Abstract

     The purpose of the study is to analyse how green reverse logistics technology impacts agricultural entrepreneurial marketing firms’ operational efficiency and sustainable competitive advantage. Systematic literature review and meta-analytical methodology was adopted to execute the current study. Reverse Logistics Model has been used for the current study as the theoretical model grounding the study as it enables a quick reaction and finding resolution for the customer return whilst regaining the highest value that is possible on each returned item. Results indicate that green reverse logistics technology has a strong influence on agricultural entrepreneurial marketing firms’ operational efficiency and sustainable competitive advantage. The study further shows existing research gaps that can be closed by future research studies. The study has limitations which may affect the generalisability of the results since they can only be applied testing the validity and reliability of the developed conceptual model. The study adds to theoretical literature development by extending knowledge on the Reverse Logistics Model theoretical modelling framework since there is paucity of research that have directly applied the same model in agricultural inputs entrepreneurial marketing firms’ operational efficiency and sustainable competitive advantage. Practically, the study enhances the need for adoption of contemporary technologies to solve the current challenges facing agricultural inputs entrepreneurial marketing firms’ sustainable operational efficiency and competitive advantage in the marginalised areas, not only in developing and emerging economies, but also dotted around the world. The study contributes to the conceptual development, theoretical and practical policy directions applicable to any agricultural inputs entrepreneurial marketing firms. A model can be tested to prove its validity and reliability in future similar studies, using alternative methodologies.

Introduction

     Environmental concerns have affected how business is done world over (Alnoor, Eneizan, Makhamreh & Rahoma, 2018; Kiatcharoenpol & Sirisawat, 2020). This has caused agricultural entrepreneurial marketing firms to re-design and re-align their processes in such a way that they are environmentally friendly (Kariuki, Ngugi & Mburu, 2022; Kazancoglu, Ekinci, Mangla, Sezer & Kayikci, 2021). The need for agricultural entrepreneurial marketing firms and consumers to ensure the dismantling of used products in a bid to extract parts for reuse, recycling or alternatively to ensure safe disposal (Martín & Fernandez, 2022). This allows companies to seamlessly integrate value creating activities of different supply chain partners (Martínez, Carracedo, Comas & Siemens, 2021). Seamless integrating of value creating activities include the movement of end of useful life goods or products from consumers to agricultural entrepreneurial marketing firms for the purposes of recapturing value and or ensuring disposal in an environmentally friendly manner (Martínez, Puertas, Martín & Ribeiro-Soriano, 2022; Nyagadza, 2021). This process of moving goods or products from the consumers to the manufacturer for recapturing value or ensuring disposal in an environmentally friendly manner is known as reverse logistics (Hills & Hultman, 2013; Isernia, Passaro, Quinto & Thomas, 2019; Julianelli, Caiado, Scavarda & Cruz, 2020). Firms aim at attaining operational efficiency as they strategically manage the process of product returns (Guarnieri, Cerqueira-Streit & Batista, 2020; Alharthi, 2012; Hersleth et al., 2022). By gaining operational efficiency through strategic management of reverse logistics (RL) can result in the improvement of the agricultural entrepreneurial marketing firm’s competitive position. Operational efficiency (OE) lead to improved competitive advantage of a firm (Job, Njihia, Maalu & Iraki, 2020). In many agricultural inputs industries RL costs tend to exceed the costs of production. Lack of an integrated supply chain strategy may in the long-term influence the agricultural entrepreneurial marketing firm’s competitiveness (Nyagadza, Pashapa, Chare, Mazuruse & Hove, 2022).

Discussion and conclusion

     With the perspective of the stated hypotheses, the modelling conceptual framework in Fig. 2 shows the antecedents of GRLT such as Reuse (X1), Repair (X2), Remanufacture (X3), and Recycle (X4), directly influence Operational Efficiency (OE) (M1) and Sustainable Competitive Advantage (SCA) (Y1 ) of the agricultural inputs entrepreneurial marketing firms. During the process of validating the structural modelling framework and its proposed hypotheses, future researchers need to make verifications of the absence of endogeneity through the simultaneity between Y1 and X1. If there is endogeneity on X1then an instrumental factor should be applied to have a solution for the problem under study.

     Further to this, suppliers and other supply chain participants receive returned goods, materials, and sub-assemblies for remanufacturing (Beamon, 1999). The basic design of a product must account for disassembly processes. Having suppliers on board is crucial for creating environmentally friendly products (Wu & Dunn, 1995). A company’s environmental impact can only be reduced by taking into account the entire system in which it operates (Andrushchak, 2018; Beamon, 1999; Richnák & Gubová, 2021). For widespread greening efforts, the green supply chain is the perfect emphasis since it reflects this comprehensive, systems-level perspective. The importance of constructing decision frameworks for reverse logistics processes for effective product take-back, reuse, and recycling of specific components and materials of end-of-life structures. The research also suggests effective choice approaches for reverse logistics vehicle routing (Lee & Lam, 2012; Kassem & Chen, 2012). Consequently, many experts in the field have proposed and executed several approaches to making decisions (Job et al., 2020). Recently, Chanintrakul, Coronado Mondragon, Lalwani and Wong (2009) provided a state-of-the-art review of the design of reverse logistics networks.

Abstract

Keywords

References

Abstract

The number of electric vehicle batteries is expected to increase. Their integration into circular economy requires their recollection at end-of-life. Decision makers need tools to determine suitable locations of recollection centers, as the decision is not trivial. Lithium batteries are hazardous materials, which require a minimization of transport duration. Here, we develop a mathematical model for locating a number of battery recollection centers. We discuss the results on the case of Germany for the time period from 2020 to 2050. The aim is to identify the influence factors on the location choice and therefore enable a founded decision.

1. Introduction

In 2019, the size of the global electric vehicle fleet was 7.2 million. Ninety-two percent of vehicles were used in the People’s Republic of China, Europe, and the United States [1]. According to the International Energy Agency (IEA), in 2030 global electric vehicle sales will reach 25 million, while the stock will be 140 million units [1]. The electric vehicle market is in growth phase.

Batteries are crucial parts of electric vehicles and have become a hot topic in research and development [2]. Within the last decade the capacity density increased by 300% [3]. Global Battery Alliance predicts that total weight of endof-life (EOL) Lithium-Ion-Batteries (LIBs) will increase more than threefold between 2018 and 2025 [4]. We must prevent formation of battery landfills. Therefore, EOL vehicle batteries must become a part of a circular economy value chain.

Circularity demands for repurposing batteries to secondlife applications through remanufacturing and recycling. As an initial step, recollection is required. Locations for recollection must be determined appropriately.

The goal of this paper is to determine the locations of recollection centers by means of minimization of the transport duration.

The paper is organized as follows. In Section 2, we give an overview of the research about repurposing of vehicle batteries and the facility location related to EOL vehicle batteries. In Section 3, we define the problem for determination of recollection center locations, and, in Section 4, we present the mathematical model. In Section 5, we solve and discuss instances of the model based on information from Germany. In Section 6, we conclude and present further research activities.

1. Introduction

2. Literature review

3. Problem Description and Assumptions

13. Formulation of a mathematical model

14. Solution methodology

15. Results and Discussion

16. Conclusion

Appendix A.

References

Abstract

Enhancing social and economic effects along with reducing environmental effect has gained significant consideration in reverse logistics network design. Electronic waste management raises serious concerns due to its increasing quantity and hazardous nature in global business. The developed model is a multi-objective reverse logistics network for electronic waste management, and the concept of the triple bottom line approach has been considered in the proposed study. The suggested study makes a trade-off between conflicting objectives. The research considers first customers, collection centers, distribution centers, second customers and reprocessing centers consisting of return evaluation centers, recycling centers and refurbishing centers. The carbon cap-and-trade policy has also been incorporated into the model. The objective of the formulated model is to maximize the profit and minimize the carbon emissions as well as maximizing the job opportunities in a reverse logistics network. To deal with the uncertainty, neutrosophic optimization has been applied to avoid unrealistic modeling. A related numerical example has been performed and the results show that the transportation cost contributes to the major fraction of the total cost. The reprocessing at the return evaluation and recycling centers are the main source of carbon emissions. Sensitivity analysis has also been conducted to assess the application of the proposed model. It shows that a drastic increase of 42.6% occurs in profit value when the per-unit carbon trading price is increased by 40% and vice-versa. Also, a variation is seen in the parameters like carbon emission at recycling centers with a change in total emissions value and the average number of units processed by one worker at return evaluation center with a variation in the number of job creation value.

Introduction

The conservation of resources needs to be considered in terms of end-of-life electrical products, electricity usage, technology usage, labor utilization, emission of carbon dioxide and increased electrical waste. The need for resource conservation in electrical products can be justified by the increasing levels of global climatic changes, e-waste and carbon emissions. World Meteorological Organization reported that 2015-2019 has been the warmest period with an increased global climate change of 0.2% as compared to the climate change in 2011-2015 (WMO, 2019). One of the reasons behind this change was the 20% increase in the level of carbon emissions globally, which will eventually become 410 ppm of carbon emissions at the end of 2019. However, emissions of carbon from transportation constitute around 25% of total carbon emissions. Similarly, the increase in e-waste rationalizes the importance of the reuse and recovery of the electrical products, for not only conservation purposes but also for creating a costsaving option for the industry. Besides reuse and recovery operations, the recycling of electrical products is also important as the Waste Electrical and Electronic Equipment (WEEE) Ordinance for waste management of electrical products and electronic equipment, specifies that at least 75% of the electrical products need to be recycled to conserve the resources and to reduce the e-waste (Laner and Rechberger, 2007). It was estimated that throughout the world, around 50 million tons of electrical waste is disposedoff each year and only 20% of this waste from electrical products is recycled each year (Baldé et al., 2017). Resource conservation also incorporates how the greenhouse emissions of carbon dioxide and other pollutants should be reduced. The increase in e-waste has also shifted the interest of researchers toward reducing carbon usage and emissions which could help in reducing global warming (Xiao et al., 2019). Emissions of carbon from transportation constitute around 25% of total carbon dioxide emissions (Nanaki and Koroneos, 2016). When considering the need for reuse, recovery, and recycling operations, the social perspective must be considered as well, in terms of job creation. However, globally the rate of unemployment was 5% which can be decreased in the future due to a rise in the number of jobs created worldwide (Kühn, 2019). This shows that an increase in the implementation of reuse, recycling and recovery operations will not only improve resource conservation but will also lead to an increase in job creation and a decrease in the unemployment rate, globally.

1. Introduction

2. Literature review

3. Problem description

4. Mathematical modelling

5. Results

6. Conclusion

Acknowledgements

References

Abstract

Reverse logistics network design (RLND) is getting momentum as more organizations realize the benefits of recycling or remanufacturing of their end-of-life products. Similarly, there is an impetus for organizations to become more environmentally conscious or green. This environmental context has driven many organizations to invest in green technologies, with a recent emphasis on reducing greenhouse gas emissions. This environmental investment situation and decision can be addressed through the integration of facility location, operational planning, and vehicle type selection, while simultaneously accounting for carbon emissions from vehicles, inspection centers, and remanufacturing centers in a reverse logistics (RL) context. In the current study, we present a mixed-integer linear programming (MILP) model to solve a multi-tier multi-period green RL network, including vehicle type selection. This research integrates facility locations, vehicle type selection with emissions producing from transportation and operations at various processing centers. Prior research does not account for carbon emissions for this design problem type. Valuable managerial insights are obtained when incorporating carbon emissions cost.

Introduction

Throughout the history of corporate environmentalism, environmental actions and concerns have evolved from a localized, pollution emissions perspective, to a global concern on general environmental sustainability through such efforts as the United Nations Global Compact (Kell, 2003). During the past three decades, there have been many international conferences and treaties, including the recent Conference of Parties (COP) emphasizing the need to rein in global climate change greenhouse gas (GHG) emissions (Boucher et al., 2016).

There is a consensus among world leaders for the need to limit GHG emissions. Global organizations recognize the need to consider inter-generational sustainability as a means of survival, given that a significant share of the economy heavily burdens the natural resource base, which is continuously depleting. Among many popular corporate environmental sustainability initiatives remanufacturing and its supporting activities will play a vital role to extend the life of resources and materials; while seeking to limit pollutant emissions (Kerr & Ryan, 2001; Diener & Tillman, 2015). In addition to this environmental benefit, business benefits also exist. Firms can strategically distinguish themselves from competitors by reducing their costs, adding value to their supply chain and end customers while achieving environmental sustainability through RL and remanufacturing efforts (Kumar, Chinnam, & Murat, 2017).

Introduction

In today’s highly competitive business environment, the success of any business depends to a large extent on the efficiency of the supply chain. Competition has moved beyond firm-to firm rivalry to rivalry between supply chains. Traditionally, businesses have concentrated on improving the forward supply chain for their products (e.g., manufacturer-wholesalerretailer-consumer). However, another important and emerging dimension of successful SCM is the reverse logistics process (Marien, 1988). As the business environment becomes more competitive, it becomes increasingly important for them to concentrate on optimizing the backward loop, as well. Reverse supply chain practices have been in existence for a long time, especially in the automotive industry, where manufacturers try to recover value from recycling car parts. Reverse supply chains differ from forward supply chains in information flow, physical distribution flow and cash flow. To manage reverse supply chain, companies need sophisticated information systems. Some of the technology involved in reverse supply chain is similar while in some areas the technology used differs from that of traditional supply chain. Technology used in reverse supply chain such as real-time inventory tracking system (bar codes and sensors) are similar to that used in the forward supply chain. On the other hand, activities such as repair optimization, slow moving inventory optimization, warranty tracking and de-manufacturing of product is different. In designing a successful reverse supply chain, it is important to know what type of product will be returned at which point in time at which place and in which condition. Hence, importance of data is immense. Tightly integrated automatic data capture, system directed disposition support, unique receipt handling, credit processing, comprehensive and flexible reporting are some of the important functional capabilities in reverse supply chain which can help a company have a competitive edge over its competitors.Reverse supply chain deals with products that have reached their life cycle or the ones returned by the final users, and then aims at best extracting their remaining values by repair, refurbishing, remanufacturing, cannibalization, and recycling ( Thierry et al.,1995) or other activities in order to protect the environment. Furthermore, reverse supply chain management can reduce the negative environmental impacts of waste disposal and resource extraction, and reduce production costs. All these factors will be taken into consideration while designing the operational framework to handle product disposition strategies for effective reverse supply chains. There are few articles on disposition decisions in reverse supply chain (Agrawal et al., 2016a; Agrawal et al., 2016b). The proposed study contributes to the very few studies available on disposition decisions in reverse supply chain. In this article, we’ve defined the reverse supply chain process, the steps involved and how it can be used as a strategic business weapon for organizations by studying the product disposition strategies. Drivers for implementing reverse supply chains are also explored alongwith inherent challenges that a reverse supply chain facessuch as managing customer expectations on returns policies, partnering with other players in the supply chain and handling the mounting pressure from regulatory authorities.

Reverse logistics (RL), an area of prime significance in the supply chain, has gained considerable ground in the last decade (Jayant et al., 2011). Industry practitioners and researchers have focussed on RL to enable organizations to attain competitive gain (Bernon and Cullen, 2007). According to Stock (1998), RL: “From a business logistics perspective… refers to the role of logistics in product returns, source reduction, recycling, materials substitution, reuse of materials, waste disposal, and refurbishing, repair and remanufacturing; from an engineering logistics perspective, it is referred to as reverse logistics management (RLM) and is a systematic business model that applies best logistics engineering and management methodologies across the enterprise in order to profitably close the loop on the supply chain.” (pp. 20-21) Product returns constitute 20 percent of everything sold to customers (Kumar and Chatterjee, 2011). This varies by product and channel type. Moreover, with challenging economic conditions, addressing returns within the reverse supply chain can help to cut costs, increase profit margins or both. RL is a $12 billion industry in India and contributes 13% of the GDP and with an enormous scope to provide the edge the companies are looking for (Anon, 2013). Also, over 92 percent of Indian retail businesses comes from the unorganized retail sector, thus offering tremendous potential for growth, consolidation, and modernization in the Indian context (Atroley and Rajat, 2014). With the degree of returns varying across industrial segments due to different return policies and legal regulations, the frequency of returns becomes essential, which might influence profitability and performance by investing in RL. There had been a continued focus on the forward supply chain, but with an increase in global competitiveness, it has become increasingly important for organizations to divert its attention towards the reverse chain as well (Kumar and Chatterjee, 2011). With an increasing trend in online marketplaces, the returns have also increased, with an estimated $800 million to $1 billion being returned in the fiscal year 2015-16, thus causing logistical challenges and potential losses (Julka and Ganguly, 2015). Despite well devised return policies, there have been fraudulent returns for which systems need to be devised for tracking customer behaviors (Julka and Ganguly, 2015). To design these systems, organizations need to allocate adequate resources, thus making resource commitment a critical construct in RL. The shift in organizational attention towards the reverse supply chain was to benefit from the supply chain, including benefits from a strategic perspective. An emphasis on the reverse chain results in greater returns, improved customer satisfaction and increased public perception as a result of handling the product returns efficiently and incorporating customer feedback (Johns, 2014; Robinson, 2015). Other strategic benefits include greater market share, reduced business risks and environmental sustainability, which might result from environmental regulations for product returns, thus enabling organizations to attain the strategic edge (Johns, 2014). To acquire the strategic benefits and to address fraudulent product returns, information technology (IT) systems – notably, information systems (IS) – are needed to enable organizations to manage the logistical activities efficiently and reduce losses due to product returns (Julka & Ganguly, 2015). These systems also enable organizations to track customer feedback, allowing them to enhance product quality, hence creating value for the customer. The selection of appropriate IS for the reverse supply chain and the ensuing IS practices are important and research-worthy. The principal objectives of this study are threefold.

Over the last decade environmental issues have become an important issue in various industries including the electronics industry due to an increase in environmental awareness, enforced legislation, industrial ecology and corporate citizenship (Prakash & Barua, 2015). The policy and decision makers have to consider environmental issues in each activity of their organization along their supply chain (Kannan, Jabbour, & Jabbour, 2014). Many companies have applied reverse logistics (RL) concept to their policies and strategies for sustainability development which focused on the reduction of waste and created value from return of used products (Sirisawat, Kiatcharoenpol, Choomrit, & Wangphanich, 2016). Rogers and Tibben-Lembke (1998), explained that RL is the process of planning, implementing, and controlling the efficient, cost effective flow of raw materials, in-process inventory, finished goods and related information from the point of consumption to the point of origin for the purpose of recapturing value or proper disposal. RL focuses on maximizing value from the returned item or minimizing the total RL cost from the backward flow of materials (Kannan, Pokharel, & Kumar, 2009). According to law and legislation, it forced producers to take care of their End of Life (EOL) products and the Waste Electrical and Electronic Equipment (WEEE) directive (directive 2002/96/EC) enforced electronics manufacturers to efficiently manage the return and proper disposal of packaging or used products (Govindan, Soleimani, & Kannan, 2015; Nikolaou, Evangelinos, & Allan, 2013). Even though the RL concept is widely used in many companies, it still has a lots of barriers that make RL practices difficult and unsuccessful. Each barrier cannot be solved at the same time and might require different solutions or treatment (Prakash & Barua, 2015; Sharma, Panda, Mahapatra, & Sahu, 2011). Hence, priority and ranking of barriers and solutions is needed to solve such barriers. Previous research has studied and introduced some barriers, drivers and also solutions for RL practices in many countries (Abdulrahman, Gunasekaran, & Subramanian, 2014; Govindan, Kaliyan, Kannan, & Haq, 2014; Prakash & Barua, 2015; Rahman & Subramanian, 2012; Ravi & Shankar, 2005; Sharma et al., 2011; Zaabi, Dhaheri, & Diabat, 2013). However, the study of barriers and solutions in Thailand’s electronics industry remains unstudied. This research focuses on the identification of barriers in Thailand’s electronics industry and ranks solutions to solve its barriers. Electronics companies or other related Thai industries could use the results from the ranking of solutions to solve RL practices barriers and also develop efficient and appropriate policies and strategies for their companies to improve competitiveness. A hybrid of decision making methods was used for prioritizing and ranking of solutions. And fuzzy approach was used to manage the vagueness and uncertainty of the human options in which human judgment in decision making has often been unclear and difficult to estimate with exact numerical values (Patil & Kant, 2014).

Reverse logistics deals with the collection and treatment of used products. Nowadays, apart from economic reasons, organizations across the globe are increasingly focusing on setting up reverse logistics networks owing to the adverse environmental effects caused due to the improper disposal of many used products. However, reverse logistics is still in a state of infancy, particularly in emerging economies (Bouzon et al., [1]). The economic potential associated with used products also makes research in this area quite attractive. According to the Environmental Protection Agency (Dat et al., [2]), there are 20–50 million metric tons of electronic waste (e-waste) alone generated worldwide every year. Thus, organizations must consider the management of reverse logistics systems in addition to forward logistics (Tahirov et al., [3]; Govindan et al., [4]). Moreover, customers are becoming more knowledgeable about environmental pollution and this affects their purchasing decisions (Kara et al., [5]). So, having a proper mechanism in place for a reverse supply chain not only helps firms reduce the negative environmental impact of its used products but also enhances its green image in the markets it operates in (Pishvaee et al., [6, 7]). Original equipment manufacturers and third party logistics service providers often carry out the reverse logistics activities. Many companies such as Kodak, Xerox, HP, Dell and GM focus on remanufacturing and recovery activities, thereby achieving significant gains (Uster et al., [8]). Nevertheless, there are cases where organizations fail to achieve gains from recovery activities. For example, Ford, the automobile manufacturing firm, admitted that automotive recycling was a poor business decision (Karakayali et al., [9]). One of the strategic decisions to be made in a reverse supply chain is the design of the network. This involves the determination of the number and location of facilities to be established. Typically, these facilities include collection centers, disassembly centers, remanufacturing centers, recycling centers etc. The design problem involves the determination of flow between different stages of the network. Reverse logistics activities involve additional supply chain costs which need to be managed. Different recovery options are associated with returned products. They can be remanufactured or the component parts can be repaired or recycled after disassembly. Remanufacturing brings the quality standards of used products up to that of new products (Thierry et al., [10]). Disposal of non-recyclable or hazardous materials is also a difficult task for organizations to carry out; but this too needs to be accomplished. In order to analyze product flows at the component and material levels, it is important to consider the product structure of the returned product by way of taking into account its bill of materials (BOM). Only a few studies have incorporated BOM of the product in the network design of a reverse supply chain (Dat et al., [2]; Alumur et al., [11]; Demirel et al., [12]; John et al., [70, 71]).

Concerns about the environmental impact of transportation and logistic activities have greatly increased in recent years. Since integrated operations can help achieve goals of lesser harm to the environment, while remaining operational effective (Qiu et al., 2017), supply chain optimization problems have attracted much research efforts. Among these problems, the production routing problem (PRP) that jointly optimizes decisions of production, inventory, distribution and routing has recently received a considerable attention (Adulyasak et al., 2015a). This integrated optimization problem is of practical relevance to success in business competitions, especially in modern logistical practices of vendor managed inventory (VMI) and just-in-time (JIT). Besides integrating operations forward, closed-loop supply chain optimization showed a further reduction in environmental impact (Savaskan et al., 2004). Return flow processes in a closed-loop supply chain usually consists of (1) product collection from consumers; (2) reverse logistics to take collected products back; (3) screening, assorting and disposal to specify the most economically attractive reuse alternatives; (4) remanufacturing; and (5) remarketing to produce and utilize new markets (Iassinovskaia et al., 2017). A closed-loop PRP naturally integrates reverse logistics and remanufacturing. This problem is important because in addition to economic benefits, environmental benefits due to extension of the product useful life, reduced energy and material consumption, pollution prevention, and other sustainability benefits can be expected. After the importance of considering production, inventory and routing decisions simultaneously was stressed by Chandra (1993), the PRP was extended in various ways to consider, e.g., multiple plants and heterogeneous fleets of vehicles (Lei et al., 2006), incapacitated production (Archetti et al., 2011), multiple homogeneous capacitated vehicles (Adulyasak et al., 2014a), demand uncertainty (Adulyasak et al., 2015b), multi-item back-order (Brahimi and Aouam, 2015), perishable products(Vahdani et al., 2017), and multiscale production(Zhang et al., 2017) in the past decade. The environmental impact of the PRP has seldom been addressed, with only a few notable exceptions, such as the PRP with carbon emissions (Qiu et al., 2017), and multi-objective production and pollution routing problem with time window (Kumar et al., 2015). However, reverse logistics and remanufacturing are completely ignored to the best of our knowledge. Battarra et al. (2014) addressed pickup-and-delivery problems for goods transportation, and reviewed various available algorithms. The vehicle routing problem with simultaneous pickups and delivery (VRPSPD), also known as the most studied and most general variant of the one-to-many-to-one (1-M-1) problems, has become increasingly popular. The electric appliances industry, beverage industry, and returnable/reusable transport items (RTI), or returnable/reusable logistical packaging have witnessed the application of the VRPSPD. Exact algorithms such as branch-and-cut method (Subramanian et al., 2013), branch-price-and-cut method (Cherkesly et al., 2015; Qu and Bard, 2015), are relatively new. Inventory routing problems with simultaneous pickups and deliveries (IRPSPD) have been explored only recently (Soysal, 2016; van Anholt et al., 2016; Iassinovskaia et al., 2017). Extending these problems and methods to the PRP is a natural step forward.

Reverse logistics (RL) aims at recovering part of the original value of used goods, producing economic, environmental, and social gains, mainly in industrialized regions (Carter and Easton, 2011). In regions with an expressive generation of waste, RL helps to reduce the pressure on public sanitation systems (Berthier, 2003), giving a proper destination to obsolete materials generated by obsolete technology-based products or by industrial processes (Chung and Wee, 2011). Furthermore, stringent legislation and consumer pressures (González-Torre et al., 2004) force companies to establish and pursue environmental objectives (Bernon and Cullen, 2007). Among other possibilities such as eco-design and cleaner production techniques, RL can help achieving such environmental objectives (Lee and Dong, 2009). RL differs from direct logistics (DL). While DL moves goods towards the customer, RL moves goods from the customer (Sellitto et al., 2015). RL and DL involve the same elements: transportation, warehousing, inventory management, and information systems (Lambert et al., 2011), sharing networks and activities (Hu et al., 2002; Schultmann et al., 2003) such as after-sales services and after-consumption collection (Rogers et al., 2012). Operations include waste identification, collection, sorting, compaction, intermediate storage, recollection, transportation, delivery, and value recovery (Ravi et al., 2005). Management stages include the definition of routes and vehicles and the integration with direct channels for resource optimization (Rogers et al., 2002), which maximizes value recovery and eco-efficiency of the entire operation (Heese et al., 2005). Process industries use raw material and generate waste in large amounts (Pati et al., 2008; Papageorgiou, 2009). In closed-loop supply chains (CLSC), waste applies as low-cost raw materials or fuel (Janse et al., 2009). Process industries add value to materials by mixing, separating, and processing raw materials by granulometric transformations or chemical reactions. Raw materials originate from extractive processes, such as mining, agriculture, or forestry and may be liquids, fibers, powders, and gases. Process industries require environmental control and investment in capital goods. The manufacturing processes are continuous, batchwise, or mixed. In continuous processes, the production run is long, interruptions are irrelevant, and the lot size is infinite. In batchwise processes, the production runs are short, the production is intermittent, and the lot size is finite. In mixed processes, the manufacturer produces a continuous product and delivers it in discrete units, like liquids in bottles or grains in bags (Fransoo and Rutten, 1994).

Logistics tasks have shown great growth with the rapid development of logistics industry as well as related industries such as E-commerce. Consequently, the dramatically increasing demands of logistics, the sustainable cost-efficiency policies related to the logistics, and the cost-profit and environmental pressure of logistics enterprises have forced enterprises to examine their current strategic decision-making on the logistics operation and distribution. Therefore, the value of reverse logistics in a sustainable way is emerging [1]. The environment and economy, as two main pillars of the sustainability, are emphasized in the sustainable systems and life cycle sustainability assessment [2]. However, the typical challenges that the sustainable reverse logistics is facing are how to construct real-time information sensing model to acquire the real-time and accurate information of logistics resources actively, how to implement the sustainable optimisation configuration of logistics resources based on the logistics enterprises information integrated system (EIS), and how to reach real-time information-driven dynamic optimisation for logistics tasks and vehicles with the objectives of reducing logistics cost and energy consumption, alleviating environmental pollution, and achieving sustainable reverse logistics. The Internet of Things technology (IoT) is a promising technology that has been applied in the manufacturing process for sensing and capturing real-time manufacturing resources data. The acquiring and sharing of real-time information of logistics activities is also the essential of the collaboration of logistics resources. Radio frequency identification (RFID)- enabled real-time information tracking infrastructure was developed to address the real-time data capturing and manufacturing information processing for the extended enterprises [3,4]. The configuration of IoT environment is the key component of the IoT-based real-time information sensing model. After capturing the dynamic information of logistics resources, instead of directly entering optimisation stage, adaptive controlling mechanisms were entailed to achieve the added value and management of real-time information [5]. Then, the framework of the Internet of Manufacturing Things to share the real-time manufacturing information, and a sensordriven remote real-time monitoring provided a good technological reference for sharing and monitoring the realtime status of logistics resources so that real-time decisionmaking of logistics could be done [6,7]. The information management and communication platform are identified as the key essentials for the sustainable and strategic management [8].

Due to environmental concerns, reverse logistics now is becoming an important strategy to increase customer satisfaction. Reverse logistics originates from a waste management standpoint. It is complicated due to the presence of driving forces, return reasons, product types, and uncertainty around the reverse flow. Also, how the material is recovered and who will execute and manage the various reverse operations are important issues [1,2]. Since reverse logistics includes a series of processes involving product return, repair, dismantling, refurbishing, recycling, remanufacturing, and disposal of used or end-of-life products, the implementation of a reverse logistics network is a strategic decision. This decision seeks a single objective or multiple objectives of cost minimization, profit maximization, customer satisfaction, or environmental benefit [2,3,4,5]. It includes the determination of locations, the number and capacity of facilities and the flow quantity sent from one facility to another. It is severely complicated by many uncertain factors; therefore, several papers have focused on the design of reverse logistics network [6,7,8,9,10,11,12]. A classification scheme for different types of reverse logistics networks has been identified by Fleischmann et al [13]. The reverse logistics networks range from simple echelons to complex echelons composed of forward and reverse supply chain networks. [14,15,16]. Due to the complexity and economic effect of reverse logistics, a common mathematical model has been developed to solve the network problem [14,15,17,18,19,20,21]. Bazan et al. [22] reviewed mathematical inventory models for reverse logistics from an environmental perspective. A more comprehensive survey of reverse logistics was taken by Agrawal et al. [14], Govindan et al. [16], and Govindan and Soleimani [23]. This research is inspired by the projects related to reverse logistics implementation of bulk waste in Taiwan. In this research, a reverse logistics network is designed and a mixed integer nonlinear programming (MINLP) model is developed to solve the strategic network design of reverse logistics. The proposed model is generic, for maximizing total profit by considering product returns with different fractions of reuse and recycle activities. It is a multi-echelon reverse logistics network designed to find the near optimal location and number of facilities, and the allocation of returned products and modules for profit maximization. Also, we consider various recovery activities based on the quality and high-value modules of recovered products. The number of remanufactured products depends on the critical and most valuable modules, and modularized remanufacturing processes make product recovery more efficient and profitable.

Reverse Logistics (RL) focus on how to take back the returns and recover them efficiently and economically. Over the last decade reverse logistics had a significant economic impact on industry as well as society (Krumwiede and Sheu, 2002). Proper handling or returns also has important customer service implications. The existence, effectiveness and efficiency of service management activities such as repair services and value recovery depend heavily on effective RL operations (Tibben –Lembke and Rogers, 2002). The effective management of RL operations increases profitability. Recycling is a product recovery option that involves techniques for creating new materials from wastes. Chen et al. (2007) observed recycling as a sub-process within reverse logistics to reduce the solid waste volume generated by the disposition of consumer products normally at the end of product’s life-span or due to defect. Both recycling stations and centers will increase their market share and become integrated to the whole remanufacturing industry by collaborating with remanufacturing businesses (Zhang et al., 2017). The advantages of recycled materials are that they generally have a lower carbon footprint than raw materials converted into finished goods through a carbon intensive process (Ravi, 2012). Bing et al. (2015) re-design a reverse supply chain from a global angle on household plastic waste distributed from Europe to China. Klausner and Hendrickson (2000) suggested that firms combine recycling operations with reusing or remanufacturing operations in order to stay profitable. Plastic recycling is a legal requirement and can yield environmental benefits. Wong (2010) confirmed that the recycling of post-consumer plastics has less environmental impact than the use of crude oil to produce virgin plastics. However, plastic collection practices vary in different countries which have an impact on the network structure of reverse logistics for plastic waste. The CO2 emissions due to the production of virgin polymer are 6 kg per kg of polymer while it is 3.5 kg for that of recycled plastics (Wong, 2010). Polyethylene Teraphalathate (PET) is used as a raw material for making bottles for packaging soft drinks, alcoholic beverages, detergents, cosmetics, pharmaceutical products and edible oils.