Thesis (Ph.D.)--Massachusetts Institute of Technology, Sloan School of Management, Operations Research Center, 2000. / Includes bibliographical references (leaves 103-112). / This thesis describes two applications of Operations Research to the field of industrial procurement, addressing problems encountered in supplier selection and supplier control, respectively. The first part addresses the problem of designing multi-item procurement auctions in capacity-constrained environments. Using insights from classical auction theory, we construct an optimization based auction mechanism ("Smart Market") relying on the dynamic resolution of a linear program minimizing the buyer's cost under the suppliers' capacity constraints. Based on the optimal allocation corresponding to each set of bids, suppliers can respond by modifying their offers, giving rise to a dynamic competitive bidding process. A first contribution of our work is the solution we develop to assist suppliers, a bidding suggestion device based on a myopic best response (MBR) calculation solving an inverse optimization problem. The second main contribution is the analytical study of the bid profile sequences arising in this smart market within a game-theoretic framework assuming linear costs for the suppliers. Under a particularly weak behavioral assumption and some symmetry requirements, we establish an explicit upper bound for the winning bids when the auction terminates as a function of the market environment parameters. This bound constitutes a performance guarantee from the buyer's perspective, and provides insights on how capacity constraints affect relative market power. We then formulate a complete behavioral model and solution methodology based on the MBR rationale and the concept of local Nash Equilibrium, and argue its realism. We derive analytically some structural and convergence properties of the MBR dynamics in the simplest non-trivial market environment, suggesting further possible design improvements, and obtain insights on market behavior, efficiency and incentive compatibility issues through numerical simulations. In particular, experiments tend to show that suppliers might be relied upon to provide their own capacity information when procurement contracts are properly designed. The second part is motivated by a strategic challenge faced in particular by electronic goods manufacturing companies. Because most of their assembly operations are highly automated, procurement delays typically account for most of the total production lead-time, and have a major impact on inventory costs. However, in an increasingly global outsourcing environment, these delays can be both long and uncertain. This leads us to examine the problem of optimally procuring components in a single-product stochastic assembly system. We consider a model where product demand follows a stationary Poisson process, assembly is instantaneous, and unsatisfied demand is backordered. The suppliers are uncapacitated and the components have independent but non-identically distributed stochastic procurement delays. The following class of policies is considered: The finished goods inventory is initially filled to its base stock level, and each customer order triggers a replenishment order for a component after a component-dependent postponement lead time. The objective is to minimize the sum of holding and backorder costs in steady-state over this class of replenishment policies. To keep the analysis tractable, we assume that no mixing occurs between component orders (synchronization assumption). Combining classical queueing network theory with original results concerning a distributional property we call closure under maximization and translation (CMT), we obtain a near-optimal solution in closed-form. We then demonstrate through simulation, using industrial data from a Hewlett-Packard facility, that the policy we derived significantly outperforms other policies commonly used in practice. In addition, we show that it is quite robust with respect to various model assumptions, except the synchronization one. We thus conclude that this work is potentially amenable to implementation in the settings where this assumption is not exceedingly demanding. Moreover, we believe that the CMT distributions we introduce could also prove useful in a variety of applications beyond the context of supply chains, such as project management, reliability analysis, and the study of natural extreme phenomena. / by Jérémie Gallien. / Ph.D.

This research is a case study based on an entrepreneurship located in Henderson, Kentucky called HorseFeathers Gifts. HorseFeathers Gifts supplies handmade, vintage-inspired jewelry and accessories to customers all over the world. The case study documents the path taken by HorseFeathers Gifts’ owners, showing exactly how the entrepreneurship reached the successful position that it currently holds. Based on the case studies available and a review of the literature, it is apparent that no other case studies like this one exist. Information for this case was gathered by interviewing both owners of HorseFeathers Gifts. The interviews helped me to learn about the business’ story from the day it was first engendered until the present day. This case study displays the business’ processes, successes, and failures, and ultimately gives struggling or aspiring entrepreneurs advice on how to better their own chances of business survival.

According to the Code on Corporate Governance Practices (CG Code), listed firms should be overseen by a board of directors that promotes the success of the firm through effective direction and supervision of the listed firm’s affairs. Remuneration paid to directors should be sufficient to attract and retain directors of a caliber required to run the company successfully, but companies should avoid paying more than is necessary. The board should appoint a remuneration committee consisting wholly or mainly of non-executive directors and chaired by a non-executive director. The role of the committee is to make recommendations to the board on executive director remuneration in all of its forms, drawing on outside advice as necessary. According to the CG Code, the committee should consult with the chairman of the board and/or chief executive officer regarding its proposals relating to the remuneration of other executive directors. However, as many listed firms in Hong Kong are majority-owned by individuals and their families, the positions of the chairman and/or chief executive officer are usually held by family members who can influence the level of remuneration paid to directors. In an effort to assess how well the CG Code works, this study examines whether directors’ remuneration is influenced by independent non-executive directors where the chairman of the board is a family member. Findings show that since the introduction the CG Code, where the number of independent non-executive directors on the remuneration committee is high, the committee acts as means of control, which leads to lower directors’ remuneration than in situations where family members have more influence on remuneration committee decisions.

This thesis seeks to formulate concepts and develop methods that facilitate the mining of urban big mobility data. Specifically, the aim of the formulations and developed methods is to identify and predict certain events that occur as a result of urban mobility. This thesis, studies unexpected gathering and dispersal events. A Gathering event is the process of an unusually large number of moving objects (e.g. taxi) arriving at the same area within a short period of time. It is important for city management to identify emerging gathering events which might cause public safety or sustainability concerns. Similarly, a dispersal event is the process of an unusually large number of moving objects leaving the same area within a short period of time. Early prediction of dispersal events is important in mitigating congestion and safety risks and making better dispatching decisions for taxi and ride-sharing fleets. This thesis solves the problems of early detection and forecasting of gathering and predicting dispersal events. Prior work to detect gathering events uses undirected patterns which lack the ability to specify the dynamic flow of the traffic and the destination of the gathering. Forecasting gathering events is a predictive approach as apposed to descriptive approaches of detection. This thesis is the first to use destination prediction to forecast gathering events. Moreover, the presented destination prediction technique relaxes independence assumptions of related work and addresses the resulting challenges to achieve superior performance. Literature of dispersal event prediction solves this problem as a taxi demand prediction problem. Those methods aim at predicting the regular pattern and are unable to predict rare events. This thesis presents the SmartEdge Algorithm for early detection of gathering events. SmartEdge outputs a gathering footprint that specifies gathering paths and gathering destination. To forecast gathering events, this thesis presents DH-VIGO, which uses a dynamic hybrid model to forecast rare gathering events ahead of the time. Comprehensive evaluations using real-world datasets demonstrate meaningful results and superior performance compared to baseline methods. To predict dispersal events, this thesis uses a two-stage framework based on survival analysis called DILSA+, to predict the start time of the event and an event demand predictor to predict the volume of the demand in case of a dispersal event. Extensive evaluations on real-world data demonstrate that DILSA+ out-performs baselines and can effectively predict dispersal events.

In this dissertation, I examine two main topics in corporate finance: executive compensation and corporate investment. First, in the chapter titled “Import Penetration and Executive Compensation”, we investigate the impact of import penetration on executive compensation. We find that import penetration reduces executives’ total compensation, stock grants, and opportunistic grant timing, suggesting that competition mitigates agency problems and the need for conventional alignment mechanisms. Furthermore, we show that import penetration increases option grants and option duration, thus incentivizing more innovation and risk-taking. Second, I study the relationship between entrenchment and corporate investment. In the chapter titled “Entrenchment, Managerial Shirking, and Investment”, I find that entrenchment reduces capital expenditures, R&D, and productivity, weakens a firm’s competitiveness in the product market, and diminishes firm value. These findings are consistent with the shirking hypothesis that entrenchment enables managers to evade the responsibilities of overseeing investment projects.

Research has determined that measures of general mental ability (GMA) and personality are valid predictors of a wide range of work outcomes. Two of the most well established findings in the field of organizational psychology are that GMA and two of the Big Five personality traits, conscientiousness and emotional stability, predict overall job performance and training performance across all jobs. Though both GMA and personality are valid predictors of job performance, the validities of personality measures are much weaker than those observed for measures of GMA. Some argue that personality may play a larger role in predicting work outcomes than currently believed, but that current measures of personality do not capture the construct fully. Several researchers have attempted to increase the validity of personality measures by altering the items in the measures so that they refer specifically to work contexts, and others have examined the validity of observer ratings of personality. This study draws on the theory of cognitive buffering to test the possibility is that GMA itself that causes the impact of personality traits on real life performances to be limited. That is, that people may use their GMA to control the expression of their personality tendencies in their behavior. The results showed that GMA and personality interacted to predict peer ratings of personality, but not as initially hypothesized. Self-monitoring and personality also interacted to predict peer ratings of personality, but, again, not as hypothesized. Several possible explanations for the results of this study are discussed, including the notion that that individuals may make efforts to manage only those personality traits that are most relevant in given situations. Moreover, it may be the case that dispositions are less subject to the process of cognitive buffering than are emotions and affect. Limitations of this study and opportunities for future research are also discussed.

Loyalty programs for convenience stores generate consumer shopping histories that are both large in size and sparse in content. Analyzing such data with traditional basket models is computationally difficult since most models are not scalable to a large set of categories. However, analyzing large data with traditional models has important advantages: the models capture consumer (shopping) behaviors that assist managers in making strategic decisions. In this thesis, we develop two studies to analyze this large and sparse convenience store shopping data. In the first study, we bridge the gap between traditional basket model analysis and the challenges of large shopping data by developing a retail market basket modeling system that captures essential elements of consumer shopping behavior in a computationally attractive manner. An application of the model to convenience store basket data yields excellent results. The main outputs of the model (segmentation structure, cross-category dependence, price elasticities) align well with managerial intuition. Moreover, the model provides excellent forecasts to a holdout sample of consumers. Using the model, we examine the revenue impact of a change in promotion policy. In the second study, we add spatial extensions to the previous model to solve a more complex problem: retail location analysis. We develop a spatial basket model to analyze the spatial pattern of consumer heterogeneity across stores, and show how to use this model to predict the demand of a new store (without any data of consumer purchase history). The main outputs of the extended model also align well with managerial intuition. Additionally, the model provides excellent forecasts to the demand of the hold-out store.

This thesis comprises of three chapters. The first essay is titled ‘Managers: Their Effects on Accruals and Firm Policies' and is joint work with Douglas V. DeJong. The second essay is titled ‘Can the Capital Market Recognize a Manager's Financial Reporting Style?' and is sole-authored. The third essay is titled ‘Executive Compensation in a Matching Model’ and is joint work with Douglas V. DeJong, Elena Pastorino and B. Ravikumar. Chapter one investigates whether top executives have significant individual-specific effects on accruals that cannot be explained by firm characteristics. Exploiting 37 years of individual executives and firm data, we find that individual executives play a significant role in determining firms' accruals. In addition, we examine whether executives' effects on accruals are related to their personal styles in investment, financing and operating decisions. Our results show that individual executives' effects on accruals are more correlated to their operating decisions than investment and financing decisions. We also compare effects exerted by CEOs to CFOs. We find CEOs are more likely to affect accruals through firm policy decisions and CFOs are more likely to affect accruals through accounting decisions. CFOs tend to report more "solid" earnings than CEOs, i.e., CFOs are more likely to push accruals to zero. Chapter two examines whether investors can recognize idiosyncratic differences in managers' financial reporting behavior. Specifically, I investigate whether the capital market can recognize a manager's financial reporting aggressiveness and whether investors' recognition of a manager's style follows a Bayesian learning process. I use a manager's specific effect on discretionary accruals to measure her financial reporting aggressiveness. My results show that investors find earnings forecasts issued by aggressive managers to be less credible and thus respond less strongly. I also find investors follow a Bayesian learning process to identify a manager's individual style. As a manager's financial reporting history becomes longer, there is less uncertainty about the manager's true style. Consequently, the discount on the market reaction to earnings forecast news due to the manager's aggressiveness becomes larger. In sum, these results suggest that a manager's prior financial reporting history allows her to develop a financial reporting reputation, which can be inferred by investors through rationally processing historical information. Chapter three outlines our future research plan to revisit the relative importance of returns to firm-specific tenure and to general labor market experience in the labor market for executives. We shed light on the importance of explicitly accounting for an executive's firm-to-firm and job-to-job mobility, within and across firms, over the course of the executive's career in order to measure the magnitude of each type of returns.

I examine the extent to which acquirers exercise discretion in the application of FIN 48 when estimating target tax reserves. By examining the change in target tax reserves recorded through purchase accounting, I am able to hold constant the underlying tax positions, and any changes can be attributed to differences in how the managers of the target and acquirer apply the recognition and measurement principles of FIN 48. For a sample of large public-for-public M&A transactions in which the amount of target tax reserves is observable pre- and post-acquisition, approximately one third (half) of the acquirers adjust target tax reserves by more than half (a quarter) of the preexisting balance. Substantially more acquirers increase rather than decrease target tax reserves, and the average change in target tax reserves recorded through purchase accounting is $25 million. I also find evidence that the change in tax reserves recorded through purchase accounting is increasing in short-term financial reporting pressures and decreasing in the costs of overstating goodwill.

This thesis comprises of three chapters. The first essay is coauthored with Professor Matthew T. Billett and is titled ‘Asymmetric Information and Open Market Share Repurchases.' The second essay is join work with Professor Matthew T. Billett and Professor Jon A. Garfinkel and is titled ‘The Effect of Asymmetric Information on Product Market Outcomes'. The third essay is sole-authored and is titled ‘Crash Risk and Firms' Cash Policies'. Chapter one reveals cross sectional differences in undervaluation by combining open market share repurchase (OMR) announcements with asymmetric information. We find that opaque firms experience significantly larger abnormal returns than transparent firms upon an OMR. Following Ikenberry, Lakonishok an Vermaelen (1995), we strategy the sample by book-to-market, which may relate to undervaluation, and examine the effect of firm opacity within book-to-market groupings. High book-to-market opaque firms experience average three-day market-adjusted returns of 5.05% compared to 1.86% for high book-to-market transparent firms. We also document significantly positive long run post-announcement returns for opaque firms, but not for transparent firms. Our results suggest undervaluation motive for OMRs is concentrated in opaque firms, and that undervaluation due to asymmetric information attenuates at the announcement of OMRs. Chapter two explores how asymmetric information in financial markets affects outcomes in product markets. Given endogeneity concerns, we study firms in industries that experience deregulatory shocks. Post-deregulation, firms with greater opacity about their financial condition lose market share to their industry rivals. We further show that opaque firms have lower capital raising activity after deregulation. We conclude that asymmetric information in financial markets is an important determinant of product market outcomes. Chapter three examines the effect of crash risk on firms' cash policies. We find high crash risk firms which experience large negative stock returns over the fiscal year or show large conditional negative return skewness tend to hold more cash than low crash risk firms. The phenomena are more pronounced for financial constraint firms and small firms. In addition, we show that the marginal value of cash for high crash risk firms is lower compared to low crash risk firms. Based on our findings, we argue that crash risk has been taken into account when firms make their cash decisions.