Browsing by Subject "Business"

This dissertation examines what drives firms' divestiture activity and how it impacts their performance. Divestitures is defined here as the sale, spin-off or liquidation of assets from an ongoing organization. This dissertation seeks to understand what drives firms' reconfiguration activities via divestitures, and in turn how the divestiture activity impacts the future performance in terms of survival and growth. The dissertation identifies differences in the performance of a firm relative to their prior performance as a driver for divestitures, as well as other financial constraints. Moreover, it shows that, counter-intuitively, divestitures are a tool for growth and helps strong firms continue to grow and helps them avoid becoming a target for acquisitions; whereas in the case of weak firms, divesting does not help them avoid shutting down. This dissertation argues that divestitures are tools firms use to reconfigure and reallocate their financial and managerial resources; in the case of weak firms, divestitures are a mode used primarily to free the necessary monetary funds necessary for firms to address problems and regain competitiveness, whereas for strong firms divestitures are a tool to free scarce managerial resources that can be more efficiently allocated in areas that can provide further growth. This dissertation contributes to our understanding of what drives firms divestitures and corporate strategic decisions in general, and provides evidence that even firms coming from positions of strength can eliminate parts of the organization as a way to grow.

This dissertation studies coordination mechanism design for sustainable supply networks in a globalized environment, with the goal of achieving long-term profitability, environmental friendliness and social responsibility. We examine three different types of supply networks in detail.

The first network consists of one supplier and multiple retailers. The main issue is how to efficiently share a scarce resource, such as capacities for green technology, among all members with private information under dynamically changing environment. We design a shared surplus supply agreement among the members which can lead to both efficient private investments and efficient capacity allocation under unpredictable and unverifiable market conditions.

The second network is a serial supply chain. The source node provides critical raw material (like coffee cherries) for the entire chain and is typically located in an underdeveloped economy, the end node is a retailer serving consumer at a developed economy (like Starbucks Co.). We construct a dynamic supply agreement that takes into account the changing market and production conditions to ensure fair compensations so that the partners have the right incentives to work together to develop sustainable quality supply.

The third network is a stylized global production network of a multinational company consisting of a home plant and a foreign branch. The branch serves the foreign market but receives a key component from the home plant. The distinctive feature is that both facilities belong to the same company, governed by the headquarters, yet they each also have their own autonomies. We analyze the role of the headquarters in designing coordination mechanism to improve efficiency. We show the headquarters can delegate the coordination effort to the home plant, as long as it keeps veto power.

I study the effect of human capital on firms' leverage decisions in a structural dynamic model. Firms produce using physical capital and labor. They pay a cost per employee they hire, thus investing in human capital. In default a portion of this human capital investment is lost. The loss of human capital constitutes a significant cost of financial distress. Labor intensive firms are more heavily exposed to this cost and respond by using less leverage. Thus the model predicts a decreasing relationship between leverage and labor intensity. Consistent with this prediction, I show in the data that high labor intensity leads to significantly less use of debt. In the model a move from the lowest to the highest decile of labor intensity is accompanied by a drop in leverage of 21 percentage points, very close to the 27 percentage point drop in the data. Overall, I argue that human capital has an important effect on firm leverage and should receive more attention from capital structure researchers.

Furthermore, I study a two-period contracting problem in which entrepreneurs need financing but have limited commitment. If an entrepreneur chooses to default, he can divert a proportion of the project's output. Entrepreneurs are heterogeneous with respect to their ability to divert output. In particular, I focus on the special case with only two types of entrepreneurs. "Opportunistic'' entrepreneurs can divert output, but "dependable'' entrepreneurs cannot. I find that, if the proportion of dependable entrepreneurs is sufficiently high, it is optimal to write contracts that induce second period default by the opportunistic entrepreneurs. This critical proportion generally decreases with the severity of the agency problem. The model delivers both cross-sectional and time-series predictions about default, investment, and output.

This dissertation extends the economics literature in industrial organization with three empirical essays on the strategic decisions of firms in imperfectly competitive markets. Using data from the U.S. airline industry, I combine reduced-form analysis with recent econometric advances in the estimation of dynamic games to examine the market-level and industry-level behavior of oligopolistic firms. The first essay presents a framework for sensitivity analysis in merger simulation. The second essay continues the market-level analysis of merger effects by examining how airline mergers influence price dispersion. The third essay shifts focus to industry-level investment behavior, examining the role played by bankruptcy policy in disciplining capital investment.

This dissertation explores the incentive issues and strategic interactions among decentralized parties in three operations management environments: inventory systems, revenue management and healthcare policies. The first model studies the impact of multilateral asymmetric information about inventories in a two-echelon inventory systems. The second model applies optimization techniques to solve a monopolist's revenue problem where the seller's cost function is not separable across buyers with multidimensional private information. The third model uses a game-theoretical approach to study the decentralized resource allocation between self-interested countries to control an epidemic disease.

This dissertation studies the optimal control of two different dynamic systems with learning: (i) diagnostic service systems, and (ii) green incentive policy design. In both cases, analytical models have been developed to improve our understanding of the system, and managerial insights are gained on its optimal management.

We first consider a diagnostic service system in a queueing framework, where the service is in the form of sequential hypothesis testing. The agent should dynamically weigh the benefit of performing an additional test on the current task to improve the accuracy of her judgment against the incurred delay cost for the accumulated workload. We analyze the accuracy/congestion tradeoff in this setting and fully characterize the structure of the optimal policy. Further, we allow for admission control (dismissing tasks from the queue without processing) in the system, and derive its implications on the structure of the optimal policy and system's performance.

We then study Feed-in-Tariff (FIT) policies, which are incentive mechanisms by governments to promote renewable energy technologies. We focus on two key network externalities that govern the evolution of a new technology in the market over time: (i) technological learning, and (ii) social learning. By developing an intertemporal model that captures these dynamics, we investigate how lawmakers should leverage on such effects to make FIT policies more efficient. We contrast our findings against the current practice of FIT-implementing jurisdictions, and also determine how the FIT regimes should depend on specific technology and market characteristics.

This dissertation focuses on understanding how negative externalities affect managerial decisions, specifically, the resource allocation and pricing in competitive environments.

We first study optimal allocation and pricing on a network of competing buyers. Buyers have private information about the value of an item being sold (such as franchise contract, good, service). Furthermore, buyers place a premium on obtaining the item exclusively, i.e., if no competitors obtain the item at the same time. We show that the seller limited to offering posted price contracts should inflate the price in order to maximize revenues and capture the value buyers put on exclusivity. However, posted prices are not revenue-maximizing and there are theoretical barriers to discovering generic optimal allocation and pricing schemes, stemming both from mechanism design theory and computational complexity theory. We present an easy-to-implement hybrid auction-pricing procedure which revenue-dominates posted prices and is optimal in a full competition setting.

We next turn to a different type of negative externalities in which a buyer faces a possibility of losses, thus suffering a negative externality, due to scarce resource being allocated to competitors. We show that the existence of such negative externalities among market participants competing for a scarce resource allows for emergence of the no-allocation equilibrium with positive revenues for the seller. A monopolist selling K indivisible items to a large number of competing unit-demand buyers who face negative externalities whenever their rivals get the items, can exploit these negative externalities. If the number of buyers is large enough, the no-allocation equilibrium emerges: no items get allocated, yet buyers still pay the seller to avoid a potential exposure to negative externalities. We provide conditions on the magnitude of externalities and on the level of buyer competition that yield optimality of the no-allocation equilibrium.

Finally, we consider the setting where the scope of negative externalities is limited. A revenue-maximizing monopolist is selling a single indivisible good to buyers who face a loss if a rival buyer obtains it. The rivalry is modeled through a network, an arc between a pair of buyers indicates that a buyer considers another buyer its rival, and the magnitude of the loss is the private information of each buyer. First, given a network, we characterize the optimal mechanism. Second, we show that revenues depend on the network structure. Thus, in applications where it is possible, the monopolist might consider designing not only the mechanism but also the network (if not fully, at least partially). Third, we provide solutions to this joint network and mechanism design problem. Specifically, we determine revenue-maximizing rivalry networks (which in turn induce optimal mechanisms), and show that they are independent of distributional assumptions on buyers' independent private loss values, provided virtual values are bounded from zero. We achieve these results under different restrictions of how the monopolist can affect the network. When rivalry is symmetric, matchings are optimal (with at most one path on three vertices). However, asymmetric competitive relationships among buyers generate higher revenues than symmetric ones. The optimal asymmetric networks are characterized by (i) every buyer having at least one rival, and (ii) the existence of a buyer not considered a rival by anyone.

In cargo logistics, a key performance measure is transport risk, defined as the deviation of the actual arrival time from the planned arrival time. Neither earliness nor tardiness is desirable for the customer and freight forwarder. In this paper, we investigate ways to assess and forecast transport risks using a half-year of air cargo data, provided by a leading forwarder on 1336 routes served by 20 airlines. Interestingly, our preliminary data analysis shows a strong multimodal feature in the transport risks, driven by unobserved events, such as cargo missing flights. To accommodate this feature, we introduce a Bayesian nonparametric model -- the probit stick-breaking process (PSBP) mixture model -- for flexible estimation of the conditional (i.e., state-dependent) density function of transport risk. We demonstrate that using simpler methods, such as OLS linear regression, can lead to misleading inferences. Our model provides a tool for the forwarder to offer customized price and service quotes. It can also generate baseline airline performance to enable fair supplier evaluation. Furthermore, the method allows us to separate recurrent risks from disruption risks. This is important, because hedging strategies for these two kinds of risks are often drastically different.

This dissertation is written in three progressively restrictive parts. Part I is a set of two expansive essays on collaborative supply chain management that proposes several new perspectives and interconnections between current day global business and economic issues, and the evolving supply chain structures and decision-making paradigms that depend on extensive inter-firm collaboration. Part I also develops new guidelines for both practitioners as well as academic researchers in their quest to incorporate collaborative requirements as an explicit component of existing planning frameworks and modeling approaches. Part I further comments on how the technological evolution of manufacturing, service, and general business processes have led to decentralized structures that require a fundamentally collaborative approach to the planning of such processes. We also argue that existing supply chain decision-making and planning approaches are modeled in the fashion of corporate and enterprise resource planning systems, which given their scope, limit the extent of collaboration in both planning and in execution. The arguments and discussion in this part are not specific to any particular supply chain function and is without technological bias. The frameworks presented in Part I are also unified in their approach to managing supply chains of service providers, manufacturing partners, or some combination of both types of activities. This unified presentation is also a fundamental contribution of this first part of the dissertation.

Part II of the dissertation, while still expansive in scope of application and the range of industry sectors and supply chain environments discussed, develops the ideas presented in Part I for more specific (or functional) categories of business processes. A commonly accepted categorization of operational processes, at least in manufacturing settings, is into (i) product design and development or related projects, which are akin to services in the nature and interaction between implied tasks, (ii) procurement, production, and customer service processes, and (iii) logistics and distribution networks. Projects are typically represented as a network of inter-related activities bound by a common purpose, and by a time-line dictated by a finite product or project life cycle; activities are also sometimes defined and created in response to project environments. Processes in the procurement, production, customer service, or logistics domains, on the other hand, are typically modeled as a set of inter-related but more loosely coupled activities that are repeated indefinitely across multiple product or project life cycles. Our primary concern in Part II is to understand environments where projects and processes span multiple firms, and therefore require a collaborative effort, not only for executing the activities entailed, but also in the planning of the tasks and projects.

Modeling of supply chain management problems (such as those discussed subsequently in Part III) assume that the fundamental structure of tasks and processes are at least well-defined for analysis and subsequent design of parameters for optimal performance. Often, however, the inclusion and structuring of these tasks is also a collaborative exercise that requires negotiation and careful consideration of the costs and advantages presented by alternative sets of tasks. The scope of tasks is also frequently determined by their assignment to one or more firms with differing capabilities. For example, the range of logistics activities and services provided by a specialized firm would be greater than a manufacturer assuming additional responsibility for the distribution or procurement logistics. Similarly, the capabilities of a supplier would either expand or restrict the range of tasks that would be included in the design and development of a product or a service. Therefore, Part II of the dissertation, consisting of Chapters 4 and 5, develops strategic frameworks that can allow the definition and structuring of tasks and processes in a collaborative setting. These chapters present frameworks for strategy and for defining project or process objectives which are commonly the guideposts for task definition and structuring.

These frameworks presented in Part II can also help determine the degree of collaboration either warranted or indeed suitable for different project and logistics environments. Thus, we propose that some business and technology environments call for more cohesive or coupled structuring of tasks that in turn require collaborative frameworks for planning and execution. Some other environments, either as a result of market forces or technological constraints, are a bad fit for collaborative efforts unless they are seamless and frictionless. Identifying such environments through a small set of market and technological factors is a fundamental contribution of Part II of the dissertation. Similar to our efforts in Part I, we also chart the evolution of collaborative planning and execution environments; here we adopt a more direct case based approach to illustrating issues, and related concepts. Another significant contribution of this second part is to outline how various facets of the operating environment shape the parameters of the collaborative arrangements between partner firms. In particular, we address the environmental and strategic forces that motivate a model of work sharing in environments where collaboration is not a technological requirement. Thus, we address the fundamental value proposition in collaborative logistics management for the outsourcing provider and the contracting firm, and discuss how product or process technology and structure influences such choices by firms.

Part III, which is more restrictive in its statements and conclusions, is devoted to models of collaborative supply chain management that are motivated by the imperatives outlined in Part I, but whose elements are defined by the strategic frameworks and structuring guidelines of Part II . While Part III derives guidance from Part II in the formulation of its models, it can also be viewed and read independently for its contributions to the (related) academic literature. Part III consists again of two independent modeling exercises. Through either of these exercises, we address two of the most important problems in collaborative supply chain planning: partner selection, or alternatively task and project assignment, and decentralized capacity management in a supply chain or logistics environment. These models describe two environments where collaborative planning is vital to the success of firms: (i decentralized and collaborative projects or programs that frequently determine how supply chains of diverse firms are structured and take form, and (ii) decentralized logistics and transportation systems where firms in a supply chain must invest in common infrastructure, and further determine the material flows utilizing such infrastructure. In both cases, we show how decentralized structures can be inefficient relative to centralized decision-models, while characterizing the equilibrium behavior of firms in decentralized decision-frameworks under the proportional risk-sharing regimes. We then provide mechanisms that can coordinate the decentralized systems. These mechanisms turn out to be highly conditional on the rules of information exchange and the decision-hierarchies in the supply chain, and therefore can claim to remedy coordination problems in only a subset of collaborative environments. However, this subset -- as it turns out -- is not insignificant, as many different supply chains operate with such restrictive information exchange and decision-hierarchies.

In the next introductory chapter, we provide a more detailed synopsis of Parts I-III with the objective of identifying the considerable interconnections between the various chapters within the three parts. We also aim to highlight the contributions of the work to various streams of academic literature. Throughout this dissertation, we strive to maintain a dual tone of discussion: One for practitioners and researchers in the field of operations strategy that focuses on synthesizing insights on supply chain structure and the crucial elements of collaborative supply chain planning for the sake of managers, and the second theme focusing on more fundamental operations research problems underlying the collaborative planning environment.

This dissertation develops new theory and evidence to show that human-capital based competitive advantage of firms varies with external markets, firm structure, and firm openness to factor markets. The dissertation includes three empirical studies.

The first study examines how labor market frictions due to strict employment protection regulations can be a source of competitive advantage for affiliates of corporate groups over standalone firms in environments where benefits from internal market flexibility are high. Utilizing the variation in labor laws and capital market development across 16 West-European countries, the study finds a stronger competitive advantage for group affiliates in countries with rigid labor markets, but flexible capital markets. In these environments, group affiliates are more prevalent and they outperform standalone firms in terms of growth and profitability.

The second study examines how structural features of a firm and the nature of managerial resources interact to influence top managerial mobility in corporate groups. Using a novel dataset on intragroup managerial mobility, the study documents decreased internal redeployment of managers to affiliates with minority shareholders, especially if those managers are high-performing. These results are driven by hired managers. In contrast, family-related managers, who are related to the controlling shareholders, are more likely to be deployed to partly-owned, strategically peripheral and affiliates operating in regions where societal trust levels are low. These results suggest the importance of trust as a managerial attribute.

The third study examines how disclosure of firm performance affects top manager mobility into and out of firms. Using managerial mobility data for 610,000 managers in over 32,000 corporate groups across Europe, the study shows the key tradeoffs in managerial markets associated with disclosure: disclosing firms lose more managers, especially if firms are performing well. Importantly, those departing managers leave to larger firms and to positions of greater responsibility. However, the results suggest that disclosing firms are better able to acquire new managers from other high-performing firms. Further, survey evidence suggests that disclosing firms can mitigate managerial outflows by implementing better human capital management practices. The study contributes to understanding how firms can capture value from strategic human capital, while protecting and refreshing sources of competitive advantage that are embodied in firm's top management.

Taken together, these three studies contribute to understanding conditions under which firms can capture value from strategic human capital, and the key tradeoffs associated with accumulating and protecting knowledge resources while tapping into external knowledge flows.

We propose an approximation scheme for single-product periodic-review inventory systems with L-natural-convex structure. We lay out three well-studied inventory models, namely the lost-sales system, the perishable inventory system, and the joint inventory-pricing problem. We approximate the value functions for these models by the class of L-natural-convex quadratic functions, through the technique of linear programming approach to approximate dynamic programming. A series of heuristics are derived based on the quadratic approximation, and their performances are evaluated by comparison with existing heuristics. We present the numerical results and show that our heuristics outperform the benchmarks for majority of cases and scale well with long lead times. In this dissertation we also discuss the alternative strategies we have tried but with unsatisfactory result.

More companies are beginning to manage the environmental impacts of their supply chain in addition to their own operations. Supply chain pressure has been shown to be generally effective at increasing practices with lower environmental practices (sustainable practices) in suppliers. However, questions have been raised about exactly how small and medium-sized enterprises (SMEs) in supply chains respond to pressure from business customers for sustainable practices and what factors influence their response. This study develops a framework for understanding what factors influence how SMEs respond to a variety of drivers of sustainability, which is then adapted to guide an empirical study of how SMEs respond to supply chain pressure for sustainable practices. A survey of 100 companies across North Carolina found suppliers generally comply with or exceed requirements from business customers. The role of supply chain pressure in suppliers' decisions to exceed requirements needs further research. The study also found evidence that supply chain pressure can act as a ceiling on what practices companies adopt by causing suppliers to abandon practices that exceeded customer requirements and were not recognized or rewarded. Care needs to be taken in designing supply chain management strategies to avoid supply chain pressure being counterproductive at increasing proactive SME sustainability.

This dissertation studies how organizations, when solving a specific problem, identify a set of potential solutions which we call "Search Space." By drawing from evolutionary theory and related literatures on strategic change, scholars have demonstrated differences in search mechanisms that explain how organizations choose solutions. However, we still face unanswered questions in understanding how organizations decide where to search, including how organizations identify a set of potential solutions or Search Space. This dissertation defines the concept of Search Space and identifies three factors - uncertainty, prior top managerial attention, and prior experience -that drive differences in Search Space. Additionally, this dissertation starts to disentangle why some firms' top managers are predisposed to paying more attention to new strategic areas by investigating the relationship between uncertainty and top managerial attention. Hypotheses first testing the effect of uncertainty, prior top managerial attention, and prior experience on size of Search Space, and second testing the effect of uncertainty on changes in top managerial attention are tested using data describing the U.S. renewable electricity sector from 2000 to 2010. We conduct both a cross-sectional analysis using data collected though a multiple respondent survey and a panel data analysis by tracking firms' memberships in renewable electricity trade groups. We find that uncertainty and prior top managerial attention increase size of Search Space, but related prior experience reduces size of Search Space. Additionally, uncertainty positively changes attention of top managers at headquarter units, but not at subsidiary units, towards renewable electricity. These results contribute to our understanding of how organizations start solving problems by deciding where to search; how the boundaries of top managerial attention direct Search Space; and how different types of top managers interpret uncertainty. Empirically, these results have important implications for how renewable policies should be structured and how firms develop new projects in the U.S. renewable electricity sector.