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This chapter acknowledges the difficulties in the empirical study of social ventures – broadly defined as market-driven ventures that produce social change – that arise from the vast differences among social venture firms in terms of missions, goals, identities, strategies, and structures. In an effort to improve research in this area and advance the field of social entrepreneurship, the authors advocate approaching social ventures from a configurational perspective.

This chapter begins with a discussion of what social ventures are and why organizational configurations – sets of firms that are similar across key characteristics – may be an appropriate perspective to utilize. Then, two methods – cluster analysis and set-theoretic analysis – are discussed in detail as ways to approach the study of social venture configurations. Details include descriptions of the techniques, instructions for use, examples, and limitations for each.

This chapter identifies research opportunities using configurations approaches in social venture research. Substantial possibilities for multilevel and temporally based research are discussed in depth.

A configurational approach can address the incongruence and non-findings in current social venture research and offers new opportunities for future research.

Product configuration is considered as one of the most successful applications of knowledge‐based approaches in the past decade. Knowledge‐based configurations can be classified into three different approaches, namely, rule‐based, model‐based and case‐based approaches. Past research has mainly focused on the development of reasoning techniques for mapping requirements to configurations. Despite the success of certain conventional approaches, the acquisition of configuration knowledge is usually done manually. This paper aims to explore fundamental issues in product configuration system, and propose a novel approach based on data mining techniques to automatically discover configuration knowledge in constraint‐based configurations.

Given a set of product data comprising product requirements specification and configuration information, the paper adopted an association rule mining algorithm to discover useful patterns between requirement specification and product components, as well as the correlation among product components. A configuration was developed which takes XML‐based requirement specification as input and bases on a constraint knowledge base to produce product configuration as output consisting of a list of selected components and the structure and topology of the product. Three modules are developed, namely product data modelling, configuration knowledge generation and product configuration generation module. The proposed approach is implemented in the configuration knowledge generation module. The configuration generation module realizes a resolution of constraint satisfaction problem to generate the output configuration.

The significance and effectiveness of the proposed approach is demonstrated by its incorporation in our configuration system prototype. A case study was conducted and experimental results show that the approach is promising in finding constraints with given sufficient data.

Novel knowledge generation approach is proposed to assist constraint generation for Constraint‐based product configuration system.

This study explores the configurations of management control systems (MCSs) while taking into account entrepreneurial cognition styles (ECSs) in small and medium enterprises (SMEs). The objective is to understand the impact of ECS on deployment and identify the various modes of MCS configurations employed by SMEs. The authors draw on and synthesise two theoretical perspectives relating to cognition and management control packages to understand the associations between ECS and MCS employed by SMEs in managing their business. This study was conducted using a quantitative approach that utilises a questionnaire survey to collect cross-sectional data from 150 SMEs. The authors uncovered three cognitive styles: knowing (e.g. preciseness), planning (e.g. organising), and creativity (e.g. innovativeness). Furthermore, five configurations of MCS utilised by SMEs were identified: customer focus, performance monitoring, administrative focus, strategic focus, and development focus. By combining both analyses, the authors discovered three constellations of significant association between ECS and MCS characterised by Cluster 1’s cohesive integration approach, Cluster 2’s revealing strategic approach, and Cluster 3’s multifaceted exploration. The study is significant because it uncovers the complex relationship between ECS and MCS configurations, highlighting their interdependence within the institutional context. Using a cognitive view, the authors explore how the cognitive styles of entrepreneurs facilitated imprinting institutional context into MCS configurations. These insights enable us to envisage that ECS is not mutually exclusive but forms a continuum that provides more plausible explanations that relax the direct universal relationship between MCS configurations and contextual factors.

The purpose of this paper is to provide a structured overview of the application of the configuration approach in the context of new and small ventures.

The paper surveys the empirical literature in the leading entrepreneurship journals from 1994 to 2006.

There are a small, but significant number of studies that deal with the empirical identification and examination of new venture types. However, researchers are just beginning to tap the potential of the configuration approach. More specifically, configuration analyses are still rather heterogeneous, and no study deals with the identification of development configuration in the context of new ventures yet.

Since the configuration approach has already delivered interesting results in research on new ventures, we might see additional studies based on this approach in the future. However, there are practical and theoretical considerations to be taken into account.

An awareness of the existence of different types of start‐ups can lead to more informed decisions in new venture management.

This literature review identifies and structures empirical configuration research in the context of new and small ventures. Also, awareness for future research opportunities is raised.

This chapter shows how configurational approaches can be a valuable inquiring system for examining and understanding complex messy phenomena in the area of digital business strategy in turbulent environments such as digital ecodynamics. Digital ecodynamics is defined as the holistic confluence among environmental turbulence, dynamic capabilities, and IT systems – and their fused dynamic interactions unfolding as an ecosystem. With fuzzy-set qualitative comparative analysis (fsQCA) we analyze firm-level field survey data and describe how IT systems, organizational dynamic capability and environmental turbulence simultaneously combine to result in multiple configurations, which have different causal structures to produce competitive firm performance. This equifinality shows how configurational approaches can create new practical insights in digital ecodynamics by suggesting multiple strategic options from which organizations can choose the best solution that fits their context.

Although the literature recognizes that coopetition plays a significant role in the success of international construction joint ventures (ICJVs), the impacts of coopetition on the performance outcomes of ICJVs remain largely unknown. This study extends this line of research by theorizing coopetition from three dimensions, i.e. coopetition intensity, coopetition balance and coopetition structure, and examining the relationships between coopetition and ICJV performance outcomes from both the contingency and configuration perspectives.

The hypotheses were tested using survey data from a sample of 188 ICJVs. Structural equation modelling was employed for the contingency approach to estimate the relationships between the three dimensions of coopetition and performance. For the configuration approach, cluster analysis was utilized to identify coopetition patterns. Subsequently, an analysis of variance was employed to analyse the relationships between these coopetition patterns and performance.

The contingency results indicate that while coopetition intensity is positively related to all types of performance, coopetition balance is only positively related to project performance and partner performance. Moreover, coopetition structure is only related to partner performance and socioenvironmental performance. The configuration approach identifies six patterns of coopetition, manifesting different levels of project, partner and socioenvironmental performance.

These findings, therefore, contribute to the ICJV literature by extending the understanding of how coopetition dimensions individually and jointly influence ICJV performance.

The purpose of this paper is to propose a three-staged approach to configuration change management that uses a combination of complexity analysis, data visualization, and algorithmic validation to assist in validating configuration changes.

In order to accomplish the above purpose, the authors conducted a review of existing configuration management practices. This was followed by an in-depth case study of the configuration management practices of a major automotive OEM. The primary means of data collection for the case study were interviews, ethnographic study, and document analysis. Based on the results of the case study, a set of support tools is proposed to assist in the configuration management process.

Through the case study, the authors identified that the OEM used a configuration management method that largely represented the rule-based reasoning methods identified in the literature review. In addition, many of the associated challenges are present, primarily, the difficulty in making changes to the rule system and evaluating the changes.

The primary limitation is that the case study was based on a single OEM. However, the results are in line with other practices identified in the literature review. Therefore, it is expected that the findings and recommendations should hold true in other applications.

A set of configuration management tools and associated requirements are identified and defined that could be used to assist companies in the automotive industry, and perhaps others, in managing their option changes as they continue to move towards full mass customization of products.

The proposed approach for configuration management has not been seen in any other organization. The value of this paper is in the effectiveness of the proposed approach in assisting in the configuration change management process.

Configuration systems are used as a means for efficient design of customer tailored product service systems (PSS). In PSS configuration, mapping customer needs with optimal configuration of PSS components have become much more challenging, because more knowledge with personalization aspects has to be considered. However, the extant techniques are hard to be applied to acquire personalized configuration rules. The purpose of this paper is to extract the configuration rule knowledge in symbolism formulation from historical data.

Customer characteristics (CCs) are defined and introduced into the construction of configuration rules. Personalized PSS configuration rules (PCRs) are thereby proposed to collect and represent more knowledge. An approach combining Local Cluster Neural Network and Rulex algorithm is proposed to extract rule knowledge from historical data.

The personalized configuration rules with CCs are able to alleviate the burden of customers in expressing functional requirements. Furthermore, in the long-term relationship with a customer in PSS realization, PSS offerings can be reconfigured according to the changing CCs with the guide of PCRs.

The contribution of this paper lies in introducing the attribute of CCs into the antecedents of PCRs and proposing the neural networks-based approach to extracting the rule knowledge from historical data.

This paper aims to explore the use of digital technologies in enabling circular ecosystems. We apply supply network (SN) configuration theory and a novel resource pooling lens, more typically used in financial systems, to identify inventory pools, information repositories and financial exchange models among network actors.

Five in-depth circular SN case studies are examined where digital technologies are extensively deployed to support circularity, each case representing alternative SN configurations. Data collection involved semi-structured interviews to map SN and resource pooling configurations across each circular ecosystem, with cross-case analysis used to identify distinct pooling and digital strategies.

Results suggest three digitally enabled circular ecosystem archetypes and their related governance modalities: consortia-based information pooling for resource recovery, intermediary-enabled material and financial pooling for remanufacturing and platform-driven information, material and financial pooling for resource optimisation.

Drawing on SN configuration and resource pooling literature, we recognise distinct configurational, stakeholder and resource pooling dimensions characterising circular ecosystems. While this research is exploratory and the identified archetypes not exhaustive, the combination of resource pooling and configuration lenses offers new insights on circular ecosystem configurations and the critical role of resource pools and enabling digital technologies.

We demonstrate the utility of the resource pooling and configuration approach in the design of digitally enabled circular ecosystems. These archetypes provide practitioners and policymakers with alternative design frameworks when considering circular SN transformations.

This paper introduces a resource netting and pooling configuration lens to circular ecosystems, analogous to financial systems, where cyclical flows and stock are critical and enabled through digital technologies.

The purpose of this paper is to explore the impact of configuration on supply network capability. It was believed that a configuration perspective might provide new insights on the capability and performance of supply networks, a gap in the literature, and provide a basis for the development of tools to aid their analysis and design.

The methodology involved the development of a configuration definition and mapping approach extending established strategic and firm level constructs to the network operational level. The resulting tools were tested and refined in a series of case studies across a range of sectors and value chain models. Supply network capability assessments, from the perspective of the focal firm, were then compared with their configuration profiles.

The configuration mapping tools were found to give new insights into the structure of supply networks and allow comparisons to be made across sectors and business models through the use of consistent and quantitative methods and common presentation. They provide the foundations for linking configuration to capability and performance, and contribute to supply network design and development by highlighting the intrinsic capabilities associated with different configurations.

Although multiple case networks have been investigated, the configuration exemplars remain suggestive models. The research suggests that a re‐evaluation of operational process excellence models is needed, where the link between process maturity and performance may require a configuration context.

Advantages of particular configurations have been identified with implications for supply network development and industrial policy.

The paper seeks to develop established strategic management configuration concepts to the analysis and design of supply networks by providing a robust operational definition of supply network configuration and novel tools for their mapping and assessment.