Assessing Service Supply Chain Vulnerability from Customer Value Perspective. Multi-Industry Insights

Transcription

1 Assessing Service Supply Chain Vulnerability from Customer Value Perspective Multi-Industry Insights Jyri Vilko School of Business and Management, Lappeenranta University of Technology, Finland Paavo Ritala School of Business and Management, Lappeenranta University of Technology, Finland

2 Assessing Service Supply Chain Vulnerability from Customer Value Perspective Multi-Industry Insights ABSTRACT As the competition is shifting from organization-based to supply-chain-based the increasing complexity of service value production is becoming one of the key challenges for companies. In order to perform competitively in a dynamic market place the companies need to have a clear understanding about the determinants that contribute and destroy service value. While the creation of value has been a popular topic in the scientific literature the vulnerability of it has not been properly addressed. Therefore, this study gives insights about the sources of value vulnerability in service networks context by presenting results from an explorative multi-industry study. Keywords: Service network vulnerability, risk management, customer value, assessment INTRODUCTION During the last two decades supply chains have become the focal point to improve competitiveness in an increasingly global marketplace. While the numerous trends (e.g. the development of communications and other technologies, e-business outsourcing and lean and agile logistics) have made it possible to develop these complex international networks of industrial partners, they have also made the organizations vulnerable to various risks (affecting the service price, quality or time for example) deriving from within and outside of the network (Waters 2007; Craighead et al., 2007; Harland et al., 2003; Hult, 2004; Mason-Jones et al., 2000; Narasimhan and Talluri, 2009; Thun and Hoenig, 2009, 2011; Brindley, 2004, Vilko, 2012). Many recent events have highlighted the vulnerability of long and complex supply chains. A risk realization affecting operations anywhere in the system can have a direct effect on its ability to continue operations, thus endangering customer value creation. A good example of how vulnerable the value provision in supply chains can be seen from the recent study (see Hendricks et al. 2009) where companies admitting to major supply-chain difficulties lost 10 percent of their shareholder

3 value on average. These issues have become increasingly relevant as the global financial crisis emphasized the role of supply chain risk management in many companies (Blome and Schoenherr, 2011). Indeed, supply chain management is undergoing continuous, considerable and rapid changes, and the vulnerability of value production is growing in importance (Frankel et al., 2008). However, for the past decade only few scholars (e.g. Peck, 2005; Sheffi, 2005) have addressed the issue of vulnerability, in the context of supply chains and even less attention have been received by the customer value production issues in this context. Transfer from production-based to service-dominant value creation has emphasised the role of the service value in the global economy and raised the attention of managers in many organizations (Barlow, 2010). In practise this can be noticed from the estimates of services in the US which state that the value produced by alone services will increase to close to 90 per cent of the total value production in the USA by Considering the previous development where the value has increased from the less than 40 per cent of the 1950 to the 84 per cent in the 2001 the development seems quite likely (Spohrer, 2010). Although the value of services have been a popular topic in the scientific literature for several decades when considering the supply chain perspective, it becomes obvious that the focus in the previous literature has mainly been on traditional manufacturing rather than services. The first studies taking account supply chain perspective were published in the beginning of the millennium (see e.g. Bowman and Ambrosini, 2000). However, after more than a decade, the network perspective to value creation remains still only little researched and especially the vulnerability perspective has not received any attention from the scientific community (e.g. Vilko, 2013; Sampson and Spring, 2012; Niranja and Weaver, 2011; Demirkan and Cheng, 2008; Sengupta et al., 2006; Ellram et al., 2004). The market place for service production is becoming increasingly dynamic and the services are being produced in networks by increasing number of companies rather than individual companies. The complex systems and turbulent operational environment cause understandable concern for the

4 companies creating the value. Overall, the research in this area is scarce and in many ways the understanding of the sources and mechanisms of the attributes that can destroy value are is still in its infancy. To address this gap in the scientific discussion, the objective of this study is to assess the determinants of vulnerability in service networks. Empirically, we utilize an multi-industry study to assess the multi-faceted vulnerability of customer value in supply chains. Our approach is explorative, as we pursue to show the broad diversity of the vulnerabilities to customer value in supply chain context. SUPPLY CHAIN RISK MANAGEMENT AND VALUE PRODUCTION The second section of the study will present the theoretical foundation of the study by first illustrating an overview of supply chain management and services in that context, followed by the determinants which determine value in service supply chains. Supply chain vulnerability To define supply chain vulnerability, it is essential to first examine the characteristics of risk. The literature defines risk in a multitude of ways. Waters (2007) defines it as a threat that something might happen to disrupt normal activities and prevent things from happening as planned. A standard formula for the quantitative definition of supply chain risk is: Risk = Probability Impact. The phenomenon of supply chain risk has attracted more attention in recent decades (Tang and Nurmaya Musa, 2010), but there are diverse perceptions among researchers from different fields, who approach it from different perspectives (Sodhi et al., 2012). The related concepts are also still rather unclear, and Jüttner et al. (2003), for example, note that the use of the term risk is confusing. They argue that risk should be clearly separated from its sources and consequences, and categorise the sources in three different groups: 1) environmental risk, 2) network-related risk and 3) organisational risk. According to Wagner and Bode (2006, p. 304), supply chain vulnerability is a function of certain supply chain characteristics, and the loss a firm incurs is a result of its supply chain vulnerability to a given supply chain disruption. Peck (2005) describes vulnerability as exposure to serious

5 disturbance, arising from risks within the supply chain as well as risks external to the supply chain. Jüttner et al. (2003) describes supply chain vulnerability as the propensity of risk sources and risk drivers to outweigh risk-mitigating strategies, thus causing adverse supply chain consequences and jeopardizing the supply chain s ability to effectively serve the end customer market. Synthesising from the previous definitions, we define supply chain vulnerability as the supply chain system s exposure to unwanted and unexpected risk events that originate both within and outside the (service) supply chain system. From the above, it becomes clear that the concepts of risk and vulnerability are related to each other. According to Asbjørnslett (2008), the difference between vulnerability analysis and risk analysis is the focus of the analysis. While vulnerability analysis focuses on the holistic supply chain perspective, risk analysis focuses more on the impact of individual events. When examined from a quantitative perspective, the difference between risk and vulnerability is expressed in terms of the exposureelement; here we define the supply chain vulnerability formula as follows: Vulnerability = (Probability Impact Exposure). Supply chain management and services Compared to the traditional supply chains, the topic of service supply chains has received only limited attention which mostly comprised from proposed management frameworks. As a concept service supply chain management has been defined as the management of information, processes, capacity, service performance and funds from the earliest supplier to the ultimate customer (e.g. Ellram et al., 2004; Baltacioglu et al., 2007). According to Arlbjørn et al. (2011), it is important to differentiate the tasks in service supply chain management, which can be achieved through different types of relationships with customers as well as suppliers (Cho et al., 2012). Ellram et al. (2004), list seven theoretical processes of service supply chains, including: information flow; capacity and skills management; demand management; customer relationship management; supplier relationship management; service delivery management; and cash

6 flow. In further developing the Ellram s model Baltacioglu et al. (2007) proposed a service supply chain framework with an application to the healthcare industry to include the following activities: demand management; capacity and resources management; customer relationship management; supplier relationship management; order process management; service performance management; and information and technology management. Determinants of value As customer value and value propositions are very complex phenomena, there is no broad-based definition available (Anderson et al., 2006). To gain insight into the distinctive features of customer value and its vulnerability, we refer to categorization introduced by Rintamäki et al. (2007). They divide customer value to four categories: 1) economic, 2) functional, 3) emotional and 4) symbolic. Each value proposition pursues to create value to the customer in one or several of these areas. Economic value refers to the financial benefits that can be offered to the customer. Functional value is the actual service, which helps to solve a concrete problem, e.g. moving products to one place to another. Emotional value refers to the feelings such as convenience, entertainment or feeling of safety. Finally, symbolic value refers to social status, respect and identity. In service supply chains, the value creation process becomes more complex when compared to dyadlevel analysis between provider and customer. While the functional and economical value creation has been seen as very difficult issue to handle in complicated, multiparty logistics services, the issue is even more pronounced when it comes to emotional and symbolic value. We expect that service supply chains produce a lot of customer value that is emotional and symbolic (in addition to functional and economical), and therefore they are also more vulnerable to broad variety of risks and costs that lower the perceived customer value in these categories. In the following sections, we introduce an empirical study where these challenges in multi-dimensional value creation are assessed. RESEARCH DESIGN

7 The study is based on both the integrated literature review and empirical evidence. The third section presents the empirical part of the research design applied by describing the methodology and the data collection. Methodology The qualitative and explorative research approach was considered appropriate to gain theoretical and empirical insight into the topic because it has not received much previous research attention (Yin, 1994). The study form was seen to work well in serving the information-oriented focus of the research and discovering causalities of the phenomenon (Yin, 1994, Jensen and Rodgers, 2001) The empirical part of the study is based on the empirical data mainly received from an expert group consisting of persons with differing executive positions in the organizations. The experiences and first-hand knowledge of the value provision in each of the informants companies and their supply chains were thus the base for the empirical sample. The fact that the empirical part of the study relies on the few informants perspective to the value creation and its challenges does oppose some limitations in terms of generalizability and furthermore includes risks in misjudging the representativeness in terms of customer value. However as several industries are under investigation there is a less likelihood that individual opinions will have great impact on the result and as an explorative study the multi-industry perspective allow wider perspective for the researchers in order to better understand different forms of value (Voss, 2002). The strategy used for the sample selection was information-oriented, where the focus is on maximizing the utility of the information (Flyvberg, 2011). As a multi-industry study, the sample selection was done on the basis of its information content and therefore the research can be considered to have both maximum variation, while retaining sufficient level of comparability in the data. Two different types of triangulation were used in this study: the triangulation of theories and the triangulation of different investigators (Denzin, 1978). Firstly, the scientific literature sources used for the study were triangulated to confirm the validity of the theoretical basis (Cresswell and Miller,

8 2000). Secondly, in the reporting of the empirical data collaboration as investigator reflexivity was used (Cresswell and Miller, 2000). The reflexivity included researchers from different disciplines, namely from industrial engineering and management and from supply management firstly to carry out the expert group discussions and data collection, secondly to review and comment on the research data and finally, to further analyse the relevance of the findings in Delphi-like group discussions. Sample and data The study was conducted as part of a larger study, which examines vulnerability of value creation in customer-oriented service network. As part of this study, cross-section of companies from different fields of industry were used to in an expert group to identify and analyse the relevant factors to both contributing and inhibiting the customer value creation. The informants organizations are presented in Table 1. The expert group of the analysis consisted six informants from six organizations from different fields. The positions of the group participators varied between the companies. The informants participating the expert group were selected on the basis that they would have the best knowledge about their customer value determinants both in the organizational and supply chain level. The experience and insights of the informants was considered essential in order to make in-depth sense of the phenomena (Eisenhardt, 1989). VALUE VULNERABILITY ANALYSIS The fourth section of the paper presents the empirical part of the study, namely a detailed description of the value vulnerability process is presented, following by the main empirical findings of the process which presented. Process of evaluation Identifying and evaluating the importance of different factors in value creation was conducted in the expert group utilizing an internet-based group decision making software. The participants were

9 positioned geographically in the same location to allow conversation and the exchange of thoughts during the workshop. Compared to a traditional workshop method with post-it notes, the internetbased software seemed to have some advantages as it allowed the group participants to follow the inputs of the other group members and thus more effective creation of ideas. Furthermore, the software allowed the participants to do amendments to the elements created by other participants, which was used to improve the generalizability to the value determinants and thus all the participants would be able to relate to them. The evaluation of the value vulnerability determinants was done in four separate phases described below: The first phase began the expert group session allowing the participants to idea the determinants of value vulnerability. The session lasted for 30 minutes resulting 97 determinants which were assessed right after. The results were reviewed and the overlapping determinants were merged with group consensus resulting 82, which were more closely evaluated. In the second phase, the evaluation of the value determinants consisted of three separate perspectives, namely the likelihood and impact elements, as well as the exposure element of the event which altogether represented the vulnerability of the customer value in the supply chain. The experts were asked to evaluate the different perspectives using the scale from zero to four, where zero was denoting impossible/no impact/no exposure, and one denoting very little possibility/impact/exposure, while four was denoting very high possibility/impact/exposure. In the third phase of the expert group the identified value vulnerabilities where evaluated according to their sources. Three different network-level-sources were given to the informants: own organization, network of the organization (supply chain), and the operational environment. From the given levels participants were asked to select the source of the vulnerability as they saw it. In the final phase, the expert group session continued by evaluating the nature of the customer value vulnerability. The nature of the vulnerability impact was categorised to four groups following

10 Rintamäki et al. (2007), namely Economic, Functional, Emotional and Symbolic. Before the group began the evaluation, the meaning of these value propositions were explained to the participants, to ensure that everyone would have the same impression of them. The rating was done with the scale from zero to four similarly to the previous step. After the evaluation was completed, all the results were reviewed with the group to ensure their validity and to discuss their meaning from the different industries perspectives. Study results The nature of value vulnerability The evaluation of the value vulnerability revealed the complexity of the determinants (See Table 2). The nature of the different determinants varied significantly. In most cases the nature of the vulnerability impacts were somewhat dispersed which might make them difficult to manage. The symbolic nature of the value seemed to be less vulnerable to the identified determinants. In the discussions with the expert group the symbolic nature was also considered as most difficult to assess and altogether the overall share of it was only 6 per cent. The functional and emotional natures of value seemed to be most affected by the identified determinants counting up to 42 per cent and 33 per cent of total in the evaluation, respectively. Finally, the economic value, which is typically the most considered in the literature counted only 19 per cent of the total vulnerability. The sources of the value vulnerability Surprisingly, the expert group identified most of the inhibitors coming from inside of their own organization counting up to 59 per cent of all the network levels. The network level counted up the second highest number with 25 per cent and the operational environment was seen as the least likely source of vulnerability with only 16 per cent. In many cases the sources of vulnerability had some dispersion, however in most cases there was clear concentration to a one of them. The high result of vulnerability from inside the own organization would suggest that the organizations have lot to improve in their processes, however it may also illustrate that the internal problems are typically easiest to spot. Considering that, might explain some of the low count of vulnerability from the

11 network and operational environment identified, and at the same time suggest some further studying of the phenomenon. DISCUSSION AND CONCLUSIONS Services are taking increasing part of the total value production in the contemporary economies (Spohrer, 2010). Concurrently, the production of service value is increasingly disintegrated over growing number of companies in complex service networks, which makes it susceptible to disturbances (Vilko, 2012). Considering these developments it is no wonder that the vulnerability of service value is receiving growing concerns from the managers, while the same time the scientific literature hasn t been able to provide guidance on how to answer to this challenge. Therefore, in this research we use an explorative multi-industry study to give insights and instigate the discussion on the sources and nature of the value vulnerabilities. The perspective of this study provides aims to instigate the discussion of service supply chain value creation and vulnerability in two important perspectives. Firstly, the study illustrates the importance of vulnerability of the value in service supply chains. The current scholarly discussion has concentrated mostly of production of customer value, while the vulnerability perspective of it has been less discussed. We argue that in order to manage the value production in a sustainable way, the risks involved should be taken better in to account. This issue is highlighted in the service supply chain context, where customer value is increasingly multi-faceted (e.g. includes also emotional and symbolic elements) and thus more vulnerable. Secondly, this study provides a network perspective to the value management. Currently, the discussion of value offering is concentrated on organizational perspective with most of the studies deriving from business to consumer experiences. In our study we analyse the network perspective to value creation taking into account also the business to business perspectives. In many ways the results of the analysis represent the cases that the participated organizations have experienced. The applied method seemed to work well in this kind of explorative analysis. As the

12 used expert represented different parts of the service supply chain, with different distances from the end customer, the results were considered to illustrate more holistic network perspective. Some of the studied service supply chains included products in their offering, however those did not seem differ greatly from pure services. Overall the results of the analysis showed that the sources vulnerabilities did differ in their significance, however none of those stood clearly out and the results were quite evenly distributed. The implications of the study The scientific implications of this study can be considered twofold. Firstly, the determinants of value have great differences in their relevance to the customer. This should be taken into account studying the offerings of service networks. By better understanding the essential determinants of value and how those comprise scholars can focus their efforts better in the further research. Secondly, the abilities to identify the inhibiting factors that reduce the customer experienced value or increase costs in delivering are severely limited outside of the organizational border. Scholars should focus more research in investigating the limited visibility to identify the inhibitors of value creation and what enables better and agile alignment of the network resources to provide more resilient value provision. Secondly, the findings of the study illustrate the multi-dimensional nature of value provision, where especially the functional and emotional natures seemed to be relatively vulnerable. The most challenging issues in the value vulnerability was related to the internal processes in the organizations. From the inhibiting factors, the most dominant ones were those internal to the organization while the network or environment related were the least identified. This might imply about the limitations organizations have in their abilities to identify the vulnerabilities outside of their own organizational border. By better understanding the essential determinants of value vulnerability and how those comprise can able both scholars and managers to focus their efforts better in the further. Limitations and suggestions for future

13 The most obvious limitation is in the conceptual and explorative nature of the study. There is a need for further empirical studies, as well as for the further refinement of the analysis framework from several viewpoints. In addition, the empirical studies could test the impact and nature of the studied value vulnerability determinants in several supply chain from same industries to better understand the differences of value creation in different fields of industry and in b2b and b2c environments. REFERENCES Asbjørnslett, B. E. (2008) Assessing the vulnerability of supply chains, in G. A. Zsidisin and B. Ritchie eds. Supply Chain Risk: A handbook of Assessment, Management and Performance, US: Springer. Arlbjørn, J. S., Freytag, P. V., and de Haas, H. (2011) Service supply chain management: A survey of lean application in the municipal sector, International Journal of Physical Distribution and Logistics Management, Vol. 41, No. 3, pp Baltacioglu, T., Ada, E., Kaplan, M. D., Yurt, O., and Kaplan, Y. C. (2007) A new framework for service supply chains, The Service Industries Journal Vol. 27, No. 2, pp Barlow, R.D. (2010) Navigating the c-space in supply chain management, Heathcare purchasing news, Vol. 34, pp Bowman, C. and Ambrosini, V. (2000) Value creation versus value capture: Towards a coherent definition of value in strategy, British Journal of Management Vol. 11, pp Chen, D.Q., Preston, D. S. and Xia, W. (2013) Enhancing supply chain performance: A Relational view and empirical test, Journal of Operations Management, Vol. 31, pp Cho D. W., Lee, Y. H. Ahn, S. H. and Hwang, M. K. (2012) A framework for measuring the performance of service supply chain management, Computers and Industrial Engineering, Vol. 62, No. 3, pp Chisholm, R.F. and Elden, M. (1993) Features of Emerging Action Research," Human Relations Vol. 46, Vol. 2, pp Cresswell, J. and Miller, D. (2000) Determining validity in qualitative inquiry, Theory in Practice Vol. 39, No. 3, pp

14 Demirkan, H. and Cheng, H. K. (2008) The risk and information sharing of application services supply chain, European Journal of Operational Research, Vol. 187, NO. 3, pp Denzin, N.K. (1978) The research act: A theoretical orientation to sociological methods (2nd ed.), New York: McGraW Hill. de Waart, K., and Kemper, S. (2004) 5 steps to service supply chain excellence, Supply chain management review, Vol. 8, No, 1, pp Eisenhardt, K.M. (1989) Building Theories from Case Study Research, Academy of Management Review, Vol. 14, No. 4, pp Ellram, L., Tate, W., and Billington, C. (2004) Understanding and managing the services supply chain, Journal of Supply Chain Management, Vol. 40, No. 4, pp Ellram, L., Tate, W., and Billington, C. (2007) Services supply management: The next frontier for improved organisational performance, California Management Review, Vol. 49, No. 4, pp Flyvbjerg, B. (2011) Case Study. In Handbook of qualitative research, editors: N. K: Denzin and Y. S. Lincoln, pp Giannakis, M. (2011) Management of service supply chains with a service oriented reference model: The case of management consulting source, Supply Chain Management: An International J. Vol. 16, No. 5, pp Hendricks, K. B., Singhal, V. R., & Zhang, R. (2009). The effect of operational slack, diversification, and vertical relatedness on the stock market reaction to supply chain disruptions. Journal of Operations Management, Vol. 27, No. 3, pp Jensen, J.L. and Rodgers, R. (2001) Cumulating the intellectual gold of case study research, Public Administration Review, Vol. 61, No. 2, pp Jüttner, U., Peck, H. and Christopher, M. (2003) Supply chain risk management: Outlining an agenda for future research, International Journal of Logistics: Research and Applications, Vol. 6, No.4, pp Niranjan, T. and Weaver, M. (2011) A Unifying View of Goods and Services Supply Chain Management, The Service Industries Journal, Vol. 31, No. 14, November,

15 Peck, H. (2005) Drivers of supply chain vulnerability: an integrated framework, International Journal of Physical Distribution and Logistics Management, Vol. 35, No. 4, pp Rintamäki, T., Kuusela, H. and Mitronen, L. (2007) Identifying competitive customer value propositions in retailing, Managing Service Quality, 17(6), Sampson, S. E. and Spring, M. (2012) Customer Roles in Service Supply Chains and Opportunities for Innovation, Journal of Supply Chain Management, 48: Sengupta, K., Heiser, D. and Cook, L.L. (2006) Manufacturing and Service Supply Chain Performance: A Comparative Analysis, Journal of Supply Chain Management, Vol. 42, No. 4, pp Sodhi, M.S., Son, B.G. and Tang, C.S. (2012) Perspectives on Supply Chain Risk Management, International Journal of Production and Operations Management, Vol. 21, No. 1, pp Spohrer, J. (2010) Service Science Progress and Directions - Working Together to Build a Smarter Planet, IBM UP Presentation, cited , [available at: Tang, O. and Nurmaya Musa, S.N. (2010), Identifying risk issues and research advancements in supply chain risk management, International Journal of Production Economics, vol. 133, no.1, pp Vilko, J. and Ritala, P. (2014) On vulnerability in supply chain risk management, The International Journal on Logistics Management, Vol 25, No. 1, pp Vilko, J. and Ritala, P. (2014) Service supply chain risk management Operations and Supply Chain Management: An International Journal, Vol. 7, No. 3. pp Voss, C., Tsikriktsis, N., Frohlich, M. (2002). Case Research in Operations Management. International Journal of Operations & Production Management, Vol. 22, No. 2, pp Wagner, S. and Bode, C. (2006) An empirical investigation into supply chain vulnerability, Journal of Purchasing and Supply Management, Vol. 12, No. 6, pp., Waters, D. (2007), Supply Chain Risk Management: Vulnerability and Resilience in Logistics, Kogan Page Limited: London.

16 Yin, R.K. (1994) Case Study Research Design and Methods, Applied Social Research Methods Series, Vol. 5, Sage Publications, Thousand Oaks, CA.

17 Table 1. Company characteristics of the expert respondents Company 1 Company 2 Company 3 Company 4 Company 5 Company 6 Offering of the company Offerings consists of own products with life-cycle service offerings. (B2B) Combined concrete- and construction service and product offering. (B2C&B2B) Energy service provision by providing gas product and the related services to the customers. (B2C&B2B) Logistics service provider with tailored solutions. (B2B) Consumer electronics retailer with enhanced after sales service offerings. (B2C) Expert organization for financing research, development and innovation in Finland Expert s position in the company Logistics manager Deputy managing director Nature of the Turnover supply chain offering ~ 15 m Service-oriented manufacturing supply chain ~ 65 m Director ~ 23 m Local director ~ 10 m Service director ~ 275 m Chief technology expert ~ 600 m Service-oriented manufacturing supply chain Service-oriented manufacturing supply chain Service supply chain Service-oriented manufacturing supply chain Service supply chain

18 Table 2. The value vulnerability analysis results Source of vulnerability Nature of vulnerability Vulnerability % Organizat. Network Environm. Economic Functional Emotional Symbolic Late delivery is not notified or notification is late 17,38 4,4 % 67 % 33 % 0 % 17 % 67 % 17 % 0 % Nuisance and anger due to reclamation of defects 16,48 4,2 % 67 % 17 % 17 % 0 % 0 % 83 % 17 % Poor reachability of experts 14,56 3,7 % 67 % 33 % 0 % 0 % 17 % 67 % 17 % More expensive offering than competitors 12,64 3,2 % 50 % 17 % 33 % 67 % 0 % 33 % 0 % Waiting an answer to a query 12,50 3,2 % 83 % 17 % 0 % 0 % 50 % 50 % 0 % Difficulty to get information 11,78 3,0 % 67 % 33 % 0 % 0 % 83 % 17 % 0 % Costs due to delay 10,86 2,8 % 67 % 33 % 0 % 83 % 17 % 0 % 0 % Customer service fails in communication and in understanding the customer 10,66 2,7 % 83 % 17 % 0 % 0 % 33 % 67 % 0 % Price paid for acquiring the product or service 9,93 2,5 % 83 % 17 % 0 % 83 % 0 % 17 % 0 % Varying quality of service 9,42 2,4 % 83 % 17 % 0 % 0 % 83 % 17 % 0 % Improperly delivered products/services incur expenses to the customer 9,25 2,4 % 83 % 17 % 0 % 100 % 0 % 0 % 0 % Product/service is difficult to compare 9,17 2,3 % 50 % 0 % 50 % 33 % 50 % 17 % 0 % Cost due to false information 8,68 2,2 % 67 % 33 % 0 % 83 % 17 % 0 % 0 % Solving a problematic situation requires contacting several people 7,27 1,8 % 83 % 17 % 0 % 0 % 50 % 50 % 0 % Uncertainty of delivery 7,27 1,8 % 67 % 33 % 0 % 0 % 83 % 17 % 0 % Uncertainty of keeping the promised delivery time 7,12 1,8 % 67 % 33 % 0 % 17 % 83 % 0 % 0 % Inaccuracy in orders of the state authorities 7,12 1,8 % 0 % 0 % 100 % 0 % 50 % 33 % 17 % Slow processing of reclaims 7,06 1,8 % 100 % 0 % 0 % 17 % 33 % 50 % 0 % Slow operations 6,99 1,8 % 67 % 33 % 0 % 0 % 67 % 17 % 17 % Poor reachability 6,99 1,8 % 100 % 0 % 0 % 0 % 67 % 33 % 0 % Unclear or complex directions 6,70 1,7 % 83 % 0 % 17 % 0 % 67 % 33 % 0 % Service level does not meet expectations 6,70 1,7 % 83 % 17 % 0 % 0 % 50 % 50 % 0 % Deviation in availability times 6,70 1,7 % 67 % 33 % 0 % 17 % 67 % 0 % 17 % Abundance of information 6,63 1,7 % 33 % 33 % 33 % 0 % 33 % 67 % 0 % Promises to customer are not met 6,40 1,6 % 83 % 17 % 0 % 0 % 17 % 67 % 17 % Cost comparison of investment and operation of it 6,11 1,6 % 17 % 33 % 50 % 17 % 67 % 17 % 0 % Sub-contractor does not know what he's doing 6,00 1,5 % 17 % 83 % 0 % 0 % 50 % 33 % 17 % Late delivery causes costs and lose of reputation 5,92 1,5 % 50 % 50 % 0 % 33 % 0 % 33 % 33 % Significant differ in the organizational culture compared to the competitor 5,63 1,4 % 67 % 17 % 17 % 0 % 0 % 67 % 33 % Unclear terms of delivery 5,59 1,4 % 83 % 17 % 0 % 0 % 67 % 33 % 0 % Long delivery time 5,59 1,4 % 50 % 50 % 0 % 0 % 100 % 0 % 0 % Difficult to understand and inconsistently functioning IT system 5,49 1,4 % 33 % 50 % 17 % 0 % 50 % 50 % 0 % Hard reachability of customer support 5,01 1,3 % 50 % 50 % 0 % 0 % 83 % 17 % 0 % Difficulty in following orders 4,87 1,2 % 33 % 67 % 0 % 0 % 67 % 17 % 17 % Unrespectful bahaviour of custormer service 4,65 1,2 % 100 % 0 % 0 % 0 % 0 % 83 % 17 % Insufficient time to compare actors 4,58 1,2 % 17 % 17 % 67 % 17 % 67 % 17 % 0 % Comparing offers 4,58 1,2 % 50 % 17 % 33 % 17 % 50 % 33 % 0 % Delivery capacity does not meet the promised 4,58 1,2 % 67 % 33 % 0 % 17 % 83 % 0 % 0 % Calling to the customer service 4,44 1,1 % 83 % 0 % 17 % 17 % 50 % 33 % 0 % Product broken in delivery 4,15 1,1 % 17 % 50 % 33 % 17 % 67 % 0 % 17 % Insufficient level of knowledge of the customer service 3,99 1,0 % 100 % 0 % 0 % 0 % 83 % 17 % 0 % Uncertainty of availability 3,99 1,0 % 67 % 33 % 0 % 0 % 67 % 33 % 0 % Inability to meet the customer in short-term 3,99 1,0 % 67 % 17 % 17 % 0 % 67 % 33 % 0 % Errors in invoicing 3,76 1,0 % 83 % 17 % 0 % 17 % 50 % 33 % 0 % Product does not meet the demand 3,75 1,0 % 67 % 17 % 17 % 0 % 33 % 67 % 0 % Product gone missing during delivery 3,65 0,9 % 17 % 67 % 17 % 33 % 50 % 0 % 17 % Failed installation 3,63 0,9 % 0 % 100 % 0 % 17 % 33 % 50 % 0 % Predictability of pricing 3,54 0,9 % 67 % 17 % 17 % 67 % 0 % 33 % 0 % Promised product is not available 3,38 0,9 % 83 % 17 % 0 % 0 % 50 % 50 % 0 % Customer loses familiar contact person due to organizational changes 3,33 0,8 % 67 % 0 % 33 % 0 % 67 % 33 % 0 % Too many options in customer support available in different companies 2,93 0,7 % 17 % 67 % 17 % 0 % 33 % 67 % 0 % Complexity of delivery options 2,85 0,7 % 67 % 33 % 0 % 0 % 67 % 33 % 0 % Product is broken at factory 2,74 0,7 % 33 % 50 % 17 % 17 % 67 % 17 % 0 % Unclear pricing 2,33 0,6 % 100 % 0 % 0 % 33 % 33 % 33 % 0 % Unclear warranty conditions 2,22 0,6 % 50 % 33 % 17 % 17 % 67 % 17 % 0 % Costs (direct and indirect) due to product return 2,22 0,6 % 67 % 17 % 17 % 100 % 0 % 0 % 0 % Errors in product information 2,22 0,6 % 67 % 33 % 0 % 0 % 83 % 17 % 0 % Problems caused by poor language skills 2,00 0,5 % 83 % 17 % 0 % 0 % 33 % 67 % 0 % Product installer does not arrive as promised 1,77 0,4 % 17 % 83 % 0 % 0 % 67 % 33 % 0 % Public shame in aking a question or commenting through social media 1,66 0,4 % 33 % 0 % 67 % 0 % 0 % 17 % 83 % Insufficient availability of new model 1,66 0,4 % 67 % 33 % 0 % 0 % 33 % 33 % 33 % Time consumed to sort out why suplementary service has failed 1,56 0,4 % 50 % 50 % 0 % 0 % 83 % 17 % 0 % Contacting for other reasons than invoising 1,56 0,4 % 100 % 0 % 0 % 0 % 17 % 83 % 0 % Returning of wrong product 1,47 0,4 % 67 % 33 % 0 % 100 % 0 % 0 % 0 % Turgidness of invoice 1,46 0,4 % 83 % 0 % 17 % 0 % 50 % 50 % 0 % Consuming time with our organization 1,33 0,3 % 83 % 17 % 0 % 0 % 50 % 33 % 17 % Costs of contacting 1,29 0,3 % 67 % 17 % 17 % 83 % 0 % 17 % 0 % Evaluating the energyefficiency of product/service 1,17 0,3 % 33 % 0 % 67 % 33 % 17 % 33 % 17 % Product finished although the availability information states different 1,11 0,3 % 50 % 50 % 0 % 0 % 33 % 50 % 17 % No e-services available 1,10 0,3 % 100 % 0 % 0 % 0 % 50 % 50 % 0 % Costs caused by own sales operations 1,03 0,3 % 50 % 0 % 50 % 100 % 0 % 0 % 0 % The availability of the product has ended 0,93 0,2 % 33 % 17 % 50 % 0 % 33 % 67 % 0 % Requirement to report 0,74 0,2 % 33 % 0 % 67 % 0 % 67 % 33 % 0 % Additional costs due to the method of payment 0,69 0,2 % 67 % 17 % 17 % 83 % 0 % 17 % 0 % Price changes after signing the contract 0,67 0,2 % 67 % 0 % 33 % 67 % 17 % 17 % 0 % Legistlation changes cause disadvantages for customer 0,59 0,1 % 0 % 0 % 100 % 17 % 50 % 17 % 17 % Staying home in order to receive delivery 0,56 0,1 % 17 % 33 % 50 % 17 % 33 % 17 % 33 % Product in offer finishes 0,50 0,1 % 83 % 17 % 0 % 17 % 17 % 50 % 17 % Receiving parking ticket during service 0,26 0,1 % 17 % 17 % 67 % 33 % 0 % 50 % 17 % Waiting in a product pickup line 0,25 0,1 % 83 % 17 % 0 % 0 % 17 % 83 % 0 % No parking spaces for customers 0,23 0,1 % 33 % 0 % 67 % 0 % 33 % 50 % 17 % Lost of warranty benefit due to manufacturers bankruptcy 0,09 0,0 % 0 % 100 % 0 % 50 % 33 % 17 % 0 % TOTAL 393,6 100,0 % 59 % 25 % 16 % 19 % 42 % 33 % 6 %