Search results

The purpose of this paper is to explain what determines the influence of reverse logistics onto green supply chain competitiveness and to find out if that influence is always uniform.

The paper contains an empirical research conducted using a survey-based study, which encompassed a sample size of 228 participants and final consumers that have experience in buying/using products derived from the reverse logistics process.

The results indicate that the influence of reverse logistics onto green supply chain competitiveness is dependent on the product return option and is mainly negative with Serbian consumers, since the perceived quality of each of the three return options is considered to be inferior compared to new products.

The study's empirical results show the there is a generally negative perception among consumers regarding the perceived quality of each of the three product return options, thus directly questioning the general justification of using reverse logistics in Serbian business practice. That is a sign for Serbian managers to enhance their efforts to raise future awareness of the green initiatives importance among business partners, but also final consumers.

The study`s contribution is twofold: first, it helps to additionally test the established and known methodology created by Hazen et al. (2011), thus contributing to the practical dimension of international comparability concerning consumer perceptions. Second, the study adds to research by addressing the gap in practical surveys regarding the reverse logistics practices.

Some essential issues about modeling of reverse logistics (RL) systems and product recovery networks include consideration of the qualities of the returned products, taking into account uncertainty and integrating the forward and reverse flows. The purpose of this paper is to develop the integrated RL model, which focuses on the control of inventory and production planning problems in a case of uncertainty in demand, quantities and qualities of returns.

The model involves a forward production route, three alternative recovery routes and a disposal route. Various levels of qualities are considered for returned products. A fuzzy mixed integer programming model (FMIP) is developed to provide a solution for the problems of production planning and inventory control. After maximizing the satisfaction degree, different solutions can have the same maximum. Moreover, policies that use all recovery routes and reduce the overall uncertainty have no chance to be chosen. To tackle these problems, a two-phase approach method is applied.

According to the results of the numerical example, using different and appropriate recovery options based on the quality of returns can significantly decrease the recovery costs. Similarly, it is shown that the two-phase approach can be an effective and efficient method to reach a satisfactory solution for such problems.

In this study, after maximizing the FMIP model, a two-phase approach ‒ as a novel optimization technique in this research ‒ is employed to achieve a desirable solution.

The purpose of this paper is to determine how best to reduce, reuse and dispose of household waste medicines in the National Health Service (NHS) (UK).

Through a combination of literature review and empirical work, this research investigates the existing household waste medicines reverse logistics (RL) system and makes recommendations for improvement by benchmarking it against household waste batteries RL. The viability and feasibility of these recommendations are evaluated through in-depth interviews with healthcare professionals and end user surveys.

The batteries RL system appears to be a more structured and effective system with more active engagement from actors/stakeholders in instigating RL practices and for this very reason is an excellent comparator for waste medicines RL practices. Appropriate best practices are recommended to be incorporated into the waste medicines RL system, including recapturing product value, revised processing approaches, system cooperation and enforcement, drivers and motivations and system design and facilitation.

This study offers academics and professionals an improved insight into the current household waste medicines RL system and provides a step towards reducing an existing gap in this under-researched area. A limitation is that only a small sample of healthcare professionals were involved in subjectively evaluating the feasibility of the recommendations, so the applicability of the recommendations needs to be tested in a wider context and the cost effectiveness of implementing the recommendations needs to be analysed.

Reducing, reusing and properly disposing of waste medicines contribute to economic sustainability, environmental protection and personal and community safety. The information retrieved from analysing returned medicines can be used to inform prescribing practice so as to reduce unnecessary medicine waste and meet the medicine optimisation agenda.

This paper advocates learning from best practices in batteries RL to improve the waste medicines RL design and execution and supports the current NHS agenda on medicine waste reduction (DoH, 2012). The recommendations made in the paper not only aim to reduce medicine waste but also to use medicines effectively, placing the emphasis on improving health outcomes.

The purpose of this paper is to explore the processing of product returns at five case companies using a complex adaptive systems (CAS) logic to identify agent interactions, organization, schema, learning and the emergence of adaptations in the reverse supply chain.

Using a multiple-case study design, this research applies abductive reasoning to examine data from in-depth, semi-structured interviews and direct researcher observations collected during site visits at case companies.

Costly or high-risk returns may require agents to specialize the depth of their mental schema. Processing agents need freedom to interact, self-organize and learn from other agents to generate emergent ideas and adapt.

Limiting the depth of individual agent schema allows managers to better allocate labor to processing product returns during peak volume. To boost adaptability, managers need to craft a dynamic environment that encourages agents with diverse schema to interact, anticipate, and self-organize to brainstorm new ideas. Managers need to resist the urge to “control” the dynamic environment that ensues.

This paper builds on existing research that studies the key decision points in the analysis of product returns by exploring how processing-agent behaviors can create adaptability in the reverse supply chain. Additionally, this research follows in the tradition of Choi et al. (2001) and Surana et al. (2005) and proposes the application of CAS to a specific part of the supply chain – the processing of product returns.

The purpose of this paper is to present a framework to manage product returns for reverse logistics by focusing on estimation of returns for select categories of products in the Indian context.

The paper develops a conceptual model and thereafter an integrated modeling framework borrowing from existing literature and industry practices. It utilizes product ownership data, average life cycle of products, past sales, forecasted demand and likely impact of environmental policy measures for estimating return flows. Informal interviews with 84 stakeholders are carried out to estimate significant parameters. Software packages, decomposition methods and heuristics are utilized for solution.

The integrated framework helps in estimating returns for select categories of products and thereafter taking simultaneous decisions on their disposition, location and capacity of facilities and flows of returned products for a given time horizon under various strategic, operational and customer service‐related constraints.

A “push” system where the volumes of returns drive the decisions. Estimations and optimization have been carried out for select product categories and not brands or original equipment manufacturers (OEMs). No free choice of facility locations.

The insights and learning under different scenarios may be utilized as inputs for decision making by various stakeholders such as OEMs and their consortia, local remanufacturers and third party service providers.

At methodological level, our framework combines descriptive modeling with optimization technique, while at topological level; it provides detailed solutions for network configuration and design.

The concept of the customer order decoupling point (CODP) has been used in many different contexts as an important structural concept for the traditional forward supply chain. The CODP is rarely explicitly applied in reverse supply chain management and the purpose of this paper is to show that the CODP can be an important corner stone of a framework for analysis of the closed‐loop supply chain containing both forward and reverse material flows.

Conceptual similarities are identified using analogies between forward and reverse supply chains. First, the concepts are discussed in their original context of forward flows and thereafter the concepts are applied on reverse flows. Finally, a holistic closed‐loop model is established.

The conventional CODP framework for forward flow supply chains can be extended to cover also reverse material flows and therefore providing a foundation for a more comprehensive discussion of closed‐loop supply chains useful in both education, research, and industrial applications. Using the suggested extended framework it is possible to identify nine fundamental supply chain configurations.

Differentiating between demand driven and forecast driven activities plays a critical role in practical supply chain management and this paper highlights that this approach also can be applied to closed‐loop supply chains and therefore extending the reach of the toolbox previously developed for the forward supply chain.

The concept CODP has not previously been comprehensively treated for the closed‐loop supply chain and this paper provides a foundation for establishing a strategic structural framework for discussing issues such as lean vs agile and balancing efficiency and responsiveness in a more comprehensive context involving also reverse material flows.

The purpose of this research is to analyse the LSQ in the context of three different omni-channel purchasing scenarios while considering four dimensions (timeliness, availability, condition and return of the product) and to assess their impact on customer satisfaction and loyalty. In addition, an evaluation of the relationship between satisfaction and loyalty in the mentioned omni-channel scenarios is investigated.

A mixed two-phase research methodology is proposed: an initial qualitative analysis with six focus groups followed by quantitative research through surveys with a sample of 323 individuals. The proposed scales were tested for three purchase scenarios: “buy-online-ship-direct” (BOSD), “buy-online-pickup-in-store” (BOPS) and “buy-in-store-ship-direct” (BSSD). The data were analysed using partial-least squares structural equation modelling (PLS-SEM) techniques.

In an omni-channel context, the most important element of the logistics service deriving in satisfaction was timeliness for all the scenarios. The return-of-product dimension of LSQ was relevant for satisfaction in “ship-direct” scenarios, while the availability dimension was only relevant for customer loyalty in the BOPS scenario. Customer satisfaction had a positive impact on loyalty in the three purchasing scenarios.

These results might provide guidance to managers in order to improve not only logistics procedures and processes but also their relationships with their customers. Moreover, retailers need to account for return policies in ship-direct channels, prioritize punctuality and adapt delivery terms to ensure product availability.

This work represents a progress in LSQ research in the B2C omni-channel environment by extending its study to a previously untested purchasing scenario (BOSD) and including a fundamental and insufficiently explored dimension of the LSQ: the return.

Both online and brick and mortar retailers have invested heavily in developing omni-channel service offerings. Though seen as a competitive necessity, these omni-channel service offerings increase costs and complexities. The purpose of this study is to examine the effects of strategies involving bundles of omni-channel services related to order fulfillment and returns management on retailer performance.

Archival data were obtained for 152 retailers and analyzed using ordinary least squares regression. Robustness tests using an alternative dependent variable and a model-based classification strategy corroborate our findings.

Retailers offering full sets of high integration omni-channel services (buy online pick up in store, ship from store and in-store returns) have better performance (e.g. sales, growth and competitive position) and web sales than retailers that offer only a partial mix of these high integration services. Retailers offering a partial bundle of high integration services, in turn, have better performance and web sales than retailers that offer none of these services.

The research extends work that has examined the performance effects of omni-channel services on individual retailers. Our results indicate retailers benefit the most when offering a full set of high integration omni-channel services, suggesting retailers who have only adopted a subset of these services could improve performance through broader adoption of services. The results further indicate partial adoption of high integration services is better than no adoption.

Nowadays companies are constantly changing their retail settings and strategies to keep up with technological developments and consumer needs. Digital transformation enabled one’s shopping experience to be more efficient in terms of money, time, physical effort and other elements that determine the price a consumer has to pay. Channels of communication and distribution have evolved, increased in number and also became integrated. Mobile devices, mobile applications and location services help consumers in their shopping journey. These developments have led us to a new concept called omni-channel management. In theory, the omni-channel refers to a single and unified channel experience with multiple touchpoints, which include physical stores, online stores and direct marketing; mass communication channels (television, radio, print media, C2C, etc.), online channels (social media, search engines, comparison sites, e-mail, display etc.) and mobile channels (SMS, branded apps, etc.). Some examples of omni-channel practices are click-reserve, click-collect, tablets as in-store sales tools, in-store product order through mobile apps, etc.

In this chapter, the latest trends in marketing channels are discussed with enabling digital technologies and relevant success factors. Challenges and opportunities in implementing omni-channel strategies and several omni-channel initiatives from Turkey are reported.

A research was employed to present consumers’ preferences of touchpoints/channels for search, payment and delivery, and to find out the drivers that lead consumers to use more than one channel simultaneously and/or interchangeably in a buying process. The results will guide the readers to understand consumer behaviour in the new omni-channel world.