Reverse logistics capabilities and firm performance: the mediating role of business strategy

Vlachos, Ilias

doi:10.1080/13675567.2015.1115471

Cited by 59 publications

(73 citation statements)

References 70 publications

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“…Excellence in logistics practices are strongly related to high‐quality business performance. According to Vlachos (2016), reserve logistics activities and capabilities have a direct impact on a firm's performance. Performance measures that indicate the influence of green practices on company performance need to be further investigated (Pinto, 2020).…”

Section: Theoretical Backgroundmentioning

confidence: 99%

Performance evaluation of reverse logistics in food supply chains in a circular economy using system dynamics

et al. 2020

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Supply chains are composed of multiple stakeholders who have complex interrelationships. In addition, the forward and reverse flow of materials, information, human resources, and finance occurs among different stakeholders in closing the loop of supply chains. Reverse logistics (RL) activities are gaining importance in terms of size and quantity due to both economic and environmental concerns. These flows in RL in supply chains are both dynamic and complex in nature. Further, the environmental impact of RL activities has barely been considered in holistic way in available literature. In this study, a system dynamics model has been developed to analyze and comprehend the green performance of RL activities by predicting the environmental impact of RL activities. The proposed model has been validated by a case study in the context of a food supply chain. In the company where the case study is carried out, the environmental effects of RL activities have been analyzed. These activities in a food supply chain in terms of CO2 (carbon dioxide), NOx (nitrogen oxide), SO2 (sulfur dioxide), and PM (particulate matter) emissions have been predicted through a system dynamics model for the years 2020 to 2024. The proposed methodology is applied in a food supply context, a major player in retail business, especially in emerging economies. According to our findings, the RL activities in a food supply chain can significantly contribute to green performance management by minimizing food waste and loss; hence, the environmental impacts of such activities should be closely examined from a managerial perspective.

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Section: Theoretical Backgroundmentioning

confidence: 99%

Performance evaluation of reverse logistics in food supply chains in a circular economy using system dynamics

et al. 2020

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“…For instance, several studies have shown that logistics IS improves economic performance [32,66], along with operational performance [45,57,66], and strategic performance [36]. However, a survey [35] conducted on the mobile phone industry in China revealed a lack of relationship between logistics IS and RL performance, indicating that even CLSC-focused IS is not the whole story.…”

Section: Value Creation Factorsmentioning

confidence: 99%

Learning from Returned Products in a Closed Loop Supply Chain: A Systematic Literature Review

2020

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Product returns are a source of valuable information that can be used by firms and supply chains to improve products, services, and decision making. However, firms are struggling to maximize the value of this information, and the extant scholarly literature is scattered among various research streams. Using a systematic literature review, the state-of-the-art of product returns informational value research and limitations in the current body of work were examined and future directions for research suggested. Three types of informational value were identified, namely operational information, product related information, and customer-related information, along with four value-creating factors, namely strategic information system (IS) decisions, organizational learning, information sharing, and technological solutions. Implications for practitioners are discussed. Lastly, the limitations are discussed, along with recommendations and directions for future research work.

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“…Green supply chain management (GSCM) is a new and evolving area of supply chain management. The GSCM has a number of areas that including internal and external management (Chan et al, 2012), green procurement (Chien & Shih, 2007), green retailing (Dabija & Pop, 2013;Dabija et al, 2018), environmental orientation (Chan et al, 2012), sustainability (Popp et al, 2018;Oláh et al, 2019) and return logistics (Vlachos, 2016;Slusarczyk & Kot 2018;Kot et al, 2018).…”

Section: Environment Friendly Practicesmentioning

confidence: 99%

The impact of green practices, cooperation and innovation on the performance of supply chains using statistical method of meta-analysis

Pakurár¹,

Khan²,

Benedek³

et al. 2020

Journal of International Studies

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Businesses have to change their traditional methods to reduce the unfavourable processes of climate change and at the same time, sustainable business performance is also a basic requirement. The aim of this paper is to investigate the relationship between green practices, cooperation and innovation on the performance of supply chains. Meta-analysis of 35 publications was conducted to explore the relationship between the factors. We found a strong relationship between green practices and performance, and a moderate association between cooperation and performance and between innovation and performance, and these SCM factors are interrelated. For supply chain management, the use of green supply chain practice is strongly recommended, as

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Reverse logistics capabilities and firm performance: the mediating role of business strategy

Cited by 59 publications

References 70 publications

Performance evaluation of reverse logistics in food supply chains in a circular economy using system dynamics

Performance evaluation of reverse logistics in food supply chains in a circular economy using system dynamics

Learning from Returned Products in a Closed Loop Supply Chain: A Systematic Literature Review

The impact of green practices, cooperation and innovation on the performance of supply chains using statistical method of meta-analysis

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