A Conceptual Model for Measuring Reverse Logistics Performance in Automobile Industry

A Conceptual Model for Measuring Reverse Logistics Performance in Automobile Industry

Kaveh Khalili-Damghani, Maryam Najmodin
Copyright: © 2014 |Pages: 9
DOI: 10.4018/ijsds.2014040102
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Nowadays, organizations are facing two major challenges. First, huge amount of consumed products is considerably destructing the environment and on the other hand, because of increasing competition in business environment, creating long-lasting competitive advantage and long-term relation with customers has become a necessity for organizations to survive and thrive. In this competitive condition, increasing emphasis on protecting environment has made manufacturers to look at reverse logistics as an important competitive factor. So in recent years, many researchers' and practitioners' attention has been focused on reverse logistics and related topics. Regarding the lack of knowledge in the literature of reverse logistics in Iran industry, this research aims to contribute to the body of knowledge in this field of supply chain and specifically talks about reverse logistics performance measurement in auto industry. This paper introduces a conceptual model which measures reverse logistics performance in auto industry and identifies the most important reverse logistics factors and classifies them. The offered model has been verified by structural equation modeling method and fit statistics have been assessed in auto-industry of Iran. The results of this research will exhibit a proper classification of factors which influence reverse logistics performance and their significance in auto-industry.
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Literature Review

Despite the importance of reverse logistics, lack of theories in this field is noticeable. In addition to that, implemented researches in reverse logistics field have been usually concentrated on a specific product or industry (De Brito & Dekker, 2004). Dowlatshahi defines five categories of RL literature: (1) general summaries and basic RL concepts (2) research on quantitative approaches (3) studies of logistical topics (4) company profiles, and (5) RL applications (Farahani et al., 2011).

General summaries and basic RL concepts in research logistic include Daugherty et al. (2005), De Brito and Dekker (2004). Research on quantitative approaches in RL systems can be found in Ravi and Shankar (2005), Schultmann et al. (2006), Tonanont (2009), Golara et al. (2012). Particular topics such as distribution, warehousing, and transportation were addressed in Pokharel and Mutha (2009), Korchi and Millet (2011), Asif (2011), Chouinard et al. (2005), Geethan et al. (2011), Lambert et al. (2011), Jayant et al. (2011), Schultmann et al. (2006), Cespón et al. (2009). On the other hand, implemented researches in the field of reverse logistics has been classified by Pokharel and Mutha (2009) based on the RL process including Inputs, structure and processes and outputs.

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