scholarly journals Design Strategy for the Reverse Supply Chain Based on Time Value of Product

2011 ◽  
Vol 2 (1) ◽  
pp. 76
Author(s):  
Huang Hui ◽  
Liang Gongqian
Keyword(s):  
Supply Chain ◽  
Supply Chain Design ◽  
Reverse Supply Chain ◽  
Design Strategies ◽  
Design Decisions ◽  
Marginal Value ◽  
Time Value ◽  
Reverse Supply Chains ◽  
Asset Recovery ◽  
Significant Opportunity

Design strategies for reverse supply chains are relatively unexplored and underdeveloped. The losses due to time delays represent a significant opportunity for asset recovery. Reverse supply chain design decisions should reflect the differences in the marginal value of time among products. The anthors propose that reverse supply chain can be designed for cost efficiency or quick response, and the decision pivots on the product’s time value. The paper analyzes the time value of return product in reverse supply chain, and the products are classified into low and high MVT based time value. In the paper both the efficient, centralized reverse supply chain matching the low MVT product and the responsive, decentralized reverse supply chain matching the high MVT product are designed In addition, the paper presents some key technologies for designing the reverse supply chain.

Analyzing disposition strategies in reverse supply chains: fuzzy TOPSIS approach

2018 ◽  
Vol 29 (3) ◽  
pp. 427-443 ◽  
Author(s):  
Rajesh Kumar Singh ◽  
Saurabh Agrawal
Keyword(s):  
Supply Chain ◽  
Literature Review ◽  
Supply Chains ◽  
Single Case ◽  
Cell Phones ◽  
Fuzzy Topsis ◽  
Reverse Supply Chain ◽  
Manufacturing Firm ◽  
Content Type ◽  
Reverse Supply Chains

Purpose The purpose of this paper is to explore the product disposition strategies in reverse supply chains and to develop a framework to prioritize these strategies for effective reverse supply chain implementation. Design/methodology/approach The disposition strategies, based on the literature review, were selected, and the fuzzy TOPSIS methodology had been applied for the prioritization of these disposition strategies. A case of cell phone manufacturing firm is discussed for the illustration and validation of the methodology. Three respondents from the firm helped in exploring the disposition strategies and data collection of the firm. Findings The results of the study show that dissemble and recycle is the most preferred disposition strategy for the firm. Redistribution of returned products after their refurbishing is second most prioritized disposition strategy. Landfill and incineration of cell phones is the last and least preferred option for the firm. Research limitations/implications The study will provide useful guidance to the firm for disposition decision making of cell phones returned to the firm. It will help academicians and practitioners for evaluating, improving, and benchmarking the disposition strategies for the disposition of returned cell phones. One of the limitations of the study is that it only considers the single case of manufacturing firm. In future, more case studies may be carried out for generalization of the results. Originality/value It is evident from the literature review that there are very few studies on disposition decisions in reverse supply chain. Also, disposition strategies for cell phones are first time being explored and prioritized. Hence, this study can be viewed as an attempt to increase the level of awareness on reverse supply chain issues.

The Effect of Supply Disruptions on Supply Chain Design Decisions

2010 ◽  
Vol 44 (2) ◽  
pp. 274-289 ◽  
Author(s):  
Lian Qi ◽  
Zuo-Jun Max Shen ◽  
Lawrence V. Snyder
Keyword(s):  
Supply Chain ◽  
Supply Chain Design ◽  
Design Decisions ◽  
Supply Disruptions

Extended TPB model to understand consumer “selling” behaviour

2017 ◽  
Vol 29 (4) ◽  
pp. 721-742 ◽  
Author(s):  
Anita Kumar
Keyword(s):  
Supply Chain ◽  
Perceived Control ◽  
Survey Methodology ◽  
Supply Chain Design ◽  
Reverse Supply Chain ◽  
Indian Government ◽  
Content Type ◽  
Starting Point ◽  
Tpb Model ◽  
Returns Management

Purpose Many academic studies on reverse supply chain management have emphasised on the development of conceptual and operational models for managing returns and extracting value, but have largely ignored the consumer selling behaviour, the starting point of a reverse supply chain. The purpose of this paper is to consider a twofold perspective to understand and analyse the reverse supply chain design of mobile phone in Delhi NCR: first, motivation and intentions of consumer selling their mobile phones and second, the returns management process through the organised and informal channels. Design/methodology/approach It first utilises a survey methodology and the theory of planned behaviour (TPB) model to understand and analyse the consumers’ intentions to recycle and then employs an in-depth interview methodology to derive qualitative insights needed to plot the reverse supply chain design. Findings In an extended TPB model, attitude, mediated by a “sense of duty” and perceived control, has a strong influence on the recycling behaviour than subjective norms and benefits. The qualitative insights draw attention to the design, configuration and management of informal and organised recycling channels that differ significantly, but remain relevant and coexist, especially in the context of emerging economies. Research limitations/implications It proposes an extended TPB model to understand consumer selling behaviour that can help the companies to plan and handle their demand-supply mechanisms in the reverse supply chain. Social implications This study calls for a proactive intervention by the Indian Government and other key stakeholders to regulate and streamline electrical and electronics waste management in India. Originality/value This research is positioned at the interface of logistics and marketing to understand and create a sustainable reverse supply chain design for high-value products.

scholarly journals An Operational Framework For Reverse Supply Chains

2012 ◽  
Vol 16 (2) ◽  
pp. 137 ◽  
Author(s):  
Rajesh Kumar Tyagi ◽  
K. Kathy Dhanda ◽  
Scott Young
Keyword(s):  
Supply Chain ◽  
Supply Chains ◽  
Transportation Network ◽  
Reverse Supply Chain ◽  
Reverse Supply Chains ◽  
Managerial Implications ◽  
Survey Results ◽  
Reverse Chain ◽  
And Performance ◽  
The Impact

In this paper, we present a framework for reverse supply chains. We identify four managerial drivers in the reverse chain as Facilities, Handling, Ease of Access, and Information. We explore the impact of each of these drivers upon the effectiveness and performance of the overall reverse chain via a survey of supply chain managers. We present the results of the survey and conclude with managerial implications derived from the survey results. The field interviews have been supplemented with survey results. The results indicate that the firms, that have reverse supply chain as a strategic priority providing a responsive and effective transportation network and that have an easy return policy, are more likely to have the most reliable reverse supply chain. The results also indicate that reverse supply chain matters the most at the late growth stage of the product life.

Reverse Supply Chain Design

2010 ◽  
pp. 283-300 ◽  
Author(s):  
Kishore K. Pochampally ◽  
Surendra M. Gupta
Keyword(s):  
Neural Network ◽  
Supply Chain ◽  
Phase I ◽  
Phase Ii ◽  
Fuzzy Topsis ◽  
Supply Chain Design ◽  
Reverse Supply Chain ◽  
Neural Network Approach ◽  
Solution Approach ◽  
Order Preference

The success of a reverse supply chain heavily relies on the efficiency of the collection facilities and recovery facilities chosen while designing that reverse supply chain. In this chapter, we propose a neural network approach to evaluate the efficiency of a facility (collection or recovery) of interest, which is being considered for inclusion in a reverse supply chain, using the available linguistic data of facilities that already exist in the reverse supply chain. The approach is carried out in four phases, as follows: In phase I, we identify criteria for evaluation of the facility of interest, for each group participating in the reverse supply chain. Then, in phase II, we use fuzzy ratings of already existing facilities to construct a neural network that gives impacts (importance values) of criteria identified for each group in phase I. Then, in phase III, using the impacts obtained in phase II, we employ a fuzzy TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) approach to obtain the overall rating of the facility of interest, as calculated by each group. Finally, in phase IV, we employ Borda’s choice rule to calculate the maximized consensus (among the groups considered) rating of the facility of interest.

scholarly journals Designing a Multistage Supply Chain in Cross-Stage Reverse Logistics Environments: Application of Particle Swarm Optimization Algorithms

2014 ◽  
Vol 2014 ◽  
pp. 1-19 ◽  
Author(s):  
Tzu-An Chiang ◽  
Z. H. Che ◽  
Zhihua Cui
Keyword(s):  
Mathematical Model ◽  
Particle Swarm Optimization ◽  
Supply Chain ◽  
Objective Function ◽  
Reverse Logistics ◽  
Particle Swarm ◽  
Supply Chain Design ◽  
Reverse Supply Chain ◽  
Swarm Optimization ◽  
Objective Function Values

This study designed a cross-stage reverse logistics course for defective products so that damaged products generated in downstream partners can be directly returned to upstream partners throughout the stages of a supply chain for rework and maintenance. To solve this reverse supply chain design problem, an optimal cross-stage reverse logistics mathematical model was developed. In addition, we developed a genetic algorithm (GA) and three particle swarm optimization (PSO) algorithms: the inertia weight method (PSOA_IWM),VMaxmethod (PSOA_VMM), and constriction factor method (PSOA_CFM), which we employed to find solutions to support this mathematical model. Finally, a real case and five simulative cases with different scopes were used to compare the execution times, convergence times, and objective function values of the four algorithms used to validate the model proposed in this study. Regarding system execution time, the GA consumed more time than the other three PSOs did. Regarding objective function value, the GA, PSOA_IWM, and PSOA_CFM could obtain a lower convergence value than PSOA_VMM could. Finally, PSOA_IWM demonstrated a faster convergence speed than PSOA_VMM, PSOA_CFM, and the GA did.

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