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To be more adaptive to the disruptions?

Investing in your staff!

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To be more adaptive to the disruptions?

Investing in your staff!

ABSTRACT

Supply chain resilience is a strategic choice in today’s turbulent business environment. However, there is little empirical research on specific tactics to improve it and investigation on its direct influence on supply chain performance. Using the resource-based view as the theoretical underpinning, this paper examines the relationships among manufacturing firms’ human capital resources, supply chain resilience, and customer service performance. Based on questionnaire response from 160 supply chain management professionals in three manufacturing industries, this study verifies the significant effects of human capital resources on supply chain resilience, meanwhile, investigates the direct links between supply chain resilience and customer service performance. In addition, this research explores the mediating role of supply chain resilience in the relationship between human capital resources and customer service performance.

Keywords: supply chain resilience, human capital resources, managerial capital, worker capital, customer service, supply chain performance

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1. INTRODUCTION

Although a unified and commonly accepted definition of supply chain resilience is currently lacking (Hohenstein et al., 2015; Tukamuhabwa et al., 2015), generally, many researchers have reached a consensus that supply chain resilience is an adaptive capability that can help organizations reduce the possibility of supply chain disruption and facilitate to recover from the disruption (Fiksel, 2006; Ponomarov & Holcomb, 2009; Stewart et al., 2009; Pettit et al., 2010; Ponis & Koronis, 2012; Xiao et al., 2012; Golgeci & Ponomarov, 2013; Pettit et al., 2013; Sawik ,2013). Due to the increasingly fast-changing, complex and turbulent global supply chain environment, in recent years, supply chain resilience, as a strategic initiative to cope with supply chain disruptions (Blackhurst et al., 2011; Hohenstein et al., 2015), has become a fast growing topic for both academics and practitioners (Ambulkar et al., 2015). However, specific tactics that can enhance supply chain resilience are calling for an investigation (Tukamuhabwa et al., 2015; Hohenstein et al., 2015).

On the basis of resource-based view theory (RBV), Barney (1991) stated that resources can create capabilities to determine a firm’s reaction to internal and external threats as well as opportunities. Further, Blackhurst et al. (2011: 376) viewed these created capabilities in their study as “the mechanism to mitigate the potential impact of disruption and thus enhance supply resiliency”, which is a similar statement as the meaning of supply chain resilience. On the other hand, one of the most important and valuable resources of a company is the human capital resources (Barney, 1991; Crook et al., 2011; Nyberg et al., 2014). Therefore, as a key component to successfully implement strategic initiative, human capital resources can be considered as a possible factor to influence supply chain resilience (Jin et al., 2010).

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generalized way, to investigate the relationship between human capital resources and supply chain resilience. Secondly, the meaning of human capital resources introduced in these two previous research mainly focused on education and training, which are dimensions of human resource practices (Jin et al., 2010). While human resource practice is means facilitate to increase the contribution of human capital resources in dealing with risk events, which is not the essence of the human capital resource (Liu et al., 2007). Adding the intensified need on researching the individual’s ability to adaptable to work in complex and turbulent situations (Jin et al., 2010), therefore, studying the impact of human capital resources, especially individual competencies of human capital, on supply chain resilience is both a blank in theoretical scope and meaningful to study on. Thirdly, human capital in Blackhurst et al.’s (2011) research was merely limited to the managerial level. While in the current paper, both managerial and operational levels are studied objects. In this way, the current research is more completed compared with previous ones. In addition, resources that create adaptive capability (supply chain resilience) employed by Blackhurst et al. (2011) were interaction and coordination of three resource categories. The human capital resource was just one of the three resources (Barney, 1991). On the basis of their results that resource categories could interact to enhance resiliency, they further suggested future research should scrutinize each factor. Finally, in both these research, human capital resources were merely one of enhancers or strategies to improve supply chain resilience. There are rare studies specifically investigated the sole influence of human capital resource on supply chain resilience. Having realized the potentially huge impact of human capital resources on supply chain resilience, and in addressing these important knowledge gaps, this study investigates supply chain resilience from a human resource perspective. Hereby the first research question of the current study is: RQ1. How does human capital resources influence supply chain resilience?

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resilience can help to reduce potential loss derived from disruptions, that is the way to indirectly improve performance by enhancing supply chain resilience. Since the performance of supply chain as a whole is more and more important (Pearson & Samali, 2005; Gellynck et al., 2007), and being part of a well-performing supply chain can generate performance benefits for individual organization (Gellynck et al., 2008), it is beneficial and meaningful to include this concept in this study. Thus, the research on the direct influence of supply chain resilience on supply chain performance is significant. To make the results more clear, this study briefly focuses on one supply chain performance indicator, customer service performance. Thus the second research question of this research is: RQ2. How does supply chain resilience influence customer service performance?

Through this study, the direct influence of supply chain resilience on supply chain customer service performance can be initially investigated. Meanwhile, the relationship between human capital resources and supply chain resilience is deeply and completely researched. On the other hand, through the contribution of this research, from the managerial perspective, companies can learn to improve supply chain resilience in a more practical way. As improving human capital is a continuous process, this method to enhance supply chain resilience is more operational and cost-efficient. Furthermore, as the concept, human capital resources, has been studied for years (Ployhart & Moliterno, 2011), various methods on how to enhance it have been explored and applied. In turn, these mature methods can be utilized to improve supply chain resilience. Additionally, as a firm’s management level are more focus on their organization’s performance, through researching on the correlation between supply chain resilience and customer service performance, as well as the effect of human capital resources on customer service performance, this paper can directly help managers to determine their strategies of these two concepts.

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2. THEORETICAL BACKGROUND

2.1 Supply Chain Resilience (SCRES)

Supply chain resilience is a multidisciplinary and multifaceted concept, which leads to difficulty to form a consensus in the literature to define it (Tukamuhabwa et al., 2015; Hohenstein et al., 2015). As aforementioned, having been accepted by many researchers, the essence of supply chain resilience is to develop an adaptive capability to deal with disruptions (Fiksel, 2006; Ponomarov & Holcomb, 2009; Stewart et al., 2009; Pettit et al., 2010; Ponis & Koronis, 2012; Xiao et al., 2012; Golgeci & Ponomarov, 2013; Pettit et al., 2013; Sawik, 2013). There are two dimensions, one is to reduce the possibility to be disrupted before the turbulence, the other is to respond and recover rapidly post the disruption (Jüttner & Maklan, 2011; Wieland & Wallenburg, 2012, 2013; Ivanov et al., 2014; Hohenstein et al., 2015). Just as Wieland & Wallenburg’s (2012) summarization, mitigating vulnerabilities in both a proactive and reactive manner.

The first dimension is to reduce the occurrence of the supply chain disruption through prevention and forecasting (Wieland & Wallenburg, 2013). Redundancy is particularly highlighted at this stage (Zsidisin & Wagner, 2010; Bode et al., 2011; Hohenstein et al., 2015). These can be achieved in terms of various resource buffers (Schmitt & Singh, 2012), including material buffers (e.g. higher level of safety stock or inventory and multiple suppliers) (Wu et al., 2013), time buffers (e.g. predefined slack planning and shortened replenishment period) (Zsidisin & Wagner, 2010), human buffers (e.g. cross-trained employees) (Kern et al., 2012), etc.. These buffers can be utilized as “shock absorbers” to reduce possibility of mistakes during execution (Hohenstein et al., 2015). For instance, once the material supplying has finished, the material flow should be replenished in a rapid way to prevent any supply disruptions.

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2010; Klibi et al., 2010; Blackhurst et al., 2011; Schimitt & Singh, 2012). Thus, companies with high supply chain resilience could deal with disruptions quickly.

2.2 Human Capital Resources (HCR)

Resources, which may be intangible or tangible, are “all assets, capabilities,…, information, knowledge, etc. controlled by a firm that enable the firm to conceive and implement strategies that improve its efficiency and effectiveness” (Barney, 1991: 101). He further classified resources into three categories: physical capital resources, human capital resources and organizational capital resources (Barney, 1991). As an important subject, human capital resource has been researched for years (Ployhart & Moliterno, 2011). It is a multidisciplinary concept as well. Scholars working in different disciplines in terms of psychology, economics, and management research have all developed the human capital construct from their own academic perspectives (Spearman, 1927; Becker, 1985; Wright et al., 1994; Coff, 1997). Therefore, the definition of human capital is various. Among different disciplines, the most accepted statement is that knowledge, skills and abilities inherent in organizational members constitute organization’s human capital (Ployhart & Moliterno, 2011; Coff & Kryscynsk, 2011; Menon, 2012; Nyberg et al., 2014). Initially, Kelly (1963) just recognized individual’s knowledge as human capital. Then Flamholtz & Lacey (1981) focused on people skills and McKelvey (1982) realized the importance of human competence. Then by concluding research of Coff (2002) and Wright et al. (1994), Crook et al. (2011: 444) summarized that “human capital refers to the knowledge, skills, and abilities (KSAs) embodied in people”. Moreover, Nyberg et al. (2014) further elaborately explained that “knowledge” is the factual or procedural information necessary for performing a specific job and the foundation on which skills and abilities are developed; “skills” are the individual’s level of proficiency and capabilities to perform a specific job task; “ability” is a more enduring capability (usually cognitive) that is necessary for an individual to perform a job.

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For a manager, technical skills refer to his or her specialized abilities based on aggregation of professional knowledge within specialty as well as analytical capabilities to make the right decisions (Benson et al., 1991). Human skills are a manager’s ability to work with others effectively through communication skills and group collaboration (Beatty, 1992; Ford & Noe, 1987). Manager’s conceptual skill is the ability to view from a supply chain perspective, that is, understanding the relationship between his or her organization and upstream/downstream firms (Beatty, 1992). It is essential for a manager to know how his or her decision-making influences the whole supply chain performance.

On the other hand, for workers, operation knowledge means to grasp the knowledge of production processes and machine operations, meanwhile, technological skills are specialized skills to be qualified for their job (Youndt et al., 1996). These two aspects make workers be highly skilled workers, which is a necessity to optimize the potential of the utilized advanced technologies (Upton, 1995; Youndt et al., 1996). The people skills of workers, similar to the human skills of managers, refer to the necessary interpersonal skills to work well with their co-workers (Norman et al., 2002). It is critical to develop collaboration among employees. While problem-solving skills require workers’ capabilities on learning and experience relevant to their job (Levy & Murnane, 2004; Levy & Murnane, 2012). All these aspects help firms on transferring routine workers to knowledge workers and providing advantaged competencies. As for the last dimension, creativity, since it is a cognitive concept, compared to other dimensions, it is much more difficult to measure.

2.3 Customer Service Performance (CSP)

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customer service is a broad term as well, containing many elements and involving almost all stages of the whole supply chain process (Ballou, 1999). As evidence exists that superior logistics customer service separately leads to better overall firm performance (Leuschner et al., 2013), to be explicit, this study briefly focuses on logistics customer service. In this respect, from a logistics perspective, customer service refers to ensuring the provision of a product in the right quantities at the right place and right time, while without damaging and satisfying customers (Emerson and Grimm, 1996; Coyle et al., 2003; Theodoras et al., 2005; Naoui, 2014).

To achieve this objective, according to the definition, service dependability is required. It is concerned with a safe arrival with correctly filled orders and consistent duration (Collin et al., 2001). The dependability is the guarantee of a delivery that is complete and on time. That is, no shortage in quantities of order completeness and no lateness of on-time delivery, which is the foundation of customer service on satisfying the customer order. In addition, it is more important to customers (Coyle et al., 1996), since it directly relates to customer service level. While in monitoring of the service levels relating to dependability, communication is vital (Collin et al., 2001). It is a two-way process, incorporates mutual information transmitting between sellers and buyers. For instance, the supplier would be well advised to notify customers in advance of the potential service level reduction, such as late deliveries or stock-out, so that the buyer can make necessary production adjustments. For a focal company, it contributes more on the strategic partnerships with downstream customers and upstream suppliers. On the other hand, within a turbulent and complex supply chain networks, to continuously satisfy customers, the operation must be sufficiently flexible and responsive to respond to the dynamic customer requests and emergency orders, which requires high flexibility to adjust corresponding operations economically (Collins et al., 2001). The causes for emergencies can either internally operation’s failure or externally customer needs change or supplier provision break. To achieve high customer service responsiveness (convenience), no matter what kind of disruptions or change, it requires supply chain to rapidly adjust and still can satisfy customer requirements in a reliable way. Finally, a reasonable or even shorter time length is favoured by buyers consistently.

2.4 The Effects of Human Capital Resources on Supply Chain Resilience

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turbulence, the first stage, in order to accurately forecast, the firm’s ability to sense changes and risks is asked for. Compared to centralized department, employees who interact closely with actual stakeholders can gain additional information. Through conducting decentralized monitoring, company’s monitoring capability can be increased (Wright et al., 1994). Moreover, this decentralized way is more flexible and suitable to the complex and dynamic environment. To implement this kind of monitoring behaviours, employees must have the necessary knowledge and skills. That is, higher levels of human capital resources can enhance the monitoring capability of the firm, in turn, increase the possibility of correct forecasting. For instance, change and risk detections throughout the whole supply chain require supply chain members share real-time demand, inventory and production information which allows all members to access relevant data and make informed decisions (Ahn et al., 2012). During this process, workers and managers should communicate well and exchange information with suppliers and customers continuously. Then managers can make the most appropriate decisions on the basis of visible and accurate information. To achieve effective and efficient communication, high managers’ human skills and conceptual skills as well as workers’ people skills are necessary.

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operational levels engage in developing the tactics necessary to function in their particular situations (Quinn, 1980). To cope with the complex environment and constant changes, these decisions should be accurate and determined as quickly as possible, which requires high technical and conceptual skills of managers as well as high operation knowledge and technological skills of workers. Afterwards, rapid and efficient implementation of new strategies is asked for as well. In order to achieve this objective, the workforce needs to quickly learn and adapt to new things as well as the environment. People with high operation knowledge, technological skills, problem-solving skills can result in the rapid adaptation (Wright et al., 1994).

As aforementioned, it is critical for the resilient supply chain to develop an adaptive capability. And according to the research of Jin et al. (2010), high level of a company’s human capital is highly adaptive to changes in both internal and external environments. Thus, high levels of human capital can result in high adaptive capability which is the objective of supply chain resilience. In addition, superior human resources provide adaptive performance, which is an ability of individuals to change behavior to meet demands of the new environment (Charbonnier-Voirin & Roussel, 2012) and adapt to dynamic work situations (Hesketh & Neal, 1999). On the other hand, facing the more complex, turbulent and unstable environment, successful adaptive performance implies that employees are able to efficiently deal with inherent uncertainty and adapt quickly through high capability on decision-making (manager’s technical skills) as well as the ability to learn and adapt to ongoing changes in sophisticated technology (worker’s operation knowledge, technological skills, and problem-solving skills) (Charbonnier-Voirin & Roussel, 2012). Besides, excellent manager’s human skills and worker’s people skills support open communications which enable them to work well with each other and ease the resistance to change (Jin et al., 2010). Such smooth transition would, in turn, promote the supply chain adaptability and resilience.

Based on the above discussion, one can propose the following hypotheses:

Hypothesis 1. Human capital resources of the supply chain are positively related to supply chain resilience.

2.5 The Effects of Supply Chain Resilience on Customer Service Performance

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market shares and financial performance. It can be reflected that there is a potential direct relationship between supply chain resilience and customer service performance.

Initially, from the definition of supply chain resilience, adaptive capability asks for high flexibility and the speed of response, which can appropriately help to obtain and improve the service responsiveness of the customer service performance. Since the objective of resiliency is to prevent potential changes influence the supply chain operations or minimize their negative impacts, which forms the basis of dependable customer service performance. Additionally, when the delivery period is shorter than the production time period or procurement lead time, it is necessary to anticipate the customer’s orders, a necessary part of the proactive stage of supply chain resilience. Obtaining responsive customer service is essential on satisfying dynamic and emergent customer service requirements, which is analogous to the circumstance of supply chain resilience, dynamic and evolving changed environment. Therefore, one hypotheses can be drawn:

Hypothesis 2. Supply chain resilience is positively related to supply chain customer service performance.

2.6 The Effects of Human Capital Resources on Customer Service Performance

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Hypothesis 3. Human capital resources of the supply chain are positively related to supply chain customer service performance.

To sum up, by focusing on the supply chain resilience, this research will empirically study its relationship with human capital resources and customer service performance, as well as the correlations between human capital resources and customer service performance. These can be reflected from the conceptual model (Figure 2.1).

FIGURE 2.1. Conceptual Model

3. METHODOLOGY

To answer research questions, one of quantitative research methods, survey is used for data collection, because it can ensure the number of respondents to achieve high generalization, and further, to draw empirical conclusions.

3.1 Data Collection and Sampling

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speed on materials and manufacturing technology is high, and the corresponding regulation policies are extremely strict. On the other hand, the preferred study population is mainly senior-level managers of production, purchasing or other supply chain functional areas, because they obtain knowledge of supply chain processes, directly involved in strategic and operational decision-making, and had, at least, a general idea of the whole chain including suppliers and customers. Furthermore, they were familiar with the performance of the organization. This purposive sampling was employed to achieve external validity as well as to contribute to the generalization of the results (Cook et al., 1979).

To ensure the randomness and coverage of data collection, in the Netherlands, the initial sample was subtracted from the databases from the Dutch Chamber of Commerce with industry codes 10 and 11. Whereas in China, the database of surveyed firms was derived from a famous questionnaire survey wetsite, Sojump Investigation Network (http://www.sojump.com). It is one of the most professional survey sites in China. Through controlling one IP, one computer and one account for only one questionnaire at the same time, Sojump survey system can gain high reliability. Meanwhile, Sojump has its own database throughout all industries and can ensure the sources of the collected data. The classified management of all investigated persons registered on this website provides conditions for surveyors to accurately position of the target population. To keep controlling on the sample quality, the Sojump regularly verify respondents’ detail information and update their attributes, such as gender, age, position, industry, etc.. By specifying the three determined industries and requiring on respondents as senior-level managers to the Sojump, investigated persons were randomly chosen. In this way, the reliability of collected data, to a certain degree, can be assured.

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informant from each industry was selected at this time. They are experienced senior managers who are familiar to supply chain operations and their cooperation with suppliers as well as customers. After recording the completing time of each respondent on the questionnaire, the mean time is calculated. After receiving replies, according to the feelings from respondents and their effective advices, the questionnaire was modified, and again, was sent to another respondent from each industry. The finishing time period for the second time is shortened a lot. Then the formal questionnaire was finished.

After the initial invitation link had sent, for non-response firms, reminders by email, phone or both were sent out in one week and again two weeks following the initial one. As a result, we obtained 228 responses (157 from Chinese firms and 71 from Dutch firms). Once receiving all the responses, the non-response bias was examined. To check for differences between early and late responders, a one-way ANOVA analysis was performed on two control variables, firm size and firm turnover. 30 earliest and 30 latest respondents were chosen to conduct comparisons. The results were (1) firm size: F = 0.572, p = 0.685 > 0.05; (2) firm turnover: F = 0.573, p = 0.671 > 0.05. From the p-value, there is no significant difference between the responses, therefore, non-response bias is not considered a problem with the data (Karlsson, 2010). Afterwards, through checking on data completeness and effectiveness, there were 68 ineffective cases excluded, 43 (18.9%) for incompleteness on questionnaire answering, and 25 (11.0%) for the unreasonable completing time period (much shorter than the mean time of the second pilot test). That is, in total, 160 data was determined to be used for following analysis representing an effective response rate of 28.4%.

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TABLE 3.1

To sum up, the sample design and industry sector selection are corresponding to and suitable for the subject of this research. Within the industrial design, through randomly chosen surveyed companies in terms of firm size and annual sales, the results are generalized. And the sample size was adequate to perform the following analysis. Therefore, the sample size (160 respondents) was acceptable in satisfying the external validity.

3.2 Measurement Development

In the questionnaire, all the questions of each factor were derived from concept definitions in the literature (Wieland & Wallenburg, 2012; Jin et al., 2010; Gimennez & Venture, 2003) to obtain initial content validity. The specific citations are shown in Appendix A. And most of them had been employed before by previous research. To ensure the reliability of the results, all scale choice questions utilized the same scale, a 5-Likert scale, ranged from strongly disagree to strongly agree. From the Appendix A, we can see which specific item represents which construct, and further which aspects/dimensions of each construct.

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and responsiveness, were measured by different items respectively. Since the resistance to provide the confidential data, it was difficult to collect quantitative performance data, the customer service performance in this study was operationalized by employing the individual cognitions or perceptions of respondent managers on absolute performance improvements (Gimenez & Ventura, 2005). Through employing absolute terms that not taking into account competitors’, the improvement of respondent companies throughout a disruption can be seen. To reflect this aspect, the statement before questions of this part is “provide an indication of the improvement of your customer service to the key buyer relative to three years ago”. Finally, based on the classification of human capital resource (HCR) (Jin et al., 2010), 4 items were chosen to represent managerial capital (HCR_M) and 2 indicators stand for worker capital (HCR_W).

The questionnaire was pre-checked in several times by consulting several professionals with extensive knowledge in this field to refine the content validity. To avoid any resistance behaviors from respondents, we made our questionnaire as short and clear as possible. Since the survey conducted both in the Netherlands and in China, it also involved translations from English to Chinese. All exclusive words were translated through checking with literature or professional database. And the initial translated version had been double checked by two additional teachers to ensure the results of translation are accurate and understandable. Then, the translated Chinese questionnaire was translated into English by other teachers. The difference of this translated English version and the initial English version was checked carefully to ensure the correctness of language translation. Especially, to avoid any mistakes on a combination of two parts’ answers, the sequence of questions and the sequence of items within each question had been double-checked.

3.3 Data Analysis

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Then, a principal component analysis was conducted on 13 items to test the retention of factors. An orthogonal rotation (varimax) was used, the results (Table 3.2) showed that three factors without cross-loading could be distinguished, as their initial eigenvalues over 1 and in combination they explained 62.806% of the variance, bigger than the benchmark of 50%. The values of the selected items are bigger than 0.6, providing the construct validity evidence. Component 1 represents human capital resources, including managerial capital and worker capital, component 2 is concerned with customer service performance, and component 3 involves three items of supply chain resilience.

Table 3.2

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comparative fit index (CFI) = 0.9903, Tucker-Lewis index (TLI) = 0.953, root mean square error of approximation (RMSEA) = 0.051 with p-value (PCLOSE) = 0.443, each supporting good model fit (Browne & Cudeck, 1993).

Finally, the reliability of the three constructs is measured by Cronbach’s alpha respectively. Reliability concerns the extent to which a set of items remain consistent over time and across surveyors (Karlsson, 2010). From the results of Table 3.2, all α-value of three factors are larger than 0.7 (0.752, 0.806 and 0.819, respectively) which represents good internal consistency of items (Nunnally, 1978).

4. RESULTS

4.1 Descriptive Statistics of Variables

Since the good evidence of construct validity and reliability, the three new variables that represent constructs of this study were computed from the 13 items. From the conceptual model, human capital resource (HCR) is the independent variable, customer service performance (CSP) is the dependent variable, and the supply chain resilience (SCRES) is the mediating variable. The descriptive statistics results of these three variables are shown in Table 4.1. From the value of correlations between constructs, there is a significant positive relationship between the independent variable (HCR) and dependent variable (CSP), r = 0.572, p < 0.001. And the correlation between independent variable (HCR) and mediating variable (SCRES) is significant and positive as well (r = 0.501, p < 0.001). In the meantime, the correlation table shows that an increase in mediator (SCRES) is significantly related to an increase in dependent variable (CSP) (r = 0.394, p < 0.001). Finally, the control variable, firm size, is positively correlated with both SCRES and CSP, in a significant way.

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4.2 Linear Regression

Using linear regression analysis, the direct relationship between variables were tested, in turn, the hypothesized relationships were verified as well.

Table 4.2 presents the results of the regression analysis for hypothesis 1. Step 1 indicates that the firm size has a significant and positive effect on supply chain resilience (β= 0.18, p < 0.001, R2 = 0.143). In step 2, it is obvious that the human capital resources has a significant effect on supply chain resilience (β = 0.537, p < 0.001, R2 = 0.348). This means that an increase of 1 in firm’s human capital resources will lead to an increase in supply chain resilience by 0.537. This increase is significant. Since the R-square value is the explained variance, we can know that the human capital resources can account for 34.8% of the variation in supply chain resilience. This result confirms the hypothesis 1. Furthermore, since managerial levels play an active role in supply chain management (Wright et al., 1994), and Hannan & Freeman (1977) had argued that managers have greater influence over firm performance than operation levels, the influence of different dimensions of human capital resources are potentially different. On the other hand, through cluster analysis, which is a statistical data analysis method to group a set of objects, items of human capital resources were classified into two clusters. Then conducting one-way ANOVA analysis on these clusters, as the p-value of between groups is 0.001, the difference between clusters is significant. Thus, two dimensions of human capital resources, managerial capital and worker capital, are distinguished in this research to see their individual effects clearly. In this regression test, both dimensions of HCR have a significant impacts on supply chain resilience, which can be reflected from step 3 (β = 0.482, p < 0.001) and step 4 (β = 0.415, p < 0.001), respectively. Although not larger than that of human capital resource, the R-square of managerial and worker capital are 0.344 and 0.273. And both the R2 value and β value of managerial capital are higher than those of worker capital.

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Hypothesis 2 and 3 are tested in a regression model predicting customer service performance. Results are displayed in Table 4.3. Similar to Table 4.2, step 1 indicates that the firm size has a significant and positive effect on customer service performance (β = 0.116, p < 0.01), though R2 = 0.057 low explained the variance of customer service performance. Step 2 added the mediator, supply chain resilience, to the regression model. The effect of supply chain resilience on customer service performance is positive and significant (β = 0.364, p < 0.001, R2 = 0.165), which confirms hypothesis 2. To verify hypothesis 3, in step 3, with control variable, the independent variable, human capital resources, was added to the model. From the result, the direct relationship between human capital resources and customer service performance is significant and positive, further, the β value is as high as 0.663. And R2 = 0.353, that is, 35.3% of the outcomes in customer service performance can be explained by human capital resources. In the following, similar to the regression analysis on H1, in step 4 and step 5, the effect of managerial capital and worker capital on customer service performance were verified respectively. The result of the former is β = 0.580, p < 0.001, R2 = 0.332, the latter is β = 0.547, p < 0.001, R2 = 0.271. Through comparison, likewise, both the R2 value and β value of managerial capital are larger than those of worker capital.

Table 4.3

4.3 Mediation Effect

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To further analyse the interaction effects, Baron and Kenny’s (1986) 3-steps for mediation through multiple regression analysis was employed, the result is shown in Table 4.4. In the first step, the path c (HCR-CSP) was tested, which showed that the independent variable (HCR) is significantly correlated with the dependent variable (CSP) (β = 0.69, p < 0.001, R2 = 0.327). This step establishes that there is an effect that may be mediated. Step 2 is to test the path a. The correlation between the independent variable and the mediator was significant (β = 0.59, p < 0.001, R2 = 0.251). Finally, in the last step, through using the interaction of both independent variable and mediator as predictors in a regression analysis, the mediation effect was tested. From the results, while controlling for the independent variable, the correlation of the mediator on the dependent variable is not sufficiently significant (p = 0.058 > 0.05, β = 0.147, R2 = 0.343). Meanwhile, under the controlling of the mediator, the correlation between the independent variable and the dependent variable was still significant (β = 0.604, p < 0.001).

Table 4.4

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The bootstrapping method provides some advantages to the Sobel’s test, primarily an increase in power, thus, especially preferred when sample size is not large (Preacher & Hayes, 2008). In the present study, the 95% interval confidence of the indirect effects was obtained with 5000 bootstrap resamples. And the result of bootstrapping analysis is presented in Table 4.5. From it, as zero did not fall between the resulting confidential intervals, it can conclude that there is a significant mediating effect of supply chain resilience in the relationship between HCR and customer service performance (CI = 0.0017 to 0.2086), confirming the mediating role of SCRES.

Table 4.5

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Table 4.6

5. DISCUSSION AND IMPLICATIONS

In today’s highly complex and dynamic global business environment, a number of scholars and senior managers have realized the importance of supply chain resilience. But most literature just provided a general overview of this concept, specific tactics on how to improve it are limited and thus companies have little guidance in practice. Through empirical test, human capital resource is verified as a significant enhancer to supply chain resilience. Additionally, adding the customer service performance as the third variable, through statistics calculation on collected data, this paper concludes that these three variables are mutually correlated in a positive and significant way, which contributes to the current literature and theoretical understanding of issues relating to human capital resources, supply chain resilience and customer service performance, and provides both research as well as managerial implications.

5.1 Discussion

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In addition, on the basis of significant effects of hypothesis 1 and 2, the mediation effect of supply chain resilience was examined. The supply chain resilience has a significant but partial mediating effect in the relationship between a firm’s human capital resources and its customer service performance. Even the mediation effect of supply chain resilience is weak, it is suggested that the influence of human capital resources on customer service performance is partly via supply chain resilience. According to Barney (1991) and Blackhurst et al. (2011), on the basis of resource-based view (RBV), resources like human capital can create capabilities like supply chain resilience to determine a firm’s reaction to internal and external threats as well as opportunities. These reactions are high-level plans or supply chain strategies to achieve objectives under environmental uncertainties (Mintzberg, 2003). One of supply chain strategies to cope with uncertainties and risks is to build a resilient supply chain through continuously improving adaptive capabilities (Somers, 2009). That is, increasing supply chain resilience. On the other hand, Mintzberg (1978) stated that the strategy is a pattern in terms of decisions. Similarly, Quinn (1980) argued that the development of firm strategies incorporates decision evolutions. As previous arguments, overall strategic directions are determined by top management, while specific strategies and tactics are set by sub-units (Wright et al., 1994). All these should be effectively implemented by operators to achieve the strategic goals, which can be measured by supply chain performance. Both managerial levels and operational levels constitute firm’s human capital resources. Through their performance on decision-making and implementation, strategies are set, executed and then evaluated through specific supply chain performance indicator, such as customer service performance. Since enhancing resilience is one of supply chain strategies, human capital resources can influence the supply chain resilience through their competencies with the results reflected from the supply chain performances. Therefore, aligning with the results, we can conclude that high quality human capital resources can contribute to higher customer service performance by improving supply chain resilience.

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dealing with the turbulence, the decision making mechanism from robust supply chain to agile supply chain is essential to supply chain resilience. So, the managerial capital is more determinant to the supply chain resilience. On the other hand, management level distinguishes high ability individuals from lower ones, it is their responsibility to develop high quality employees for the organization. In this way, top management may create the conditions under which the remainder of the human capital pool becomes a source of sustainable competitive advantage (Wright et al., 1994), and therefore, managers greater influence over firm performance. Finally, on analysing supply chain resilience’s mediating effect, both two dimensions of human capital resources can improve customer service performance via increasing supply chain resilience. This is because both managers and workers with high competencies can increase supply chain resilience and in turn results in better customer service performance. For instance, to deal with turbulence, top management rapidly adjusts the overall strategic directions, sub-units design corresponding specific tactics and implement quickly to achieve higher responsiveness and then lead to higher performance.

5.2 Theoretical and Managerial Implications

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increasing both the level of supply chain resilience and customer service, it is worth to improve human capital resources. From Wright et al. (1994), human resource practice is an enhancer to develop HCR. This concept is very easy to be mixed up with human capital resources (e.g. Blackhurst et al., 2011), but they are different. Wright et al. (1994: 304) defined human resource practices as “the organizational activities directed at managing the pool of human capital and ensuring that the capital is employed towards the fulfilment of organizational goals”. They further explored that these practices are essential levers that can help to develop human capital resources and facilitate high quality employees to bring their advantages into full play. Managers can attract, identify and retain high quality employees through HR practices. For instance, many prior research provide practical suggestions on retaining quality human capital, such as enhancing employees’ fit with the values and culture of a firm (Bernardin, 2002; Liu et al., 2007), offering continued trainings and forming teamwork focus (Hottenstein & Bowman, 1998), as well as motivating staff through reward system and internal promotion practices (Aeppel, 2010). The cross-training, according to Jin et al. (2010), is especially better to equip workers to develop adaptive performance. Besides, from the results of this paper, for obtaining higher supply chain resilience and customer service performance, the impact of managers’ competencies is higher than that of workers’. This finding allows organizations to more effectively determine their strategies for human capital possess and development. Since managerial level and operational level play different roles in supply chain management, once organizations determined their strategies and objectives, specific requirements of human capital resources are accordingly decided, in turn, investments and other resource allocations are conducted properly. Take an example, organizations, to gain higher resiliency and customer service performance, should more stress on improving the competencies of managerial level rather than operational level. Furthermore, once has formed a general idea which kind of competencies of managers and workers can maximize their influence on the determined strategy and objective, then through specific human resource practices or other methods, companies can further boost corresponding capabilities of the two parties to gain optimal results.

6. CONCLUSIONS

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important. The current study underscores the importance of supply chain resilience and establishes relationships among manufacturing firm’s human capital resources, supply chain resilience and customer service performance in a supply chain context. It illustrates the direct and positive link between human capital resources and supply chain resilience, which is the goal and main contribution of this research. Meanwhile, this paper contributes that it verified supply chain resilience can positively lead to higher customer service performance in a direct way. In addition, this paper extends the previous literature on the direct positive relationship between human capital resources and customer service performance, further, it investigates their indirect correlations through mediation effect. That is, human capital resources are related to the company’s customer service performance in two ways: there is a direct positive relationship between human capital resources and customer service performance, and human capital resources indirectly relate to customer service performance through the supply chain resilience of the firm.

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