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Service organization supply chains provide a context that amplifies the complexity of interorganizational interdependencies and the need to build unique capabilities and innovative solutions, especially when confronted with man-made or natural disasters. Using the lens of complex adaptive systems (CAS), this study aims to investigate the role of absorptive capacity (AC), change management capability and information quality in improving a firm’s ability to cope with disasters – disaster immunity (DI). The study uniquely parses absorptive capacity into a three-variable, second-order construct (absorptive human resource management, absorptive complementary knowledge and absorptive infrastructure).

Using data collected from 264 US service firms in a supply chain context, this paper evaluates the research model using the structural equation modeling approach.

The second-order, three-dimensional framework for AC has far superior psychometric properties as compared to the previous unidimensional conceptualizations. Results show that AC influences a firm’s DI through change management capability and information quality – two DI enhancing resources.

The paper builds on previous conceptual discussions of absorptive capacity as a multidimensional construct by operationalizing AC as a latent variable with three dimensions (above). Moreover, this paper shows that AC, change management capability, information quality and DI are interrelated parts of a CAS.

Drawing on the social identity theory, this paper explores the impact of rider–driver ethnicity match on the driver’s expected ride satisfaction and willingness to perform, and rider’s trust on the driver.

The study relies on scenario-based online experiments with 291 ride-hailing drivers and 282 riders in the USA.

The findings indicate that ethnicity match between ride-hailing drivers and riders positively impact driver’s ride satisfaction and willingness to perform, and rider’s trust in the driver. The study also revealed a significant positive moderation effect of ethnic identity on the relationship of ethnicity match and those constructs.

While it may be challenging to influence an individual’s level of ethnic identity, managers can take steps to educate and train their employees regarding the impact of ethnic identity and discrimination, with a particular focus on those individuals who possess a strong sense of ethnic identity.

The findings of this research provide theoretical contributions to the existing literature on ride-hailing services and adds to the limited stream of logistics research that examines the impact of ethnicity on ride-hailing operations.

In today’s turbulent business environment, firms continually turn to technology as a panacea for supply chain resilience and performance problems. This article seeks to understand if information and communication technology (ICT) platforms, specifically cloud-based platforms, differ in their ability to enable supply chain resilience and operational performance.

Empirical survey data was gathered, and a partial least squares structural equation model was performed on responses from 174 logistics and supply chain operations managers. A multigroup analysis compared the structural model measures of cloud-based and non-cloud-based platforms.

This research provides evidence that supply chain resilience and performance are agnostic of the ICT platform type and deeply rooted in the relational antecedents of cooperation and coordination. Tangentially, this study confirms concepts of coordination and cooperation supported by ICT are antecedents to the robustness and agility of supply chains. Moreover, empirical evidence also reveals that supply chain robustness mediates the relationships between supply chain agility, coordination and cooperation.

While firms continually seek technological solutions to bolster the resilience of their supply chains, we show that they should focus on developing the social elements of supply chain partnerships.

This study’s examination of the influence of ICT on supply chain resilience and performance contributes to the growing body of empirical analysis in the literature. Through its theoretical lens, this article deepens the understanding of analyzing supply chain resilience and performance measures between firms utilizing different ICT platforms.

This study aims to explore the impact of one significant threat to the rigor of theory building within supply chain management, namely, the improper development of different measures for the same construct.

Two survey studies are conducted. Study 1 investigates the impact of three firm orientations on five of the most cited supply chain agility (SCA) scales. Study 2 explores the impact of the same five SCA scales on three firm performance indicators.

The findings reveal that the five SCA scales display adequate discriminant validity and thus measure distinct concepts. Further, the relationships between SCA and its antecedents and consequences vary significantly depending on the SCA scale used. In essence, the scale used determines whether a relationship is supported or not, implying that researchers have been loosely applying the same label (i.e. SCA) to distinct constructs.

In essence, the scale used determines whether a relationship is supported or not, implying that researchers have been loosely applying the same label (i.e. SCA) to distinct constructs. The findings indicate the need for further scrutiny and investigation regarding the rigor and validity of theory building within the area of SCA. Importantly, rigorous scale development should be encouraged. Scholars should develop new scales when necessary while carefully distinguishing their proposed constructs and measures from extant ones.

This study aims to empirically test the effects of key characteristics of performance-based contracting (PBC) (i.e. reward/payment scheme, increased supplier autonomy and transfer of responsibilities) on supplier goal commitment.

This study developed a conceptual model applying goal-setting theory (GST), expectancy theory (ET) and job characteristics theory (JCT). Survey data were collected and analyzed using structural equation modeling (SEM) to establish a validated measurement instrument for testing the hypotheses.

The findings revealed that PBC positively affects supplier goal commitment due to its unique characteristics, which translates into improved supplier performance. Furthermore, this study validated the mediating role of goal alignment and felt accountability operating between PBC characteristics and supplier goal commitment.

This study explored the buyer–supplier relationship from the supplier's standpoint. Using a more inclusive data set, future research may involve a dyadic analysis and focus on the effects of the following factors on the supplier goal commitment: relational aspects (e.g. trust and collaboration), the risk transfer from the buyer to the supplier, different incentive schemes and successful PBC implementation factors.

This study presents new, validated insights for contract selection, design and management. It underlines the importance of choosing the proper contract, having the appropriate contract design based on the desired outcomes and effective contract management by exhibiting the psychological/behavioral effect of fundamental PBC characteristics.

PBC represents an active research stream, but its psychological/behavioral implications are understudied. Therefore, this research puts forth a conceptual framework with multiple testable hypotheses illustrating the relationship between PBC and supplier goal commitment.

The study of supply chain resilience (SCRES) continues to gain interest in the academic and practitioner communities. The purpose of this paper is to present a focused review of the SCRES literature by investigating supply chain (SC) capabilities, their relationship to SCRES outcomes and the underpinning theoretical mechanisms of this relationship.

The paper uses the systematic literature review approach to examine 383 articles published between 2000 and 2017, ultimately down selecting to the most relevant 228 peer-reviewed studies. Context-interventions-mechanisms-outcomes (CIMO) logic is applied to organize and synthesize these peer-reviewed studies. A typological framework is developed from the CIMO-based classification of the SCRES literature.

The findings of this study outline the gaps in the SCRES literature and present an agenda for future research.

This paper presents an exploratory research; therefore, the typological model presented is just one of the possible perspectives.

The typology of SCRES literature can help practitioners to understand SCRES and to measure and assess the resilience of SCs.

The paper provides clear definitions of SCRES constructs, develops a typological framework to further understand SCRES and identifies SCRES measures and assessment techniques.

Research suggests that service-dominant logic (SDL) is well suited to support supply chain management (SCM) research and practice. Qualitative research has shown that SDL is particularly consistent with an outcome-based supply chain strategy known as performance-based logistics (PBL). The purpose of this paper is to extend theory and practice by exploring the degree to which SDL is utilized in practice. Specifically, PBL is examined for consistency with the underlying fundamental premises (FPs) of SDL. In doing so, this paper answers the positive question, “what exists”, at the intersection of SDL and SCM.

This study employs a mixed methodological approach. First, the FPs of SDL are operationalized using the language of PBL. The PBL FPs are tested quantitatively through an online survey of 52 supply chain PBL experts. A qualitative analysis is conducted using comments associated with each premise.

The survey results suggest that PBL is consistent with SDL. These results indicate that PBL is a supply chain context of SDL.

This is one of the first works to examine the degree to which SDL concepts are being utilized in practice.

Performance‐based logistics (PBL) strategies are providing governments and for‐profit organizations with a contractual mechanism that reduces the life cycle costs of their systems. PBL accomplishes this by establishing contracts that focus on the delivery of performance not parts. PBL establishes a metric based governance structure where suppliers make more profit when they invest in logistics process improvements, or system redesign, that reduces total cost of ownership. While work has been done to outline an overall PBL theoretical framework, the underlying theory explaining the enablers that lead to organizational and team‐level, team‐goal alignment associated with the PBL governance structure requires testing. The purpose of this paper is to quantitatively test previously posited relationships between enablers of PBL and PBL effectiveness. An additional objective is to explore any differences in PBL effectiveness between different business sectors.

A multiple regression model was developed, tested and validated to explain the effectiveness of PBL. The model was externally validated with exploratory cross‐sectional survey data of 61 practitioners.

This study strongly supports recent PBL theory explaining PBL effectiveness. Key antecedents include investment climate, relational exchange, PBL leadership, and business sector. Further, government organizations lag behind their commercial counterparts in PBL effectiveness and PBL leadership.

PBL business arrangements are more effective in more favorable investment climates. Thus, leaders should welcome new ideas, empower employees, and encourage entrepreneurship. Since PBL effectiveness increases with relational exchange, building trust and communicating with suppliers is key. Leadership is also important to PBL effectiveness. Leaders should accept risk, focus on long‐term affordability and performance, and align activities to achieve end‐user goals.

This research is the first quantitative test of previously posited factors affecting PBL effectiveness. Additionally, this research unveils key differences in business sectors' use of PBL strategies.

The purpose of this paper is to describe the conversion of knowledge into value by examining the confluence of service-dominant logic (S-D logic), supply chain management (SCM), human resource management (HRM), and neuroeconomics. S-D logic suggests that knowledge is the raw material of value creation. SCM provides an organized foundation to study the conversion of raw materials into value. HRM recognizes the centrality of human decisions in the process of converting knowledge into value. Neuroscience gives insight into the efficiency and effectiveness of the human decisions processes. Global SCM provides more than markets and raw materials – global SCM provides the human resources central to value creation.

This paper combines literature review with interviews from members of supply chain teams engaged in performance-based logistics (PBL) to develop a model of the S-D logic knowledge conversion process.

The model describes individual-based decision constructs managers can expect to face as they convert knowledge, from a global supply chain team, into value. The model relates the decision maker mindset, based in neuroscience principals, to the efficiency of the knowledge conversion process. These principals are extended to suggest how managers can modulate human resource processes to improve the efficiency of economic exchange and increase supply chain resiliency.

This paper provides theoretical and practical insight into how differences in culture, neuronal predisposition, and genetics may influence managerial decisions. These findings provide a mechanism that researchers and managers may take to expand the boundaries of HRM in a global supply chain.

This work uses a foundation of SCM research to explain efficient conversion in a knowledge-based economy. This perspective demonstrates the criticality of global HRM mindsets and decision processes necessary to achieve competitive advantage in a knowledge-based economy. This provides a context for the study and improvement of neuroeconomic efficiency of firms.

The evolution of six sigma has morphed from a method or set of techniques to a movement focused on business‐process improvement. Business processes are transformed through the successful selection and implementation of competing six sigma projects. However, the efforts to implement a six sigma process improvement initiative alone do not guarantee success. To meet aggressive schedules and tight budget constraints, a successful six sigma project needs to follow the proven define, measure, analyze, improve, and control methodology. Any slip in schedule or cost overrun is likely to offset the potential benefits achieved by implementing six sigma projects. The purpose of this paper is to focus on six sigma projects targeted at improving the overall customer satisfaction called Big Q projects. The aim is to develop a mathematical model to select one or more six sigma projects that result in the maximum benefit to the organization.

This research provides the identification of important inputs and outputs for six sigma projects that are then analyzed using data envelopment analysis (DEA) to identify projects, which result in maximum benefit. Maximum benefit here provides a Pareto optimal solution based on inputs and outputs directly related to the efficiency of the six sigma projects under study. A sensitivity analysis of efficiency measurement is also carried out to study the impact of variation in projects' inputs and outputs on project performance and to identify the critical inputs and outputs.

DEA, often used for relative efficiency analysis and productivity analysis, is now successfully constructed for six sigma project selection.

Provides a practical approach to guide the selection of six sigma projects for implementation, especially for companies with limited resources. The sensitivity analysis discussed in the paper helps to understand the uncertainties in project inputs and outputs.

This paper introduces DEA as a tool for six sigma project selection.