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In a dynamic environment such as the supply chain, even basic supplier‐customer systems with structurally simple information and material flow formations have a tendency to exhibit operational complexity. The operational complexity of supplier‐customer systems is primarily characterised by the uncertainty of the system. As the operational complexity of a system increases there is an associated increase in the amount of information required to monitor and manage that system. Based on this understanding, a novel information‐theoretic entropy‐based methodology for measuring and analysing the operational complexity of supplier‐customer systems has been developed. This paper makes contributions in the theoretical, conceptual and practical developments of the methodology. The methodology can quantitatively detect and prioritise operational complexity hotspots. At the interface, the framework can identify and quantify the transfer of operational complexity. Within the internal manufacturing system, the framework provides a comparative operational complexity measure across sub‐systems such as flows and products. This entropy‐based methodology provides a tool for identifying and measuring four classes of operational complexity transfer corresponding to the extent to which organisations generate, absorb, export and import operational complexity.

Based on the reception of the principle of self-organization, the core of Heinz von Foerster's operational theories, I hypothesize how Heinz von Foerster's theory can be an orientation model for the epistemological problem of complexity. I have chosen this study to demonstrate complexity as an epistemological problem. This is because the question of how order arises - the core problem of complexity - is an epistemological question for which Heinz von Foerster developed an epistemology of self-organization. I do not present new research because HvF already had the complex organization of systems in mind. Rather, I build a critical approach to complexity on the research and work on operational epistemology in HvF.

This article aims to provide an orientation for a philosophical and epistemological understanding of complexity through a reading of Heinz von Foerster's operational theory. The article attempts to establish complexity as an epistemological phenomenon through the following method: (1) a conceptual description of the science of complexity based on the turn to thermodynamic time, (2) a genealogy of complexity going back to the systemic method, and (3) Heinz von Foerster's cybernetic approach to self-organization.

Based on the reception of the principle of self-organization, the core of Heinz von Foerster's operational theories, the conclusion is drawn that complexity as a description is based on language games.

The results present complexity not as an object of science, but as a description that stands for the understanding of complex description.

The hypothesis that complexity is a question of description or observation, i.e. of description for what language serves, has enormous social implications, in that the description of complexes and the recognition of their orders (patterns) cannot be left to algorithmic governmentality, but must be carried out by a social agency.

HvF's operational epistemology can serve as an epistemological model for critical complexity theory.

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.

The purpose of this research is to enhance understanding of the sources of relational rents in supply chains and the nature of their relationships with performance. Using the relational view framework and contingency perspective, the study develops a model and hypotheses to understand the nature of the relationships of collaboration and resource specificity with operational performance under technology context contingencies.

Data for testing the hypothesized relationships in the conceptual model were collected through a survey of managers in the Hoover’s database of manufacturing firms. The survey sample included 115 responses from a wide variety of manufacturing forms.

Findings support the conventional wisdom relating collaboration and operational improvements. Notably, technological turbulence has a differential interactive influence on collaboration and resource specificity in predicting operational performance. In the former, the strength of the performance relationship is enhanced, while in the latter, it diminishes. Product complexity enhances the collaboration–operational performance linkage. The results, however, have to be further corroborated by more confirmatory analysis in future research.

The research findings are not conclusive but of an exploratory initial evidence, as stepwise regression analysis has its limitations. Additionally, while the study specifically focused on demand-side collaboration aspects, supply chain management envelops upstream and internal collaboration as well. Investigating the performance implications and the interactive dynamics among all three partnerships in the supply chains provides a richer understanding of supply chain partnerships. Besides, more comprehensive insights could be obtained by modeling the interactive effects of other factors in the operating context.

Firms derive performance benefits from close collaboration with downstream partners because the operational enhancements from such relationships have customer service implications. Besides, the results provide a framework to managers for understanding the technology context conditions that may be best suited for leveraging collaborative initiatives and idiosyncratic investments in pursuit of operational performance improvements.

Much of the evidence on the rent generation capabilities in supply chain partnerships is still anecdotal and extant empirical research lacks adequate explanation. Another critical shortcoming in extant literature is research on the disentangled interactive influence of operating context factors on the supply chain sources of rent (i.e. capabilities)–performance relationships. The study contributes by addressing these issues.

This study aims to investigate the influence of supply chain (SC) complexity on the effectiveness of resilience capabilities in mitigating SC disruptions. Hypotheses about direct and moderating influences of complexity on resilience capabilities and performance change after disruption are built and quantitatively tested.

Partial least square-based structural equation modelling with formative constructs was used as an overall approach. Secondary data on SC disruptions, related performance change and resilience practices were collected from multiple sources through a predefined procedure. The collected data were systematically encoded prior to performing statistical analysis.

SC structural complexity is found to have a significant positive relation with performance improvement after disruption, along with resilience capability; it also positively moderates the resilience–performance link.

The SC complexity factors the authors considered in this study do not include dynamic forms because of the nature of data collected. Future research may attempt to include and test whether the results of this study also hold when additional complexity parameters are taken into account.

Managers are often trying to reduce SC complexity. This study implies that some level of complexity is beneficial also for a better recovery of operational performance affected because of disruption. Resilience capabilities become more effective when leveraged on complexity in the SC.

This is the first study to empirically investigate the influence of SC complexity on the resilience–performance link.

Social systems are produced by people’s interactions. They are by and large the outcome of self‐organising processes, which often produce undesirable properties like corruption, violence and other forms of social malaise. Yet, we want transparent, fair and effective social systems. Explores some of the issues involved in the production of desirable social systems. It is argued that this production requires more than self‐organisation, it requires also the participants’ awareness of the processes grounding their purposes and values in social reality and the use of this awareness to steer their recurrent interactions towards the production of a desirable social system. This is called a process of self‐construction. Understanding this process requires clarifying the role of organisation in the transformation of collectives into social systems. In the end, more than clarification, this paper offers a research agenda.

Complexity has been called the 21st-century supply chain (SC) challenge. Most SC managers view it as a necessary evil, ever-present, costly and tough to manage, and few prioritize it. Still, anecdotes suggest some leverage it to drive operational excellence. This study aims to explore how they do it, delving into the development of a complexity management capability, under what circumstances it emerges and its effect on competitiveness.

To better understand why, and how, companies develop (or not) a distinctive SC complexity management capability, this study employed an inductive study of 10 leading European companies, each operating a complex SC.

Although SC complexity raises costs, increases disruptions and makes decision-making difficult, few companies have made complexity management a priority. Among those, most focus on reducing or absorbing complexity to improve operational excellence. A few invest to develop a distinctive SC complexity management capability. They manage complexity for market success. The interaction among competitive pressures, managerial attitudes and investments delineate a dynamic capability development process.

Despite extensive research on complexity drivers, the tools used to manage SC complexity and the impact of SC complexity on performance, the interplay among factors that promote, or hinder, the development of an SC complexity capability continues to be poorly understood. By mapping the complexity capability development process, this study explicates a more nuanced approach to managing SC complexity that can yield a competitive edge.

SC complexity prevails because the dynamic, iterative complexity capability development process is overlooked. Managers can use the complexity capability roadmap to assess the cost/benefits of pursuing a distinctive complexity management capability more accurately.

This study demystifies the development of a complexity management capability, showing how some companies develop the capability to distinguish between value-added and value-dissipating complexity and thus become empowered to leverage SC complexity for competitive advantage.

The purpose of this paper is to empirically investigate the impact of complexity on the triple bottom line by applying information-processing theory. Specifically, the paper assesses the impact of internal manufacturing complexity on environmental, social, and financial performance. Furthermore, the paper assesses the moderating role of connectivity and shared schema in reducing the potential negative impact of complexity on performance.

Multi-country survey data collected through the Global Manufacturing Research Group were utilized to test the hypotheses. The authors used structural equation modeling to test the measurement and initial structural model. Furthermore, to test the proposed moderating hypotheses, the authors applied the latent moderated structural equations approach.

The results indicate that while complexity has a negative impact on environmental and social performance, it does not significantly affect financial performance. Furthermore, this negative impact can be reduced, to some extent, through connectivity; however, shared schema does not significantly impact on the complexity-performance relationship.

This study presents a comprehensive analysis of the impact of complexity on sustainability. Furthermore, it provides managerial applications as it proposes specific tools to deal with the potential negative influences of complexity.

The purpose of this paper is to analyze the operations of the quality management systems (QMS) in multinational companies, and develop a framework for classifying the QMS features based on the global operational and marketing structures arising from their expansion process. This paper is based on doctoral research conducted at the Department of Statistics, University of Haifa, Israel in 2007–2015.

This study used the innovative approach of adopting a systems perspective in analyzing the operation of a global QMS. In total 18 multinational companies at different levels of global expansion were studied in depth using observations, longitudinal studies, content analyses and depth interviews.

The result of this study is the global hierarchical model (GHM) that presents a classification of representative global operational and marketing structures deriving from the expansion process of multinational companies, and the extrapolated features of the respective global QMS.

This classification serves as a diagnostic tool for identifying the proper globalization level of a QMS, thereby helping plan global quality strategy and identifying the steps necessary for its effective implementation.

This research seeks to fill a lacuna in the field of global quality system development with regard to modes of competition and challenge. Integration of strategic, operational and marketing rationales into the QMS’s processes augments the functional level of management and supports the development of a strategy for global quality management that is derived from and supports the company’s global strategy.

Organization theorists and strategy researchers have effectively leveraged archival assessments of the environment to better understand organizational actions and performance. Despite the successes, several issues continue to plague research. Vague constitutive definitions and mismatches between constitutive and operational definitions are among the most pressing of these issues. To further develop the archival tradition, we clarified existing definitions and proposed new definitions where warranted. Our work has implications not only for the selection of concepts and measures in future work but also for interpretations of past research.