http://hdl.handle.net/1903/2761 2013-06-19T08:22:41Z 2013-06-19T08:22:41Z Gunnec, Dilek http://hdl.handle.net/1903/13103 2012-10-11T02:34:28Z 2012-01-01T00:00:00Z

Title: Integrating Social Network Effects in Product Design and Diffusion Authors: Gunnec, Dilek Abstract: Connectivities among people are amplified with recent advancements in internet technology increasing the number of communication channels. Information spread over these networks strengthen the social influence among individuals and affect their purchasing decisions. In this thesis, we study three problems in the product design and diffusion context by integrating such social network effects where influence takes place over neighborhood relationship ties among the users of the product. We consider the setting where peer influence plays a significant role in a consumer's product choice or there is a tangible benefit from using the same product as the rest of one's social network. Building upon the well-known Share-of-Choice problem, we model an influence structure and define the Share-of-Choice problem with Network Effects. It is an NP-Hard combinatorial optimization problem which we solve using a Genetic Algorithm. Using simulated data we show that ignoring social network effects in the design phase of a product results in a significantly lower market share for a product. Our genetic algorithm obtains near-optimal solutions and is very robust in terms of its running time, scalability, and ability to adapt to additional constraints/variations of the model. In this setting, we introduce a product diffusion problem, the Least Cost Influence Problem, which increases the market share of a product by intervening the natural diffusion of it over the social network. This intervention is in the form of incentive supply to a group of people in a least costly way while maximizing the spread of the product. We generalize the Least Cost Influence Problem by moving away from the marketing setting and by treating the previous product as any piece of "information" that can spread over a social network by adoption. We show that this problem is polynomially solvable over tree networks under some conditions. We provide a Dynamic Programming algorithm to solve this problem and show that it can be interpreted as a greedy algorithm that gives incentives starting with the people that are least influenced by their neighbors, albeit the definition of susceptibility to influence from neighbors is updated throughout the algorithm. We introduce a two dimensional influence model and extend our modeling and solution methods for the product line design problem which involves designing multiple products within the same product line with the objective of appealing to the heterogeneous structure of the market. The first dimension of influence is the affection of individuals from using the same product, and the second dimension is the influence of using a similar product from the same product line which has a lower intensity of influence. We reexamine the Least Cost Influence Problem in the product line setting.

2012-01-01T00:00:00Z Zhong, Ming http://hdl.handle.net/1903/13098 2012-10-11T02:31:46Z 2012-01-01T00:00:00Z

Title: MODELS AND SOLUTION ALGORITHMS FOR EQUITABLE RESOURCE ALLOCATION IN AIR TRAFFIC FLOW MANAGEMENT Authors: Zhong, Ming Abstract: Population growth and economic development lead to increasing demand for travel and pose mobility challenges on capacity-limited air traffic networks. The U.S. National Airspace System (NAS) has been operated near the capacity, and air traffic congestion is expected to remain as a top concern for the related system operators, passengers and airlines. This dissertation develops a number of model reformulations and efficient solution algorithms to address resource allocation problems in air traffic flow management, while explicitly accounting for equitable objectives in order to encourage further collaborations by different stakeholders. This dissertation first develops a bi-criteria optimization model to offload excess demand from different competing airlines in the congested airspace when the predicted traffic demand is higher than available capacity. Computationally efficient network flow models with side constraints are developed and extensively tested using datasets obtained from the Enhanced Traffic Management System (ETMS) database (now known as the Traffic Flow Management System). Representative Pareto-optimal tradeoff frontiers are consequently generated to allow decision-makers to identify best-compromising solutions based on relative weights and systematical considerations of both efficiency and equity. This dissertation further models and solves an integrated flight re-routing problem on an airspace network. Given a network of airspace sectors with a set of waypoint entries and a set of flights belonging to different air carriers, the optimization model aims to minimize the total flight travel time subject to a set of flight routing equity, operational and safety requirements. A time-dependent network flow programming formulation is proposed with stochastic sector capacities and rerouting equity for each air carrier as side constraints. A Lagrangian relaxation based method is used to dualize these constraints and decompose the original complex problem into a sequence of single flight rerouting/scheduling problems. Finally, within a multi-objective utility maximization framework, the dissertation proposes several practically useful heuristic algorithms for the long-term airport slot assignment problem. Alternative models are constructed to decompose the complex model into a series of hourly assignment sub-problems. A new paired assignment heuristic algorithm is developed to adapt the round robin scheduling principle for improving fairness measures across different airlines. Computational results are presented to show the strength of each proposed modeling approach.

2012-01-01T00:00:00Z Kim, Yongjae http://hdl.handle.net/1903/13076 2012-10-11T02:35:02Z 2012-01-01T00:00:00Z

Title: ESSAYS IN (I) STRATEGIC ORDERING WITH ENDOGENOUS SEQUENCE OF EVENTS IN SUPPLY CHAIN (II) STRATEGIC MANAGEMENT OF NEW PRODUCT INNOVATION AND PROCESS IMPROVEMENT Authors: Kim, Yongjae Abstract: This dissertation discusses two research problems. First topic is strategic information management in supply chain, and second topic is analytical modeling approach in productivity dilemma. The first two chapters of dissertation discuss the impact of information asymmetry and competition on vertical contractual relationships, and risk neutral firms' strategic ordering decisions with minimal assumptions. Modern business environment caused by competition and information asymmetry plagues most firms across industries, often leading to suboptimal outcomes. Given the lead times in planning capacity, suppliers prefer earlier orders from their downstream partners (retailers). Much attention has been given in the literature to Advance Purchase Discount (APD), where the supplier lowers the wholesale price to entice the retailers to order early. In this dissertation, we suggest another avenue of early purchase model considering more realistic ways - competition between downstream retailers and information flows (from information acquisition to dissemination) in supply chain. We show that with one retailer having "better" market demand information on uncertain demand than the other, the supplier can induce earlier ordering from the better-informed retailer without any reduction in the wholesale price, or creating rationing risk. In addition, we investigate firm's information investment decisions corresponding to the timing of the orders. We extend the model with different information structures of firms such as imperfect and evolving information. In reality, firms can have more accurate market information near the selling season by acquiring it from more diverse resources. Consistent with practice, we explorer firm's equilibrium outcomes of endogenous sequencing game with this setting. The third chapter of dissertation is in the trade-off between production efficiency and new product innovation. A firm's ability to compete over time has been rooted not only in improved efficiency, but also in its ability to be simultaneously innovative (Abernathy (1978)). This trade-off between efficiency and innovation has long been discussed in the business context, but limited analytical research has been done using the `extreme value theory' (Dahan & Mendelson (2001)) to investigate this issue. Our model considers important exogenous innovation factors such as innovation characteristics (Benner & Tushman (2003)) and degree of competition, which has yielded the following theoretical results and practical implications. First, we highlight new product characteristics. If R&D projects are paradigm-shifting innovations, there is a stronger adverse effect between efficiency and innovation than incremental innovation. Second, competition results in underinvestment effort in innovation performance for the firms. For example, in the symmetric firms' competition, the optimal size of R&D projects decreased, as competition increases. On the other hand, firms are more likely to focus on process improvement activities.

2012-01-01T00:00:00Z Goh, Jie Mein http://hdl.handle.net/1903/12321 2012-02-18T03:34:00Z 2011-01-01T00:00:00Z

Title: APPROPRIATING VALUE FROM INFORMATION TECHNOLOGY IN HEALTHCARE Authors: Goh, Jie Mein Abstract: The value potential of information technology (IT) in healthcare settings has generated considerable optimism yet, significant questions remain unanswered. This dissertation employs the lens of social structure to investigate the value of information technology in healthcare situated in two distinct contexts: hospitals, that exemplify the traditional institutional form for the delivery of healthcare services, and online patient communities that represent new organizational forms enabled by IT. It seeks to address the following fundamental research questions "What is the impact of information technology in healthcare settings? How does social structure influence the appropriation of the value of information technology in healthcare?" Each of the two contexts is investigated in a separate essay, drawing upon distinct bodies of literature and using both qualitative and quantitative analytical methods. Essay 1: Evolving Work Routines: A Theory of Successful Adaptation to Information Technology in Healthcare The first essay investigates the impact of healthcare technologies such as electronic medical record systems in the traditional hospital environment. It traces the development of changes in social structure before and after an IT implementation. Using a longitudinal field study, the process of how information technology and routines interact is deconstructed. A theory of the co-evolution of routines and technology is proposed and described. Essay 2: The Social Value of Online Health Communities The second essay examines the impact of health information technology in the form of online patient communities by uncovering the social structure of the community. Using data collected from a popular online patient community, I identify the generative processes using support patterns between patients within the community. I find that online patient communities yield social value through information and emotional support to patients by enabling the transfer of support between patients with differential needs. Results also provide descriptive insights into the attributes of patients that contribute to variation in the provision of support within such online patient communities. The two studies in this dissertation make theoretical and empirical contributions. They shed light on the impact of information technology in healthcare, and further inform us about the appropriation of HIT value from a social structure perspective.

2011-01-01T00:00:00Z