191,216 research outputs found
Reverse supply chain forecasting and decision modeling for improved inventory management
Thesis (S.M.)--Massachusetts Institute of Technology, Engineering Systems Division; and, (M.B.A.)--Massachusetts Institute of Technology, Sloan School of Management; in conjunction with the Leaders for Global Operations Program at MIT, 2013.Cataloged from PDF version of thesis.Includes bibliographical references (p. 69-71).This thesis details research performed during a six-month engagement with Verizon Wireless (VzW) in the latter half of 2012. The key outcomes are a forecasting model and decision-support framework to improve management of VzW's reverse supply chain inventory. The forecasting model relies on a reliability engineering formulation and incorporates a learning component to allow incremental forecast improvement throughout the device lifecycle. The decision-support model relies on Monte Carlo simulations to quantify the uncertainty and risk associated with different inventory management policies. These tools provide VzW stakeholders with a full-lifecycle perspective so that inventory planners can avoid costly end-of-life underages and overages. Prior to this effort, inventory planners at VzW relied on a three month returns forecast despite the fact that customers can return devices more than three years after launch. The decision-support model replaces existing heuristics to improve inventory management. Model efficacy is demonstrated through case studies. For a variety of representative SKUs, the returns forecast model is found to predict cumulative lifecycle returns within 10% using data available six months from launch. Had inventory been managed according to the policies recommended by the decision support model instead of policies from existing heuristics, VzW could have avoided an end-of-life stockout of more than 20,000 devices for a particular SKU.by Brian J. Petersen.M.B.A.S.M
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
Sustainability ranking of desalination plants using Mamdani Fuzzy Logic Inference Systems
As water desalination continues to expand globally, desalination plants are continually under pressure to meet the requirements of sustainable development. However, the majority of desalination sustainability research has focused on new desalination projects, with limited research on sustainability performance of existing desalination plants. This is particularly important while considering countries with limited resources for freshwater such as the United Arab Emirates (UAE) as it is heavily reliant on existing desalination infrastructure. In this regard, the current research deals with the sustainability analysis of desalination processes using a generic sustainability ranking framework based on Mamdani Fuzzy Logic Inference Systems. The fuzzy-based models were validated using data from two typical desalination plants in the UAE. The promising results obtained from the fuzzy ranking framework suggest this more in-depth sustainability analysis should be beneficial due to its flexibility and adaptability in meeting the requirements of desalination sustainability
AI and OR in management of operations: history and trends
The last decade has seen a considerable growth in the use of Artificial Intelligence (AI) for operations management with the aim of finding solutions to problems that are increasing in complexity and scale. This paper begins by setting the context for the survey through a historical perspective of OR and AI. An extensive survey of applications of AI techniques for operations management, covering a total of over 1200 papers published from 1995 to 2004 is then presented. The survey utilizes Elsevier's ScienceDirect database as a source. Hence, the survey may not cover all the relevant journals but includes a sufficiently wide range of publications to make it representative of the research in the field. The papers are categorized into four areas of operations management: (a) design, (b) scheduling, (c) process planning and control and (d) quality, maintenance and fault diagnosis. Each of the four areas is categorized in terms of the AI techniques used: genetic algorithms, case-based reasoning, knowledge-based systems, fuzzy logic and hybrid techniques. The trends over the last decade are identified, discussed with respect to expected trends and directions for future work suggested
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Evaluating eREVERSE auctions (EeRA): A research note
This eGISE network paper seeks to evaluate issues relating to the implementation of
electronic reverse auctions (eRA) within local government procurement processes. The
adoption of an eRA invites pre-qualified suppliers to compete with each other for a specified
good or service. Consequently, there is a unique opportunity for the buyer to receive a
reduced cost through the successful bidder. However, the literature identifies a number of
adverse effects within these arrangements depending upon the nature of the buyer/supplier
relationship. The objectives of the research involves identifying a set of business scenarios to
demonstrate the impact of different eRA strategies in this respect. This will be achieved
through a structured case analysis approach to enable qualitative data to be modelled through
a visual toolset simulation. It is believed the outcome of the investigation will provide
valuable insights into the complexities associated with the eProcurement process
Contingent Information Systems Development
Situated approaches based on project contingencies are becoming more and more an important research topic for information systems development organizations. The Information Services Organization, which was investigated, has recognized that it should tune its systems development approaches to the specific situation. A model has been developed, dealing with the matching between prevailing contingency factors and the preconditions of already existing situated approaches. Furthermore, a generic process model for systems development, including the information systems operations stage, is proposed. This model makes it possible to derive from it specific systems development strategies. A number of basic development strategies, specific for the Information Services Organization, are described. Preconditions, specific for this organization, are added to the standard situated approaches
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