1. Introduction
In recent years, the nature of competition has increasingly shifted toward one supply chain competing against another supply chain [
1]. Bromiley and Rau and Breton-Miller and Miller have raised the question that why, under uncertainty, some firms outperform others [
2,
3]. Typically, supply chains serve the strategic goals through inter-reliant value-adding processes. Hult et al. have argued that the “strategic supply chain management” role is not merely moving products where they need to be, but is also a tool to enhance key outcomes [
4,
5]. By nature, supply chain entities are interdependent through sequential, parallel, and network structures, and collaboratively transform raw materials into finished products which can be highly vulnerable to uncertain risks and disruptions [
6,
7].
McKinsey Global Institute (MGI, USA) commissioned a study on globalization and found that geopolitical and domestic political instability will increasingly affect global businesses and their companies. Hence, business continuity and sustainable business performance are going to be a challenge. This is a rising phenomenon and common concern shared by 84% of executives who took part in this survey, which has been part of an on-going research for the last ten years. Findings indicated that most respondents expect that severe disruptions due to geostrategic risks (characterized by geopolitical, political, and macroeconomic instability) will affect their companies, with decidedly negative implications for profits and slowing growth. At the same time, a vast majority say their organizations are not ready to address these issues. While geostrategic risks are complex issues, these risks could be a potential source of competitive advantage for companies that develop better strategic capabilities to manage them. In a related study, Culp posits that natural disasters and extreme weather conditions are not the only threats to supply chains, but that systemic vulnerability, such as oil dependence and information fragmentation, also pose serious risks, as do political unrest and cyber-crime [
8]. In addition, in a related study, Culp reported that 80% of companies worldwide see better protection of supply chains as a priority, because significant supply chain disruptions reduce the share price of affected companies by as much as 7% on average. For instance, events like the Japanese earthquake and tsunami, and the floods in Thailand have demonstrated how far the consequences of such risks can extend. The recent earthquake in Japan, for example, severely affected global electronics production and led to extended business disruptions for the automotive industry. The Thai flooding created significant shortages in the hard disk drive market that generated millions of dollars of losses for well-known electronics manufacturers. In addition to these headline events, however, the nature of supply chain risk is constantly changing. New risks and new vulnerabilities can often be better addressed if given close attention from management. Culp also found that the fragility of global supply chains is related to emerging risks and to supply and network design strategies [
9]. Volatility and uncertainty are not going away anytime soon. Risk-based, cost-effective supply chain management can be an essential element of success. This capability cannot only help prevent losses, but can also prove, for many companies, to be a lasting source of competitive advantage.
Linton et al. posit sustainability are deeply rooted in the supply chain. Since the supply chain deals with the specific product from end-to-end with initial processing of raw materials until final delivery to the customer [
10]. Sustainable operational performance (OP) is a vital element in achieving competitive advantage for the entire supply chain. When the resources are scarce and vitally important, companies are faced with uncertainty in managing the supply and demand to pursue specific supply chain strategy (SCS) to maintain sustainable OP [
11]. Firms that are capable of managing these uncertainties with appropriate strategy will thrive with sustained performance and develop a source of competitive advantage [
12]. Markley and Davis argued, in the near future, due to competitive pressure, as the sources of competitive advantage for firms become limited and they will search for new areas of excellence [
13]. This study contributes towards sustainability by analyzing the potential source of competitive advantage firms can create from the creation of a sustainable supply chain. Moreover, uncertainty about the scarcity of the environmental and natural resource for companies’ will demand adopting or pursuing supply chain strategies that will continue to deliver sustainable OP.
Responding to uncertainty through managing supply chains is central to a firm’s strategic success. The unpredictability of consumer demands, shorter product life cycles, price and quality fluctuations in supply markets, continuous improvement initiatives by competitors, along with market dynamics, imply that supply chains are struggling for stability [
14]. In response to this phenomenon, firms are searching for ways to overcome uncertainty [
15]. By building on contingency theory, Hult et al., have found synergies between supply chain uncertainty (SCU) and SCS, and their positive impact on OP [
6]. However, their links to OP are still unexplored. Resource dependence theory (RDT) asserts that firms facing substantial environmental uncertainty will attempt to stabilize themselves by imposing inter-organizational ties [
16]. Contingency theory emphasizes the effectiveness of realizing an intended match between an uncertain environment within which an organization operates and its strategy [
17,
18]. Uncertainty within the supply chain arises from both upstream and downstream. In the case of downstream uncertainty, SCU stems from volatile demands, while upstream uncertainty arises from supply markets.
Hitt et al. [
19] and later on followed by Qi et al. [
18] explored this relationship have considered uncertainty as a moderator between inter-organizational relationships and performance [
15]. Hence, this study attempts to extend this stream of research by focusing on the following gaps in the literature. First, RDT is adopted to examine the direct relationship between SCU (demand and supply) and SCS due to the fact that earlier studies by Wu et al. [
20], Qi et al. [
18], Yusuf et al. [
21], Lee [
22], and Fisher [
23] concluded SCS is a broad and multidimensional phenomenon represented by multiple strategies [
18,
20,
21,
22,
23]. Second, this research further extends on Fisher and Lee’s model who introduced the concept of “strategic supply chain” in response to uncertain environments, and who also examined the context of achieving superior performance through responding to uncertainty [
23,
24]. Taking these previous studies as our point of departure, we used RDT [
24], as the theoretical lens to examine an appropriate strategy to achieve superior performance under uncertain supply chain conditions.
This study proceeds as follows. Next section proposes and develops some empirically testable hypotheses. Subsequent sections present the data and methodologies used in this research and explain the results. Finally, section five and six brings together the discussion, implications, limitations and future work.
5. Discussion and Conclusions
This study provides empirical support for RDT in explaining the relationship between SCU and SCS, which leads to firms’ OP. By focusing on uncertainty and strategy this study contributes towards context specific sustainable supply chain management research, as prescribed by Busse and Mollenkopf [
80]. Also, fsQCA provides a more fine-grained analysis of SCU and strategy alignment. Findings from both PLS-SEM and fsQCA constitute a significant contribution to and an extension of the literature in supply chain management. For researchers, this study also demonstrates that the application of PLS-SEM, along with fsQCA, allow one to test an interlinked set of hypotheses simultaneously in a prediction oriented modeling because the model in this study contained a series of dependence relationships.
This study also illustrates predictive validation testing of models using holdout samples and testing for causal asymmetry. From a research implication standpoint, this research contributes by illustrating a PLS-based estimation for a rapidly emerging field of study of supply chain management. In an uncertain environment, supply chain partners tend to work in close collaboration; they often become more dependent on each other. However, instead of just collaborating, firms should seek supply chain-wide integration and avoid dependencies.
Based on the results, we found support for hypotheses H1 and H2. This implies that SCU internally leads to the selection of a specific strategy that will contribute to firms’ OP. In addition, the empirical findings lend support for hypothesis H3, which illustrates that SCS has a mediating role in a firm’s OP. This finding is due to businesses that engage in managing SCS look for ways to enhance each other’s competitiveness.
Overall, this study contributes to the literature on the most debated link between SCU and OP which is mediated by the SCS. The combined causal relationship investigated through fsQCA nuances those contributions. Unlike Paulraj and Chen, who found that demand uncertainty has no impact on SCS [
25], this study shed insights into the link between SCU and SCS. Indeed, this study shows that in the relationship leading to OP, SCU dimensions offer alternative decision-making approaches (see Solutions 1a and 1b).
According to the adopted theoretical premise of RDT, under uncertain (both supply and demand) circumstances, due to resource scarcity, firms attempt to collaborate with their supply chain partners to respond to the volatile environment. This finding is also supported by Berti and Mulligan that, in an uncertain market environment firms typically experience declining profit and the reduced cost price [
81]. As a result, sustainability of firms may be at stake that leads to increased barriers to market access with the inevitable effect of market abandonment.
From a methodological perspective, this study illustrates the usefulness of applying complementarities of PLS-SEM and fsQCA in empirically unpacking the OP differentials as they are examined in SCU and SCS research. The PLS-SEM methodology is suitable in explaining the causal paths through which SCU and SCS ultimately affect performance, whereas fsQCA provides a deeper understanding of the complex, non-linear, and synergistic effects of supply chain risk management in conditioning the effect of SCU and SCS on performance. The PLS-SEM results demonstrate the general tendency, whereas fsQCA uncovers the multiple realities that exist in terms of achieving the desired state [
55,
82]. Ultimately, this study confirms that the use of PLS-SEM supplemented with fsQCA approach suggests that the scholarly community may apply such combinative approach to make this multi-mixed approach a formidable statistical tool.
The findings of the research have several meaningful implications for managers in the global marketplace. Before formulating a strategy, managers should analyse the nature and source of inherent uncertainty within their supply chain, and align this source with an appropriate strategy. This will contribute to better OP. Solutions 2 and 5 indicate that whether or not uncertainty is apparent, managers do not need/have an SCS to achieve OP (Solution 2), whereas in an uncertain supply environment, one needs to have a strategy for high performance (Solution 5).
The practitioners may utilize this knowledge as a guideline to ensure that a “strategic fit” between firm and supply chain partners is created and to support the improvement of decision-making to ensure that there is an appropriate strategic approach for the customer and supplier to best influence a firm’s OP. We are also aware that core to fsQCA is to consider each indicator of the latent constructs with equal importance in the causal paths. Using importance-performance map analysis (IPMA) [
37,
77], we might gain a deeper understanding of the importance which each indicator composing SCS and SCU intervenes in the causal paths to sustainable OP. IPMA enables managers to prioritize their organizational and managerial actions. It also helps managers to identify important areas for the improvement of marketing or management activities. In this study, both PLS-SEM and fsQCA results show that SCS and SCU have the highest importance on sustainable OP. Therefore, practitioners may note that a one-point increase in the performance of SCU and SCS are expected to increase the performance of OP by the value of the total effect (0.46) and (0.17) respectively.
6. Research Limitations and Future Research
The current study is based on the data collected from one single economy within one single industry. Hence, the findings may not be generalizable to other economies and industries. This study has been conducted based on an inductive approach with cross-sectional data. However, future research may consider using longitudinal data to see the changes over time. In addition, supply chain uncertainty should encourage collaborative efforts within the partners that would contribute to better operational performance [
83], future research should incorporate the supply chain collaborative dimensions in the model. Touboulic and Walker suggested sustainable supply chain management is emerging as an applied field of knowledge and due to its’ applied orientation, an action research approach would be more meaningful [
84]. By nature, the problems in the supply chain are often inter-disciplinary and concerned with the impact on society and business, at large. Also, this raises a future research question, ‘to what extent can market/supply chain forces drive sustainability?’ Finally, taking into consideration Schlittgen et al., PLS-IRRS, instead of PLS-SEM, should be jointly used with fsQCA [
36]. This could be useful to address issue related unobserved heterogeneity that our data may contain. For future research and taking into consideration Schlittgen et al., the iteratively reweighted regressions segmentation method for PLS (PLS-IRRS), instead of PLS-SEM, should be jointly used with fsQCA [
36]. This could be useful to address issue related unobserved heterogeneity that our data may contain.