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The study investigates how supply base structural complexity influences both supply chain agility and resilience. It employs Normal Accident Theory and Portfolio Theory to disentangle the effects of three structural facets of complexity – numerousness; technical and functional diversity; geographical distribution of suppliers – on the two capabilities simultaneously.

The study is grounded in the Italian footwear industry. 31 manufacturing firms with their global supply base have provided a cross-sectional time series database over a 10-year period (310 observations).

The results show that supply base numerousness has nonlinear effects on both supply chain agility and resilience. The directions of these effects are opposites. They also show that supply base diversity has an inverted U-shaped effect on supply chain agility while it is insignificant for resilience. Finally, the results show that suppliers' geographical dispersion is detrimental to both capabilities.

This is the first study that considers the multifaceted effects of supply base complexity on both supply chain agility and resilience. In doing so, it also sheds light on some of the most common trade-offs that firms address when they seek a balance between different strategies, such as increasing agility without damaging supply base resilience and vice versa. Considering the resource constraints firms normally face, by disentangling the dual effects of each complexity facet, this study helps decision-makers to develop scalability and leverage the supply base characteristics in order to survive and prosper in uncertain markets.

This paper aims to empirically examine the moderating role of strategic purchasing on the relationship between supply base complexity (SBC) and purchasing performance.

Survey data were collected from 209 firms listed in the Capital Top 500 Firms of Turkey. Measurement properties were assessed via confirmatory factor analysis, and the conceptual model was tested via hierarchical regression analysis. A supplementary analysis based on 14 semi-structured interviews was conducted to provide further insights on the survey findings.

Regarding structural SBC, the results suggest that horizontal complexity and supplier interaction improve purchasing performance, but only in firms with high strategic purchasing. By contrast, spatial complexity reduces purchasing performance in firms with high strategic purchasing, while supplier differentiation does not have any effect. Regarding dynamic SBC, the results show that both delivery complexity and supplier instability reduce purchasing performance when firms have low strategic purchasing. Interviews further suggest that firms with high strategic purchasing leverage the positive effects and mitigate the negative effects of SBC by having a long-term focus, considering multiple performance criteria and adopting advanced purchasing practices.

In contrast to what is widely posited in the existing literature, the nuanced findings of this study reveal that complexity is not always detrimental. The results suggest that practitioners should aim for high levels of strategic purchasing to suppress the negative effects of SBC while leveraging its benefits.

By investigating the contingency role of strategic purchasing, this study provides novel insights into the under-investigated issue of how to best “manage” SBC.

The purpose of this paper is to discuss complexity assessment in supply chains, to describe a methodology for measuring supply chain complexity in distributive trade and to illustrate the measurement of supply chain complexity and mechanisms to cope with supply chain complexity in distributive trade.

The paper discusses literature on measuring supply chain complexity and uses five case studies among wholesale companies to illustrate a methodology to measure supply chain complexity and to discuss strategies to cope with supply chain complexity.

The study confirms the multifaceted nature of supply chain complexity. The paper identifies eight drivers of supply chain complexity and uses these to illustrate the measurement of supply chain complexity in a wholesale environment. The paper identifies six strategies used by wholesalers for coping with supply chain complexity and identifies interrelations between supply chain complexity drivers and these strategies.

The research is based on case studies in wholesale companies; future research may include survey research, including other sectors to analyze industry differences but may also focus on other parts of the supply chain.

The study provides insights into how to identify and measure complexity in a supply chain and what can be done to manage supply chain complexity.

The measurement approach is new to supply chain management and is based on multiple drivers of supply chain complexity. The research is focused on wholesalers, which is a segment that has received limited academic attention in supply chain research to date.

The purpose of this paper is to understand and measure empirically the objective and perceived dimensions of supplier-induced complexity in supply chains.

An equal-weight, complementary mixed-method approach is used to investigate supplier-induced complexity and understand its impact on outcomes. Initial qualitative research and extant literature review allowed the identification of supplier characteristics that add complexity to supply chains and development of four research hypotheses. Subsequently, quantitative analysis was used for testing the hypotheses.

The results suggest that supplier-induced complexity is related to adverse outcomes, and both perceived and objective dimensions of complexity are valuable in understanding and measuring supplier-induced complexity.

This study employs a mixed-method approach to establish and test relationships among perceived and objective supplier-induced complexity, and their outcomes. The unit of analysis is the first-tier suppliers of one farm equipment manufacturing firm. This limits the generalizability of the results to similar industrial manufacturing firms.

This paper presents an approach to identify suppliers that add the highest levels of complexity to a supply chain and, thus, require closer monitoring. Specific supplier characteristics are identified for individual suppliers. Developing specific complexity-related measures helps better identify critical suppliers compared to traditional approaches (e.g. ABC analysis).

This paper contributes to supply chain management literature by comprehensively exploring supplier-induced complexity, incorporating the often-ignored perceived complexity dimension, and providing a managerially useful framework.

In today's globalized business environment, growing supply chain complexity (SCC) is arguably a major threat to the firm's business continuity with an adverse impact on the firm's competitive advantage and business performance. Researchers, though, investigated the impact of SCC drivers on a firm's operational performance, but the key question “Which supply chain complexity drivers severely impact the supply chain performance (SCP)?” remains largely unanswered from empirical research. The present study aims to decompose the SCC into four major constituting sub-categories (upstream, operational, downstream and external) to explore the causal impact of SCC drivers on SCP in direct and mediated manner.

The indicators applied for measuring constructs in the “Measurement model” are obtained from existing literature to increase the validity and reliability of the model. First, a pilot survey involving 25 SC managers from various manufacturing firms was conducted for indicator refinement and content validation. Second, the large-scale response data were collected through extensive surveys. This research explores the causality by testing the hypothesis applying Structural Equation Modeling (SEM) based on the responses received from 246 firms.

The study investigates the impact of SCC drivers on SCP through direct and mediation effect. The results indicate that upstream and operational SCC drivers play a mediating role in managing SCP. The findings reveal that upstream and operational SCC drivers adversely impact the SCP. Furthermore, the impact of downstream complexity on SCP is moderated through operational complexity drivers. The result explains the theoretical relation among SCC drivers supported by empirical validity.

The outcome offers practical relevance to supply chain (SC) managers in SCC and SCP management. Knowing the effect of SCC drivers among themselves and on SCP will facilitate the SC managers in devising the right strategies. The study provides a framework for prioritizing the resource in addressing the SCC issues among many.

The study addresses the apparent gap in the literature by modeling the impact of SCC drivers on SCP, which remained largely unexplored. First, it contributes to developing complex relationships among SCC drivers. Second, the direct and mediated causal effect of the SCC drivers individually and combinedly on SCP are explicated.

A low-carbon economy is the pressing need of the hour. Despite several efforts taken by the government and large corporations, there is still research to be conducted exploring the role of top management commitment in translating external pressures into responses that help to build low-carbon emissions in supply chains.

The authors have grounded their framework in institutional theory, agency theory and contingency theory. On the basis of existing literature, four hypotheses were drawn. To test these hypotheses, a questionnaire was developed and pre-tested. Finally, statistical analyses were performed to test the research hypotheses using 176 samples gathered using a pre-tested questionnaire following Dillman’s (2007) total design test method.

The results suggest that coercive pressures and mimetic pressures under the mediating effect of top management commitment have a significant influence on organizational response to low-carbon emissions. The authors further note that supply base complexity has moderating effects on the link between top management commitment and organizational response towards low-carbon emissions.

This study offers valuable insights to those managers and environmental consultants who view supply base complexity as a limitation. However, the results indicate that supply base complexity may help to enhance the effectiveness of the top management commitment on organizational response towards low-carbon emissions.

The purpose of this paper is to examine the nuanced effects of downstream complexity on supply chain resilience, based on portfolio theory and normal accident theory. Intelligent manufacturing is considered to clarify their boundary conditions.

The ordinary least squares regression was conducted, based on the data collected from 136 high-tech firms in China.

Horizontal downstream complexity has a positive effect on supply chain resilience significantly, while the negative impact of vertical downstream complexity on supply chain resilience is not significant. Contingently, intelligent manufacturing plays a negative moderating role in the relationship between horizontal downstream complexity and supply chain resilience, while it positively moderates the relationship between vertical downstream complexity and supply chain resilience.

This study disentangles the nuanced effects of both horizontal and vertical downstream complexity on supply chain resilience, based on portfolio theory and normal accident theory. It also clarifies their boundary conditions by considering the focal firm's intelligent manufacturing level as the contingent factor.

The purpose of this paper is to examine and discuss the responses and strategies firms use in relation to their supply base when dealing with current trends in the business landscape, and the different options that they have.

The paper draws on case study research of a company within the international health care sector to illustrate the relationship between trends, supply base characteristics and supply base strategies.

The paper presents a framework for a systematic approach that companies can use to develop supply base strategies. The framework illustrates that developing supply base strategies is a dynamic process that not only involves individual actions by the buying company, but also requires close interaction with suppliers.

Previous literature has not specified how different trends affect a company’s supply base in terms of increased complexity and (inter)dependence, and which supply base strategies companies use and the options that they have. The research presented here contributes to fill this void.

The purpose of this research is to systematically review the properties of supply chains demonstrating that they are complex systems, and that the management of supply chains is best achieved by steering rather than controlling these systems toward desired outcomes.

The research study was designed as both exploratory and explanatory. Data were collected from secondary sources using a comprehensive literature review process. In parallel with data collection, data were analyzed and synthesized.

The main finding is the introduction of an inductive framework for steering supply chains from a complex systems perspective by explaining why supply chains have properties of complex systems and how to deal with their complexity while steering them toward desired outcomes. Complexity properties are summarized in four inter-dependent categories: Structural, Dynamic, Behavioral and Decision making, which together enable the assessment of supply chains as complex systems. Furthermore, five mechanisms emerged for dealing with the complexity of supply chains: classification, modeling, measurement, relational analysis and handling.

Recognizing that supply chains are complex systems allows for a better grasp of the effect of positive feedback on change and transformation, and also interactions leading to dynamic equilibria, nonlinearity and the role of inter-organizational learning, as well as emerging capabilities, and existing trade-offs and paradoxical tensions in decision-making. It recognizes changing dynamics and the co-evolution of supply chain phenomena in different scales and contexts.

The purpose of this paper is to conduct a large-sample empirical examination of how intangible supply chain complexity impacts firm performance in light of a firm's organizational structure.

The study uses panel data from 2,580 Indian manufacturing firms and constructs empirical proxy for intangible supply chain complexity, i.e. CHQ distance from major cities. The proposed conceptual model is grounded in the dynamic capability view (DCV) and social network theory (SNT). Multivariate regression analyses are performed to investigate the effect of intangible complexity on firm performance.

Results show that intangible supply chain complexity, as proxied by “CHQ distance from major cities”, negatively affects firm performance and a firm's organizational structure plays an important role in conceiving CHQ locational strategies. Firms with interconnected supply chain and social network (e.g. business group firms) have a higher propensity to locate their CHQs farther away from major cities, and business group firms that have more distantly located CHQs experience better financial performance compared to independent firms (with less network resources).

In light of the supply chain literature and relevant theories, the study conceptualizes intangible supply chain complexity as “CHQ distance from major cities” and deepens our understanding of the relationship between intangible complexity and firm performance in light of organizational structure. Further, it develops an objective understanding of intangible supply chain complexity by relying on secondary panel data.