D.Ed. / The aim of this study is the construction of a model according to -which theoretical educational concepts can be operationalized for purposes of empirical research, with maximal validity. The rationale for the study is that high level terminology in education must continually be established and tested against empirical reali ty for purposes of meta-theoretical justification. Such a model for operationalization must satisfy numerous criteria as well as conditions. An indication is given of the position of operationalization as a methodological step wi thin the broad scope of scientific practice. The following meta-scientific characteristics or conditions are postulated as guidelines for a model for valid operationalization: The external validity and effectiveness of scientific statements; The logical consistency of scientific statements; The informativeness and epistemic truth of statements;...

<p> The purpose of this quantitative correlational study was to identify relationships between organizational culture types, supply chain integration, and firm performance. The study process included obtaining data from 201 supply chain professionals and procurement specialists working in various companies throughout the United States. Supply chain integration data and firm performance derived from results obtained from participants completing a 5-point Likert-type scale survey. The Organizational Culture Assessment Instrument helped with determining organizational culture types. The results revealed a significant correlation between supply chain integration and firm performance. All three integration variables, customer, supplier, and internal had a significant positive correlation with total integration and firm performance. The data also indicated that supply chain integration increased when organizational flexibility was present. An unexpected result was both clan and adhocracy cultures had a significant correlation to supply chain integration and firm performance. Conducting this study and revealing the findings added to literature and informs supply chain practitioners by determining the influence of organizational culture on supply chain integration performance. The results of this study substantiate that a flexible organizational structure, as shown in the clan and adhocracy cultures, increases supply chain integration and firm performance. As competitive forces intensify, the need for firms to develop a flexible organizational structure to leverage supply chain integration practices will increase. The results of this research could provide organizational leaders more insights into increasing supply chain integration efforts and improved firm performance through flexible culture alignment.</p><p>

<p> Lean manufacturing is a collection of management practices that minimize resources used in the company&rsquo;s transformation process through systematic reduction of process waste. Some lean business practices may harm workers causing muscular-skeletal disorders, mental stress, and both mental and physical fatigue, leading to reduced productivity and labor loss through burnout, absenteeism, presenteeism, and turnover, thus increasing labor cost. In this exploratory qualitative case study, the researcher evaluated effects experienced in an exemplar lean production facility using exploratory structured interviews, examining worker outcomes, relationships between leaders, system design, and operation, and worker motivations for engaging in continuous improvement. The researcher interviewed 22 people working in an exemplar lean production facility. Findings included the discovery of a highly structured bureaucracy led by value-based leaders. The bureaucracy freed workers of responsibility for process outcomes, and enabled workers to enact system improvements. The researcher concluded that an enabling bureaucracy led by authentic value-based servant leaders contributed to the success of the lean production system. The researcher also concluded that servant leadership, where the growth and development of workers&rsquo; leadership skills were the leader&rsquo;s focus, led to a high level of worker engagement in process improvement activity. </p><p>

<p> The recent emergence of social media and online retailing become increasingly important and continue to grow. More and more people use social media to share their real life to the digital world, at the same time, browse the virtual Internet to buy the real products. In the process, a huge amount of data is generated and we investigate the data and crowdsourcing for areas of the public transportation and last-mile delivery for online orders in the perspective of data analytics and operations optimization. </p><p> We first focus on the transit flow prediction by crowdsourced social media data. Subway flow prediction under event occurrences is a very challenging task in transit system management. To tackle this challenge, we leverage the power of social media data to extract features from crowdsourced content to gather the public travel willingness. We propose a parametric and convex optimization-based approach to combine the least squares of linear regression and the prediction results of the seasonal autoregressive integrated moving average model to accurately predict the NYC subway flow under sporting events. </p><p> The second part of the thesis focuses on the last-mile same-day delivery with store fulfillment problem (SDD-SFP) using real-world data from a national retailer. We propose that retailers can take advantage of their physical local stores to ful?ll nearby online orders in a direct-to-consumer fashion during the same day that order placed. Optimization models and solution algorithms are developed to determine store selections, fleet-sizing for transportation, and inventory in terms of supply chain seasonal planning. In order to solve large-scale SDD-SFP with real-world datasets, we create an accelerated Benders decomposition approach that integrates the outer search tree and local branching based on mixed-integer programming and develops optimization-based algorithms for initial lifting constraints. </p><p> In the last part of the dissertation, we drill down SDD-SFP from supply chain planning to supply chain operation level. The aim is to create an optimal exact order ful?llment plan to specify how to deliver each received customer order. We adopt crowdsourced shipping, which utilizes the extra capacity of the vehicles from private drivers to execute delivery jobs on trips, as delivery options, and define the problem as same-day delivery with crowdshipping and store fulfillment (SDD-CSF). we develop a set of exact solution approaches for order fulfillment in form of rolling horizon framework. It repeatedly solves a series of order assignment and delivery plan problem following the timeline in order to construct an optimal fulfillment plan from local stores. Results from numerical experiments derived from real sale data of a retailer along with algorithmic computational results are presented. </p><p>

<p> Global optimization problems sometimes attain their extrema on infinite subsets of the search space, forcing mathematically rigorous programs to require large amounts of data to describe these sets. This makes these programs natural candidates for both vectorization methods and parallel computing. Here, we give a brief overview of parallel computing and vectorization methods, exploit their availability by constructing a fully distributed implementation of a mathematically rigorous Vector Parallel Branch and Bound Algorithm using MATLAB&rsquo;s SPMD architecture and interval arithmetic, and analyze the performance of the algorithm across different methods of inter-processor communication.</p><p>

<p> Analyzing fact based preventive approach to address foreign material contamination in the food industry is a necessary analysis, focused on using statistical evaluations to analyze the disturbing trend of foreign material food recall in the meat and poultry industry today. Even though recalls due to microbiological contaminations and allergens seem to get more media attention, foreign material meat and poultry food contaminations are also on the rise and the market is starting to show disturbing trends of increasing volumes of products that are recalled due to potential adulteration. </p><p> Unfortunately, tighter regulatory oversight and new food safety modernization acts have not demonstrated significant success towards reducing the occurrence of these foreign material food recalls. It appears that the incident rates have remained somewhat flat year over year, but the volume of product that are being destroyed due to extraneous material contaminations continues to show exponential increase. </p><p> Food producers cannot continue to conduct business as usual in a world that is constantly changing. They must begin to adapt and invest in technology and in fact based foreign material prevention initiatives, in order to close the disparity in technology between the production equipment and the foreign material detection equipment. </p><p> The outcome of my research has suggested that maintaining a status quo to foreign material prevention has not proven successful in limiting recall occurrences in the food industry. The research supports that a switch to fact based prevention approach can yield superior outcomes that are beneficial to both the food manufacturers and food consumers.</p><p>

The purpose of this research is to propose a leadership model for Chinese enterprises which could be suitable to the current diverse and changing environment in China. The Chinese business environment is under extraordinary pressures and its organizations face many challenges including integration into the global market. In the face of these challenges, it is very important to enhance the competitive position of Chinese organizations. A critical aspect of such an enhanced position is the leadership and management of Chinese businesses and enterprises. The current ideal leadership behaviors in contemporary China appear to be quite different from the more traditional style since leaders are challenged by a changing business environment driven by global dynamics and changing skills and expectations in the workforce. Chinese managers and leaders have more opportunities to be exposed to and draw from Western advanced managerial theories since China has largely opened itself to the world. Chinese leadership behaviors are none-the-less sculptured by Chinese customs, and leaders still carry on some traditional ways that reflect their culture. This study examines descriptions of preferred Chinese leadership behavior generated from an elite group of Chinese MBA students, themselves having been leaders in modern Chinese businesses. It proposes a leadership model which combines old and new styles together in a way designed to improve not only productivity and performance but also the relationship and connection with followers in order to lead Chinese organizations to success.

This study is concerned with the practicability of using operations research in a small business. For purposes of the study, operations research is regarded as a separate management function for applying scientific methods to the understanding of the operations of goal-directed organizations. A small business is defined with regard to the size of its operations as having a value added of less than five million dollars per year. An examination of recent surveys demonstrates that operations research is a prevalent, growing and valuable management aid in large and medium sized companies. They also provide evidence that OR is not used extensively in small business. On the other hand, statistics on business failures and reports of research on the management of small companies provide evidence that small businesses have management problems which possibly could be solved by operations research. A survey of local small business management was conducted principally to determine the extent to which operations research is used by small companies, the reasons for non-use of OR by most small businesses and the existence of operating problems which might be effectively solved by operations research. This survey, as well as other evidence indicates that operations research is used to a very limited extent by small business. The reasons for non-use are: 1) the non-analytical approach of small business management, 2) the managers' lack of familiarity with operations research, 3) the lack of trained personnel, 4) the unavailability of accurate, relevant data, 5) the high cost of leasing and operating electronic computers and 6) the opinion that OR is not economical for small business. This survey and other research has identified small business problems to which OR might effectively be applied. Retaining consultants is a means of overcoming the lack of trained personnel especially if the small business maintains a continuing relationship with a consultant who has a small, flexible operation and the ability to assist in other management functions. Computer time-sharing and computer service bureaus are inexpensive means of obtaining the computer capability which is often necessary for operations research. Small computers may also be feasible for a small business if it has enough other data processing work. A case study of a local small business identified sales forecasting, capital budgeting, production scheduling and inventory control as areas in which operations research could possibly contribute towards the Company's goals. Formulation and testing of decision rules for inventory management and estimation of the costs of an inventory control system for the Company demonstrate that operations research is practical for this small business. / Business, Sauder School of / Graduate

Variational inequalities have been used to study problems involving partial differential equations with unilateral constraints, such as free-boundary problems. They have also gained much recent interest in the field of operations research, particularly in the study of competitive equilibrium problems. The main focus of this work is to develop efficient algorithms for the computation of large-scale economic equilibria under weaker conditions than those considered previously. The prototype that we use in the analysis is the spatial market equilibrium system with direct price functions. We take advantage of the special structure of the variational inequalities, hence reformulate the problems, via a dual approach of Mosco and a linear algebra argument, as multivalued equations involving two maximal monotone operators. We then apply a relaxed proximal point method with variable parameters to the new formulation. In finite dimensions, we prove that the splitting sequences so generated are convergent to the equilibrium and the Lagrange multipliers, respectively. We also develop variational inequality formulations for migration networks and spatial market systems with goaling constraints. Based on the given economic equilibrium conditions, we establish the corresponding variational inequality formulations. In the second case, we provide direct equivalence proof that is motivated by the governing economic conditions. Essentially, we establish that the economic conditions are the dual forms of the corresponding variational inequalities. By applying the theory of variational inequalities, we then study the qualitative properties of these spatial equilibrium systems. In particular, we show the existence and uniqueness of the equilibrium in each case, assuming some monotonicity conditions that can be interpreted economically. We then apply the above numerical scheme to the variational inequality formulations of spatial equilibrium systems. As a result, we obtain a class of methods of multipliers for the computation of the studied economic equilibria. The methods so derived have an important feature that they require only monotonicity instead of strong monotonicity of supply price functions and demand price functions. They still require strong monotonicity of transaction cost functions. Finally, since they are splitting algorithms, they are suitable for decomposing large-scale problems. With a sequence of penalty parameters being set properly, each split part can then be computed sequentially or parallelly.

Whatever the economic entity, firm, industry, or nation, intensified worldwide competition has increased the need for effective competitive strategies and renders more pressing the need for methods to analyze swelling volumes of information prior to making any decision. A successful strategy is the equivalent of an efficient production plan, allowing a player to operate on the frontier of its feasible achievements. In practice however, such frontiers are not known and have to be estimated empirically. Locating an empirical frontier is at the core of Data Envelopment Analysis (DEA), a mathematical programming technique developed by Charnes, Cooper et al. in 1978 to evaluate the relative performance of decision-making units (DMUs). Several models have since emerged, all aiming at the identification of which of n DMUs, each characterized by s outputs and m, determine an envelopment surface. DEA therefore represents a methodological opportunity for the strategy field. The viability of DEA rests on its ability to foster sound economic decisions and the economic principles embedded in DEA performance evaluations must be clearly enunciated. The overall purpose of this research is hence twofold: (1) the integration of DEA with production theory via the concepts of efficiency; (2) the formalization of DEA as a tool for strategic planning. This dissertation develops a new measure of efficiency that is shown to be superior to existing measures in terms of the number of properties it satisfies and also with respect to the economic interpretation it affords. A unifying perspective of DEA models is offered by means of a taxonomy which affords systematic connections between the various models and production theory, hence providing a consistent interpretation of all models and their limitations. A new model, called the Frontier model, is developed which strengthens the bridge between DEA and economics and addresses the measurement of economic efficiency. All developments are supported by numerical illustrations. Finally a new model, the Comparative Advantage model, is developed that adapts the methodology of DEA to identify a DMU's competitors and derive information regarding the DMU's comparative strengths and weaknesses to assist the unit in formulating its strategy. An application to regional economics using Census of Manufactures data is presented.