries of the firm (Das and Teng, 2000), or within the network of inter-firm relationships (Afuah, 2001). These recent approach to strategic resources termed the extended resource based view of the firm, suggests the attainability of strategic assets outside of the firm boundaries (Mathews, 2003). Based on the resource based view, Ireland et al. (2002) especially emphasize that effectively managed strategic alliances can be a source of valuable firm resources and create sustained competitive advantage. They suggest that strategic alliances provide access to previously unavailable resources and opportunities to develop new resources by collaboration. Moreover, strategic alliances allow firms to access complementary resources, which can develop new competitive advantage (Ireland et al., 2001) through economies of scope, synergies, and development of new resources and subsequent skills (Hitt et al., 2001). 2.2 Social Capital Theory 6

7 Social capital is a valuable asset that stems from access to resources made available through social relationships (Granovetter, 1992). Nahapiet and Ghoshal (1998) suggest that there are three highly interrelated dimensions of social capital that can be developed between partner firms: structural dimension, relational dimension, and cognitive dimension. The structural dimension of social capital refers to the overall pattern of connections between actors (Nahapiet and Ghoshal, 1998). The relational dimension of social capital refers to the strength of network ties between actors (Krause et al., 2007), or assets embedded in personal relationships, such as trust, obligation and reciprocity (Nahapiet and Ghoshal, 1998). Nahapiet and Ghoshal (1998) identify the cognitive dimension of social capital as the resources providing shared representations, interpretations, and system of meaning between actors. Recently, the supply chain management literature has applied social capital theory in the context of buyer-supplier relationships. Krause et al. (2007) suggest that relational capital (buyer and supplier dependence) accumulation has significant positive effects on buyer cost and total cost performance improvements, while structural capital (supplier development activities) accumulation has more impacts on quality, delivery, and flexibility. Cognitive capital (shared goals 7 and values) accumulation has important effects on buyer performance improvements in cost and total cost, as well as quality,

8 delivery, and flexibility. Lawson et al. (2008) argue that relational capital (personal interaction, mutual respect, and mutual trust) accumulation and structural capital (managerial communication and technical exchange) accumulation have positive relationships with buyer performance improvement in product design, process design, lead time, and product quality. Cousins et al. (2006) put more focus on relational capital and investigate how formal and informal socialization mechanisms facilitate relational capital accumulation and impact supplier relationship outcomes. Gupta and Govindarajan (2000: 483) refer socialization mechanisms to those organizational mechanisms which build interpersonal familiarity, personal affinity, and convergence in cognitive maps among personnel from different subsidiaries. Applying the extended resource based view, Cousins and Menguc (2006) suggest that relational capital created by inter-firm socialization mechanisms may be seen as a strategic resource of the firm, since it is valuable, rare, and difficult to imitate or substitute. Drawing on these arguments, it can be suggested that inter-firm socialization plays an important role in sustaining competitive advantage of the firm. 2.3 Supply Chain Management Supply Chain Integration 8

9 Supply chain integration is defined as linking their internal processes to external suppliers and customers in unique supply chains (Frohlich and Westbrook, 2001: 185). Ragatz et al. (2002) point out that supply chain integration is critical for the delivery of superior consumer value and improves cost performance, delivery, quality, and cycle time. Frohlich and Westbrook (2001) argue that companies with seamlessly integrated supply chain with both suppliers and customers have higher rates of performance improvement. Based on their empirical research investigating 322 manufacturers around the world, they introduce a graphical illustration of strategic positions in supply chain integration called the arcs of integration to suggest that firms with the outward-facing supply chain strategy (extensive integration with both suppliers and customers) have the highest rates of performance improvement. Another empirical research of Frohlich and Westbrook (2002) on demand chain management (DCM) shows similar results. Demand chain management is based on pull control, where supply chain actions and movements of materials are triggered by the end-customers demand (Lummus and Vokurka, 1999). Based on the data collected from United Kingdom manufacturers and services, Frohlich and Westbrook (2002) 9 compare the web-based demand chain management model to the web-based demand integration, web-based supply integration,

10 and web-based low integration models. The result of their study shows that adopting the demand chain management strategy brings more benefits (faster delivery time, reduced transaction costs, greater profitability, and enhanced inventory turnover) than adopting the demand integration, supply integration, or low integration strategy. Paulraj and Chen (2007) investigate the antecedents of supply chain integration and argue that strategic buyer-supplier relationships and information technology have positive effects on supply chain integration. Better coordination based on trust and commitment between buyers and suppliers facilitates supply chain integration (Cavinato, 2005). Information technology also enhances supply chain integration by facilitating collaborative planning (Karoway, 1997) and linking demand information to upstream supply chain activities (Min and Galle, 1999). In addition to identifying the antecedents of supply chain integration, Paulraj and Chen (2007) argue that supply chain integration and supply chain agility performance are positively related Agile Supply Chains Supply chain agility is defined as the supply chain s capability to adapt or respond in a speedy manner to a changing marketplace 10 environment (Swafford et al., 2006: 172). Agile supply chains allow firms to have competitive advantage over competitors by

11 enabling firms to have better market sensitivity, capability of synchronizing supply with demand, and ability to reduce cycle times (Swafford et al., 2006). Brown and Eisenhardt (1998) argue that to be competitive, firms have to adapt to unpredictable, constantly changing marketplace conditions. Fisher (1997) proposes that the design of a supply chain should be aligned with the type of products to pursue higher performance of the supply chain. He categorizes products and supply chains into functional / innovative products and physically efficient / market responsive supply chains, respectively. Market-responsive supply chains can be alternatively termed agile supply chains. He argues that innovative products with demand variation and short life cycles should be processed by an agile supply chain. On the other hand, he suggests that functional products should be processed by a physically efficient or lean supply chain. Selldin and Olhager (2007) empirically test Fisher s (1997) model and show that the companies with the match between products and supply chain type perform better in cost, delivery speed, and delivery dependability. As Fisher (1997) suggests the differences between physically efficient supply chains and market responsive supply chains, Christopher (2000) distinguishes agility from leanness. He notes that leanness focuses on the elimination 11 of waste and by itself it does not enable the ability of the organization to meet specific customer needs more rapidly.

12 Lee (2004) emphasizes the importance of agile, adaptable, and aligned supply chain, which he terms the triple-a supply chain, to build a sustained competitive advantage. According to Swafford et al. s (2006) definition of supply chain agility, Lee s (2004) term of adaptability can be also described as agility. Alignment, which is achieved by exchange of information and knowledge, sharing risks, costs, and benefits between buyers and suppliers (Lee, 2004), can be described as supply chain integration. Therefore, Lee s (2004) argument of agile, adaptable, and aligned supply chains is also highlighting the importance of supply chain integration and supply chain agility. Current business practices, such as efficient consumer response (ECR) and Collaborative Planning, Forecasting, and Replenishment (CPFR) are pursuing both supply chain integration and supply chain agility. 2.4 ECR and CPFR Efficient Consumer Response (ECR) is a retailer-supplier collaboration process developed for the United States grocery retailers and branded manufacturers in the early 1990s. ECR is based on the pull principle pursuing synchronization of production and distribution on the basis of the real demand 12 information from consumers (Seifert, 2003). ECR practices consist of three major areas of joint marketing and sales activities, joint

13 logistics and supply chain activities, and collaborative information technology and process improvement tools (Corsten and Kumar, 2005). The benefits of efficient consumer response (ECR) have been addressed by large retailers and manufacturers, such as Coca-Cola (CCRRGE, 1994) and Wal-Mart (Seifert, 2003; p.1). Collaborative Planning, Forecasting, and Replenishment (CPFR) is a secondgeneration ECR suggested by the Voluntary Interindustry Commerce Solutions (VICS) (VICS, 2000; Seifert, 2003). CPFR requires more collaboration between participating partners than ECR, because it includes joint long-range forecasting rather than solely relying on inventory replenishment triggered by actual customer demand (Grant et al, 2006: 157). VICS suggests the following CPFR process model (see Table 2.1) as a guideline for CPFR implementation (Seifert, 2003). <Table 2.1> CPFR Process Model 1. Develop Collaboration Arrangement Planning 2. Create Joint Business Plan 3. Create Sales Forecast Forecasting 4. Identify Exceptions for Sales Forecast 5. Resolve/Collaborate on Exception Items 6. Create Order Forecast Generate Order Replenishment 7. Identify Exceptions for Order Forecast 8. Resolve/Collaborate on Exception Items <Adapted from Seifert (2003: 35)>

14 CPFR process model has three stages of planning, forecasting, and replenishment. These stages are subdivided into nine steps as shown in Table 2.1. The first step of the model is to identify and agree the objectives and rules of collaboration between customer and manufacturer. The second step is to develop joint business plan, which defines product group roles, objectives, and articles (Seifert, 2003: 37). The third to fifth steps are to cooperate on sales forecast by creating sales forecast, agree exceptions for sales forecast, and clarifying exceptions to the sales forecast. The sixth to eighth steps are to synchronize order forecast between customer and manufacturer. The final step (step 9) is order generation. CPFR implementation cases in business practices support the positive effect of CPFR on supply chain performance. Motorola s CPFR initiative improved forecast accuracy, reduced inventory at the retailer s distribution center, stock-out rates and transportation costs, and increased long-term shipments (Cederlund et al., 2007). A pilot CPFR-based program of West Marine reduced stock-outs and improved forecast accuracy and ontime delivery (Smith, 2006). Sears, Roebuck and Co. and the Michelin North American Tire Co. s CPFR initiative in 2001 helped 14 Sears to achieve improvement in store instock levels and increase in distribution-centers-to-store fill rate, while reducing

15 combined Michelin and Sears inventory levels (Steermann, 2003). Procter & Gamble in Europe implemented projects applying the CPFR concept and experienced benefits, such as improved forecast accuracy and product availability, and reduction in inventory and rush orders (Seifert, 2003: 276). Modeling-based researches also support the positive effect of CPFR implementation on supply chain performance. Chen et al. (2007) use simulation modeling to investigate the effect of non-collaboration and CPFR implementation on supply chain performance. The result of their simulation shows that CPFR implementation scenarios perform significantly better than non-collaboration scenario in average system service level, average system fulfillment rate, average system cycle time, and total system cost (Chen et al., 2007). Raghunathan (1999) models a supply chain of two customers and a manufacturer to investigate the effect of shared forecasts and shows that forecast information sharing decreases customer and manufacturer s costs. Aviv (2001) compares two models of joint forecasting and individual forecasting and concludes that joint forecasting is more beneficial. 3. Conceptual Model and Hypotheses 15

16 In this section, the research question How does CPFR implementation affect responsiveness of manufacturer s suppliers? is hypothesized into a conceptual model. The model consists of the constructs developed from the theoretical discussions in Section 2 and the relationships between the constructs are represented as four hypotheses (Hypothesis 1, Hypothesis 2a, Hypothesis 2b, and Hypothesis 3). 3.1 Proposed Conceptual Model Figure 3.1 shows the conceptual model illustrating the relationship between CPFR implementation, manufacturer s forecast accuracy, and supplier responsiveness. As shown in the research question in Section 1.2, the objective of this study is to find out the relationship between CPFR implementation and supplier responsiveness. In addition, this research project intends to identify the driver of CPFR adoption. Applying Fisher s (1997) proposition, the conceptual model adopts the manufacturer s intention to build agile supply chain as an antecedent of CPFR adoption. Lastly, as a reflection of the recent research on supply chain socialization, the conceptual model hypothesizes the relationship between supply chain socialization and the effect of CPFR implementation. 16 <Figure 3.1> Conceptual model for the effect of CPFR

17 CPFR H2a Manufacturer s Forecast H2b Supplier Implementation Accuracy Responsiveness H1 H3 Intention to Agile Supply Chains Supply Chain Socialization Moderator Agile Supply Chains and CPFR Implementation Fisher (1997: 108) argues that the primary purpose of agile supply chains is to respond quickly to unpredictable demand in order to minimize stock-outs, forced markdowns, and obsolete inventory. He suggests that innovative products should be produced by agile supply chains. Innovative products have characteristics, such as short product life cycle, high product variety, high stock-out rate, and short required lead-time (Fisher, 1997). Consumer electronics and mobile handset manufacturers recognize their products as innovative products and implement collaboration processes with their customers to respond quickly and efficiently to consumer demand (Collin and Lorenzin, 2006; Cederlund et al., 2007). In other words, 17 it can be argued that these manufacturers are implementing collaborative planning to build agile supply chains. Therefore, it can

18 be hypothesized that: Hypothesis 1. Manufacturer s intention to have agile supply chains leads Collaborative Planning, Forecasting, and Replenishment (CPFR) implementation CPFR Implementation, Forecast Accuracy, and Supplier Responsiveness The direct positive effect of CPFR on forecast accuracy is highlighted by a number of studies. Seifert (2003) argues that collaboration on sales forecasting between trading partners combines knowledge of them and provides more reliable sales forecasts. Chopra and Meindl (2007) also suggest that collaboration with supply chain partners creates more accurate forecast. For a manufacturer, collaboration with customers improves forecast accuracy because it can not only obtain valuable data, such as pointof-sale (POS) data, but also coordinate on promotion, order generation, and production planning. Thus, this study posits the following hypothesis: Hypothesis 2a. Implementation of Collaborative Planning, Forecasting, and Replenishment (CPFR) improves manufacturer s forecast accuracy. Frohlich and Westbrook (2001) emphasize the importance of integration with both customers and suppliers. Without collaboration 18 between all supply chain partners, the manufacturer cannot achieve higher supply chain performance. In the context of CPFR

19 implementation, supplier responsiveness has to be improved to achieve higher responsiveness of the manufacturer. Linking demand information to upstream supply chain activities (Min and Galle, 1999) is an important part of supply chain integration. Paulraj and Chen (2007) argue that supply chain integration and supply chain agility performance including responsiveness, are positively related. If forecast accuracy is improved through CPFR implementation, the manufacturer can provide better demand information to suppliers and improve their demand planning and responsiveness. Suppliers inventory, production, transportation, sourcing, and pricing depend on accurate forecasting (Chopra and Meindl, 2007: 211). Friscia et al. (2004) argue that demand forecast accuracy improves responsiveness and reduces cost of the supply chain. Hence, Hypothesis 2b. Manufacturer s improved forecast accuracy improves supplier responsiveness Supply Chain Socialization It is suggested that supply chain socialization mechanisms facilitate information flows between firms (Cousins and Menguc, ). Examples of supply chain socialization mechanisms are: cross-functional team between a major buyer and a major

20 supplier (Ghoshal and Bartlett, 1990); and frequent inter-organizational rotation of individuals (Kumar and Seth, 1998). Cousins and Menguc (2006) argue that supply chain socialization has a significant impact on supplier s operational performance and communication performance. In addition, Cousins et al. (2006) show that informal socialization processes facilitate creation of buyer-supplier relational capital. Lawson et al. (2008) found that relational capital and structural capital accumulation has positive effects on performance improvement including lead-time performance. This study suggests that if socialization mechanisms are used between the manufacturer and the supplier, forecast accuracy will have a greater impact on supplier responsiveness. Therefore, Hypothesis 3. Socialization mechanisms between the manufacturer and suppliers enhance the effect of forecast accuracy on supplier responsiveness. Chapter 4 - Research Methods This study mainly employs a single case study to answer the research question. In a case study, the multiple tools for data collection 20 may include interviews, questionnaires, observation and analysis of documents. Yin (2003) highlights that the case study

21 approach is appropriate for the why and how research questions. The case study method can provide in-depth understanding about the poorly understood phenomena and be also used to test theories in particular circumstances (Meredith, 1998; Voss et al., 2002). Considering the research question of this study how does CPFR implementation affect responsiveness of manufacturer s suppliers?, the case study method can be appropriate for providing in-depth understanding of the effect of CPFR implementation. Although this study developed a conceptual model with hypothesized relationships between constructs, the logic behind these relationships are more easily understood through a case study. Moreover, Voss et al. (2002) suggest that case studies can be also appropriate for testing hypotheses. This study adopts a single case study because there is only limited number of large scale CPFR implementation cases in the consumer electronics industry. As the previous research pointed, CPFR is a relatively newly developed collaboration process (Chen et al., 2007) and large scale implementation of it is still scarce (Småros, 2007). As one of the largest consumer electronics manufacturers implementing CPFR, Samsung Electronics can provide an exploratory and representative case in the consumer electronics industry. 21

22 4.1 Sample Frame and Selection Samsung Electronics is selected as a sample of this single case study. Samsung Electronics is relevant in the telecommunications and electronics industry, because it has the largest market share in the television market (Samsung Electronics, 2007) and second largest in the mobile handset market after Nokia (Cellular-news, 2007). The manufacturer has been implementing CPFR with different customers since The researcher first contacted an employee at Samsung Electronics Europe Headquarter in Surrey, United Kingdom who is in charge of managing CPFR implementation with European consumer electronics retailers and mobile network operators (interviewee I1, see Table 4.1). Interviewee I2 is an external consultant at Samsung SDS, an information technology and business consulting service provider. He is in charge of making CPFR partnerships and coordinating information technology systems between Samsung Electronics and its customers. His answers were based on Samsung Electronics experience in CPFR adoption with various European customers, rather than a specific customer. On the other hand, interviewee is selected as a sample to give more specific context on this research project. As a CPFR analyst, he exclusively manages CPFR implementation for television products 22 with Dixons, a consumer electronics retailer in the United Kingdom. As this study focuses not only on customer-facing

23 integration, but also on supplier-facing integration (Frohlich and Westbrook, 2001), the researcher needed to contact a purchasing manager at Samsung Electronics Corporate Procurement Strategy Team in South Korea (interviewee I4, see Table 4.1). Interview questions for him were focused on supplier-facing integration part of the conceptual model (Hypothesis 2b and Hypothesis 3, see Figure 3.1). <Table 4.1> Sample Frame Interviewee (code) Department Title Date 1. Sungwon Choi (I1) Samsung Electronics Europe Process Innovation 13/06/2008 Headquarter Coordinator 2. Iksoon Im (I2) Samsung SDS Europe Senior Consultant 13/06/ Daniel Kim () Samsung Electronics UK CE CPFR Analyst 13/06/2008 Division 4. Eungsok Song (I4) Samsung Electronics Purchasing Manager 16/06/2008 Corporate Procurement Strategy Team 4.2 Development of the Interview Questions Development of the interview questions are based on the conceptual model and the existing literature. Interview questions or questionnaire items are designed to support or reject hypothesized relationships of the conceptual model. Questions to measure the 23 firm s intention to have market-responsive supply chains (Hypothesis 1) are adapted from Selldin and Olhager s (2007) survey items and Fisher s (1997) research paper. To

24 assess CPFR on forecast accuracy (Hypothesis 2a), secondary data (internal documents, see Secondary Data in Appendix 1) provided by the case organization are compared to the answers from the interviews. Interview questions about supplier responsiveness (Hypothesis 2b) are developed based on the survey items of Handfield and Bechtel (2002). Lastly, the survey instruments of Cousins and Menguc (2006) and Cousins et al. (2006) are adopted to build questions on socialization and relational capital (Hypothesis 3). It is important to note that these questions are developed not only to support or reject hypotheses, but also to provide insights to understand the logic behind the hypothesized relationships. In addition, general questions such as T1-1 to 6 are designed to provide context to the answers. The list of all the interview questions and questionnaire items is presented in Appendix 1 (see Interview Template). 5. Research Analysis and Discussion To answer the research question, this section tests the conceptual model (see Figure 3.1) using the data collected from Samsung Electronics. After testing the conceptual model, this chapter discusses each hypothesis 24 by analyzing the answers of the interviewees and the secondary data.

25 5.1 Case Organization Samsung Electronics Co., Ltd. Samsung Electronics has the following five major business areas: Semiconductors, LCDs, Telecommunications Networks, Digital Appliances, and Digital Media (Samsung Electronics, 2007). Since 2004 Samsung Electronics has been implementing CPFR with its customers, such as Best Buy, Circuit City (US), Dixons, T-Mobile, O2, and Vodafone (Europe). Samsung Electronics has its global headquarter in South Korea and eight regional headquarters for North America, Latin America, Europe, Southeast Asia, China, the Commonwealth of Independent States (CIS) and Baltic countries, Middle East and Africa, and Southwest Asia. In addition, Samsung Electronics has its production facilities in thirteen countries and sales subsidiaries over forty countries (Samsung Electronics, 2007). 5.2 Conceptual Model and the Collected Data First, Hypothesis 1 shows the relationship between the manufacturer s intention to build agile supply chains and CPFR adoption. This study suggests that the manufacturer implements CPFR because it intends to have 25 agile supply chains. Interview questions T2-1 to 11 and T3-1 to 4 (see Interview Template in Appendix 1) are designed for

26 Hypothesis 1 and investigates Samsung Electronics product characteristics, importance of agile supply chains, and the reasons for adopting CPFR. The product characteristics are focused on Samsung Electronics television products and relevant questions are answered by interviewee (see Table 4.1). Second, Hypothesis 2a suggests that CPFR implementation improves forecast accuracy. This hypothesis will be supported or rejected by analyzing answers for interview question T3-5 (see Interview Template in Appendix 1) and secondary data (internal documents, see Secondary Data in Appendix 1) provided by Samsung Electronics. Interview question T3-5 is not only developed to confirm that CPFR implementation improves forecast accuracy but also to understand the reason why it improves forecast accuracy. Third, Hypothesis 2b suggests the positive effect of more accurate forecasts on supplier responsiveness. Interview questions T4-1 to 3 (see Interview Template in Appendix 1) are developed to understand the information sharing process between Samsung Electronics and its suppliers. Answers for interview questions T4-4 and 5 (see Interview Template in Appendix 1) will be analyzed to check whether higher forecast accuracy improves supplier responsiveness 26 and explain how it improves supplier responsiveness.

27 Finally, Hypothesis 3 focuses on the effect of socialization and suggests that socialization mechanisms moderate the effect of higher forecast accuracy on supplier responsiveness. Interview questions T5-1 and T6-1 (see Interview Template in Appendix 1) are developed for Hypothesis Analysis of the Collected Data and Discussion Analysis and Discussion for Hypothesis 1 Hypothesis 1 is developed based on Fisher s (1997) model, which proposes that innovative products should be processed by agile supply chains. To provide a specific context, this study focused on Samsung Electronics television products and investigated product characteristics of them. Table 5.2 shows interviewee s (see Table 4.1) answers for the questionnaire about Samsung Electronics television product characteristics and compares them to the characteristics of innovative products and functional products suggested by Fisher (1997). <Table 5.2> Product Characteristics of Samsung 27 Televisions and Innovative Products Products Samsung Televisions Innovative Products (Predictable Demand) Functional Products (Unpredictable Demand)

28 Average forecasting errors Less than 10%* 40 to 100% 10% Average stock-out rate 20% 10 to 40% 1 to 2% Product life cycle 12 to 18 months 3 months to 1 year More than 2 years Production lead-time 26 weeks 1day to 2 weeks 6 months to 1 year Product variety 20 to 100 variants High (often millions) Low (10 to 20) Contribution margin Not answered** 20 to 60% 5 to 20% End-of-season markdown Not answered** 10 to 25% 0% * Order forecast error for Dixons ** Confidential data <Adapted from Fisher (1997)> By comparing Samsung Electronics television products to Fisher s (1997) classification of innovative products and functional products, this study concludes that Samsung Electronics television products are close to innovative products. Average forecasting errors of Samsung televisions are close to the characteristics of functional products but this is because the figure is based on Samsung Electronics television order forecast for Dixons, the retailer already implementing CPFR with Samsung Electronics. According to a Samsung Electronics internal document ID1 (see Secondary Data in Appendix 1), average forecasting error for television products is 43 per cent. After concluding that Samsung Electronics television products can be classified as innovative products (Fisher, 1997), this study examines whether the manufacturer 28 intends to have agile supply chains to produce innovative products. To examine this, the

29 researcher conducted questionnaires to interviewees I2 and (see Table 4.1) using Selldin and Olhager s (2007) survey items. The questions are designed to know the importance of agile supply chains for the manufacturer. Figure 5.1 shows the answers for the questionnaires. According to Figure 5.1, both interviewees recognize the extensive importance of agile supply chains and reducing lead-time. However, they showed that the importance of deploying excess buffer capacity and buffer stocks is less significant. Interviewee I2 (see Table 4.1) commented that Samsung Electronics generally does not like having excess inventory. He explained that Samsung Electronics is trying to reduce inventory and increase responsiveness at the same time by reducing supply lead-times and standardizing parts. Interviewee (see Table 4.1) also added that Samsung Electronics policy is maintaining minimum buffer stocks. Summarizing Figure 5.1 and the interviewees comments, it can be concluded that Samsung Electronics intends to have agile supply chains but not excess buffer capacities or inventories. <Figure 5.1> The Importance of Agile Supply Chains for Samsung Electronics 29

30 To what extent is it important in the resource strategy to deploy excess buffer capacity in the supply chain? Not important at all To a large extent I2 Not answered To what extent is it important in the inventory strategy to deploy significant buffer stocks of parts or finished goods? Not important at all To a large extent I2 To what extent is it important in the overall supply chain design to respond quickly to unpredictable demand? Not important at all To a large extent I2 To what extent is it important in the lead-time strategy to invest aggressively in ways to reduce lead-time? Not important at all To a large extent I2 From the above arguments, this study concludes that Samsung Electronics produces products (televisions) with the characteristics of innovative products (Fisher, 1997) and intends to build agile supply chains. In addition to this conclusion, this study needs to decide whether Samsung Electronics intention to have agile supply chains led CPFR adoption in order to support or reject Hypothesis 1. Interview question T3-2 (see Interview Template in Appendix 1) directly 30 asks this point. All the respondents (interviewees I2, and I4, see Table 4.1) strongly agreed that their company s intention

31 to build agile supply chain led the implementation of CPFR (see Figure 5.2). Interviewee (see Table 4.1) added that responding to market demand and being prepared for that is extremely important. <Figure 5.2> Intention to Build Agile Supply Chains and CPFR Implementation Your company s intention to build agile supply chain led CPFR implementation Strongly disagree Strongly agree I2 I4 When they were asked about the main objectives of CPFR, two (interviewees I1 and ) of the three respondents (interviewees I1, I2 and, see Table 4.1) gave supporting comments for Hypothesis 1. Interviewee I1 (see Table 4.1) emphasized that the main objective of CPFR is to increase visibility in the process. He explained that by sharing retail information and knowing how the market is changing, Samsung Electronics is enabled to respond quickly to demand. Moreover, interviewee (see Table 4.1) added that CPFR allows the manufacturer to meet customer demand in peak seasons 31 and reduce loss of sales opportunities. However, the interviewees also pointed other reasons of CPFR adoption. Interviewee

32 I1 (see Table 4.1) noted that Samsung Electronics was able to get additional marketing benefits through CPFR. For example, when Samsung Electronics continues to meet customer orders perfectly though CPFR, customers trust Samsung Electronics and display its products more often than other products. Interviewee I2 (see Table 4.1) stressed that the main objective of CPFR is to reduce retail inventory. He commented that CPFR reduces inventory and loss of sales opportunities, improves robustness and accuracy of forecasts, and helps Samsung Electronics business units to better manage materials and capacities. In overall, it can be argued that the case organization clearly intends to have supply chains responding quickly to the changes in the market (agile). However, it is important to note the fact that Samsung Electronics also intends to reduce inventories in its supply chains, which is one of the characteristics of physically efficient or lean supply chains (Fisher, 1997; Selldin and Olhager, 2007). As Selldin and Olhager (2007) suggest the possibility of combinations of lean and agile supply chain as new technologies advance, this study concludes that Samsung Electronics adopted CPFR to combine the benefits of agile and lean supply chains. Therefore, Hypothesis 1 is partially supported Analysis and Discussion for Hypothesis 2a

33 The literature suggests that collaborative forecasting improves forecast accuracy (Chopra and Meindl, 2007; Fliedner, 2003; Seifert, 2003). Figure 5.3 shows Samsung Electronics forecast accuracy with its four CPFR partners in Europe. The last bar of the chart shows Samsung Electronics average sales forecast accuracy with all customers in the world including CPFR partners and others. Figure 5.3 clearly shows that sales forecast accuracy with the four CPFR partners is higher than the average forecast accuracy. According to interviewee I2, average sales forecast accuracy with CPFR partners ranges 60 to 70 per cent, while forecast accuracy with non- CPFR partners is approximately 45 per cent CPFR Forecast Accuracy Dixons 0 T-Mobile (UK) (Benelux) P4U Vodafone (UK)(Germany) Average 33 <Figure 5.3> CPFR Forecast Accuracy Order Sales forecast

34 In order to know the reasons for the forecast accuracy improvement through CPFR, the researcher asked how and why CPFR improves forecast accuracy (interview question T3-5, see Interview Template in Appendix 1). Interviewee I1 (see Table 4.1) noted that in addition to the information about market situation, new product introduction, marketing policies and prices, CPFR provides other important information customer s intention about how much it wants to sell. Customers implementing CPFR with Samsung Electronics promise purchase and remove uncertainties in customer orders. Sales forecast accuracy is also improved through CPFR because Samsung Electronics can analyze the data provided by customers, find market trends and make suggestions to customers. Interviewee I2 (see Table 4.1) also commented that CPFR synchronizes Samsung Electronics sales planning with customers sales planning. Order forecast accuracy is significantly improved when Samsung Electronics sells and customers buy based on already agreed quantity. Similarly, interviewee (see Table 4.1) presented better market information and predicted orders as the reasons for improved forecast accuracy through CPFR 34 As argued in the literature (Chopra and Meindl, 2007; Fliedner, 2003; Seifert, 2003) implementation.

35 and Hypothesis 2a, Samsung Electronics showed improvements in forecast accuracy through CPFR. In summary, sales forecast accuracy is improved by getting access to better market information and combining expertise of Samsung Electronics and customers. Order forecast accuracy is improved by stabilizing changes in customer order quantities through promised purchasing from customers. Therefore, Hypothesis 2a is supported Analysis and Discussion for Hypothesis 2b Hypothesis 2b suggests that manufacturer forecast accuracy and supplier responsiveness are positively related. Supporting arguments (Frischia et al., 2004; Min and Galle, 1999) to this hypothesis are presented in Section Interview questions T4-1 to 3 (see Interview Template in Appendix 1) are developed to investigate Samsung Electronics information sharing process with its suppliers. Interviewee I4 (see Table 4.1) notes that all suppliers of Samsung Electronics suppliers can receive forecasting information through the Materials Resource Planning (MRP) system. It allows suppliers to know forecasts for 12 to 24 weeks in advance and plan their production. Orders to suppliers are generated 35 automatically once a week through the MRP system when Sales and Operations Planning team inputs customer order

36 quantity into the system and purchasing managers confirm the order. Suppliers give the feedback Return-to-Forecast and Return-to-Purchasing-Order showing the maximum amount that the supplier can supply for Samsung Electronics within seven days after receiving the purchasing order. Samsung Electronics adjusts production planning reflecting the feedback from suppliers. Using the survey items of Cousins and Menguc (2006), the researcher asked interviewee I4 (see Table 4.1) to what extent Samsung Electronics is integrated with its suppliers. Figure 5.4 shows his answers. <Figure 5.4> Samsung Electronics Integration with Suppliers To what extend does Samsung Electronics cooperate with major suppliers on following activities? (Respondent: interviewee I4) Not at all To a great extent Order management Forecasting Operations planning After understanding how Samsung Electronics shares forecasting information and cooperates on operations planning, this study investigates the effect of improved forecast accuracy through CPFR on supplier responsiveness. Figure 5.5 shows the effect of Samsung Electronics improved forecast 36 accuracy on lead-times, delivery, and product modification. These three items are used by Handfield and Bechtel (2002) to

37 measure supplier responsiveness. <Figure 5.5> The Effect of Improved Forecast Accuracy on Supplier Responsiveness Samsung Electronics improved forecast accuracy through CPFR improved the following factors of major Suppliers. (Respondent: interviewee I4) Not at all To a great extent Shorter lead-times On-time delivery Ability to modify their products to meet Samsung Electronics requirements Samsung Electronics is reducing its supplier lead-times through CPFR. Suppliers can access more accurate forecasts on a real-time basis and produce at least three days in advance of the actual order. As Samsung Electronics stabilizes changes in customer order through CPFR, it can reduce changes in its order to its suppliers. Suppliers produce three days in advance of the order and Samsung Electronics promises to purchase the ordered quantity. In this way, Samsung Electronics keeps 90 per cent of the delivery from suppliers on time with exact order quantity. About the ability of suppliers to modify their products to meet Samsung Electronics requirements, interviewee I4 (see Table 4.1) noted that it differs in terms of 37 materials and suppliers. However, he added that in general, accurate forecasting data provided on a real-time basis allows suppliers

38 to be prepared in advance for product modifications. In summary, Samsung Electronics is improving supplier responsiveness by providing more accurate forecasting data to its suppliers and allowing them to be prepared for orders in advance. Thus, Hypothesis 2b is supported Analysis and Discussion for Hypothesis 3 Hypothesis 3 suggests that socialization mechanisms between the manufacturer and suppliers positively moderate the effect of improved forecast accuracy on supplier responsiveness. Cousins et al. (2006) argue that socialization mechanisms facilitate creation of buyer-supplier relational capital and Lawson et al. (2008) suggest that relational capital accumulation has positive effects on performance improvement including lead-time performance. According to Interviewee I4 (see Table 4.1), Samsung Electronics employs socialization mechanisms including joint workshops, on-site visits, regular supplier conferences, and cross-functional teams. For example, Samsung Electronics purchasing managers and developers visit supplier plants more than once a year. They analyze the problems in the plants and provide education 38 and solution for suppliers. Interviewee I4 (see Table 4.1) agreed to the statement that the use of socialization mechanisms

39 facilitate information flows between Samsung Electronics and suppliers (see Figure 5.6). The question is designed to measure the moderating effect of socialization mechanisms on the relationship between forecast accuracy and supplier responsiveness (interview question T5-3, see Interview Template in Appendix 1). <Figure 5.6> The Effect of Socialization Mechanisms The use of socialisation mechanisms facilitate information flows between Samsung Electronics and suppliers. (Respondent: interviewee I4) Strongly disagree Strongly agree Using the survey items of Cousins et al. (2006), this study attempts to measure relational capital accumulation through socialization mechanisms. Interviewee I4 (see Table 4.1) agreed to the statements that socialization mechanisms enhance mutual respect and mutual trust between Samsung Electronics and suppliers. However, he strongly disagreed to the positive effect of socialization mechanisms on personal interactions (see Figure 5.7). He added that Samsung Electronics impedes personal interactions to prevent corruption but facilitates group interactions. 39 <Figure 5.7> Socialization Mechanisms and Relational Capital

40 The use of socialisation mechanisms enhance the following factors between Samsung Electronics and suppliers (Respondent: interviewee I4) Strongly disagree Strongly agree Personal interaction Mutual respect Mutual trust Interviewee I4 (see Table 4.1) pointed that mutual respect and mutual trust between Samsung Electronics and suppliers are enhanced by better understanding each other through joint workshops, on-site visits, and regular supplier conferences. By understanding each other, Samsung Electronics and suppliers can complement their weaknesses and develop strengths. Interviewee I4 (see Table 4.1) stressed that the development of suppliers through mutual understanding is becoming the basis of Samsung Electronics global market leadership. Although Samsung Electronics impedes personal interactions to prevent corruption, it clearly recognizes the importance of the relationships based on mutual respect and mutual trust with its suppliers. Analyzing the case of Samsung Electronics, it can be concluded that socialization mechanisms create relational capital between the manufacturer and suppliers and positively moderates the effect of forecast accuracy on supplier responsiveness by facilitating 40 information flows between them. Thus, Hypothesis 3 is supported.

41 6. Conclusion 6.1 Summary of the Study As an answer to the research question how does CPFR implementation affects responsiveness of manufacturer s suppliers?, this study concludes that supplier responsiveness is positively impacted by more accurate forecasts. It is important to note that Samsung Electronics was able to be benefited from CPFR by integrating and collaborating with suppliers. Without integration with suppliers, Samsung Electronics improved forecast accuracy through CPFR may have only limited effects on supplier responsiveness. This study also suggests that socialization mechanisms facilitate supply chain integration and enhance the positive effect of forecast accuracy on supplier responsiveness. 6.2 Managerial Implications and Recommendations This study brings several interesting prospects for managers considering the implementation of formal inter-firm collaboration 41 processes. Why firms adopt collaborative demand planning processes such as CPFR? What are the benefits of

42 collaborative demand planning? How can firms be fully benefited from collaborative demand planning? Based on the theoretical discussions and analysis of Samsung Electronics case, this study provides several important implications and recommendations for the managers. First, CPFR appears to be an effective strategy for combining the benefits of lean and agile supply chains. By collaborating more closely with customers, manufacturers can have better information about changing demand and market situations. Improved forecast accuracy is an example of better market information. This allows manufacturers to be prepared for and respond quickly to market changes without having excess inventory or production capacity. Second, manufacturers must share market information and collaborate with suppliers to be fully benefited from the implementation of CPFR. CPFR is a customer-facing inter-firm collaboration process and does not automatically integrate manufacturers and suppliers. The manufacturer and suppliers should be well integrated enough to respond quickly to customer demand to improve responsiveness of the whole supply chain. CPFR becomes useless when the manufacturer s suppliers cannot access better market information and improve their responsiveness. 42 This study suggests manufacturers to use socialization mechanisms with their suppliers as well as customers to enhance supply

43 chain integration and improve responsiveness. 6.3 Limitations and Suggestions for Further Research This study has several limitations. The small sample size is the main limitation of this study. Although the use of a single case study is justified in Section 4.2, the sample size is not sufficient to generalize the research findings. In addition, this study is not free from the danger of the researcher s biased interpretation. As a deductive approach, this study proposed a conceptual model and tested it by analyzing the Samsung Electronics case. However, without statistical inference, the analysis completely depends on the researcher s interpretation of the collected data. Considering above limitations of this study, suggestions for further research are presented in this section. First, a survey-based research using the conceptual model of this study may extend the reliability. This study attempted to provide an in-depth understanding about the logic behind the conceptual model by employing a single case study. The other reason of employing a single case study is the limited number of largescale CPFR implementation. However, it is difficult to generalize the arguments of this study since it is focused on a single case 43 of Samsung Electronics in the consumer electronics industry. As the number of CPFR implementation in different industry

44 sectors increases in the future, a survey-based research will be able to generalize the arguments of this research project. Second, contrary to Fisher s (1997) model, the case of Samsung Electronics in this research project showed the possibility of successfully combining the benefits of lean and agile supply chains. Focusing on this point, further studies can investigate the conditions for successful combinations of lean and agile supply chains. 6.4 Contribution CPFR is a relatively newly developed inter-firm collaboration process. Although the research based on simulation modeling supports its positive effects on supply chain performance, there are limited number of empirical studies on it. Moreover, these studies mainly focus on its direct effects on performance of retailers and manufacturers. This research project will enhance understanding of CPFR implementation by looking at its impacts to further upstream of the supply chain and give implications about the integration not only between customer and manufacturer but also between manufacturer and its suppliers. 44

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49 Appendix 1 Supertable Sample Frame Interviewee (code) Department Title Date Length 1. Sungwon Choi (I1) Samsung Electronics Europe Headquarter Process Innovation Coordinator 13/06/ mins 2. Iksoon Im (I2) Samsung SDS Europe Senior Consultant 13/06/ mins 3. Daniel Kim () Samsung Electronics UK CE Division CPFR Analyst 13/06/ hour 4. Eungsok Song (I4) Samsung Electronics Corporate Procurement Strategy Team Purchasing Manager 16/06/2008 n/a ( ) Interview Template Theme (code) Question Hypo- thesis Interviewee Literature Source General (T1) 1. Could you explain your role in CPFR implementation? 2. Could you briefly explain your work experience at your current company? 3. When did your company start implementing CPFR? 4. To what extent is your company keeping close relationship with CPFR partner company? 5. What is the annual spend for/revenue form CPFR partner company? 6. Who has more influence on joint decision making between your company and CPFR partner company? All All 49

50 Agile supply Product characteristics Selldin chain (T2) 1. What is the range of the product s average forecasting errors? H1 and 1. Less than 10%; %; % Olhager 2. What is the range of the product s stock-out levels? H1 (2007) %; %; % Fisher 3. How long is the product life cycle? H1 (1997) 1. 3 month to 1 year; years; 3. more than 2 years 4. How long is the production lead-time? H1 1. 1day to 2 weeks; 2. 2 weeks to 6 months; 3. 6 months to 1 year 5. How many product variants are there in the product category? H1 1. Less than 20; ; 3. More than What is the product s contribution margin? H1 1. Less than 5%; %; % 7. How high is the average end-of-season markdown of the product? H1 1. 0%; %; % Agile supply chain (five-point Likert scale from not important at all to to a large extent important ) 8. To what extent is it important in the resource strategy to deploy excess buffer capacity in the supply H1 I2, chain? 9. To what extent is it important in the inventory strategy to deploy significant buffer stocks of parts or H1 I2, To what extent is it important in the overall supply chain design to respond quickly to unpredictable finished goods? demand? H1 I2,

51 11. To what extent is it important in the lead-time strategy to invest aggressively in ways to reduce lead- H1 I2, time? CPFR (T3) 1. What are the main objectives of CPFR implementation? H1 I1, I2, 2. Your company s intention to build agile supply chains led CPFR implementation (five-point Likert scale H1 I2,, I4 from strongly disagree to strongly agree ). 3. How important is it for your company to have agile supply chains? Is it the main reason for CPFR H1 implementation? 4. What are other reasons of the implementation of CPFR? H1 5. Could you describe about the process about how and why CPFR implementation improves your H2a I1, I2, company s forecast accuracy? 6. Who did suggest CPFR implementation first? 7. What are the main difficulties in CPFR implementation? 8. What are the main benefits of CPFR implementation realised so far? 9. Could you describe your company s CPFR process? 10. Is the CPFR with one company much different from CPFR with others? 11. Who is the lead side in sales forecast? 12. Who is the lead side in order forecast? 13. Who is the lead side in order generation? What kind of information does your company share with CPFR partner? Chen et al. (2007)

52 Supply Chain Information Flows Integration 1. How does Samsung Electronics share forecast data with major suppliers? H2b I2, I4 (T4) 2. How does Samsung Electronics generate order to major suppliers? H2b I2, I4 3. To what extent does Samsung Electronics cooperate with major suppliers on following activities (five- H2b I2, I4 Cousins point Likert scale from not cooperate at all to cooperate to a great extent )? and a. Order management Menguc b. Forecasting (2006) c. Operations planning Supplier responsiveness 4. Samsung Electronics improved forecast data through CPFR implementation improved the following H2b I2, I4 Handfield factors of major suppliers (five-point Likert scale from strongly disagree to strongly agree ). and a. Shorter lead-times Bechtel b. On-time delivery (2002) c. Ability to modify their products to meet Samsung Electronics requirements 5. How do you think the information flows from Samsung Electronics to suppliers affect supplier H2b I2, I4 responsiveness? Socialisation (T5) 1. What kind of socialisation mechanisms does Samsung Electronics apply to suppliers? a. Social events H3 I4 Cousins and b. Joint workshops c. On-site visits d. Regular supplier conferences e. Cross-functional teams 52 Menguc (2006)

53 2. Could you briefly explain how above socialisation mechanisms are used? 3. The use of socialisation mechanisms facilitate information flows between Samsung Electronics and suppliers (five-point Likert scale from strongly disagree to strongly agree )? H3 H3 I4 I4 Relational capital (T6) Summary (T7) 1. The use of socialisation mechanisms enhance the following factors between Samsung Electronics and suppliers (five-point Likert scale from strongly disagree to strongly agree )? a. Personal interaction b. Mutual respect c. Mutual trust 1. Are there other points that you want to add to your answers? 2. Are there any important points that I missed to ask? H3 I4 Cousins et All al. (2006) Secondary Data Title Provider Language Documented date Acquired date Code Global SCM Results and Plans Samsung Electronics Korean 10/ /11/2007 ID1 08 Integrated Retail Information Management Samsung Electronics Korean 12/ /05/2008 ID2 SCM Day Execution Guide Samsung Electronics Korean 06/ /05/2008 ID3 Plans for Strengthening Demand Management During Peak Seasons Samsung Electronics Korean 06/ /05/2008 ID4 53

54 Summary of the Interview Statements Hypothesis Interviewee Positive Statement Negative Statement Hypothesis I1 Adopted CPFR to increase visibility There are other marketing 1 Sharing retail information makes it benefits of CPFR possible to respond quickly to demand I2 Samsung is continuously reducing lead- The objective of CPFR is time reducing retail inventory Sales responding to market demand are extremely important Reduce loss of sales opportunities Hypothesis I1 Provides customers intention about how 2 much they want to sell Transforms order forecast into sales planning I2 On average, Samsung has 45% forecast accuracy with non-cpfr partners and 60-70% with CPFR partners We can see which model is sold at what time Forecast accuracy of CPFR models is almost 100% Hypothesis I4 We are reducing lead-times through 3 CPFR Improved forecast accuracy has a great impact on suppliers on-time delivery Hypothesis I4 We know better and respect each other We don t facilitate personal 4 through workshops and regular interactions to prevent conferences corruption Through regular meetings, workshops and plant visits, we enhance mutual understanding and trust 54