On April 10, 2019, a global crisis began outside Ethiopia’s capital, Addis Ababa. A Boeing 737 Max 8 airplane owned and operated by Ethiopian Airline crashed in the desert killing all on board. The accident mimicked a six months old Lion Air flight 610 which happened in Indonesia and claimed the lives of all crew and passengers. Together, these accidents claimed the lives of 346 people and have been noted as one of the dark days in modern aviation history. Subsequently, the aviation world grounded all Boeing 737 Max aircrafts amid safety concerns. This brought severe public criticism to Boeing, America’s biggest manufacturing exporter, relative to the safety of its flagship airplane. Applying crisis communication theories such as Apologia, SCCT, and Image Restoration, the study finds that these strategies together with other public relations strategies could support public perception in favor of Boeing.

In intermodal freight transport context, the selection process of appropriated transport services that fit with user requirements is a big challenge, this master thesis project analyze different alternatives to improve that process based on reputation information of transport providers. Reputation is a social abstract concept which is analyzed in this research establishing a categorization of reputation parameters in the freight transportation context. Using this categorization is proposed two different architectures of reputation systems to manage the sources and processing of this kind of data. This project is based on a framework to develop generic system architecture for intermodal transport management based on previous European efforts.

In Chapter 1, I describe the hospice industry in California and highlight the key institutional details, then estimate a structural model of hospice choice by patients. Hospices are firms that give palliative care to dying patients. There is no price competition because Medicare pays hospices a fixed per-day rate for each patient, so hospices compete on reputation. I define a hospice's reputation as a stock of its past quality choices. Thus, a hospice can build up its reputation stock over time by consistently choosing high quality. The reputation stock also partially depreciates every period, meaning that a hospice which repeatedly shirks on quality will lose its reputation over time. To study reputation and hospice choice in this setting, I build and estimate a demand model of hospices using yearly hospice-level data from California for 2002-2018. Each consumer makes a discrete choice from a set of hospices in her market, taking into account hospices' reputations and characteristics. The demand estimates show that reputation plays a significant role in consumer choice and depreciates at an annual rate of 53%. In Chapter 2, I build a dynamic oligopoly model of hospices choosing quality to compete on reputation against rivals. This is used to recover the hospice cost function. I use my model and estimates to conduct the following policy counterfactuals. As reputation becomes more persistent - for instance, through the creation of an online hospice rating system - hospices choose higher quality. Hospices also choose higher quality as Medicare prices increase, but the response depends on how differentiated they are in characteristics from rivals. Finally, a hybrid per-day per-visit hospice reimbursement scheme achieves the same quality with nearly 30% lower spending than the current per-day Medicare scheme. In Chapter 3 (joint work with Rena Conti), we study market dynamics in the pharmaceutical industry after loss of market exclusivity by a branded drug. Branded drug manufacturers often respond to generic entry by releasing an Authorized Generic (AG), which is chemically identical to the branded drug but without the brand label attached. This is used to price discriminate between consumers, with the branded drug charging high price and AG charging low price to compete with generics. Using total drug sales and revenue data on US for 2004-2016, we build a stylized structural model to study entry and pricing decisions. We estimate a random-coefficients discrete choice demand model and find significant heterogeneity in brand valuation and price sensitivity among consumers. Then we build a dynamic structural model of generic entry, AG release, and pricing. Combined with calibrated entry-cost parameters, this is used to conduct policy counterfactuals. First, we study the impact of various demand-side policies (such as improving consumer valuation of non-branded drugs and increasing price-sensitivity) on market outcomes. Second, we show that a faster generic approval rate leads to greater generic entry, lower likelihood of AG being released, and lower prices. Third, we find that banning AGs leads to greater generic entry but also higher industry prices overall.

An ad hoc network adopts a decentralized unstructured networking model that depends on node cooperation for key network functionalities such as routing and medium access. The significance of node cooperation in ad hoc networks makes network survival particularly sensitive to insider node behavior. The presence of selfish or malicious nodes in an ad hoc network could greatly degrade the network performance and might even result in a total communication breakdown. Consequently, it is important for both security and performance reasons to discourage, expose, and react to such damaging misbehavior. Reputation management systems have been proposed to mitigate against such misbehavior in ad hoc networks. The functions of a reputation management system are to evaluate nodes' quality of behavior based on their cooperation (evaluation), distinguish between well-behaved and misbehaving nodes (detection), and appropriately react to misbehaving nodes (reaction). A significant number of reputation management systems have been proposed for ad hoc networks to date. However, there has been no attempt to consolidate all current research into a formal framework for reputation management systems. The lack of a formal framework is a potential weakness of the research field. For example, a formal comparison of proposed reputation management systems has remained difficult, mainly due to the lack of a formal framework upon which the comparison could be based. There is also a lack of formal metrics that could be used for quantitative evaluation and comparison of reputation management systems. Another major shortcoming in this research field is the assumption that the functions of reputation management (evaluation, detection, and reaction) are carried out homogeneously across time and space at different nodes. The dynamic nature of ad hoc networks causes node behavior to vary spatially and temporally due to changes in the local and network-wide conditions. Reputation management functions do not adapt to such changes, which may impact the system accuracy and promptness. We herein recognize an adaptive reputation management system as one where nodes carry out the reputation management functions heterogeneously across time and space according to the instantaneous perception of each of its surrounding network conditions. In this work, we address the above concerns. We develop a formal framework for reputation management systems upon which design, evaluation, and comparison of reputation management systems can be based. We define and discuss the different components of the framework and the interactions among them. We also define formal metrics for evaluation of reputation management systems. The metrics assess both, the effectiveness (security issues) of a reputation management system in detecting misbehavior and limiting its negative impact on the network, and its efficiency (performance issues) in terms of false positives and overhead exerted by the reputation management system on the network. We also develop ARMS, an autonomous reputation management system, based on the formal framework. The theoretical foundation of ARMS is based on the theory of Sequential Probability Ratio Test introduced by Wald. In ARMS, nodes independently and without cooperation manage their reputation management system functions. We then use ARMS to investigate adaptation in reputation management systems. We discuss some of the characteristics of an adaptive reputation management system such as sensitivity, adaptability, accuracy, and promptness. We consider how the choice of evaluation metric, typically employed by the evaluation function for assessment of node behavior, may impact the sensitivity and accuracy of node behavior evaluation. We evaluate the sensitivity and accuracy of node behavior evaluation using a number of metrics from the network and medium access layer. We then introduce a time-slotted approach to enhance the sensitivity of the evaluation function and show how the duration of an evaluation slot can adapt according to the network activity to enhance the system accuracy and promptness. We also show how the detection function can adapt to the network conditions by using the node's own behavior as a benchmark to set its detection parameters. To the best of our knowledge, this is the first work to explore the adaptation of the reputation management functions in ad hoc networks. / Ph. D.

No / Islamic Banks (IBs) are considered as having ethical identity, since the foundation of their business philosophy is closely tied to religion. In this article, we explore whether any discrepancy exists between the communicated (based on information disclosed in the annual reports) and ideal (disclosure of information deemed vital based on the Islamic ethical business framework) ethical identities and we measure this by what we have termed the Ethical Identity Index (EII). Our longitudinal survey results over a 3-year period indicate the overall mean EII of only one IB out of seven surveyed to be above average. The remaining six IBs suffer from disparity between the communicated and ideal ethical identities. We further found the largest incongruence to be related to four dimensions: commitments to society; disclosure of corporate vision and mission; contribution to and management of zakah, charity and benevolent loans; and information regarding top management. The results have important implications for communication management if IBs are to enhance their image and reputation in society as well as to remain competitive.

No / The paper examines the determinants of stabilization and its impact on the aftermarket prices. We use a unique dataset to relax several assumptions in the stabilization literature. We find that underwriters support IPO prices shortly after listing, particularly in cold markets and when demand is weak. We also show that stabilized IPOs are more common amongst reputable underwriters. This finding suggests that stabilization may be used as a mechanism to protect the underwriter’s reputation. It also implies that reputable underwriters may possess private information and price IPOs closer to their true values (i.e., higher than those indicated by the weak premarket demand). Consistent with the latter view, we show that stabilized IPOs are offered at higher prices and suffer less underpricing than those indicated by the premarket demand, firm characteristics and market-wide conditions. The post-IPO performance results indicate that stabilized IPOs are unlikely to be mispriced as their prices do not exhibit any significant reversal after the initial stabilization period. We conclude that stabilization may be superior to underpricing as it protects investors from purchasing overpriced IPOs, benefits issuers by reducing the total money “left on the table” and enhances the overall profitability of underwriters.

Yes / This article examines the impact of small and medium-sized enterprises’ (SMEs’) proactive environmental strategy on market performance through the mediating mechanism of environmental reputation. In addition, we investigate the potential moderating role of competitive strategies on the environmental reputation-market performance nexus. Data were collected from 223 SMEs. Using the hierarchical multiple regression analysis, the results show that a proactive environmental strategy positively enhances environmental reputation. Also, the influence of proactively environmental strategy on market performance is mediated by environmental reputation. In addition, our findings show the relationship between environmental reputation and market performance is greater for firms that adopt the differentiation strategy but not significant for firms adopting the low-cost and integrated strategies. Our study offers several theoretical and practical implications.

京都大学 / 新制・課程博士 / 博士(経済学) / 甲第25077号 / 経博第684号 / 新制||経||305(附属図書館) / 京都大学大学院経済学研究科経済学専攻 / (主査)教授 関口 格, 准教授 陳 珈惠, 教授 渡辺 誠 / 学位規則第4条第1項該当 / Doctor of Agricultural Science / Kyoto University / DFAM

Diese Dissertation diskutiert zwei Modellvarianten der Spieltheorie und Industrieökonomik: asymmetrische Information und vertikale Beziehungen. In einem Reputations-Spiel, in welchem Kurzfristspieler hintereinander entscheiden, ob sie mit einem Langfristspieler interagieren wollen, stoppt die Interaktion oft für immer, sobald einer der Spieler sich entscheidet nicht zu interagieren. Ist der Aktionsraum des Langfristspielers ausreichend groß, kann es passieren, dass obwohl die Einschätzungen über die Reputation des Langfristspielers identisch sind, das Verhalten sich verändert, da der vorhergehende Stopp der Interaktion den Langfristspieler dazu bringt, sich mehr anzustrengen. In einer vertikalen Struktur, in welcher Intermediäre ein Input-Gut von einer exogenen Anzahl an Zulieferern beziehen müssen, können diese Intermediäre die Menge eines homogenen Produkts, welches an Konsumenten verkauft werden soll, wählen. Falls einer der Intermediäre in Form einer Genossenschaft organisiert ist, steigt der durchschnittliche Gewinn der Zulieferer, was zu einem ineffizient geringen Angebot an die Konsumenten führt. Eine Kooperative kann sich als Monopol behaupten, sofern die Kapazität der Zulieferer ausreichend gering ist, während eine Duopolstruktur vorliegt, wenn diese Kapazität hoch ist. In einer Wertschöpfungskette mit einem Zulieferer, einem Händler und Unsicherheit über die Nachfrage am Markt sind die Entscheidungen über kostenlose Informationsbeschaffung, um diese Unsicherheit aufzulösen, strategische Komplemente. Wenn die technische Beschränkung der Signalpräzision so ist, dass die Informationsbeschaffung nicht genug Unsicherheit beseitigt, ist die Informationsrente klein und der Zulieferer kann sich entscheiden uninformiert zu bleiben, um ein Glaubwürdigkeitsproblem zu umgehen und Verträge anzubieten die keine private Information signalisieren. Steigt die Signalpräzision, entscheiden sich beide Marktteilnehmer so gut wie möglich informiert zu sein. / This dissertation discusses two modelling variants in game theory and industrial economics: asymmetric information and vertical relations. In a reputation game, in which a sequence of short-run players chooses if to interact with a long-run player, often interactions stops forever, if one short-run player decides not to interact. If the long-run player''s action set is sufficiently rich, although beliefs about the long-run player''s reputation may be identical, choices may be different, as the preceding refusal to interact can lead the long-run player to improve on effort. In a vertical structure, in which intermediaries have to acquire an input from an exogenously given number of suppliers, intermediaries can choose the quantities of a homogenous product to be sold to consumers. In case one of the intermediaries is organized as a cooperative the average profit of suppliers, increases, leading to inefficiently low supply to consumers. Furthermore, a cooperative may be a monopoly in the downstream market, if the upstream production capacity is sufficiently small, whereas there is a duopoly with one firm maximizing its profit and one firm maximizing average profit, if upstream capacity is large. In a supply chain with one supplier, one retailer and uncertainty about market demand, the choices on costless information acquisition to resolve this uncertainty are strategic complements. If the technical limitation on the precision of the signals is such that being informed does not reduce enough uncertainty, the potential information rent is small and the supplier may choose to stay uninformed and avoid a credibility problem by offering pooling contracts. If the precision of private signals increases, both agents decide to be informed as much as possible.

This thesis investigates both theoretical and practical aspects of the design and analysis of iterative algorithms for trust and reputation management and recommender systems. It also studies the application of iterative trust and reputation management mechanisms in ad-hoc networks and P2P systems. First, an algebraic and iterative trust and reputation management scheme (ITRM) is proposed. The proposed ITRM can be applied to centralized schemes, in which a central authority collects the reports and forms the reputations of the service providers (sellers) as well as report/rating trustworthiness of the (service) consumers (buyers). It is shown that ITRM is robust in filtering out the peers who provide unreliable ratings. Next, the first application of Belief Propagation algorithm, a fully iterative probabilistic algorithm, on trust and reputation management (BP-ITRM) is proposed. In BP-ITRM, the reputation management problem is formulated as an inference problem, and it is described as computing marginal likelihood distributions from complicated global functions of many variables. However, it is observed that computing the marginal probability functions is computationally prohibitive for large scale reputation systems. Therefore, the belief propagation algorithm is utilized to efficiently (in linear complexity) compute these marginal probability distributions. In BP-ITRM, the reputation system is modeled by using a factor graph and reputation values of the service providers (sellers) are computed by iterative probabilistic message passing between the factor and variable nodes on the graph. It is shown that BP-ITRM is reliable in filtering out malicious/unreliable reports. It is proven that BP-ITRM iteratively reduces the error in the reputation values of service providers due to the malicious raters with a high probability. Further, comparison of BP-ITRM with some well-known and commonly used reputation management techniques (e.g., Averaging Scheme, Bayesian Approach and Cluster Filtering) indicates the superiority of the proposed scheme both in terms of robustness against attacks and efficiency. The introduction of the belief propagation and iterative message passing methods onto trust and reputation management has opened up several research directions. Thus, next, the first application of the belief propagation algorithm in the design of recommender systems (BPRS) is proposed. In BPRS, recommendations (predicted ratings) for each active user are iteratively computed by probabilistic message passing between variable and factor nodes in a factor graph. It is shown that as opposed to the previous recommender algorithms, BPRS does not require solving the recommendation problem for all users if it wishes to update the recommendations for only a single active user using the most recent data (ratings). Further, BPRS computes the recommendations for each user with linear complexity, without requiring a training period while it remains comparable to the state of art methods such as Correlation-based neighborhood model (CorNgbr) and Singular Value Decomposition (SVD) in terms of rating and precision accuracy. This work also explores fundamental research problems related to application of iterative and probabilistic reputation management systems in various fields (such as ad-hoc networks and P2P systems). A distributed malicious node detection mechanism is proposed for delay tolerant networks (DTNs) using ITRM which enables every node to evaluate other nodes based on their past behavior, without requiring a central authority. Further, for the first time. the belief propagation algorithm is utilized in the design and evaluation of distributed trust and reputation management systems for P2P networks. Several schemes are extensively simulated and are compared to demonstrate the effectiveness of the iterative algorithms and belief propagation on these applications.