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Master Thesis Supply Chain Management
University of Groningen
The role of social capital in building supply network
resilience: A triadic approach
Michael J. Kroon s2512548 michaelkroon@live.com
Supervisor, University of Groningen: Dr. Kirstin Scholten Co-Assessor, University of Groningen: Dr. Manda Broekhuis
June 22nd, 2015 Word count: 11,144
Acknowledgments:
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Table of Contents
Abstract: ... 3
1. Introduction ... 4
2. Theoretical Background ... 6
2.1 Supply Chain Resilience ... 6
2.1.1 Supply chain (re)engineering ... 7
2.1.2 Collaboration ... 8 2.1.3 Agility ... 8 2.1.4 Risk Awareness ... 9 2.2 Social Capital ... 10 2.2.1 Structural... 11 2.2.2 Relational ... 11 2.2.3 Cognitive... 12 2.3 Conceptual Model ... 13 3. Methodology ... 14
3.1 Introduction and unit of analysis ... 14
3.2 Research context ... 15
3.3 Case selection ... 16
3.4 Data collection ... 17
3.4 Data analysis... 19
4. Findings ... 21
4.1 Supply chain (re)engineering ... 22
4.2 Collaboration ... 23 4.3 Agility ... 24 4.4 Risk awareness ... 26 5. Discussion ... 28 6. Conclusion ... 33 6.1 Managerial implications ... 34
6.2 Limitations and further research ... 35
References ... 36
Appendices ... 42
Appendix A: Supply chain resilience capabilities review ... 42
Appendix B: Coding tree excerpt ... 43
Appendix C: Operational definitions of theoretical concepts ... 46
Appendix C: Case study protocol ... 47
Appendix E: Case Narratives ... 60
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Abstract:
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1. Introduction
Within supply chains, vulnerabilities to disruptions can have severe financial, market, and operational consequences (Hendricks & Singhal, 2003, 2005; Wagner & Bode, 2008; Narasimhan & Talluri, 2009). Realizing the consequences of such disruptions, firms are building resilience into their supply chains (Jüttner & Maklan, 2011; Wieland & Wallenburg, 2013) as resilient supply chains are less vulnerable to disruptions and are better able to manage disruptions once occurred (Blackhurst, Dunn, & Craighead, 2011; Pettit, Croxton, & Fiksel, 2013). Accordingly, in building resilience into the supply chain, firms are required to look outside of themselves and focus on the realization of resilience within the entire supply network (Christopher & Peck, 2004), as in many cases supply disruptions do not originate simply on the firm level but rather are rooted in the supply network (Kim, Chen, & Linderman, 2015). However, this network view of resilience has been limited in literature to date, as the focus has mostly been on dyadic supply chain structures and relationships (see Jüttner & Maklan, 2011; Wieland & Wallenburg, 2012, 201). Furthermore, as organizations within the supply chain are connected through relationships, prior research has indicated that the strengthening of or building of relationships between organizations acts as a means of building a resilient supply chain (Blackhurst et al., 2011; Jüttner & Maklan, 2011; Kleindorfer & Saad; Peck, 2005; Wieland & Wallenburg, 2013). However, within current literature it remains unclear how these relationships influence supply chain resilience on a network level. Therefore taking a network level perspective, the purpose of this research is to explore how they may do so.
Recent supply chain resilience research shows that mutual dependence of organizations within a supply chain indirectly affects resilience through an increase in collaboration (Scholten & Schilders, 2015). In other words, the necessitation of organizations to work together/develop relationships due to being interdependent with one another. Building on this, the use of a triadic view warrants the ability to delve deeper into the interdependencies within a network (allowing for multiple interactions between organizations) and to expand further on influences of interdependencies towards supply network1 resilience. Additionally, by utilizing social capital theory the relational context within the interdependent triad is able to be analyzed for its facilitating influences on supply chain network capabilities. Social capital theory is widely used within literature to analyze relationships, however when applied to resilience it has been
5 limited to dyadic relationships (Johnson, Elliott, & Drake, 2013). Our research expands on this to bring social capital to a network level. To accomplish this, we have set the context of the study within multi-tiered supply networks. Multi-tiered supply networks possess a high degree of interdependency which typically “involve an actor that is performing two different roles; a supplier role in relation to one actor, and a customer role in relation to the other actor” (Wynstra, Spring, & Schoenherr, 2015, p. 3). For the purpose of this study, the research question to be addressed is: “What is the role of social capital in building resilience in multi-tiered supply network triads?”
In answering the research question, this research makes the following contributions. First, our study expands current research in supply chain resilience, which is primarily limited to dyadic observations, by taking a network level view through the use of triads. Ours is among the first studies to take resilience a step further, from a chain perspective to a network perspective. In this way, the intricacies of a network may be considered, along with the influential and relational factors that working with interdependent multiple parties in a supply network resilience setting presents. Second, our research investigates the role of social capital in building resilience, a conceptual link not yet well defined in supply chain resilience literature. In this way, delving deeper into the underlying mechanisms that influence resilience within a supply chain, as well as the underlying mechanism of social capital that can be utilized in the quest to build a resilient supply chain, or rather network. Third, through the identification of such underlying mechanism, practical managerial implications come to light as to how the dimensions of social capital may be utilized and what decisions and/or considerations are required when building resilience into a supply network. This allows a connection or link between theoretical and practical application, lending to a duality of contributions within this research.
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2. Theoretical Background
Despite trends towards supply chains with greater complexity and diversity, researchers, for over two decades, have focused their efforts on studying supply chain relationships as either monadic or dyadic (eg. Ellram & Hendrick, 1995; Golicic & Mentzer, 2005). Critics argue that complexities of networks cannot be captured when analyzed simply through a dyadic lens (Choi & Wu, 2009; Rowley, 1997). Alternatively, supply systems studied through a multi-tier supply chain approach avoid the drawbacks of dyads without the extensive complexities of networks (Mena, Humphries, & Choi, 2013). A triad, the simplest form of a multi-tiered supply network (Mena et al., 2013), grants a fuller understanding of the link-based system dynamics within a supply chain (Choi & Wu, 2009) while still capturing the complexities of networks (Choi & Wu, 2009a, 2009b; Rowley, 1997). In this, triads allow the analysis of third party interaction on the relationship between two other parties (Choi & Wu, 2009a; Wu, Choi & Rungtusanatham, 2010). In other words, the triad is the “fundamental building block” of networks, as “understanding how a link affects another link and how a node affects a link that is not directly connected to it unlocks the essence of a network” (Mena et al., 2013, p. 60). Therefore, the network level perspective (Kim et al., 2015) we take in this research of supply chain resilience warrants the use of triads to allow greater depth into the dynamics of a network where a dyadic analytical position would be crude and superficial (Andersson-Cederholm & Gyimothy, 2010). While research regarding triads has grown in importance and popularity (Choi & Wu, 2009c), further research is still warranted (Wynstra et al., 2015) as the concept is still underdeveloped. Autry, Williams, & Golicic (2014) suggest that “only by examining supply chain relationships in an expanded structural context (triadic or greater) can understanding of the underlying dynamics of multiple, nested supply chain relationships more fully develop” (p.54). A triadic lens/context (to support a network level perspective) is used in this research to be able to fully analyze the role of social capital in building supply network resilience. First, a review of supply chain resilience capabilities is needed to lay the groundwork of the research, which will then be followed up by social capital theory.
2.1 Supply Chain Resilience
7 and as used in our research, are defined as “unplanned and unanticipated events that disrupt the normal flow of goods and materials within the supply chain (Svensson, 2000; Hendricks & Singhal, 2003; Kleindorfer & Saad, 2005) and, as a consequence, expose the firms within the supply chain to operational and financial risks (Strauffer, 2003)” (Craighead, Blackhurst, Rungtusanatham, & Handfield, 2007, p. 132)
Expanding on this, through taking a network level perspective, we define supply chain resilience as “the ability of a system to return to its original state or move to a new, more desirable state after being disturbed” (Christopher & Peck, 2004, p. 4). Conceptualizing this definition, from a system-level approach, Christopher and Peck (2004) include four main capabilities for the development of a resilient supply chain: supply chain (re)engineering, collaboration, agility, and risk awareness. The system-level approach of Christopher and Peck (2004) operationalizes resilience capabilities at a higher level of analysis than that of other authors (i.e. Jüttner & Maklan, 2011, Wieland & Wallenberg, 2012, 2013), and in doing so encompasses the capabilities mutually recognized in the supply chain resilience field. A comparison of supply chain resilience literature and associated capabilities is reviewed in table 1 (appendix A). As empirical research should clarify the level at which resilience capabilities are discussed (Kim et al., 2015), the system-level approach as given by Christopher and Peck (2004) is in line with the network level perspective taken on triads, therefore we chose the conceptualization of supply chain resilience by Christopher and Peck (2004).
2.1.1 Supply chain (re)engineering
8 paths” to create supply chain understanding. Supply chain understanding contributes to resilience through allowing an understanding of the network connecting the organizations, including its risks and opportunities (Christopher & Peck, 2004). With an understanding on a network level, redesign may be accomplished more effectively and efficiently. Furthermore, a supply base strategy allowing the use of “back up” or alternative supply sources in case of disruption is shown to positively influence supply chain resilience (Christopher & Peck, 2004). The opposite side to this, single sourcing, while possibly advantageous for costs and quality management, exposes organizations to risks and is dangerous with regards to resilience (Jüttner, 2005; Pettit et al., 2010). All in all, the ability to redesign towards a balance between efficiencies and redundancies increases supply network resilience through facilitating preparation, response, and recovery from disruptions (Blackhurst et al., 2011)
2.1.2 Collaboration
Collaboration is a key ingredient in building supply chain resilience, as it acts to unify chain members to be resilient to disruptions. To accomplish collaboration the parties involved must align forces and attitudinal predispositions (Jüttner & Maklan, 2011). An underlying principle of collaboration is the exchange of information (Christopher & Peck, 2004) which in turn increases information visibility (Pettit et al., 2013, 2010; Wieland & Wallenburg, 2012, 2013). Prior to a supply chain disruption, collaboration generates supply chain intelligence, which is the application of supply chain generated knowledge to be used in risk source identification thus helping to decrease uncertainty (Christopher & Peck, 2004). Post-supply chain disruption, collaboration has been shown to act as a containment factor for the negative impacts/consequences of the disruption (Jüttner & Maklan, 2011). Within collaboration, defining communication networks and developing supplier relationships are both positively related to supply chain resilience (Blackhurst et al., 2011). In this way, collaboration plays an integral role in resilience.
2.1.3 Agility
9 2011). Velocity is a supportive capacity throughout the resilience cycle (Jüttner & Maklan, 2011), and acts as a key ingredient in quickly restoring supply chain operations to the desired state (Christopher & Peck, 2004; Jüttner & Maklan, 2011, Wieland & Wallenburg, 2013). Visibility, also a key ingredient, is the ability to see from one end of the supply chain to the other (Christopher & Peck, 2004). The main determinate of visibility is information, particularly timely access to information shared within the supply chain. Increased visibility has the ability within the supply chain to reveal resource locations, to identify risks of disruption, and to allow understanding of the flow of disruptions through the supply chain (Blackhurst et al., 2011). As a result, visibility is also effective in response and recovery after a disruption (Jüttner & Maklan, 2011). All in all, agility in the supply chain is an effective and efficient way of dealing with disruptions (Wieland & Wallenburg, 2012) as visibility enables effective response (Brandon-Jones et al., 2014) and velocity promotes efficient recovery.
2.1.4 Risk Awareness
Risk awareness plays an integral role in building resilience in a supply network and managers should establish formal risk management infrastructures (Ambulkar et al., 2015). Furthermore, organizations should facilitate a culture of risk awareness within the supply network (Christopher & Peck, 2004) as “it is important not to underestimate the contribution of culture to an organization’s flexibility and resilience” (Sheffi & Rice, 2005, p. 47). Christopher and Peck (2004) argue that a supply chain risk assessment tool should be used to enhance the resilience of a supply chain. “To be resilient, organizations need to develop appropriate management policies and actions that assess risk continuously and coordinate the efforts of their supply network (Kleindorfer & Saad, 2005)” (Scholten et al., 2014). A common understanding of risks in the network coupled with the strategic ways of dealing with them allows organizations to effectively and efficiently prepare for, respond to, and recover from disruptions.
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2.2 Social Capital
With the increase of economic, social, and environmental consciousness of firms, multi-tier triads have emerged to take a more prominent position in business arrangements/supply networks (Tachizawa & Wong, 2014). Buying companies are becoming more concerned with the specifications and traceability of products further upstream in the supply chain, thus requiring monitoring and management of not only a supplier but also supplier’s suppliers in order to reduce liabilities (Hartmann & Moeller, 2014). This triadic configuration results in a high use of single source suppliers, thus increasing the vulnerabilities of organizations to supply chain disruptions (Christopher & Peck, 2004; Pettit et al., 2010). However, research has also identified that increases in relational aspects between organizations may act to mitigate the increased risks/vulnerabilities associated with such a limited supply base, thus necessitating the need to develop strong relationships (Christopher & Peck, 2004; Christopher, Mena, Khan & Yurt, 2011; Jüttner & Maklan, 2011; Kleindorfer & Saad; Peck, 2005; Wieland & Wallenburg, 2013).
11 rather intangible nature and joint ownership requirement, social capital cannot be easily traded, sold, or bought, or easily passed from person to person. However, when present in relationships, social capital allows for achievement of ends which, without it, would not be possible or only accomplished through additional costs (Nahapiet & Ghoshal, 1998).
2.2.1 Structural
The structural dimension of social capital is regarded as the configuration of linkages in a social structure (Nahapiet & Ghoshal, 1998) that determines who you know and how you are able to reach them (Burt, 1992). Within this social structure, network ties are present which allow and/or permit early access to valuable information and resources (Bolino, Turnley, & Bloodgood, 2002; Coleman, 1990), promoting visibility and subsequently velocity in the network. Furthermore, it has been noted (see Capaldo, 2007; Koka & Prescott, 2002) that to acquire the benefits of structural social capital, such as early access to information and information reliability (Burt, 1992), that the network configuration should contain dense interactions along multiple connections (connectivity), an aspect that should be (re)engineered into the supply network for resilience purposes. In this way, information diversity is enhanced through the number, as well as the characteristics, of the contacts between parties (Villena et al, 2011), creating supply chain understanding. This in turn allows access to more consistent, non-redundant, and diverse information when combined with collaborative activities (Villena et al., 2011). Furthermore, within triads structural social capital containing dense social ties is correlated with greater content fluidity (Autry et al., 2014) leading to increased visibility and velocity of information through multiple paths. Appropriable organization, another aspect of structural capital, can influence flexibility through allowing ties, norms, and trusts to be transferred from one social setting to another (Fukuyama, 1995; Johnson et al., 2013; Nahapiet & Ghoshal, 1998). This illustrating that structural social capital is, however, facilitated and enhanced through the relational capital present between firms (Nahapiet & Ghoshal, 1998).
2.2.2 Relational
12 key aspect, allowing the benefits of relational social capital, is trust (Coleman, 1990; Fukuyama, 1995; Inkpen & Tsang, 2005). With a basis of trust, parties are willing to engage in communication with one another promoting openness and transparency between parties (Villena et al., 2011), promoting collaborative activity as well as positively influencing visibility. Furthermore, relationships containing trust support an awareness of risks as well as confidence between organizations subsequently requiring reduced monitoring of opportunistic behavior, thus reduced monitoring costs, as relational influences extend beyond established contractual settings (Bendoly, Croson, & Goncalves, 2010; Granovetter, 1992). This is partly due to norms of behavior established within the relationships, while obligations and expectations due to interdependence in relationships motivate organizations to reciprocate actions (Nahapiet & Ghoshal, 1998). Subsequently, this behavior creates identification within the supply network wherein organizations relate to one another and consider themselves as part of the collective group (Nahapiet & Ghoshal, 1998), thus contributing to collaborative behavior (Johnson et al., 2013). Given the interrelatedness of the social capital dimensions, relational capital is further influenced according to the cognitive capital present.
2.2.3 Cognitive
13 In reviewing the dimensions of social capital, the possible relations with supply network resilience can be seen, however no other research has addressed the connection between the two. To address this gap, our research implements a multiple case study to explore the intricacies of the relationship between the two concepts. For further reference, a list of the social capital variables presented in the theoretical background, along with associated definitions, can be found in appendix C.
2.3 Conceptual Model
Given that a network is connected through relationships, it is fitting to examine and analyze how these relationships are related to and how they may be utilized in building supply network resilience. Social capital, with the ability to enhance information flow, creates visibility, allow access to resources, and promote collaboration (Bolino et al., 2002; Coleman, 1990; Nahapiet & Ghoshal, 1998; Villena et al., 2011), contains substantial potential in developing and building supply chain resilience capabilities, leading to a resilient supply network. However, while potential links can be observed in theory, empirical research is required to fully understand exactly what the role of social capital is related to building supply network resilience. Therefore, for the purpose of this research the following model illustrates the conceptual framework of our study.
Figure 2.1: Conceptual Model
14 Following the theme/level of this research, a network level perspective, the triadic view of the supply network is a critical element within the relational analysis, allowing a more comprehensive understanding of the interdependencies within the network. Therefore, within this research, the three dimensions of social capital, as set within a triadic structure, are posed against the capabilities of supply network resilience. The resulting analysis lends insight into a higher level (network level) understanding of the relation between the two main variables, as compared to a dyadic study.
3. Methodology
3.1 Introduction and unit of analysis
15 As our research takes a network level perspective, the unit of analysis used must also follow suit. Therefore, the unit of analysis used in this research is triads. In triads vulnerabilities increase as disruptions in the chain affecting one actor subsequently affect the other two actors based on their dependent relationship, thus increasing the probability of disruption threefold. Therefore, actors in the triad must build resilience into the network to act against such vulnerabilities.
3.2 Research context
An industry wherein multi-tiered supply networks are populous and in which buying companies are influencing and managing multiple tiers is the highly-specialized electronics industry. In this industry the specificity of product design dictates control and management of key component suppliers in order to maintain product specifications, certifications, and functionality (Chin & Tat, 2015).
16 Figure 3.1: Triad network structure
3.3 Case selection
In order to accomplish the aim of the study, investigating the role social capital in supply network resilience, two cases (triads) were selected for study. To accomplish replication logic, both literal and theoretical (Voss et al., 2002), we aimed at selecting rival cases with extreme opposites to demonstrate unusual manifestation of the phenomenon being studied (Yin, 1994). In other words we chose cases with differing degrees of social capital (structural, relational, and cognitive), assuming that different dimensions of social capital would influence supply chain resilience capabilities in different ways. Furthermore, it was assumed that a higher overall degree of social capital would result in a higher overall degree of supply chain resilience.
Case/Social
Capital
Structural
Relational
Cognitive
Case A
-
Low quantity of interaction, limited amount of shared information, limited face-to-face contact+
Long term relationship (25+ years), high degree of trust built through the years, strongly developed norms present
+
Shared Western European cultural background, same high end electronics industry (common understanding)Case B
+
High quantity of interaction on a daily basis, dedicated personnel for cooperation, large amount of shared information, face-to face-contact+
Medium length relationship (10 years), high degree of interaction resulting in high degree of trust, high degree of obligations present-
Different cultural backgrounds: Asian vs. Western European, different industries: high volume consumer electronics vs. low volume high end electronics Table 3.1: Case selection criteria*
Supplier Buyer EMS Customer*
17 In each case the focal company and the buyer remained the same, due to the resource restrictions present (availability of options). We decided to focus on buyer selected suppliers of strategic items due to the interdependency of these suppliers in the triad as well as the associated financial and operational impacts present during a disruption with such suppliers (single source). First a group meeting with the six departmental managers within the focal company was conducted to assist in determining potential suppliers, along with associated disruptions, to be used in the study. Then, through analysis of various documents provided by the focal company (see table 3.2 below), six suppliers were pre-selected based upon a combination of a presence in the triad network and a history of disruptions. The potential suppliers were then presented to two key employees of the focal company, the operations manager and the project leader, to assist in determining suitability and how suppliers fit into categories in regards to perceived social capital. The use of this funnel type approach, combined with the willingness of participation of selected companies, resulted in the selection of two cases, each with differing aspects of social capital. In order to maintain privacy and to ensure security of information the selected suppliers were given codenames Supplier A and Supplier B. Furthermore, the triad containing supplier A was labeled as case A, likewise for B. Upon analysis of the interview data and supporting documentation, it was determined that the initial perceived levels of social capital of each case were in line with the actual levels present in the cases.
3.4 Data collection
Qualitative data, as well as quantitative data, was systematically collected in order to sufficiently and fully answer the research question. While qualitative data was the main type of data used, quantitative data acted to support the gathering and interpretation of qualitative data, allowing for data triangulation supporting the reliability of the data and construct validity (Voss et al., 2002). Table 3.2 provides a general overview of the data collected.
Data collection documents
Qualitative Data
Semi-structured interview Historical issuesCommunication records Field notes
18 Qualitative data was gathered primarily through the use of semi-structured interviews. Per case, we conducted a minimum of three interviews, at least one interview per company in the triad to ensure reliability and provide triangulation of perspectives from each company. The interviewee chosen at each company was the person with the most knowledge and interaction with the other two companies in the triad and the person with the most knowledge about the particular disruption being studied, this was accomplished using the snowball sampling method (Miles & Huberman, 1994, Yin, 2009). Additional interviewees were used to allow for a more in-depth investigation and to supplement the data collected by reducing respondent bias and increasing data richness (Voss et al., 2002).
Organization
Interviewee
Location
Case
Supplier A Sales Manager Telephonic A
Supplier B Sales Manager Telephonic B
Buyer Purchasing Manager Telephonic A/B
Buyer Quality Manager Telephonic A/B
Focal company Project Engineer Main office B
Focal company Head of Purchasing Main office A/B
Focal company Purchaser Main office A/B
Focal company Project Manager Main office A/B
Focal company Head Planner Main office A/B
Table 3.3: Interview details
19 progressed. Example questions are provided to allow a greater understanding of the question types: “Could you describe the flow of information within the triad?” (broad and open) ; “What was the communication process between the companies during the disruption?” (specific and detailed). The average duration of an interview was around 50 minutes. Interviews with participants of the focal company were conducted in person at the company office, while all other interviews were conducted over the phone as the interviewees were located abroad. All interviews were recorded, transcribed verbatim, and sent to each interviewee for review and approval, in this way increasing construct validity (Yin, 1994). The interview data was then retained for the chain of evidence.
Furthermore, interview data was supplemented with informal means of data gathering. As construct validity is enhanced through multiple sources of evidence (Yin, 1994), we spent more than 100 working hours at the focal company in order to develop more insightful information, to make visual observations, to participate in meetings, and to take informal field notes. Data collected was then subject to the same data analysis as the interview data, as described in further detail below. Examples of data collected through such means can be found in appendix F.
3.4 Data analysis
20 second-order codes. This produced third-order themes based upon the three dimensions of social capital. Finally, selective coding was used to compare and link third-order themes with the supply network resilience capabilities supply chain (re)engineering, collaboration, agility, and risk awareness. An excerpt of the coding is provided in appendix B.
The analyses were then set side-by-side for exploration of relation and influence between social capital and supply chain resilience. This analysis was conducted through three distinct stages as displayed in figure 3.2. First, the embedded dyadic relationships were analyzed. This allowed an intimate understanding of the specific relational circumstances present (Eisenhardt, 1989). Second, the three dyadic relationships were analyzed as one unit of analysis, the triad as a whole for within-case analysis. Each was documented through comprehensive case narratives, located in appendix E, supplemented by the additional documentation presented in table 3.2 above. Third, a cross-case analysis was conducted to identify patterns relating to social capital influences on supply chain resilience capabilities. This pattern matching activity helped strengthen the internal validity of the research (Yin, 1994), while gaining greater depth of understanding and enhancing generalizability of results (Miles & Huberman, 1994).
While all attempts were made to develop and implement a strong, valid, and reliable methodology in our research, it still contains some limitations. First, the use of a limited number of case studies (two) limits the external validity of the research, as external validity is one of the benefits of using a greater number of cases. Additionally, the use of only two cases further limits the generalizability of the research. However, we tried to balance this deficiency through the use of greater depth in each case allowing greater detail into the intricacies contained within, something that is possible as fewer cases required fewer resources, most notably time. Second, due to the geographic distances present between the researchers and a number of the interviewees, interviews were required to be conducted telephonically. While
Step 1: Embedded dyadic relationships Step 2: Triadic within-case analysis Step 3: Cross-case analysis
21 sufficient data was collected through telephonic means, face-to-face interviews provide additional benefits (i.e. personal contact, more open communication) which are not present over the telephone.
4. Findings
Through the analysis of our data we were able to investigate, discover, and explore the relationships and influences of the three social capital dimensions (structural, relational, and cognitive) within an interdependent triad structure on the building of supply network resilience capabilities: supply chain (re) engineering, collaboration, agility, and risk awareness. The findings of our analyses are presented below, while the related levels of social capital per case are displayed in figure 4.1. Additionally, figure 4.2 at the end of the section visually illustrates the social capital present per relationship in each case (rated as high/low/medium as determined during within-case analysis).
Figure 4.1: Social Capital findings per case/triad
Structural
Cognitive
Relational
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4.1 Supply chain (re)engineering
In our findings, supply chain understanding was found to be a strong influencing factor supporting the capability of supply chain (re)engineering. The knowledge of the capabilities and processes (supply chain understanding) of the companies in the triad is provided by a high degree of cognitive social capital as exemplified in case A as the operation purchaser of buyer Y states, “They have produced a lot of them [products] for us and they know, are familiar with the products, and also of course if there are any problems they can handle it themselves. Of course this operation has developed during the years.” Interestingly, while case A shares high levels of cognitive capital between all parties, the degree of structural capital is relatively low, with limited network ties and configuration. However, as also found in the above quote, buyer Y and supplier A have been working together for over 25 years and a high degree of relational capital is present and resultantly the development of trust based on a history of reliability, mutual confidence, and mutual respect. This has led to the willingness of supplier A to hold buffer stocks for both buyer Y and focal X, thus creating redundancy in the supply network, supporting a resilient supply network. Additionally, while relational capital between supplier A and focal X is lower, buffer stocks are held for focal X as well based upon the identification present in the triad, developed mainly through obligations and expectations involved in the relational capital between supplier A and buyer Y. This demonstrates organizational appropriation wherein one relationship influences the relationship of the other.
23 are fully in sync.” (sales manager, supplier B). Thus indicating the use of structural capital to compensate for a low level of cognitive capital.
We found that the supply base strategy, in both cases, is limited through single sourcing, thus negatively influencing supply chain (re)engineering, which may be enhanced through being able to switch suppliers, or have backup suppliers for redundancy in the network. The supply base strategy employed is mainly due to the nature of the industry and having to meet certification requirements. Within both cases social capital is used to compensate for this limited supply base. In case A, high cognitive and relational capital ensure availability of consistent supply enabled through safety stocks, as well as through stocks of suppliers further upstream: “I think we have really good relationships with our suppliers and most of our customers anyway…some standard materials we buy in very large quantities, we have a stock, our supplier has that in stock as well.” (sales manager, supplier A). While in case B strong structural ties between the companies work to enhance collaborative activities used to compensate for limited supply base opportunities “Yeah, but if you can’t move [suppliers], the other way is to improve communication and use physical meetings. We had problems with [product] and then we went to Germany and talked to them and became better when we understood each other.” (quality manager, buyer Y).
4.2 Collaboration
24 production until the highest level in our organization, buyer Y and focal X are communicating.” (purchasing manager, focal X)
Where, case B has a high degree of structural capital positively influencing collaboration, case A has a high degree of relational capital positively influencing collaboration. Again, this relational capital exists primarily between supplier A and buyer Y due to their long-lasting relationship. However, the trust present in the triad coupled with identification, which is enhanced through interdependency, acts towards open communication between all parties, thus including between supplier A and focal X. This is expressed in two specific quotes one from the senior buyer at focal X: “I think buyer Y has a long relationship with supplier A. So I think they [supplier A] know the importance of a relationship with buyer Y. So therefore, also the importance of the relationship with us because we deliver to buyer Y” and one from the sales manager at supplier A when asked about communication with buyer Y and focal X: “Yes it helps, it’s always good with personal relations and so on.” In case A the high level of cognitive capital between all parties also adds to the exchange of information as stated by the sales manager of supplier A when talking about shared cultures: “I think it helps with the information, because you get a more relaxed communication and so on. People are a bit more open minded.” We found that the supply chain intelligence developed in both cases relates to and contributes to the next supply network resilience capability of agility.
4.3 Agility
25 structural capital may have a negative effect on agility. While the higher degree of structural capital between buyer Y and focal X in case A has the ability to increase agility in response to disruptions. However, if the source of the disruption comes from the side of supplier A then, due to low visibility, buyer Y and focal X will receive the information at a later time resulting in a delayed response with decreased velocity. In this way the strength of the structural capital between buyer Y and focal X has little compensatory power over the lower degree of structural capital in the other two relationships in the triad.
26
4.4 Risk awareness
We found that cognitive capital has an influence on risk awareness in the triad in that it creates a common understanding of the supply network (similar to supply chain intelligence). This common understanding is useful in acknowledging the risk within the contextual setting of the network, in both cases the high end electronics industry containing high product and development uncertainty. In this way, the risks are recognized and accounted for based upon cognitive capital reinforced through the interdependency of the triadic structure. The lack of mutual cognitive capital in case B demonstrates the effects of cognitive capital on risk awareness as stated by the sales manager of supplier B when talking about the different cultures: “The background of it is that most Asian suppliers, they are by nature coming from the high volume market, and that is quite, there is always a strong focus on the consumer side of it…in order to comply to the enhanced or high value markets, like industrial, medical, military applications we had to install additional securities and additional processes to make sure all the components maintain identical production quality and also the understanding that the supply of high value customers or high end markets have got much lower volume but a much higher value of the product.” The sales manager follows this statement up with the statement above concerning the use of structural capital to compensate for a lack of cognitive. In this way, we found that structural capital contributes to risk awareness, but through the increased communication (visibility) mentioned in the agility section and shown through a statement by the quality manager at buyer Y when talking about risk awareness: “And another way that we prevent them [disruptions] is that we have very good formal and informal communication paths.” We found that communication and information sharing was indicated as the most cited means of risk awareness and risk management: “Yeah so the main thing is that we need to communicate and have weekly meetings and so on with focal X just be sure that there are no problems and issues in the project and if there are, then we can take care of that as soon as possible.” (operational buyer, buyer Y) This, of course, leads to visibility within the network facilitated through such structural capital, but then also reinforces velocity. This also contributing to the recognition of the interrelatedness of the supply chain resilience capabilities.
28 Figure 4.2: Social capital per connection in the triad
5. Discussion
Extant literature in the field of supply chain resilience indicates the need to develop resilience as a precursor to survival when a disruption occurs in the supply chain (Jüttner & Maklan, 2011; Zsidisin et al., 2005). To accomplish this, supply chain resilience must be built into the
29 supply chain through the development and reinforcement of key resilience capabilities (Christopher & Peck, 2004; Scholten et al., 2014). Further, literature indicates that social capital has the ability to promote such things as collaboration between organizations, allow access to resources, enhance information flow, and create visibility (to just name a few) within relationships (Bolino et al., 2002; Coleman, 1990; Nahapiet & Ghoshal, 1998; Villena et al., 2011). Johnson et al. (2013) studied the role of social capital in facilitating supply chain resilience, however limited to a dyadic level. Our research took this further and expanded the study of social capital to a network level, through the use of triads, with application to building supply network resilience with capabilities at a system-level.
As identified in the findings, social capital plays a significant role in building supply network resilience through the capabilities identified by Christopher and Peck (2004): supply chain (re)engineering, collaboration, agility, and risk awareness. Our findings indicate that across both cases higher levels of social capital dimensions positively resulted in higher levels of supply network resilience capabilities. While our findings are based on a triadic view, the triad forms the basis of the network (Choi and Wu, 2009a, 2009b; Rowley, 1997). Meaning that the more structural, relational, and cognitive capital present in the network, the higher the levels of supply chain (re)engineering, collaboration, agility, and risk awareness capabilities present in the network, thus leading to a more resilient supply network. Therefore, from a network level perspective we propose that:
P1a: The higher the level of social capital in a supply network, the more resilient the network will be.
Additionally, wherein a lack of or opposing dimensions of social capital existed, a negative effect on supply network resilience was identified. This was identified, for example, when organizations possessed differing cultures, rendering cognitive capital obsolete or minimalistic. This then resulted in negatively affecting supply network resilience capabilities such as supply chain (re)engineering and risk awareness. Given these findings, we propose that:
30 However, each capability of supply network resilience is influenced by the dimensions of social capital in their own way. This section will further discuss these intricacies in further detail and provide additional propositions based upon the findings presented.
First, we found that supply chain (re)engineering was positively influenced through high levels of all three social capital dimensions, namely structural, relational, and cognitive. Our findings indicate that relational capital and cognitive capital are the most dominate dimensions of social capital positively affecting supply chain (re)engineering. Relational capital is primarily bolstered through a history of positive interactions (Inkpen & Tsang, 2005) while cognitive capital is inherent to the contextual setting, as was indicated in our findings. The history of interactions creates supply chain understanding within the network, wherein the organizations develop the knowledge of the processes and capabilities of the other organizations. This understanding is essential in identifying the locations of risks and vulnerabilities in the network that are created through ‘pinch points’ and ‘critical paths’ (Christopher & Peck, 2004). Additionally, the longer organizations work together (in a positive manner), the greater the level of trust between the organizations becomes (Coleman, 1990; Fukuyama, 1995). This trust facilitates cooperative behavior and stimulates organizations to commit to actions intended toward the benefit of the network as a whole. Furthermore, structural capital supports supply chain (re)engineering through providing the means or pathway facilitating supply network understanding. It acts to create linkages between organizations increasing efficiencies in information flow and is able to create redundancies in information resources, through surplus information capacity. All in all, if balanced correctly, supporting an ‘efficiency vs. redundancy’ tradeoff (Christopher & Peck, 2004). In these ways, supply chain (re)engineering is supported by all three dimensions of social capital, therefore we make the following proposition:
P2: High levels of structural, relational, and cognitive social capital positively contribute to building the supply network capability supply chain (re)engineering.
31 Early access to information as well as the quality of the information were found to be critical success factors in collaborating toward network resilience, a finding supported by Scholten and Schilder (2015). Multiple connections in the network support supply chain intelligence through the exchange of strategic, tactical, and operational information across all levels within the organization, as required for resilience according to Christopher & Peck (2004). Furthermore, relational capital promotes openness in communication through the trust developed between and within the organizations in the triadic network. Identification within a triad stemming from relational capital works to justify the need for extensive information exchange towards a collaborative goal. Additionally, cognitive capital (to a lesser extent) supports collaboration through enhancing openness in communication through a shared understanding of each other. Therefore, we make the following proposition:
P3: High levels of structural, relational, and to a lesser extent cognitive social capital positively contribute to building the supply network capability collaboration.
32
P4: High levels of structural, relational, and cognitive social capital positively contribute to building the supply network capability agility.
Fourth, risk awareness is influenced to a large degree by cognitive capital. Cognitive capital’s role in risk awareness is shown through the common understanding of the supply network it creates. In this, the risks inherent to the contextual setting and the network that organizations are embedded in are recognized, understood, and managed when the organizations share a common culture and congruent goals. This finding is in congruence with research conducted by Christopher & Peck (2004). Additionally, our findings indicate that structural capital may be used to support risk awareness within the network, however its influence is indirect as structural capital increases visibility and collaboration within the network enhancing risk awareness. Relational capital plays a role in risk awareness in that it creates trust within the network giving way to greater behavioral transparency, which in essence is visibility. We therefore make the following proposition:
P5: The building of the supply network capability risk awareness is positively influenced by a high level of cognitive capital, indirectly influenced by a high level of structural capital through visibility and collaboration, and indirectly influenced by a high level of relational capital through visibility.
Interestingly, our findings indicate that not every dimension of social capital must be present in order to build supply network resilience. We found, within an interdependent triad, that a strong presence of a dimension (i.e. structural or relational) is able to act in a compensatory nature for a weak or limited dimension (i.e. cognitive) which might otherwise have a negative effect. Our findings indicate that structural capital can be compensated for by cognitive and relational capital, as is found in case A, while cognitive capital can be compensated for with structural capital as in case B. We therefore make the following proposition:
P6: Within an interdependent network, the dimensions of social capital may take on a compensatory nature wherein a stronger dimension out-weighs the negative aspect of a weaker or non-existent dimension.
33 may compensate for another relationship in the triad with weak relational capital. This is mediated through the structural capital of the triad and is identified as appropriable organization (Nahapiet & Ghoshal, 1998). Research by Johnson et al. (2013) found that appropriable organization leads to increases in flexibility and velocity, or in other words agility, however with limited explanation and reasoning. Our research extends this to identify that interdependency within a network facilitates appropriation of relational capital for supply network resilience purposes. Therefore, we make the following proposition:
P7: Interdependency in a triad promotes the appropriability of relational capital, mediated through structural capital
Overall, as discussed social capital plays a significant role in the building of supply network resilience in multi-tiered supply triads. Additionally, we have discussed the multi-faceted influence of the dimensions on social capital on the capabilities of supply network resilience, this way showing support for and providing reasoning regarding the role that social capital plays in building supply network resilience.
6. Conclusion
This multiple case study shows interesting theory contributing results leading to new insights in the field of supply chain resilience. By investigating the role of social capital in building resilience in a multi-tier supply chain network we expand current supply chain resilience theory which has been primarily limited to a dyadic view of the supply chain, with only a few exceptions. Based upon theory, the possible links between the dimensions of social capital and the capabilities of supply chain resilience existed, but these links were for the most part undiscovered in empirical research. Lending to this, through the use of a network level perspective, the underlying mechanisms of social capital were investigated for application within an interdependent triad network, with regards to supply network resilience.
34 resilience. Additionally, our findings indicate that the dimensions of social capital may compensate for each other when being applied towards resilience efforts, for example a strong structural capital presence within a network may compensate for a lack of cognitive capital in the network. Our study also helped to uncover that interdependency in a network promotes the ability of relationships to take on a compensatory nature for other relationships within a triad. This was particularly noted in the strong relational capital of connections compensating for the weak relational capital of other connections, mediated through the structural capital of the triad. These considerations may be used when building supply network resilience.
6.1 Managerial implications
Our research, aside from its theoretical implications, is complimented with managerial implications and contributions. We provide managers with knowledge and information allowing for an understanding of the underlying mechanisms that lead to and promote building resilience, not only on a supply chain level but on a network level. We offer guidance to managers on how social capital may be used to improve supply chain (re)engineering, collaboration, agility, and risk awareness. For example, managers should consider the contribution structural capital has in facilitating information exchange and collaboration. Frequency and quality of interaction were deemed to be crucial in fast disruption response. Additionally, we demonstrate that organizations that engage in regular meetings develop supply chain intelligence within the network, promoting early access to information, visibility, and risk awareness, leading to resilience.
Additionally, relational capital has been found to be an underlying mechanism supporting resilience in an interdependent network. Therefore, manager should consider investing in relation capital. For example, dedication of personnel for the purpose of managing relations was found to significantly boost visibility and leading to rapid mutual problem solving and resolution, thus velocity. Also, managers should not only consider their direct dyadic relationships in the network, but also the relationships their partner organizations possess. In this way, managers in an interdependent network may be able to exploit the compensatory nature of social capital contained within the network.
35 and velocity in dealing with disruptions. In this, if able to choose between multiple suppliers, cost and delivery speed (common determinates) should not be considered solely, but cognitive capital should also be considered.
6.2 Limitations and further research
Although we strived for rigor and reliability in our research, limitations still exist. First, the use of only two cases based on limited resources (time and access to suppliers) results in the limited generalizability of the findings and conclusions. To compensate for this, we aimed at going in-depth into the cases through the use of eight interviews supported with field notes, meeting observations, and ancillary documentation. Another point of concern is that the different supplier’s products vary in product complexity, even though the importance of the products to the end product are the same. This may have an influence on how the network builds supply network resilience, however is an area that is limited in supply chain resilience literature and is area requiring future research: the role of product complexity in supply chain resilience. Further research should explore additional combinations of social capital dimensions and relations to resilience, i.e. exploring if relational capital is enough, or if structural can stand alone such as in a transactional relationship or in a new relationship with a company. Also along these lines, further research should investigate if different dimensions of social capital affect different stages in supply chain resilience, for example preparation, response, and recovery stages. Where relational and cognitive may help in a preparation stage (due to visibility and supply chain knowledge), and structural may be effective in response/recover stages (due to increasing information exchange/collaboration and velocity). As the amount and quality of research of supply chain resilience on a network level is limited, future research should expand upon this and further explore resilience on a network level.
36
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42
Appendices
Appendix A: Supply chain resilience capabilities review
Table 1: Supply chain resilience capabilities (adapted from Scholten et al. (2014))
System-Level resilience capabilities Resilience Elements Christopher and Peck (2004) Ponomarov and Holcomb (2009)
