Stefan E. Genchev

The role of resource commitment and innovation in reverse logistics performance

Purpose – Aims to provide empirical evidence of the relationships between and among reverse logistics, resource commitment, and innovation.Design/methodology/approach – Mail surveys were sent to members of the Automobile Aftermarket Industry Association, a large trade association. Factor level results followed by between‐item results, as typically reported in general linear modeling and mediated regression, are developed using a split sample methodology. Ultimately, Resource‐Advantage Theory provided the framework for examining the impact of developing innovative reverse logistics‐related dynamic capabilities.Findings – Resource commitment makes reverse logistics programs more efficient and more effective. However, the resources must be used in such a manner as to develop innovative capabilities/approaches to handling returns. Resource commitment was not found to be significantly related to innovation in reverse logistics at smaller firms. This is likely to be related to the level of resources available. ...

Evaluating reverse logistics programs: a suggested process formalization

Purpose – Suppliers, manufacturers, wholesalers, and retailers alike are still considering reverse logistics (RL) to be the “necessary evil” in their day‐to‐day operations rather than an opportunity for future performance. At the same time, a well‐structured RL program can create a substantial value‐added and positively affect the bottom‐line. Based on in‐depth investigation of best‐in‐class RL programs implemented in practice, the purpose of this paper is to offer a grounded flow charting approach for assessing the state of program development and, potentially, identifying areas for improvement across different companies in various industries.Design/methodology/approach – The current study utilizes rich qualitative research methodology based on the combination between a thorough review of existing literature and multiple field studies. The findings from existing research, semi‐structured interviews and observation at companies’ sites, and RL‐related documentation at those companies, provide the backbone ...

Supply chain learning, integration, and flexibility performance: an empirical study in India

Purpose 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. Design/methodology/approach 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. Findings 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. Research limitations/implications 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. Originality/value 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.