A diagnostic framework for demand amplification problems in supply chains

This dissertation delivers a framework to diagnose the Bull-Whip Effect (BWE) in supply chains and then identify methods to minimize it. Such a framework is needed because in spite of the significant amount of literature discussing the bull-whip effect, many companies continue to experience the wide variations in demand that are indicative of the bull-whip effect. While the theory and knowledge of the bull-whip effect is well established, there still is the lack of an engineering framework and method to systematically identify the problem, diagnose its causes, and identify remedies. ^ The present work seeks to fill this gap by providing a holistic, systems perspective to bull-whip identification and diagnosis. The framework employs the SCOR reference model to examine the supply chain processes with a baseline measure of demand amplification. Then, research of the supply chain structural and behavioral features is conducted by means of the system dynamics modeling method. ^ The contribution of the diagnostic framework, is called Demand Amplification Protocol (DAMP), relies not only on the improvement of existent methods but also contributes with original developments introduced to accomplish successful diagnosis. DAMP contributes a comprehensive methodology that captures the dynamic complexities of supply chain processes. The method also contributes a BWE measurement method that is suitable for actual supply chains because of its low data requirements, and introduces a BWE scorecard for relating established causes to a central BWE metric. In addition, the dissertation makes a methodological contribution to the analysis of system dynamic models with a technique for statistical screening called SS-Opt, which determines the inputs with the greatest impact on the bull-whip effect by means of perturbation analysis and subsequent multivariate optimization. The dissertation describes the implementation of the DAMP framework in an actual case study that exposes the approach, analysis, results and conclusions. The case study suggests a balanced solution between costs and demand amplification can better serve both firms and supply chain interests. Insights pinpoint to supplier network redesign, postponement in manufacturing operations and collaborative forecasting agreements with main distributors.^

Transnational Capital and the Politics of Global Supply Chains

In the latest phase of globalization, transnational corporations based in the U.S. have worked closely with U.S. foreign policymakers to secure favorable foreign direct investment provisions within U.S. domestic legislation and within U.S. trade agreements. These interactions between transnational firms and the U.S. state have provided many of the preconditions for an expansion of foreign direct investment connected to capital liberalization and the growth of global supply chains from the 1980s to the present. This relationship is best conceptualized as representing a “transnational interest bloc,” whose policy objectives are incorporated within investment provisions in US-backed trade and investment agreements.

Fast-Food Franchises: An Alternative Menu for Hotel/Casinos

In their discussion - Fast-Food Franchises: An Alternative Menu for Hotel/Casinos - by Skip Swerdlow, Assistant Professor of Finance, Larry Strate, Assistant Professor of Business Law, and Francis X. Brown, Assistant Professor of Hotel Administration at the University of Nevada, Las Vegas, their preview reads: Hotel/casino food service operations are adding some non-traditional fare to their daily offerings in the form of fast-food franchises. The authors review aspects of franchising and cite some new Las Vegas food ideas.” The authors offer that the statewide food and beverage figures, according to the Nevada Gaming Abstract of 1985, exceeded $1.24 billion. Most of that figure was generated in traditional coffee shops, gourmet dining rooms, and buffets. With that kind of food and beverage figure solidly on the table, it was inevitable that fast-food franchises would move into casinos to garner a share of the proceeds. In a March 1986 review of franchising, Restaurant Business reported the following statistics: “Over 60 percent of all restaurants are franchisee owned. This relationship is also paralleled in dollar sales, which has exceeded $53 billion.” “Restaurant franchising expansion has grown at an annual rate of 12 percent per year for the past five years.” The beginning of the article is dedicated to describing, in general, the franchise phenomenon; growth has been spectacular the authors inform you. “The franchise concept has provided an easy method of going into business for the entrepreneur with minimal business experience, but a desire to work hard to make a profit,” say professors Swerdlow, Strate, and Brown. Lured by tourist traffic, and the floundering Chapter 11 afflicted, Riviera Hotel and Casino in Las Vegas, Burger King saw an attractive opportunity for an experiment in non-traditional outlet placement, say the authors. Although innately transient, the tourist numbers were way too significant to ignore. That tourist traffic, the authors say, is ‘round-the-clock. Added to that figure is the 2000-3000 average employee count for many of the casinos on the ‘Vegas strip. Not surprisingly, the project began to look very appealing to both Burger King and the Riviera Hotel/Casino, the authors report. In the final analysis, the project did work out well; very well indeed. So it is written, “The successful operation of the Burger King in the Riviera has sparked interest by other existing hotel/casino operations and fast-food restaurant chains. Burger King's operation, like so many other industry leadership decisions, provides impetus for healthy competition in a market that is burgeoning not only because of expansion that recognizes traditional population growth, but because of bold moves that search for customers in non-traditional areas.” The authors provide an Appendix listing Las Vegas hotel/casino properties and the restaurants they contain.

A methodology to select an enterprise resource planning system for a small or medium sized enterprise

Enterprise Resource Planning (ERP) systems are software programs designed to integrate the functional requirements, and operational information needs of a business. Pressures of competition and entry standards for participation in major manufacturing supply chains are creating greater demand for small business ERP systems. The proliferation of new offerings of ERP systems introduces complexity to the selection process to identify the right ERP business software for a small and medium-sized enterprise (SME). The selection of an ERP system is a process in which a faulty conclusion poses a significant risk of failure to SME’s. The literature reveals that there are still very high failure rates in ERP implementation, and that faulty selection processes contribute to this failure rate. However, the literature is devoid of a systematic methodology for the selection process for an ERP system by SME’s. This study provides a methodological approach to selecting the right ERP system for a small or medium-sized enterprise. The study employs Thomann’s meta-methodology for methodology development; a survey of SME’s is conducted to inform the development of the methodology, and a case study is employed to test, and revise the new methodology. The study shows that a rigorously developed, effective methodology that includes benchmarking experiences has been developed and successfully employed. It is verified that the methodology may be applied to the domain of users it was developed to serve, and that the test results are validated by expert users and stakeholders. Future research should investigate in greater detail the application of meta-methodologies to supplier selection and evaluation processes for services and software; additional research into the purchasing practices of small firms is clearly needed.^

Habitat use and foraging ecology of a batoid community in Shark Bay, Western Australia

Worldwide declines in populations of large elasmobranchs and the potential cascading effects on marine ecosystems have garnered considerable attention. Far less appreciated are the potential ecological impacts of changes in abundances of small to medium bodied elasmobranchs mesopredators. Crucial to elucidating the role of these elasmobranchs is an understanding of their habitat use and foraging ecology in pristine conditions. I investigated the trophic interactions and factors driving spatiotemporal variation in abundances of elasmobranch mesopredators in the relatively pristine ecosystem of Shark Bay, Australia. First, I describe the species composition and seasonal habitat use patterns of elasmobranch mesopredator on the sandflats of Shark Bay. Juvenile batoids dominated this diverse community and were extremely abundant in nearshore microhabitats during the warm season. Stomach content analysis and stable isotopic analysis revealed that there is a large degree of dietary overlap between common batoid species. Crustaceans, which tend to be found in seagrass habitats, dominated diets. Despite isotopic differences between many species, overlap in isotopic niche space was high and there was some degree of individual specialization. I then, investigated the importance of abiotic (temperature and water depth) and biotic (prey and predator abundance) factors in shaping batoid habitat use. Batoids were most abundant and tended to rest in shallow nearshore waters when temperatures were high. This pattern coincides with periods of large shark abundance suggesting batoids were seeking refuge from predators rather than selecting optimal temperatures. Finally, I used acoustic telemetry to examine batoid residency and diel use of the sandflats. Individual batoids were present on the sandflats during both the warm and cold seasons and throughout the diel cycle, suggesting lower sandflat densities during the cold season were a result of habitat shifts rather than migration out of Shark Bay. Combined, habitat use and dietary results suggest that batoids have the potential to seasonally impact sandflat dynamics through their presence, although foraging may be limited on the sandflats. Interestingly, my results suggest that elasmobranch mesopredators in pristine ecosystems probably are not regulated by food supply and their habitat use patterns and perhaps ecosystem impacts may be influenced by their predators.

Branch and price solution approach for order acceptance and capacity planning in make -to -order operations

The increasing emphasis on mass customization, shortened product lifecycles, synchronized supply chains, when coupled with advances in information system, is driving most firms towards make-to-order (MTO) operations. Increasing global competition, lower profit margins, and higher customer expectations force the MTO firms to plan its capacity by managing the effective demand. The goal of this research was to maximize the operational profits of a make-to-order operation by selectively accepting incoming customer orders and simultaneously allocating capacity for them at the sales stage. ^ For integrating the two decisions, a Mixed-Integer Linear Program (MILP) was formulated which can aid an operations manager in an MTO environment to select a set of potential customer orders such that all the selected orders are fulfilled by their deadline. The proposed model combines order acceptance/rejection decision with detailed scheduling. Experiments with the formulation indicate that for larger problem sizes, the computational time required to determine an optimal solution is prohibitive. This formulation inherits a block diagonal structure, and can be decomposed into one or more sub-problems (i.e. one sub-problem for each customer order) and a master problem by applying Dantzig-Wolfe’s decomposition principles. To efficiently solve the original MILP, an exact Branch-and-Price algorithm was successfully developed. Various approximation algorithms were developed to further improve the runtime. Experiments conducted unequivocally show the efficiency of these algorithms compared to a commercial optimization solver.^ The existing literature addresses the static order acceptance problem for a single machine environment having regular capacity with an objective to maximize profits and a penalty for tardiness. This dissertation has solved the order acceptance and capacity planning problem for a job shop environment with multiple resources. Both regular and overtime resources is considered. ^ The Branch-and-Price algorithms developed in this dissertation are faster and can be incorporated in a decision support system which can be used on a daily basis to help make intelligent decisions in a MTO operation.^

Branch and Price Solution Approach for Order Acceptance and Capacity Planning in Make-to-Order Operations

The increasing emphasis on mass customization, shortened product lifecycles, synchronized supply chains, when coupled with advances in information system, is driving most firms towards make-to-order (MTO) operations. Increasing global competition, lower profit margins, and higher customer expectations force the MTO firms to plan its capacity by managing the effective demand. The goal of this research was to maximize the operational profits of a make-to-order operation by selectively accepting incoming customer orders and simultaneously allocating capacity for them at the sales stage. For integrating the two decisions, a Mixed-Integer Linear Program (MILP) was formulated which can aid an operations manager in an MTO environment to select a set of potential customer orders such that all the selected orders are fulfilled by their deadline. The proposed model combines order acceptance/rejection decision with detailed scheduling. Experiments with the formulation indicate that for larger problem sizes, the computational time required to determine an optimal solution is prohibitive. This formulation inherits a block diagonal structure, and can be decomposed into one or more sub-problems (i.e. one sub-problem for each customer order) and a master problem by applying Dantzig-Wolfe’s decomposition principles. To efficiently solve the original MILP, an exact Branch-and-Price algorithm was successfully developed. Various approximation algorithms were developed to further improve the runtime. Experiments conducted unequivocally show the efficiency of these algorithms compared to a commercial optimization solver. The existing literature addresses the static order acceptance problem for a single machine environment having regular capacity with an objective to maximize profits and a penalty for tardiness. This dissertation has solved the order acceptance and capacity planning problem for a job shop environment with multiple resources. Both regular and overtime resources is considered. The Branch-and-Price algorithms developed in this dissertation are faster and can be incorporated in a decision support system which can be used on a daily basis to help make intelligent decisions in a MTO operation.