Service - Oriented Challenges for Design Science: Charting the “E”-volution

This article links service-dominant (S-D) logic and design science to advance service system design, which is characterized by the indeterminacy of the design problems and outcome measures. Although much progress has been made in IT and IS toward service-orientation, these developments are often adaptations of goods-dominant (G-D) logic, rather than a full transition to a service orientation. In this paper, the “e”-volution of systems design, transitioning from G-D logic to S-D logic, is described and the IS design challenges implied by S-D logic are identified. To devise new, service-oriented modeling, methods and evaluation measurements, S-D logic endorses a fundamental shift in design thinking for design science from “bounded rationality” for problem solving to “expandable rationality” for design for the unknown. Available at: https://aisel.aisnet.org/pajais/vol2/iss1/3

The Role of Consumer Behaviour in Service Operations Management

In this thesis, I study the impact of consumer behaviour on service providers’ operations. In the first study, I consider service systems where customers do not know the distribution of uncertain service quality and cannot estimate it fully rationally. Instead, they form their beliefs by taking the average of several anecdotes, the size of which measures their level of bounded rationality. I characterise the customers’ joining behaviour and the service provider’s pricing, quality control, and information disclosure decisions. Bounded rationality induces customers to form different estimates of the service quality and leads the service provider to use pricing as a market segmentation tool, which is radically different from the full rationality setting. When the service provider also has control over quality, I find that it may reduce both quality and price as customers gather more anecdotes. In addition, a high-quality service provider may not disclose quality information if the sample size is small. In the second study, I analyse the performance of opaque selling in countering the negative revenue impact from consumers’ strategic waiting behaviour in vertically differentiated markets. The advantage of opaque selling is to increase the firm’s regular price, whereas the disadvantage lies in the inflexibility of segmenting different types of consumers. Both the advantage and the disadvantage are radically different from their counterparts in horizontally differentiated markets, and this contrast generates opposite policy recommendations across the two settings. In the third study, I investigate an online store’s product return policy when competing with a physical store, in which consumers can try the product before purchase. I find that the online store should offer product return only if it is socially efficient. Moreover, it should allocate product return cost between the online store and the consumers to minimise the total return cost

Barriers to industrial energy efficiency: a literature review

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Normalizing White-Collar Wrongdoing in Professional Service Firms

There is extensive literature on top managers committing wrongdoing, but few studies examine white-collar wrongdoing. Drawing on the experiences of a professional service firm, we examine why and how engineering consultants normalize wrongdoing. Leveraging bounded rationality theory, we find that organizational myopia promotes inadequate administrative systems that hold consultants prisoner to their rules and procedures, leading to normalized wrongdoing. Our theoretical contributions are threefold: (1) we contribute to the literature on wrongdoing, presenting the relation between organizational myopia and normalized wrongdoing, (2) we contribute to the administrative systems literature, showing their link with poor project performance, and (3) we show how administrative systems and normalized wrongdoing play a role in project scope creep. We introduce an iceberg model to show that the failed project (the tip of the iceberg) is due to organizational myopia and inefficient administrative systems that need to be addressed before starting any project

Normalizing White-Collar Wrongdoing in Professional Service Firms

There is extensive literature on top managers committing wrongdoing, but few studies examine white-collar wrongdoing. Drawing on the experiences of a professional service firm, we examine why and how engineering consultants normalize wrongdoing. Leveraging bounded rationality theory, we find that organizational myopia promotes inadequate administrative systems that hold consultants prisoner to their rules and procedures, leading to normalized wrongdoing. Our theoretical contributions are threefold: (1) we contribute to the literature on wrongdoing, presenting the relation between organizational myopia and normalized wrongdoing, (2) we contribute to the administrative systems literature, showing their link with poor project performance, and (3) we show how administrative systems and normalized wrongdoing play a role in project scope creep. We introduce an iceberg model to show that the failed project (the tip of the iceberg) is due to organizational myopia and inefficient administrative systems that need to be addressed before starting any project

Control and game-theoretic methods for secure cyber-physical-human systems

This work focuses on systems comprising tightly interconnected physical and digital components. Those, aptly named, cyber-physical systems will be the core of the Fourth Industrial Revolution. Thus, cyber-physical systems will be called upon to interact with humans, either in a cooperative fashion, or as adversaries to malicious human agents that will seek to corrupt their operation. In this work, we will present methods that enable an autonomous system to operate safely among human agents and to gain an advantage in cyber-physical security scenarios by employing tools from control, game and learning theories. Our work revolves around three main axes: unpredictability-based defense, operation among agents with bounded rationality and verification of safety properties for autonomous systems. In taking advantage of the complex nature of cyber-physical systems, our unpredictability-based defense work will focus both on attacks on actuating and sensing components, which will be addressed via a novel switching-based Moving Target Defense framework, and on Denial-of-Service attacks on the underlying network via a zero-sum game exploiting redundant communication channels. Subsequently, we will take a more abstract view of complex system security by exploring the principles of bounded rationality. We will show how attackers of bounded rationality can coordinate in inducing erroneous decisions to a system while they remain stealthy. Methods of cognitive hierarchy will be employed for decision prediction, while closed form solutions of the optimization problem and the conditions of convergence to the Nash equilibrium will be investigated. The principles of bounded rationality will be brought to control systems via the use of policy iteration algorithms, enabling data-driven attack prediction in a more realistic fashion than what can be offered by game equilibrium solutions. The issue of intelligence in security scenarios will be further considered via concepts of learning manipulation through a proposed framework where bounded rationality is understood as a hierarchy in learning, rather than optimizing, capability. This viewpoint will allow us to propose methods of exploiting the learning process of an imperfect opponent in order to affect their cognitive state via the use of tools from optimal control theory. Finally, in the context of safety, we will explore verification and compositionality properties of linear systems that are designed to be added to a cascade network of similar systems. To obfuscate the need for knowledge of the system's dynamics, we will state decentralized conditions that guarantee a specific dissipativity properties for the system, which are shown to be solved by reinforcement learning techniques. Subsequently, we will propose a framework that employs a hierarchical solution of temporal logic specifications and reinforcement learning problems for optimal tracking.Ph.D

Boundedly rational versus optimization-based models of strategic thinking and learning in games

The paper is a comment on the article by R. Harstad and R. Selten and considers the tradeoff between bounded rationality and optimization models in the game-theoretic context. The author shows that in most of the models elements of opimization are still retained and that it is thus more productive to further improve the optimization-based modeling rather than to abandon them altogether in favour of bounded rationality