A Conceptual Framework of Reverse Logistics Impact on Firm Performance

This study aims to examine the reverse logistics factors that impact upon firm performance. We review reverse logistics factors under three research streams: (a) resource-based view of the firm, including: Firm strategy, Operations management, and Customer loyalty (b) relational theory, including: Supply chain efficiency, Supply chain collaboration, and institutional theory, including: Government support and Cultural alignment. We measured firm performance with 5 measures: profitability, cost, innovativeness, perceived competitive advantage, and perceived customer satisfaction. We discuss implications for research, policy and practice

Supply chain uncertainty:a review and theoretical foundation for future research

Supply-chain uncertainty is an issue with which every practising manager wrestles, deriving from the increasing complexity of global supply networks. Taking a broad view of supply-chain uncertainty (incorporating supply-chain risk), this paper seeks to review the literature in this area and develop a theoretical foundation for future research. The literature review identifies a comprehensive list of 14 sources of uncertainty, including those that have received much research attention, such as the bullwhip effect, and those more recently described, such as parallel interaction. Approaches to managing these sources of uncertainty are classified into: 10 approaches that seek to reduce uncertainty at its source; and, 11 approaches that seek to cope with it, thereby minimising its impact on performance. Manufacturing strategy theory, including the concepts of alignment and contingency, is then used to develop a model of supply-chain uncertainty, which is populated using the literature review to show alignment between uncertainty sources and management strategies. Future research proposed includes more empirical research in order to further investigate: which uncertainties occur in particular industrial contexts; the impact of appropriate sources/management strategy alignment on performance; and the complex interplay between management strategies and multiple sources of uncertainty (positive or negative)

COOPERATION SUPPORT IN A DYADIC SUPPLY CHAIN

To improve the supply chains performance, taking into account the customer demand in the tactical planning process is essential. It is more and more difficult for the customers to insure a certain level of demand over a medium term period. Then it is necessary to develop methods and decision support systems to reconcile the order and book processes. In this context, this paper aims at introducing a collaboration support tool and methodology dedicated to a dyadic supply chain. This approach aims at evaluating in term of risks different demand management strategies within the supply chain using a simulation dedicated tool. The evaluation process is based on an exploitation of decision theory and game theory concepts and methods.supply chain ; simulation ; collaboration ; decision theory ; risk

Decision support for build-to-order supply chain management through multiobjective optimization

This paper aims to identify the gaps in decision-making support based on multiobjective optimization for build-to-order supply chain management (BTOSCM). To this end, it reviews the literature available on modelling build-to-order supply chains (BTO-SC) with the focus on adopting multiobjective optimization (MOO) techniques as a decision support tool. The literature has been classified based on the nature of the decisions in different part of the supply chain, and the key decision areas across a typical BTO-SC are discussed in detail. Available software packages suitable for supporting decision making in BTO supply chains are also identified and their related solutions are outlined. The gap between the modelling and optimization techniques developed in the literature and the decision support needed in practice are highlighted and future research directions to better exploit the decision support capabilities of MOO are proposed

Cooperation in manure-based biogas production networks: An agent-based modeling approach

Biogas production from manure has been proposed as a partial solution to energy and environmental concerns. However, manure markets face distortions caused by considerable unbalance between supply and demand and environmental regulations imposed for soil and water protection. Such market distortions influence the cooperation between animal farmers, biogas producers and arable land owners causing fluctuations in manure prices paid (or incurred) by animal farmers. This paper adopts an agent-based modeling approach to investigate the interactions between manure suppliers, i.e., animal farmers, and biogas producers in an industrial symbiosis case example consisting of 19 municipalities in the Overijssel region (eastern Netherlands). To find the manure price for successful cooperation schemes, we measure the impact of manure discharge cost, dimension and dispersion of animal farms, incentives provided by the government for bioenergy production, and the investment costs of biogas plants for different scales on the economic returns for both actor types and favorable market conditions. Findings show that manure exchange prices may vary between −3.33 €/t manure (i.e., animal farmer pays to biogas producer) and 7.03 €/t manure (i.e., biogas producer pays to animal farmer) and thanks to cooperation, actors can create a total economic value added between 3.73 €/t manure and 39.37 €/t manure. Hence, there are cases in which animal farmers can profitably be paid, but the presence of a supply surplus not met by demand provides an advantage to arable land owners and biogas producers in the price contracting phase in the current situation in the Netherlands