Foreign Direct Investment and Political Uncertainty

Recent developments in the general equilibrium theory of multinationals emphasize the importance of multilateral considerations. Yet, existing explanations and corresponding estimations of FDI patterns have largely limited political and institutional investment impediments to a bilateral framework. Through the application of spatial econometric techniques, I demonstrate that the presence of both domestic and regional political uncertainty generate real options effects that lead to the delay or redirection of foreign direct investment. The magnitude and direction of these effects is conditional upon the host country regime type and the predominant multinational integration strategies in the region. Comparing these results with FDI of U.S. origin, I find evidence for divergent investment behavior by U.S. multinationals during regime changes in partner countries. Additionally, I find no evidence that multinationals from developing countries are more likely to complete cross-border deals in environments characterized by greater political risk or political uncertainty.

UNDERSTANDING CUSTOMER CHOICES IN SERVICE OUTSOURCING AND REVENUE MANAGEMENT

This dissertation investigates customer behavior modeling in service outsourcing and revenue management in the service sector (i.e., airline and hotel industries). In particular, it focuses on a common theme of improving firms’ strategic decisions through the understanding of customer preferences. Decisions concerning degrees of outsourcing, such as firms’ capacity choices, are important to performance outcomes. These choices are especially important in high-customer-contact services (e.g., airline industry) because of the characteristics of services: simultaneity of consumption and production, and intangibility and perishability of the offering. Essay 1 estimates how outsourcing affects customer choices and market share in the airline industry, and consequently the revenue implications from outsourcing. However, outsourcing decisions are typically endogenous. A firm may choose whether to outsource or not based on what a firm expects to be the best outcome. Essay 2 contributes to the literature by proposing a structural model which could capture a firm’s profit-maximizing decision-making behavior in a market. This makes possible the prediction of consequences (i.e., performance outcomes) of future strategic moves. Another emerging area in service operations management is revenue management. Choice-based revenue systems incorporate discrete choice models into traditional revenue management algorithms. To successfully implement a choice-based revenue system, it is necessary to estimate customer preferences as a valid input to optimization algorithms. The third essay investigates how to estimate customer preferences when part of the market is consistently unobserved. This issue is especially prominent in choice-based revenue management systems. Normally a firm only has its own observed purchases, while those customers who purchase from competitors or do not make purchases are unobserved. Most current estimation procedures depend on unrealistic assumptions about customer arriving. This study proposes a new estimation methodology, which does not require any prior knowledge about the customer arrival process and allows for arbitrary demand distributions. Compared with previous methods, this model performs superior when the true demand is highly variable.

ASSESSING QUALITY IN HIGH-UNCERTAINTY MARKETS: ONLINE REVIEWS OF CREDENCE SERVICES

In economics of information theory, credence products are those whose quality is difficult or impossible for consumers to assess, even after they have consumed the product (Darby & Karni, 1973). This dissertation is focused on the content, consumer perception, and power of online reviews for credence services. Economics of information theory has long assumed, without empirical confirmation, that consumers will discount the credibility of claims about credence quality attributes. The same theories predict that because credence services are by definition obscure to the consumer, reviews of credence services are incapable of signaling quality. Our research aims to question these assumptions. In the first essay we examine how the content and structure of online reviews of credence services systematically differ from the content and structure of reviews of experience services and how consumers judge these differences. We have found that online reviews of credence services have either less important or less credible content than reviews of experience services and that consumers do discount the credibility of credence claims. However, while consumers rationally discount the credibility of simple credence claims in a review, more complex argument structure and the inclusion of evidence attenuate this effect. In the second essay we ask, “Can online reviews predict the worst doctors?” We examine the power of online reviews to detect low quality, as measured by state medical board sanctions. We find that online reviews are somewhat predictive of a doctor’s suitability to practice medicine; however, not all the data are useful. Numerical or star ratings provide the strongest quality signal; user-submitted text provides some signal but is subsumed almost completely by ratings. Of the ratings variables in our dataset, we find that punctuality, rather than knowledge, is the strongest predictor of medical board sanctions. These results challenge the definition of credence products, which is a long-standing construct in economics of information theory. Our results also have implications for online review users, review platforms, and for the use of predictive modeling in the context of information systems research.

Interorganizational Innovation: The Role of Suppliers in Enhancing Buyer Innovation

This dissertation explores the effect of innovative knowledge transfer across supply chain partners. My research seeks to understand the manner by which a firm is able to benefit from the innovative capabilities of its supply chain partners and utilize the external knowledge they hold to increase its own levels of innovation. Specifically, I make use of patent data as a proxy for firm-level innovation and develop both independent and dependent variables from the data contained within the patent filings. I further examine the means by which key dyadic and portfolio supply chain relationship characteristics moderate the relationship between supplier innovation and buyer innovation. I investigate factors such as the degree of transactional reciprocity between the buyer and supplier, the similarity of the firms’ knowledge bases, and specific chain characteristics (e.g., geographic propinquity) to provide greater understanding of the means by which the transfer of innovative knowledge across firms in a supply chain can be enhanced or inhibited. This dissertation spans three essays to provide insights into the role that supply chain relationships play in affecting a focal firm’s level of innovation. While innovation has been at the core of a wide body of research, very little empirical work exists that considers the role of vertical buyer-supplier relationships on a firm’s ability to develop new and novel innovations. I begin by considering the fundamental unit of analysis within a supply chain, the buyer-supplier dyad. After developing initial insights based on the interactions between singular buyers and suppliers, essay two extends the analysis to consider the full spectrum of a buyer’s supply base by aggregating the individual buyer-supplier dyad level data into firm-supply network level data. Through this broader level of analysis, I am able to examine how the relational characteristics between a buyer firm and its supply base affect its ability to leverage the full portfolio of its suppliers’ innovative knowledge. Finally, in essay three I further extend the analysis to explore the means by which a buyer firm can use its suppliers to enhance its ability to access distant knowledge held by other organizations that the buyer is only connected to indirectly through its suppliers.

Essays in Corporate Finance

Prior research has been divided regarding how firms respond to bankruptcy risk, largely revolving around two competing forces. On the one hand, asset substitution encourages firms to increase the riskiness of assets to extract value from creditors. On the other, firms want to minimize bankruptcy risk, either by reducing cash flow risk or through increasing the size of the firm. I test these two theories using a natural experiment of chemicals used in production processes being newly identified as carcinogenic to explore how firms may respond to potential negative cash flow resulting from litigation risk. I use plantlevel chemical data to study firm exposure to risk. I examine how responses between firms of differing levels of chemical exposure may vary within the industry, how firm financial distress affects firm response and whether public and private firms respond differently. In general, my research provides support for the asset substitution theory. My first paper studies how investment response varies based on level of carcinogenic exposure. I find that firms with moderate levels of exposure make efforts to mitigate their cash flow risk and reduce their exposure. At the same time, firms with high levels of exposure increase their exposure and riskiness of future cash flows. These findings are consistent with asset substitution theory. My second paper analyzes the interaction of financial distress and risk exposure. I find that firms in a stronger financial position are more likely to limit their exposure by reducing the number of exposed facilities. On the other hand, not only do firms in weaker financial position not decrease their exposure, I find that, in some instances, they increase their exposure to carcinogens. This work again supports the theory of asset substitution. Finally, in my third paper, I explore if public firms respond differently to a potential negative cash flow shock than do private firms. I test whether existing public firms are more likely to attempt to minimize their cash flow risk and thus reduce their carcinogen exposure than are private firms. I do not find evidence that public firms respond differently to this shock than do private firms.

Too Busy to Be Fair? The Effect of Managers’ Perceived Workload on Their Core Technical Performance and Justice Rule Adherence

Despite the organizational benefits of treating employees fairly, both anecdotal and empirical evidence suggest that managers do not behave fairly towards their employees in a consistent manner. As treating employees fairly takes up personal resources such as time, effort, and attention, I argue that when managers face high workloads (i.e., high amounts of work and time pressure), they are unable to devote such personal resources to effectively meet both core technical task requirements and treat employees fairly. I propose that in general, managers tend to view their core technical task performance as more important than being fair in their dealings with employees; as a result, when faced with high workloads, they tend to prioritize the former at the expense of the latter. I also propose that managerial fairness will suffer more as a result of heightened workloads than will core technical task performance, unless managers perceive their organization to explicitly reward fair treatment of employees. I find support for my hypotheses across three studies: two experimental studies (with online participants and students respectively) and one field study of managers from a variety of organizations. I discuss the implications of studying fairness in the wider context of managers’ complex role in organizations to the fairness and managerial work demands literatures.

TAKING THE PERSPECTIVE OF A SELLER AND A BUYER: IMPLICATIONS FOR PRICE ELICITATION AND PRICE FRAMING

This dissertation consists of two essays which investigate how assuming the role of a seller or a buyer affects valuations in a price elicitation task (essay I) and how different presentations of an equivalent price affect evaluations when a consumer plays the dual roles of a buyer and a seller in transactions involving trade-ins (essay II). Sellers’ willingness to accept (WTA) to give up a good is typically higher than buyers' willingness to pay (WTP) to obtain the good. Essay I proposes that valuation processes of sellers and buyers are guided by a motivational orientation of “getting the best.” For a seller (buyer) indicating WTA (WTP), getting the best implies receiving as much as possible to give up a specific good (giving up as little as possible to get the specific good). Results of six studies suggest that the WTA-WTP elicitation task activates different directional goals, leading to the WTA-WTP disparity. The different directional goals lead sellers and buyers to focus on different aspects and bias their cognitive reasoning and interpretation of information. By connecting the valuation process to the general motivation of getting the best, this research provides a unifying framework to explain the disparate interpretations of the WTA-WTP disparity. Many new purchases and replacement decisions involve consumers’ trading in their old products. In such transactions, the overall exchange may be priced either as separate transactions (partitioned) with price tags for the payment and the receipt or as a single net price (consolidated) which takes into account the value of the trade-in. Essay II examines whether consumers prefer a partitioned price versus a consolidated price presentation. The findings suggest that when consumers are trading in a product which has a low value relative to the price of a new product, they prefer a consolidated price. In contrast, when trading in a product which has high value, they prefer a partitioned price. The results suggest that consumers use the price of the new product as an anchor to evaluate the trade-in value, and the perception of the trade-in value influences the overall evaluation especially when the transaction is partitioned.

Mathematical Programming Models for Influence Maximization on Social Networks

In this dissertation, we apply mathematical programming techniques (i.e., integer programming and polyhedral combinatorics) to develop exact approaches for influence maximization on social networks. We study four combinatorial optimization problems that deal with maximizing influence at minimum cost over a social network. To our knowl- edge, all previous work to date involving influence maximization problems has focused on heuristics and approximation. We start with the following viral marketing problem that has attracted a significant amount of interest from the computer science literature. Given a social network, find a target set of customers to seed with a product. Then, a cascade will be caused by these initial adopters and other people start to adopt this product due to the influence they re- ceive from earlier adopters. The idea is to find the minimum cost that results in the entire network adopting the product. We first study a problem called the Weighted Target Set Selection (WTSS) Prob- lem. In the WTSS problem, the diffusion can take place over as many time periods as needed and a free product is given out to the individuals in the target set. Restricting the number of time periods that the diffusion takes place over to be one, we obtain a problem called the Positive Influence Dominating Set (PIDS) problem. Next, incorporating partial incentives, we consider a problem called the Least Cost Influence Problem (LCIP). The fourth problem studied is the One Time Period Least Cost Influence Problem (1TPLCIP) which is identical to the LCIP except that we restrict the number of time periods that the diffusion takes place over to be one. We apply a common research paradigm to each of these four problems. First, we work on special graphs: trees and cycles. Based on the insights we obtain from special graphs, we develop efficient methods for general graphs. On trees, first, we propose a polynomial time algorithm. More importantly, we present a tight and compact extended formulation. We also project the extended formulation onto the space of the natural vari- ables that gives the polytope on trees. Next, building upon the result for trees---we derive the polytope on cycles for the WTSS problem; as well as a polynomial time algorithm on cycles. This leads to our contribution on general graphs. For the WTSS problem and the LCIP, using the observation that the influence propagation network must be a directed acyclic graph (DAG), the strong formulation for trees can be embedded into a formulation on general graphs. We use this to design and implement a branch-and-cut approach for the WTSS problem and the LCIP. In our computational study, we are able to obtain high quality solutions for random graph instances with up to 10,000 nodes and 20,000 edges (40,000 arcs) within a reasonable amount of time.