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Supply chain flexibility has been acknowledged as a necessity in the context of constantly changing operational and service requirements in the global marketplace. However, limited research has focused on analyzing and empirically testing the dynamics of achieving enhanced flexibility performance. Drawing upon the knowledge-based view of the firm, the purpose of this paper is to address this research gap by introducing supply chain learning (SCL) and integration as key factors in the process.

Survey data were collected in India. Structural equation modeling technique was used as the main analysis method to test the proposed conceptual model on SCL, integration, and flexibility performance.

Research findings indicate that the supply chain integration construct (in its internal and external dimensions) mediates the proposed SCL-flexibility performance relationship. The analysis also confirms the positive relationship between cross-functional integration and inter-firm integration.

Focusing on only one country may limit the generalizability of the findings. Also, cross-sectional data collection may not be the ideal approach for evaluating the impacts of SCL. Therefore, future research with longitudinal data and in different contexts is warranted to validate the research results of this study.

The proposed conceptual model adds to the limited existing knowledge body of SCL and links SCL, integration, and flexibility performance. It also provides a new venue for future research in this area.

The field of returns management has become an important supply chain management topic. The purpose of this paper is to develop a conceptualization of returns management orientation (RMO), a topic that has been largely ignored by the academic community.

A series of interviews with experts and a review of the literature were used to develop the construct. Empirical survey data were used to validate the proposed RMO measurement scale.

Statistical results support the validity and reliability of the new RMO construct. Different analyses show that the proposed conceptualization satisfies the criteria of the tests for unidimensionality, construct validity, internal consistency reliability, and nomological validity. Furthermore, the results of this study confirm the positive relationship between a firm’s RMO and returns management performance.

The present study provides a starting-point for further empirical research on returns management from a behavioral perspective.

RMO has a significant impact on returns management performance. The proposed RMO measurement scale provides a useful tool for companies to evaluate their management’s emphasis or recognition of the returns management function.

While the field of returns management has gained increased attention from both academics and practitioners, empirical research efforts on this topic are still limited. In order to address this issue, this study takes a behavioral perspective and follows a well-established approach to operationalize the construct of RMO.

Interest in reverse logistics (RL) as a critical component of supply chain management (SCM) is gaining more traction with both practitioners and academics. Because of RL’s growing strategic importance, it is imperative to conduct a timely and comprehensive literature review and to identify associated opportunities for future research. The paper aims to discuss these issues.

In this paper, the researchers conduct an extensive bibliometric analysis of published academic articles on RL for the period of 1992-2015. Specifically, the CiteSpace software is utilized to conduct document co-citation analysis and burst detection analysis on 912 selected RL articles and their 22,642 references.

This research identifies the most influential RL research publications/citations in each of the five periods and their research contribution. Using co-citation analysis, the authors are able to identify and illustrate major research themes, knowledge groups, and future research opportunities in the RL field.

In contrast to existing literature review studies in the logistics field, the study uses impact factor as a key article selection criterion. The influential articles identified in this process well represent the core literature and RL body of knowledge and have important implications for future research.

The purpose of this paper is to investigate relationships among dependence, trust, and integration in the Chinese 3PL context. 3PL integration is manifested in two key dimensions: information sharing and process coordination.

This study develops a dependence-trust-3PL integration-performance model and tests it using structural equation modeling with survey data collected from 361 companies in the Greater China area (i.e. mainland China, Hong Kong, and Taiwan).

The results show that switch dependence is indirectly related to information sharing and process coordination through goodwill trust, while goal dependence has direct links with both integrative behaviors. The authors also found that only goodwill trust mediates the relationship between dependence and integrative behaviors, while ability trust does not mediate any relationships. Finally, the analysis validated the direct link between process coordination and financial performance, but did not find a significant link between information sharing and financial performance.

Different from most previous studies on similar topics, this study examines the impacts of different types of dependence and trust on different 3PL integration dimensions. As a result, the findings are more specific and have direct relevance to effective 3PL relationship management in China.

The purpose of this paper is to empirically investigate the antecedents and impacts of a largely overlooked concept, employee development, within the challenging area of returns management.

The proposed relationships are validated through structural equation modeling analysis with survey data collected in India.

Combining the ability–motivation–opportunity model in human resource management and the theoretical tenets associated with dynamic capabilities, the authors confirmed that supply chain learning, returns management orientation and information support are important antecedents of returns management employee development. In turn, the findings suggest that, as a dynamic capability, returns management employee development positively impacts a firm’s returns management and market performance.

To successfully tackle the challenges related to handling returns, companies must focus their resources not only on new technologies and related processes, but also on employee training and development as well.

Although recruiting and retaining talent in supply chain management has long been recognized as a serious global challenge, no previous research has empirically studied employee development practices in the returns management context.

The purpose of this paper is to explore the influence of a physician’s prosocial behavior on a patient's choices in the online health community (OHC) context. Moreover, the authors explore how such effects differ across different online word-of-mouth (WOM) and professional titles.

Guided by the motivation, opportunity and ability (MOA) framework, this paper develops hypotheses and an econometric model. Then this paper used spline regression to test hypotheses on 6,204 physicians at The Good Doctor (www.Haodf.com), which is one of the largest Chinese OHCs. The authors conducted the propensity score matching and difference-in-difference method (PSM-DID) to address the concern about the bias caused by possible endogeneity concerns.

The authors’ results show that a physician’s prosocial behavior improves a patient's choice only when the strength of a physician’s prosocial behavior is below the tipping point. In addition, the influence of a physician’s prosocial behavior is heterogeneous for physicians with different online WOM and professional titles. For physicians with higher online WOM, the effect of a physician's prosocial behaviors on a patient's choice is positive, while for physicians with lower online WOM, a physician’s prosocial behavior has no impact on a patient’s choice. For physicians with higher professional titles, the quantity of a physician’s prosocial behavior has a positive impact on a patient’s choice, while for physicians with lower professional titles the quality of a physician’s prosocial behavior has a positive impact on a patient’s choice.

This study contributes new knowledge and provides new perspectives to study a patient's choice by addressing the importance of physician's prosocial behavior. With the effort of explicitly explaining the complex mechanisms, this study encourages physicians' engagement in a physician’s prosocial behavior and gives some implications on how to perform the behaviors strategically.

The purpose of this paper is to solve a post-disaster humanitarian logistics problem in which medical assistance teams are dispatched and the relief supplies are distributed among demand points.

A mixed integer-programming model and a two-stage hybrid metaheuristic method are developed to solve the problem. Problem instances of various sizes as well as a numerical example based on the 2016 Kyushu Earthquake in Japan are used to test the proposed model and algorithm.

Computational results based on comparisons with the state-of-the-art commercial software show that the proposed approach can quickly find near-optimal solutions, which is highly desirable in emergency situations.

Real data of the parameters of the model are difficult to obtain. Future collaborations with organizations such as Red Cross and Federal Emergency Management Agency can be extremely helpful in collecting data in humanitarian logistics research.

The proposed model and algorithm can help governments and non-governmental organizations (NGOs) to effectively and efficiently allocate and coordinate different types of humanitarian relief resources, especially when these resources are limited.

This paper is among the first ones to consider both medical team scheduling (routing) and relief aid distribution as decision variables in the humanitarian logistics field. The contributions include developing a mathematical model and a heuristic algorithm, illustrating the model and algorithm using a numerical example, and providing a decision support tool for governments and NGOs to manage the relief resources in disasters.