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We present configurational theorising as a novel approach to developing middle-range theory in two steps: (1) we illustrate configurational theorising as a new form of supply chain inquiry by connecting its philosophical assumptions with a methodological execution, and (2) we generate new insights underpinning a middle-range theory for supply chain resilience.

We synthesise information from a range of sources and invoke ‘critical realism” to suggest a five-phase configurational theorising roadmap to develop middle-range theory. We demonstrate this roadmap to explain supply chain resilience by analysing qualitative data from 22 organisations within the Australian food supply chain.

Coopetition and supply chain collaboration are necessary causal conditions, but they need to combine with either supply chain agility or multi-sourcing strategy to build supply chain resilience. Asymmetrical analyses showed that the simultaneous absence of supply chain collaboration, supply chain agility and multi-sourcing results in low supply chain resilience, but coopetition was indifferent to low supply chain resilience. Similarly, high supply chain resilience is possible with the non-presence of supply chain agility and multi-sourcing.

The configurational middle-range theorising roadmap presented and empirically tested in this paper constitutes a substantial advancement to both theory and the methodological domain.

This is the first attempt at developing a middle-range theory for supply chains by explicitly drawing on configurational theorising.

The notion of configuration – that the whole is best understood from a systemic perspective and should be viewed as a constellation of interconnected elements – is arguably one of the central ideas of organization studies. Yet, this idea also remains one of the field’s least understood aspects. In this volume and its introduction, we outline a new perspective for understanding configuration. Our starting point is the emergence of set theoretic configurational methods, and especially Qualitative Comparative Analysis (QCA), which provides novel ways for analyzing configurations. Our volume goes beyond introducing a new method to the fields of management and organization, as these methods furthermore offer an opportunity to rethink our understanding of the field and to develop different ways of theorizing the rich complexity of relationships that characterize organizational life. In this introduction, we introduce some of the key themes that differentiate the approach taken here from previous work on organizational configurations and provide evidence for the emerging renaissance of the configurational approach in organizational theory and research.

The purpose of this paper is to critically reflect and offer insights on how to justify the use of qualitative comparative analysis (QCA) as a research method for understanding the complexity of organizational phenomena, by applying the principles of the neo-configurational approach.

We present and critically examine three arguments regarding the use of QCA for management research. First, they discuss the need to assume configurational theories to build and empirically test a causal model of interest. Second, we explain how the three principles of causal complexity are assumed during the process of conducting QCA-based studies. Third, we elaborate on the importance of case knowledge when selecting the data for the analysis and when interpreting the results.

We argue that it is important to reflect on these arguments to have an appropriate research design. In the true spirit of the configurational approach, we contend that the three arguments presented are necessary; however, each argument is insufficient to warrant a QCA research design.

This paper contributes to management research by offering key arguments on how to justify the use of QCA-based studies in future research endeavors.

On many occasions, organizational science research has been referred to as fragmented and disjointed, resulting in a literature that is, in the opinion of many, difficult to navigate and comprehend. One potential explanation is that scholars have failed to comprehend that organizations are complex and intricate systems. In order to move us past this morass, we recommend that researchers extend beyond traditional rational, mechanistic, and variable-centered approaches to research and integrate a more advantageous pattern-oriented approach within their research program. Pattern-oriented methods approximate real-life phenomena by adopting a holistic, integrative approach to research wherein individual- and organizational-systems are viewed as non-decomposable organized wholes. We argue that the pattern-oriented approach has the potential to overcome a number of breakdowns faced by alternate approaches, while offering a novel and more representative lens from which to view organizational- and HRM-related issues. The proposed incorporation of the pattern-oriented approach is framed within a review and evaluation of current approaches to organizational research and is supplemented with a discussion of methodological and theoretical implications as well as potential applications of the pattern-oriented approach.

In this concluding chapter, we look ahead to future theoretical and methodological directions that emerge from the contributions in this volume and that carry the potential to enrich contemporary organizational research. We furthermore point to some issues that remain unsolved and need to be addressed in future research to further establish the configurational approach in the field of organizational studies, such as the growing need for homogeneity in how the analysis is conducted and results are presented. We argue that the momentum of the configurational approach in organizational research is strong, but that important challenges remain.

Previous research reports mixed results regarding the performance impact of servitization in manufacturing firms. To resolve this, the purpose of this paper is to develop a conceptually consistent and comprehensive measurement framework for both dimensions, servitization and its performance effect, and apply in a configurational analysis to reexamine previous evidence, arriving at a configurational theory of the relationship between servitization and firm performance.

Combining systematic literature review (SLR) and inductive reasoning, the existing indicators for servitization and performance are identified and clustered into groups that adequately represent both dimensions. The dataset is reanalyzed against the resulting framework to identify the configurational patterns and to formulate the theoretical propositions.

Financial and nonfinancial indicators of servitization and its performance impact are organized into a comprehensive measurement framework grounded on existing research. The subsequent meta-analysis shows that the positive or negative impacts of servitization on performance depend on how firms implement servitization strategies and which performance aspects are examined.

The results explain when servitization can be successful and confirm the existence of the so-called servitization paradox. The meta-analysis identified patterns that explain the previous mixed results, shaping a configurational theory of servitization. Thus, the measurement framework is conceptually robust and has sufficient detail to capture servitization and its performance outcome as it feasibly distinguished between different organizational configurations.

The framework provides a comprehensive portfolio of indicators for both managers and scholars to measure servitization intensity and performance. This supports managers of servitizing firms in leading this organizational transformation while avoiding its organizational and financial paradoxes.

As purveyors of knowledge-based and high value-added services to the manufacturing sector, industrial service small- and medium-sized enterprises (SMEs) must develop the information technology (IT) capabilities that, in combination with other non-IT capabilities, enable their capacity for organizational learning (OL) and for explorative learning in particular. In this context, this study aims to identify the different causal configurations that account for the nonlinear complex interplay of IT capabilities for exploration and strategic capabilities for explorative learning as they affect these firms’ competitive performance.

Survey data obtained from 92 industrial service SMEs were analyzed with a configurational approach, using fuzzy set qualitative comparative analysis (fsQCA).

As it allows for equifinality, the fsQCA analysis identified two sets of causal configurations that characterize the sampled firms’ explorative learning capability as it relates to competitive performance. In the first set, two configurations were equally associated with high innovation performance, whereas in the second set, four configurations were equally associated with high productivity.

By viewing explorative learning as a dynamic capability that is enabled by the firm’s IT and strategic capabilities, the study contributes to OL theory by providing a more concrete or “operational” grounding, which allows for a greater practical applicability of this theory. By taking both the configurational and capability-based views of the OL-IT-performance causal framework, the authors provide an empirical basis for unraveling, explaining and understanding the complex non-linear relationships embedded within this framework.

Innovation ambidexterity is crucial for fostering growth and gaining a competitive advantage in small and medium enterprises (SMEs). Previous research indicates that achieving a balance between exploration and exploitation is a multifaceted phenomenon occurring across various levels. This paper aims to examine the influence of individual, organizational and institutional factors on the ambidextrous innovation of Chinese niche leaders using a configurational perspective.

This study uses secondary data collected from 69 Chinese niche leaders in the new equipment manufacturing industry. The authors use fuzzy-set qualitative comparative analysis to investigate how owner openness, age, digitization, the formal institutional environment and the informal institutional environment jointly influence innovation ambidexterity.

By using fuzzy set analysis, this study categorizes combinations of interdependent factors that promote innovation ambidexterity. In particular, the authors pinpoint three configurations that foster high innovation ambidexterity and two configurations that lack such high levels of innovation ambidexterity. The analysis results suggest that innovation paradoxes in SMEs are linked to a nested system comprising leadership, organizational factors and the institutional environment.

This study elucidates the mechanism of innovation ambidexterity through a configurational perspective. This research proposes and validates a framework that enables SMEs to develop ambidextrous innovation capabilities, thereby integrating organizational ambidexterity theory and shedding light on the intricately complex nature of innovation ambidexterity.

This chapter explores the integrative effects of individual psychology and social context in explaining why managers would behave in socially responsible ways. To identify how factors at different levels of analysis combine to shape attitudes toward social responsibility, I apply fuzzy-set qualitative comparative analysis (fsQCA) to survey and archival data from 335 managers of overseas subsidiaries of three Dutch corporations. Attention to the simultaneous effects of individual psychological factors, the organizational context, and the broader social context offers a configurational perspective on the micro and macrofoundations of social responsibility.

Although QCA was originally developed specifically for small-N settings, recent studies have shown its potential for large-N organization studies. In this chapter, we provide guidance to prospective researchers with the goal of opening up QCA’s potential for widespread use in organization studies involving large-N settings, both as an alternative and as a complement to conventional regression analyses. We compare small-N and large-N QCA with respect to theoretical assumptions and objectives, processes and decisions involved in building the causal model, selecting the sample, as well as analyzing the data and interpreting the results. Finally, we discuss the prospects for large-N configurational analysis in organization studies and related fields going forward.