Reverse logistics performance measures: a survey of Brazilian companies

Abstract

Goal: The purpose of this research was to determine the most frequently used performance measures for the evaluation of reverse logistics in Brazilian companies. Furthermore, we sought to verify whether a correlation exists between certain performance measure dimensions (cost, asset management, customer service, and productivity), company size (micro, small, medium, and large), and their sectors of the economy.
 Design/Methodology/Approach: A survey of 125 Brazilian companies from different industrial sectors was conducted. Hypothesis testing allows carrying out inferences about population parameters, and the results indicate the acceptance or rejection of the hypothesis formulated.
 Results: This study presents a list of measures for the assessment of reverse logistics in different industrial segments, evidencing the major performance measures used. According to statistical analysis, large-sized companies are those that most frequently adopt performance measures to assess reverse logistics in Brazil. However, no correlation was verified between the performance measure dimensions evaluated and the sectors of the economy.
 Limitations of investigation: This study could not conclude about the maturity level of performance measurement in the investigated companies. The results presented are the first step towards reverse logistics performance measurement and more complementary studies are necessary.
 Practical implications: This paper presents a list of performance measures for reverse logistics assessment. This information could support decision making as it provides a possibility of analyzing the choice of the best measures.
 Originality/value: The main contribution of this paper is related to the scarcity of reverse logistics metrics in the literature. As an exploratory study, it could be used to improve the reverse logistics performance measurement studies and practice.

A mixed-method approach for modelling customer-centric mobile phone reverse logistics: application of social media data

“…Examining the literature review, we found that previous studies in the field of RL have been conducted on several key topics; namely, RL network design (Yan and Yan (2019); Zarbakhshnia et al , 2019; Liao, 2018; John et al , 2018; Alshamsi and Diabat, 2017; Yu and Solvang, 2016; Kilic et al , 2015); Model for the evaluation of RL performance (Hammes et al , 2020; Kazancoglu et al , 2020; Chaves et al , 2020; Han and Trimi, 2018; Peña-Montoya et al , 2020); Investigation of critical success factors in RL implementation (Chakraborty et al , 2018; Adabavazaeh and Nikbakht, 2019; Mangla et al , 2016); Identification of different options in RL and choosing the best option (Wang et al , 2019; Agrawal et al , 2016); RL for sustainability (Asees and Ali, 2019; Agrawal and Singh, 2019); Investigation of the barriers to RL implementation (Sirisawat and Kiatcharoenpol, 2018; Ali et al , 2018; Bouzon et al , 2018; Prakash and Barua, 2016; Bouzon et al , 2016; Bouzon et al , 2016a) and few studies in supply chain management and RL have been conducted using Twitter social media data (Schmidt et al , 2020; Sharma et al , 2020; Tseng et al , 2019; Iftikhar and Khan, 2018; Singh et al , 2018; Mishra et al , 2017; Chan et al , 2016; Chae, 2015; He et al , 2013). We also found that research on the use of customer feedback in RL decisions is very limited (Mishra et al , 2017).…”

“…These activities in a food supply chain in terms of CO 2 (carbon dioxide), NO x (nitrogen oxide), SO 2 (sulfur dioxide) and PM (particulate matter) emissions have been predicted through a system dynamics model for the years 2020 to 2024. Chaves et al (2020) have determined the most frequently used performance measures for the evaluation of RL in Brazilian companies. Furthermore, they sought to verify whether a correlation exists between certain performance measure dimensions (cost, asset management, customer service and productivity), company size (micro, small, medium and large) and their sectors of the economy.…”

Analysis of activities that make up reverse logistics processes: proposition of a conceptual framework

“…According to Chaves et al (2020) it is also called the Coordinating System, the first and most important key element of the RL process since it is responsible for this system's overall management and performance. It is the planning stage that takes place throughout the whole RL process.…”

“…It is the refined selection (filtering) of waste and accurate definition of quantities to be collected and transported to processing facilities. Also called Grading, it starts when materials to be collected must be screened for entering the return stream according to their functionality and determining the flow to be followed in the RL process (Chaves et al, 2020). According to Agrawal et al (2015) this stage represents the main entrance of RL and constitutes a set of practices performed usually by retailers to identify the products which are allowed into the RL system or given back to the user after resolving issues at their end or to proper disposal (Agrawal et al, 2016a).…”

“…This process, in general, has the same objective as Sorting, which is the definition of the appropriate destination for the returned product. Some researchers have considered Inspection/Testing and Sorting synonymous (Agrawal et al, 2015;Chaves et al, 2020;Conti and Orcioni, 2019;Nel and Badenhorst, 2020;Shi et al, 2012;Starostka-Patyk, 2019;Zouari, 2019). However, in other situations there is a separation between these two processes (Alshamsi and Diabat, 2017;Chan et al, 2012;Cline et al, 2015).…”