Effects of Random Yield in Remanufacturing with Price‐Sensitive Supply and Demand

In this study, we investigate the effects of recovery yield rate on pricing decisions in reverse supply chains. Motivated by the automotive parts remanufacturing industry, we consider an end‐of‐life product from which a particular part can be recovered and remanufactured for reuse, and the remainder of the product can be recycled for material recovery. Both the supply of end‐of‐life products and demand for remanufactured parts are price‐sensitive. Yield of the recovery process is random and depends on the acquisition price offered for the end‐of‐life products. In this setting, we develop models to determine the optimal acquisition price for the end‐of‐life products and the selling price for remanufactured parts. We also analyze the effects of yield variation to the profitability of remanufacturing, benefits of delaying pricing decisions until after yield realization, and value of perfect yield rate information.     

Social Work Practice for Social Development in Bangladesh: Issues and Challenges

Social work addresses social issues that constrain the betterment of a community. However, social work practice is struggling to deal effectively with the development challenges of Bangladesh. Based on a literature review and the experiences of the authors, this paper explores the emerging issues where social work practice is anticipated as a promising alternative for bringing sustainable social development in Bangladesh. Simultaneously, the paper discovers the limitation of social work practice in Bangladesh addressing these challenges.     

Two measures of geographic location and their relation to income

Two different ways of categorizing people’s geographical location are compared as to their relation to earned incomes of family heads, after adjustment for education, age, sex and race. One, the traditional code, uses the size of the city in which the family lives. The other, originally suggested by Bernard Lazerwitz, focuses on the distance to, and the size of, the central city of the nearest standard metropolitan statistical area. Both appear useful, and their joint effects are examined.     

Supporting the collaborative decision-making process in an automotive supply chain with a multi-agent system

Collaborative initiatives such as collaborative design, collaborative planning and forecasting, and open collective innovation are increasingly accepted as approaches that can effectively support decision-making (DM) processes in a range of different industries. However, justifying and demonstrating the benefits of collaborative solutions remains a challenge and has been under-researched. Demonstrating the feasibility of implementing collaborative solutions as opposed to traditional, linear and transactional solutions is even less evident. The purpose of this paper is to conceive a collaborative solution that supports the multi-level DM process in a real, tree-based automotive supply chain environment. The hypothesis presented posits that by sharing information collaboratively, improvements in terms of the profit and service levels will be found within the supply chain and at every supply chain node.