Doctor of Philosophy (PhD), Ohio University, 2019, Industrial and Systems Engineering (Engineering and Technology)

As a strategic decision in the supply chain design, the manufacturing system design impacts the quality, flexibility and the profitability of the entire supply chain. The global supply chain network confronts challenges such as the uncertain market demand and the global trade tariffs. The main goal of this dissertation is to design global supply chain under the stochastic demand considering manufacturing operations and the impact of tariffs. The methodology consists of eight steps. First, the local manufacturer, located in USA, groups the similar products into families to save time, effort and cost. Second, as a clustering approach, the p-median model is studied and then modified to identify families considering the minimum average family similarity. Third, the manufacturer decides the best design for the manufacturing operations, in this step, the classical-cellular manufacturing system is designed under the stochastic market demand. Fourth, the expected revenues generated by the cells open for product families, considering the expected sales and selling prices, are determined. Besides, the expected manufacturing costs including the labor, machine, material and shortage costs are determined as well. Eventually, the expected profits are calculated and the optimal number of cells is identified based on the highest profits generated. Although, the optimal design of the manufacturing system generates higher profits, the demand may not be fully covered.Fifth, based on the optimal design obtained in the third step, the optimal expected profits of the product, based on the scenarios of restrictions on their demand coverage probabilities, are determined by a proposed mathematical model. In this step, if there is no restriction, the maximum profits are made when only one product is produced and sold. This is due to that it has the lowest processing time among all products. When restrictions are applied on the demand coverage, other products are produced and sold; however, l (open full item for complete abstract)

Committee: Gürsel Süer (Advisor); Khurrum Bhutta (Committee Member); Gary Weckman (Committee Member); Tao Yuan (Committee Member); Ashley Metcalf (Committee Member) Subjects: Business Administration; Industrial Engineering; Management; Systems Science

Doctor of Philosophy, University of Toledo, 2013, Manufacturing and Technology Management

The healthcare industry in both developed and developing economies is facing many challenges in reducing cost and improving service quality. The $860 billion global pharmaceutical industry is one of the most important components of the healthcare system and it plays a vital role in improving the performance of the healthcare system. The pharmaceutical supply chain is an important business component supporting the pharmaceutical industry. At this time, People's Republic of China is placing a great deal of emphasis on improving its pharmaceutical supply chain, thus opening up this research opportunity. This research begins by studying the Chinese Pharmaceutical Supply Chain (PSC), through an in-depth analysis of a Chinese PSC member followed up by a survey of a few representative members through a questionnaire. Motivated by this initial study of the Chinese PSC and other similar supply chains, we address the inventory problems faced by such supply chains. The supply chains face multiple customer-types with different characteristics defined by price and demand. We investigate both single and multi-period models with different customer-types. In each case, we develop heuristics that find optimal or near optimal inventory strategies. We use computer simulation to investigate the effectiveness of the heuristics. We also develop some general recommendations for the managers of these supply chains.

Committee: P.S. Sundararaghavan (Committee Co-Chair); Udayan Nandkeolyar (Committee Co-Chair); Jerzy Kamburowski (Committee Member); Yue Zhang (Committee Member); Donald Saftner (Committee Member); Matthew Franchetti (Committee Member) Subjects: Applied Mathematics; Asian Studies; Business Administration; Business Costs; Entrepreneurship; Geographic Information Science; Health Care Management; International Relations; Management; Marketing; Operations Research; Pharmaceuticals; Sustainability

Master of Arts, The Ohio State University, 1967, Graduate School

Committee: Not Provided (Other) Subjects:

Master of Science in Engineering, University of Akron, 2022, Civil Engineering

The main goal of this study is to help the Ohio department of transportation (ODOT) in determining areas that may have future fine or coarse aggregate supply shortfalls, estimate the economic impact of those shortfalls, and recommend appropriate policy changes to deal with these shortfalls in the aggregate supply. The state of Ohio was divided into different study regions based on aggregate quality and availability, data was obtained from ODOT and the Ohio Department of National Resources to help estimate the amounts of aggregates produced and consumed in each region. Furthermore, information for individual mines were gathered from their representatives to help estimate the local aggregate reserves in each study region, also, different models were used in this study to forecast the number of years needed to deplete these reserves. Furthermore, this study discusses information that was collected from several aggregate industry representatives about barriers to expanding existing aggregate mines or permitting new ones. Furthermore, zoning laws related to the mining industry in Ohio are examined in this study. The study also proves that the geological deposits of the limestone and sand and gravel aggregate supplies are not uniformly distributed across the state, for example limestone reserves are limited in the eastern regions, whereas sand and gravel reserves are limited in the southern and northwestern regions. This will cause an increase in the demand for imported aggregates from other regions to cover the needs for good quality aggregates or use the locally availably lower quality aggregates. The study also recognizes areas within the state that are liable to be depleted from available aggregates in the future, this may be caused by the fact that the region in question already has low reserves of that specific aggregate type or caused by the high consumption rate of aggregates in that region. For example, currently, the central region has moderate amounts of re (open full item for complete abstract)

Committee: Ala Abbas (Advisor); Nariman Mahabadi (Committee Member); Ping Yi (Committee Member) Subjects: Civil Engineering

Doctor of Philosophy, The Ohio State University, 2018, EDU Physical Activity and Educational Services

Workforce related issues in the Science, Technology, Engineering and Mathematics (STEM) fields are of great importance and have been the subject of many research studies. Academic research is essential to a country's ability to remain competitive in the global economy. Furthermore, the future economic strength of the United States is reliant on having a productive and well-prepared scientific workforce. Although behavioral and social science research (BSSR) is known to play a vital role in addressing health, security, and other complex challenges facing the country, most existing STEM workforce research does not consider BSS disciplines. Therefore, this dissertation explores academic BSSR workforce supply and demand dynamics, including various factors that influence its stability and size, by developing a simulation model framework. This research considers academic science workforce system behaviors attributable to individual level factors that influence career decisions and the eventual outcomes associated with them. Traditional labor market economics studies are based on linear estimations that do not capture the complexity associated with the overall system, including macroeconomic contexts at the regional level and individual level heterogeneity. However, other recent studies have successfully used system dynamics models to understand some of the less intuitive workforce system behaviors, such as feedback loops, though they use aggregate level factors. Thus, individual level heterogeneity has not been well represented in past academic research workforce supply and demand studies. This dissertation contributes to existing knowledge by investigating the distribution and attributes of BSS researchers employed in the academic workforce in the context of their dynamic interactions with top research universities. The primary research question is how does the relationship between individual BSS researcher characteristics and R1 universities' hiring decisions combin (open full item for complete abstract)

Committee: Joshua Hawley Ed.D, (Advisor); David Stein Ph.D. (Committee Member); Anand Desai Ph.D. (Committee Member) Subjects: Education

Master of Science (MS), Ohio University, 2017, Industrial and Systems Engineering (Engineering and Technology)

The main purpose of this thesis is to design a global supply chain network for a pharmaceutical company located in Puerto Rico, which manufactures blood sugar strips products. As a design aspect of supply chain, layered cellular manufacturing systems consist of dedicated, shared and remainder cells are considered. One of the main differences between classical cellular manufacturing systems and layered cellular manufacturing systems is, in layered cellular design, some cells may needed to be utilized by various parts of product families. Depending on the required demand and similarity in essential processes or manufacturing characteristics for each product family, products are grouped together and form a product family. If the product family assigned to one cell and just one product family utilizes that cell, the cell is a dedicated cell. Shared cells and remainder cells are employed by, two families and three or more families, respectively. In the first part of this study, a new heuristic layered-cellular manufacturing design approach is proposed and later in the second part, two mathematical models are proposed. The first one is with the objective of minimizing number of cells and cost of opening cells, and the second one is maximizing Net Present Value considering budget limitations for the whole manufacturing system. In the first step, the required number of cells are determined for a product family to meet an acceptable demand coverage (MADC) percentage. It is assumed that customer demand follows normal distribution with the established parameters mean (µ) and standard deviation (s). An attempt is made to increase the utilization of each cell by combining multiple families (thus creating shared and remainder cells) to increase the utilization of each cell as long as it is economically acceptable. As demand coverage increases, revenue also increases. However, this also increases operational costs. The expected profit is calculated based on the expected cell ut (open full item for complete abstract)

Committee: Gursel Suer (Advisor); Tao Yuan (Committee Member); Diana Schwerha (Committee Member); Ashley Metcalf (Committee Member) Subjects: Industrial Engineering

Doctor of Philosophy, The Ohio State University, 1985, Graduate School

Committee: Not Provided (Other) Subjects: Economics

Doctor of Philosophy, The Ohio State University, 1952, Graduate School

Committee: Not Provided (Other) Subjects: Economics

Doctor of Philosophy (PhD), Ohio University, 2016, Industrial and Systems Engineering (Engineering and Technology)

This dissertation aims to fulfill the gap of designing the supply chain system as a whole and looking at overall design across the supply chain of the company in the long term rather than short term. This dissertation is inspired from the window manufacturer which manufactures and distributes vinyl windows to meet new construction and replacement/remodeling sector demand. In this dissertation, complementary analytical models are discussed to determine efficient way to design a supply chain network. Mainly, design aspect and operational aspect of a supply chain system are considered. In the design aspect, number of manufacturing facilities, location/allocation decisions are determined. Then, the number of distribution centers, location and allocation decisions are made. Continuing with that, manufacturing configuration of each individual manufacturing facility is designed in detail and analyzed. In the proposed layered cellular manufacturing system design, based on the demand and processing requirements, products are grouped into product families and assigned to dedicated, shared and remainder cells. In the operational aspect, based on the designed manufacturing system, cell loading and product sequencing are performed. Moreover, vehicle routing system is designed to reach out the end customers in the supply chain system. All in all, this dissertation is unique in the sense of covering different levels of supply chain planning and decisions with nested approaches of facilities location, manufacturing system design, network design and vehicle routing design. New mathematical models and various new heuristic approaches are proposed to design a supply chain system in the presence of high-volume and low-volume windows demand.

Committee: Gürsel A. Süer PhD (Advisor); Faizul Huq PhD (Committee Member); M. Khurrum Bhutta PhD (Committee Member); Dale Masel PhD (Committee Member); Diana Schwerha PhD (Committee Member) Subjects: Engineering; Industrial Engineering; Operations Research

Doctor of Philosophy, University of Toledo, 2015, Civil Engineering

Rainwater harvesting can be a strategy to address challenges with urban water and wastewater infrastructure such as leakage, underfunding energy usage and combined sewer overflow. Rainwater harvesting system has been used for centuries to meet urban water demands such as toilet flushing, lawn irrigation, cleaning and recreational activities. Of these uses of harvested rainwater, toilet flushing is more common as it constitutes a higher percentage of indoor water use. Life cycle assessment is becoming a powerful tool to estimate environmental sustainability of rainwater harvesting systems. With growing interest in rainwater harvesting systems, it is now essential to understand and estimate the factors affecting its environmental sustainability to better design the system as well as to provide a framework for future researchers. Three research needs were identified and addressed in this study. Knowing that the prior studies lacks generalization of results to other cases, a water demand to supply ratio (D/S) ratio was proposed and demonstrated to estimate environmental impacts from rainwater harvesting systems. A decision framework was also proposed based on the result to help designers and practitioners estimate the environmental impacts without much effort. This study hypothesized that there is a lack of consistency in the analysis of rainwater harvesting systems. Supply and demand based approach was compared for rainwater harvesting system at ten climatic regions with one cubic meter of rainwater supplied and sanitation service in the building throughout its life time as respective functional units. Unexpectedly, the result showed that the region with lower environmental impact for one functional unit did not necessarily have lower impacts for the other functional unit making it clear that regional preference for rainwater harvesting system depends on the specific goal to be met: using harvested rainwater as a potential supplemental source versus using it to meet th (open full item for complete abstract)

Committee: Defne Apul Dr. (Committee Chair); Steven Burian Dr. (Committee Member); Ashok Kumar Dr. (Committee Member); Gruden Cyndee Dr. (Committee Member); Seo Youngwoo Dr. (Committee Member) Subjects: Civil Engineering; Environmental Engineering; Water Resource Management

Doctor of Philosophy (PhD), Wright State University, 2015, Engineering PhD

Part demand forecasting methods assume that the demand for a part over time follows a predictable pattern, and that the patterns observed in historical data provide a reliable indication of future demands. Generally, forecasting studies focus on topics such as: the span of time from which to sample the historical data, an assessment of data in order to find weekly or annual patterns, and the assignment of probabilities of different demand quantities in any given time period. Using the demand models derived from these forecasting methods, inventory decisions are made--decisions which directly impact operating cost and equipment availability. Like most general part demand forecasting methods, aircraft spare part demand forecasting considers historical trends in order to predict future demand. It is a well-known practical observation that aircraft spare part demands are often very erratic (quantity variability), intermittent (variable in timing), and otherwise unpredictable. However, contemporary science does not explain the causes of these variations, and suffers from very poor forecasting accuracy. The objective of this research is to study the likely causes of the variations in demand quantity and from that understanding to develop forecasting methods which are more appropriate for the wearout characteristics and high reliability of many aircraft parts. As a first look at the problem, models of part failure are developed. These models are used to simulate multiple simultaneous parts operating identically. The simulations found that aircraft spare parts demands tend to be lumpy, and that this lumpiness tends to consist of two parts: a random element (called noise), and a cyclic element (called signal). These simulation results are compared to existing aircraft spare parts demand data, and similar lumpy characteristics are identified. The research then more deeply understands these elements of spare part demand lumpiness by developing equations explaining thi (open full item for complete abstract)

Committee: Frank Ciarallo Ph.D. (Advisor); Xinhiu Zhang Ph.D. (Committee Member); Pratik Parikh Ph.D. (Committee Member); Steven Demmy Ph.D. (Committee Member); Alan Johnson Ph.D. (Committee Member) Subjects: Aerospace Engineering; Industrial Engineering; Operations Research

PhD, University of Cincinnati, 2005, Business Administration : Business Administration

We examine the behavior of a manufacturer and a retailer in decentralized supply chains under price-dependent demand. We investigate the use of several price-commitment policies as coordination mechanisms. The first policy we examine is a retailer's fixed markup (RFM) policy where the retailer commits to a fixed price markup over wholesale price to determine her retail price. The second is a price protection policy where the manufacturer agrees to reimburse the retailer for decreases in the wholesale price. In our first paper we examine the effect of RFM on individual agents' profits and supply chain performance under single period, stochastic demand. Our focus here is on exogenously determined markup values and linear additive demand forms. We prove the existence of optimal pricing and replenishment policies. We also find that RFM can result in significantly greater profit for the supply chain than the price-only contract and leads to Pareto-improving solutions. The second paper extends our analysis by examining the RFM policy under both multiplicative and linear additive demand forms. We obtain closed-form solutions for both RFM and price-only policies and analytically prove that Pareto-improving solutions are not possible under iso-price-elastic, multiplicative demand. We also consider the effect of pricing power in the supply chain by varying who determines the retail price markup. Our results reveal that the effect of retailer ex-ante markup commitment is heavily dependent on both the nature of the demand function and the relative pricing power of different players in the supply chain. The final paper in this dissertation investigates a multi-period, deterministic demand setting. We compare price commitments made by both the retailer and the supplier. RFM represents the retailer's price commitment and price protection is a form of manufacturer price commitment. We prove the existence of unique, optimal pricing and ordering solutions for all policies considered. (open full item for complete abstract)

Committee: Dr. Michael Fry (Advisor) Subjects: Business Administration, Management

Doctor of Manufacturing Management, University of Toledo, 2007, Manufacturing Management

In retail stores, we often see that products are placed on sales promotion programs in a cyclical manner. Demand for the product increases during promotional period and returns to the regular level at the end of promotion. This cycle is then repeated with almost regular frequency. We refer to this demand pattern as bi-level demand and the supply chains operating in such environments are the main focus of this study. We study the problem of formulating an inventory policy in such supply chain. Because of the periodic steps in the demand function and the uncertainly of the demand, the problem is very challenging and the optimal solution is hard to obtain. First we consider only the retailer, and narrow down focus to the development of the inventory policy for such retailer operating in bi-level deterministic demand environment. We define bi-level demand problem (BDP) as finding the order quantity (how much) and ordering time (when) given the holding and ordering costs. We develop three heuristics for the BDP and a procedure for finding an optimal solution for a subset of BDP. We generated a large set of test problems using appropriate experimental design based on problem parameters and compare the performance of heuristics against lower bounds or optimal solution as the case may be. The heuristics are found to be efficient and provide close to optimal results in most cases. Next, we model a generic version of supply chain consisting of three members—the retailer, distributor and manufacturer—and focus on the problem of formulation of inventory policy for members of such supply chain operating in stochastic (uncertain) bi-level demand environment. Considering the tradeoff between ordering/setup cost, holding cost, and shortage cost, we develop three ordering policies—Moving Average Policy (simple policy), Target Inventory Level Policy (sophisticated policy), and Complete Cooperation Policy (CCP). First two policies assume supply chain members do not share any informati (open full item for complete abstract)

Committee: P. Sundararaghavan (Advisor) Subjects:

Doctor of Philosophy, The Ohio State University, 2006, City and Regional Planning

The shopping center system of a city or metropolitan area includes regional shopping centers, community centers, and neighborhood centers, each characterized by attributes such as size, layout, goods/services offered, number/type of stores, and trade area characteristics. There is a strong relationship between trade area characteristics of a shopping center and its attributes, and the shopping center systems of cities/metro areas are based on these relationships. A thorough evaluation of the trade area characteristics helps developers select the best sites for shopping centers and public officials make appropriate commercial zoning decisions. These characteristics can be proxied by demographic and socioeconomic characteristics, housing patterns, and the nature of retail competition in the trade areas. The purpose of this research is to empirically analyze the relationships between shopping center attributes and trade area characteristics, and to measure the level of geographic interdependence among consumers and shopping centers across counties and zip code areas in the state of Ohio. Two statistical techniques are used for these analyses: 1) Standard OLS Multiple Regression, 2) 2SLS Simultaneous Equations Estimation. The conceptual framework is based on Oppenheim's retail allocation model. A large database is assembled using proprietary databases, such as Directory of Major Malls, National Research Bureau, and Demographics U.S.A., and public databases, such as Census of Population and Housing and County Business Patterns. The research finds strong relationships between shopping center attributes, proxied by shopping center size, and trade area characteristics, proxied by population, income, age groups, ethnicity, etc. In addition, the research uncovers various levels of geographical interdependence across shopping centers and consumers, pointing to the nature of retail competition in a shopping center system. The level of interdependence is higher at smaller geogra (open full item for complete abstract)

Committee: Burcu Guldmann (Advisor) Subjects: Urban and Regional Planning

Doctor of Philosophy, The Ohio State University, 2003, Business Administration

The purpose of this research was to present the conceptual development of dynamic time-based postponement and empirically test it in the context of short-lived products in a supply chain formed by independent firms. Postponement, the deliberate delay of activities, is used to reduce manufacturing and logistics costs while maintaining or increasing product availability. Postponement as described here is time-based because only the time when activities are performed is changed, not the design of the product, the manufacturing process, or the supply chain network. It is dynamic because it represents a method for capturing a number of managerial objectives that change within a short time horizon. The following are the major conclusions of this research: 1. Adapting inventory policies across a supply chain, from speculation to postponement, in short periods results in cost savings to the supply chain while allowing managers to comply with strategic objectives such as meeting strict customer service levels. In this research setting, implementing dynamic time-based postponement resulted in a cost savings of between $5.3 and $6.9 million annually while improving product availability from approximately 92% to 99.5%. 2. Confidentiality remains the biggest hurdle to achieve integration in the supply chain. Despite the closeness of the relationships among the members of the supply chain, there was reluctancy to share cost data. Suppliers felt they were at risk of giving away information that could be used to negotiate better deals. 3. Dynamic time-based postponement represents true implementation of collaborative replenishment because it's a method for managing the product flow throughout the life cycle of a product across the supply chain. There are three differentiating aspects of this dissertation. First, this is supply chain management research; that is, research that views a supply chain formed by independent organizations holistically and that extends a dyad. Second, post (open full item for complete abstract)

Committee: Douglas Lambert (Advisor) Subjects:

PHD, Kent State University, 2011, College of Business and Entrepreneurship, Ambassador Crawford / Department of Management and Information Systems

Supply chain coordination has attracted much attention lately. On the one hand, it helps create more streamlined business processes and enables cost reduction. On the other hand, supply chain members may become more concerned about their own individual profits than the overall supply chain profits. However, the question of how to divide total profits fairly among supply chain members still exists, especially in a stochastic demand market. Therefore, drawing from the accounting concept of transfer prices, this research will complement the research stream of fair division of supply chain profits among supply chain members and should help coordinate supply chains. I first investigate fairness in supply chain profit division. Common principles of justice are used to show what conditions should be satisfied for a profit division to be fair. Thereafter, a value-sharing method based on the Shapley value from cooperative game theory (Shapley, 1953) is proposed to determine the transfer prices among supply chain members. The Shapley value solution is an appealing allocation rule since it takes into account the potential payoff from alternative options. Once reached, such an agreement could simplify the process of bargaining on transfer prices which embody fairness. To illustrate the Shapley value solution and procedures, a two-echelon supply chain consisting of one supplier and two heterogeneous retailers is examined. Each company is an autonomous profit-generating entity. Each retailer faces a stochastic demand, and thus the combined demand of the supplier from the two retailers is also random. In addition to their independent operations, each company has the option to conduct transactions for the same product from external markets. My goal is to figure out ideal transfer prices for products delivered among supply chain members. These transfer prices will achieve the suggested profit allocations among the three companies. This research will contribute to the literature i (open full item for complete abstract)

Committee: Marvin D. Troutt PhD (Committee Co-Chair); Eddy Patuwo PhD (Committee Co-Chair); Alfred L. Guiffrida PhD (Committee Member); Emmanuel Dechenaux Phd (Committee Member) Subjects: Management

Doctor of Philosophy, Case Western Reserve University, 2009, Management

It is a well-accepted consensus in the literature that technological change is a key source of entrepreneurial opportunity. This work investigates the nature of the relationship between opportunity and the business cycle by examining the relationship between technological change and the business cycle. We use the application dates of the top 1% of US patents in terms of citations received and match these to a monthly series of economic expansions and contractions as defined by the NBER for the time period January 1973 to December 1992. The opportunity literature identifies two broad schools of thought; counter-cyclical arguments that suggest economic contractions are fertile times for the emergence of opportunity due to the release of resources previously employed or due to the opportunity cost of redirecting productive resources in times of economic expansion to new projects, and pro-cyclical arguments that suggest that access to financing or access to markets is enhanced during economic expansions thereby facilitating opportunity emergence. We find a strong pro-cyclical relationship for technological change in the private sector but a clear counter-cyclical relationship when considering the public sector. Further, the industries of focus between the two are quite different. If we accept, as Schumpeter argues, that technological change is the most significant source of entrepreneurial opportunity, then the resulting temporal pattern of technological change implies a temporal pattern for the emergence of entrepreneurial opportunity. Implications for both the entrepreneur and government are discussed.

Committee: Bo Carlsson (Committee Chair); Leonard Lynn (Committee Member); Susan Helper (Committee Member); Nicola Lacetera (Committee Member) Subjects: Economics; Management

Doctor of Philosophy (PhD), Ohio University, 2013, Mechanical and Systems Engineering (Engineering and Technology)

Strategy denotes actions or patterns of actions intended for the attainment of goals. In an organizational setting, the term strategy covers more than just intended or planned strategy; it also includes the sequence of decisions that exhibit posteriori consistencies in decisional behavior, involving the selection of product markets or industries and the allocation of resources among them. Within the broader purpose of developing a decision making framework for competitive strategy development practices, the thrust of this study is to investigate the impact of environmental uncertainty on corporate strategy, and the influence of corporate strategy on business performance, operational structure and market dynamics. Another incidental purpose of the study is to review, classify, clarify, define, and integrate ideas and concepts from diverse disciplines including Engineering, Economics and Business Administration to consequently establish a strategic decision making framework. The factors influencing the short term and long term standing of companies in a particular market are focused with the objectives of increasing the business capability and profitability as well as improving the market share. The case studied is the global blood sugar monitoring industry. The demand structure of the market is modeled considering four major companies in three regional markets; Asia, Europe, North America. LifeScan Inc., a Johnson & Johnson Company, is selected as the focus of greater discussions. The decision making framework is established for LifeScan Inc. incorporating a layered cellular manufacturing design integrated with different supply chain alternatives. The framework is then employed in a multi-period strategic analysis where competition games are developed and studied in three categories; price competition, quality/reputation competition and product competition. The outcomes of different competition strategies are presented and evaluated in terms of profitability and (open full item for complete abstract)

Committee: Gursel Suer (Advisor); Douglas Adie (Advisor); David Koonce (Committee Member); Dusan Sormaz (Committee Member); Namkyu Park (Committee Member); Ana Feger (Committee Member) Subjects: Business Administration; Economics; Industrial Engineering