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A supplier may sell not only to one buyer (sole relationship configuration) but also to the buyers competitors (shared relationship configuration) for a specific product category. This study examines the performance implications when suppliers establish shared relationships with the buyer’s competitors.

Secondary data are used to test hypotheses relating a supplier’s relationship configurations to its operational performance. A seemingly unrelated regression approach (SUR) is applied to analyze the data, followed by endogeneity checks of the empirical findings.

The study shows that suppliers with less-shared ties with buying firms’ competitors exhibit superior inventory efficiency and asset turnover. Thus, suppliers can improve operational efficiency by creating relatively exclusive, deep and trust-based relations instead of more extensively shared and shallower relationships.

Based on agency theory as a theoretical lens and aerospace industry data, this research contributes by addressing the supplier’s perspective and linking its operational efficiency performance with its chosen supply relationship configuration.

Suppliers need to understand the performance implications of choosing relatively exclusive relationships versus shared relationships with buying firms. The research provides new insights for managers and can guide their supply chain decision-making.

Little is known about how a supplier’s relationship configurations can elevate, or impair, its operational efficiency. While conventional wisdom holds that suppliers should focus on multiple avenues of revenue growth by selling to buyers’ competitors, this study demonstrates that more sales to a buying firm’s rivals might, in fact, reduce a supplier’s efficiency.

This paper investigates how the configuration of a supplier’s sustainable operations practices (SOPs) with a high sustainable performance affects a buyer’s organizational performance in the buyer-supplier dyad.

This study first identifies the key SOPs using bibliometric and content analyses. Then, the research hypotheses are proposed using complexity theory and the resource-based view. This study applies fuzzy-set qualitative comparative analysis (fsQCA) on a sample of 74 buyer-supplier dyads in China to explore the configurations of a supplier’s SOPs that may attain a high sustainable performance. An analysis of variance (ANOVA) is performed to test the effects of these configurations on a buyer’s financial and operational performance.

The empirical findings inform that six configurations of a supplier’s key SOPs lead to a high sustainable performance, and are linked to a buyer’s operational and financial performance. A buyer’s financial performance is highest when its supplier adopts a combination of SOPs corresponding to the defensive, accommodative, and proactive sustainability strategies. A buyer’s operational performance is relatively high when its supplier adopts a combination of SOPs corresponding to the defensive and accommodative sustainability strategies.

This study is the first to draw on complexity theory and the resource-based view as complementary frameworks to analyze how the configuration of a supplier’s SOPs with a high sustainable performance affects a buyer’s organizational performance in the buyer-supplier dyad.

The main objective of this paper is to study the optimal system for series systems with mixed standby (including cold standby, warm standby and hot standby) components.

The paper deals with the reliability and availability characteristics of four different series system configurations. The failure time of the operative, hot standby and warm standby are assumed to be exponentially distributed with parameters λ, λ, and α respectively. The repair time distribution of each server is also exponentially distributed with parameter μ.

The mean time to failure, MTTF_i, and the steady‐state availability A_i(∞) for four configurations are examined and comparisons made. For all four configurations, the configurations are ranked based on: MTTF_i, A_i(∞), and C_i/B_i where B_i is either MTTF_i or A_i(∞). Obviously, the system with height MTTF_i and A_i(∞), do not need frequent maintenance, i.e. less maintenance.

Numerical results for the cost/benefit measure have been obtained for all configurations. It is interesting to note first that the optimal configuration using the cost/MTTF_i measure is configuration 4. Next the optimal configuration using the cost/A_i(∞) measure is configuration 2.

The purpose of this paper is to research the impact of hybrid series‐parallel and parallel‐series system configurations on system performances based on system reliability and to develop a configuration model to meet the requirement of reconfigurable manufacturing system (RMS).

Based on the criterion of system reliability, a RMS configuration model is presented – the hybrid parallel‐series model with waiting system characteristics. The configuration model is evaluated from reliability, productivity, and cost by combining system engineering theory, Boolean algebra methodology with statistical analysis theory. The model reliability has been used to ameliorate by adopting the integrated algorithm based on Shrama and Misra optimization algorithm.

The need for application of this method and model – some constraints must be limited, the hybrid parallel‐series configuration is superior and the integrated algorithm is effective to RMS system configuration.

Cost constraints, equipment weight constraints, and function independency of equipment are main limitations.

The model and method have been used to ameliorate the reconfigurable automobile parts product line in SH automobile motor company of Shanghai. The operation result illustrates the validity of this configuration model and algorithm.

The new RMSs configuration model has been proposed. The new algorithm is proposed to ameliorate and optimize a reconfigurable product line with the integrated algorithm based on Shrama and Misra algorithm. The actual running effect is significant.

This paper contains a generalization of the existing theory of Garden of Eden configurations in tessellation automata. We consider spaces of at most two dimensions but with transition functions having arbitrarily large neighborhoods. A configuration c is said to be Garden of Eden of degree n just in case there is no configuration from which c can arise in n time steps; c is Garden of Eden of minimal degree n just in case there is no smaller m such that c is Garden of Eden of degree m. Necessary and sufficient conditions for the existence of Garden of Eden configurations of higher degree (and of degree 1) are established. Results are obtained relating decision procedures for Garden of Eden configurations of degree one to decision procedures for Garden of Eden configurations of higher degree.

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.

The purpose of this paper is to examine the cost/benefit (C/B) analysis of four configurations for a repairable system with two primary components/units and one standby.

The four configurations are set to the status of the detection and switching failure of standby, as well as the possible reboot of failed units. The time to failure for each of the primary and standby is assumed to follow an exponential distribution. The time to repair and the time to reboot is assumed to have a k‐stage Erlang distribution. The paper develops the explicit expressions of the mean time to failure (or MTTF) and the steady‐state availability (or A) for four various configurations and performed some comparative analysis. Based on the C/B criterion, comparisons are made for specific values of distribution parameters and of the costs of the units. The four various configurations for a repairable system are ranked by using MTTF, A and C/B, where B is either MTTF or A.

Although it is uncertain which configuration is the optimal one among the four ones, the paper provides much comparative information to manager and manufacturers. Managers can use these results to choose the best configuration according to the used data of parameters and selections of the weight of MTTF or Cost/MTTF.

This paper shows a comparative analysis for a two‐unit online repairable system with one standby under four different configurations. It is the first discussion of comparable work on reliability and availability models for redundant repairable systems in which the units are characterized by detection, switching failure and reboot.

The paper aims to explore the value generated by a specific configuration of a smart city's infrastructure by proposing a comparison between a silos configuration versus a crowd configuration at the data storage and processing level.

A system dynamics simulation is adopted to determine and compare the value created by the two configurations of smart city's infrastructure. The simulation outlines the flow of data and their positive and negative feedback that reinforce and hinder the smart city value generation.

The results demonstrate the huge impact of the availability of data for App developers when crowdsourcing configuration is adopted. Furthermore, results unveil the potential in value generation of a crowdsourcing smart city platform configuration compared to a silos architecture.

The authors have proposed a comparison between two alternative smart city digital platform configurations. The paper seeks to test the magnitude of the pros and cons of a crowdsourcing approach in setting up a smart city digital platform. The paper provides new guidelines for improving the data management of smart cities.

This study applies asymmetric rather than conventional symmetric analysis to advance theory in occupational psychology. The study applies systematic case-based analyses to model complex relations among conditions (i.e., configurations of high and low scores for variables) in terms of set memberships of managers. The study uses Boolean algebra to identify configurations (i.e., recipes) reflecting complex conditions sufficient for the occurrence of outcomes of interest (e.g., high versus low financial job stress, job strain, and job satisfaction). The study applies complexity theory tenets to offer a nuanced perspective concerning the occurrence of contrarian cases – for example, in identifying different cases (e.g., managers) with high membership scores in a variable (e.g., core self-evaluation) who have low job satisfaction scores and when different cases with low membership scores in the same variable have high job satisfaction. In a large-scale empirical study of managers (n = 928) in four (contextual) segments of the farm industry in New Zealand, this study tests the fit and predictive validities of set membership configurations for simple and complex antecedent conditions that indicate high/low core self-evaluations, job stress, and high/low job satisfaction. The findings support the conclusion that complexity theory in combination with configural analysis offers useful insights for explaining nuances in the causes and outcomes to high stress as well as low stress among farm managers. Some findings support and some are contrary to symmetric relationship findings (i.e., highly significant correlations that support main effect hypotheses).

Purpose – This chapter examines the potential of qualitative comparative analysis (QCA) for strategy research.

Methodology/approach – We introduce the set-theoretic framework of QCA and provide an overview of recent methodological developments.

Findings – We utilize a variety of examples relevant to strategy research to illustrate the action steps and key concepts involved in conducting a QCA study.

Originality/value of paper – We develop examples from core research areas in strategic management to illustrate QCA's potential for examining issues of causality and diversity in strategy research, and in settings involving medium-N samples. We conclude by emphasizing that QCA offers an alternative mode of inquiry to open and redirect important lines of strategy research.