Contract Design for Collaborative Response to Service Disruptions

This dissertation studies firms' strategic interactions in anticipation of random service disruption following technology failure. In particular it is aimed at understanding how contracting decisions between a vendor and one or multiple clients affect the firms' subsequent decisions to ensure disruption response and recovery are managed as efficiently as possible. This dissertation consists of three studies that were written as standalone papers seeking to contribute to the literature on contract design and technology management in operations management. Together, the three studies justify the importance of structuring the right incentives to mitigate disruption risks. In the first study we contribute to this literature by means of an analytical model which we use to examine how a client and vendor should balance investments in response capacity when both parties' efforts are critical in resolving disruption and each may have different risk preferences. We study the difference in the client's optimal expected utility between a case in which investment in response capacity is observable and a case in which it is not and refer to the difference in outcomes between the two cases as the cost of complexity. Firstly, we show that the cost of complexity to the client is decreasing in the risk aversion of vendor but increasing in her own risk aversion. Secondly, we find that a larger difference in risk aversion between a client and vendor leads to underinvestment in system uptime in case the client's investment is observable, yet the opposite happens when the client’s investment is not observable. In the second study we further examine the context of the first study through a controlled experiment. We examine how differences in risk aversion and access to information on a contracting partner’s risk preferences interact in affecting contracting and investment decisions between the client and vendor. Comparing subject decisions with the conditionally optimal benchmarks we arrive at two observations that highlight possible heuristic decision biases. Firstly, subjects tend to set and hold on to an inefficiently high investment level even though it is theoretically optimal to adjust decisions under changing differences in risk preferences. Secondly, subjects tend to set and hold on to a penalty that is too high when interacting with more risk averse vendors and too low in case the vendor is equally risk averse. Furthermore, cognitive feedback on the vendor’s risk aversion appears to have counterproductive effects on subject’s performance in the experiment, suggesting cognitive overload can have a reinforcing effect on the heuristic decision biases observed. In the third study we construct a new analytical model to examine the effect of contract design on a provider's response capacity allocation in a setting where multiple clients may be disrupted and available response capacity is limited. The results show that while clients may be incentivized to identify and report network disruptions, competition for scarce emergency resources and the required investment in understanding their own exposure may incentivize clients to deliberately miscommunicate with the vendor.This work was supported by the Economic and Social Research Council [Award No. ES/J500033/1]. Additional funding was provided by Cambridge Judge Business School and Downing College

Reciprocity towards Incentives for Supply Chain Restoration Investment: Models, Experimental Studies and Surveys

In this thesis, we evaluate the use of incentives offered beyond a contract compared with those within a contract to motivate supplier investment in restoration capability, which can serve as a signal of reciprocity. In the rst chapter, we analytically examine to what extent a Direct incentive, which is paid by the manufacturer unconditionally prior to disruption, differs from an Indirect incentive, which is promised to be paid when a disruption occurs in a dyadic supply chain. We specify the conditions under which the two types of incentive are economically equivalent for both a manufacturer and a supplier. More importantly, we derive a ratio of investment amount to incentive value as a proxy of supplier reciprocity towards incentives offered by the manufacturer. Our analytical results indicate that reciprocal concern drives higher investment amount per unit incentive under Direct incentive than under Indirect incentive. The results further suggest that the manufacturer should always offer a Direct incentive as long as it is economically equivalent to an Indirect one, and should do so particularly when an ambiguous prospect for recovery outcomes is anticipated with less optimism. The following chapter examines supplier reciprocal behaviour towards manufacturer incentives in a laboratory setting. The experimental study confirms prior analytical results that a Direct incentive can induce stronger reciprocal responses as opposed to an Indirect incentive. We reveal that the offer of a Direct incentive particularly strengthens suppliers reciprocal behaviour in long-term relationships. This result provides evidence for a synergy by coupling Direct incentives with long-term relationships. Furthermore, we observe that subjects decisions in repeated game conditions are associated with learning behaviours, in which the selfish motive of maximising their own benets can be restrained when they repeatedly interact. In the third chapter, we evaluate the moderating effects of perceived relational factors on the relationship between manufacturer incentives and observed supplier investments in the experiment. A post-experiment survey was developed to capture individual differences in subjects perceptions of the buyer-supplier relationship. We provide evidence that a supplier's investment decision towards its manufacturer's incentive offered is moderated by self-perception and felt obligation of the relationship. The underlying determinants of the perceived relational factors are explored. We suggest that ambiguity and other-regarding preferences are associated with self-perception; whereas, perpetrator justice sensitivity is related to the felt obligation for reciprocity in the buyer-supplier relationship

Solving Multi-objective Integer Programs using Convex Preference Cones

Esta encuesta tiene dos objetivos: en primer lugar, identificar a los individuos que fueron víctimas de algún tipo de delito y la manera en que ocurrió el mismo. En segundo lugar, medir la eficacia de las distintas autoridades competentes una vez que los individuos denunciaron el delito que sufrieron. Adicionalmente la ENVEI busca indagar las percepciones que los ciudadanos tienen sobre las instituciones de justicia y el estado de derecho en Méxic

Operational Research: Methods and Applications

Throughout its history, Operational Research has evolved to include a variety of methods, models and algorithms that have been applied to a diverse and wide range of contexts. This encyclopedic article consists of two main sections: methods and applications. The first aims to summarise the up-to-date knowledge and provide an overview of the state-of-the-art methods and key developments in the various subdomains of the field. The second offers a wide-ranging list of areas where Operational Research has been applied. The article is meant to be read in a nonlinear fashion. It should be used as a point of reference or first-port-of-call for a diverse pool of readers: academics, researchers, students, and practitioners. The entries within the methods and applications sections are presented in alphabetical order. The authors dedicate this paper to the 2023 Turkey/Syria earthquake victims. We sincerely hope that advances in OR will play a role towards minimising the pain and suffering caused by this and future catastrophes

Investigating the impact of big data analytics on supply chain operations: case studies from the UK private sector

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel UniversityIn the era of increasing competitive pressure and pace of changing demand, volatility and disturbance have become the standard in today’s global markets. The spread of Covid-19 is a prime example of this. Supply chain (SC) managers are urged to rethink their competitive strategies and to identify ways to offer personalised products and services through making use of advanced technologies. With many SC executives recognising the role of data exploitation in improving performance, big data analytics (BDA) has become a salient factor for all kinds of organisations to increase efficiency and gain competitive advantage. Extant research in supply chain management (SCM) has provided limited understanding of strategic SC decision-making concerning BDA. Moreover, inquiry in this area is still poor in relation to providing a conceptual framework that illustrates the potential benefits of BDA utilisation in the SCO context. This study aims to investigate the real impact of BDA implementation in this context. A theoretical framework is developed to explain the motives behind adopting BDA in SCO along with the potential benefits of implementing BDA in SCO. Multiple case studies are the strategy utilised to collect qualitative data in order to gain detailed and in-depth understanding of the BDA as a new phenomenon in the context of SCOs. Semi-structured interviews were conducted in a cross-sectional time horizon across four different industries. Institutional theory and Task-Technology fit theories are utilised to provide better understanding regarding how and why firms adopt BDA as a novel technology, along with the drivers and opportunities of this technology utilisation. The empirical findings reveal that BDA is still in its infant stage, but it is a growing area which has recently been given more attention by scholars and managers. There is a disconnect between the hype and knowledge discussed in the literature and the real practice of BDA. That is, the current state of BDA use is relatively fragmented and rhetoric in discussion among practitioners and researchers. The main contribution of this study is breaking-down the process of BDA utilisation in order to evaluate its implementation in the SCO context by drawing upon a wide range of existing literature regarding BDA and SCO, in addition to present conceptual framework explaining the potential impact of BDA implementation through presenting BDA utilisation drivers, BDA capabilities, and its role in solving different issues

Operational Research: Methods and Applications

Throughout its history, Operational Research has evolved to include a variety of methods, models and algorithms that have been applied to a diverse and wide range of contexts. This encyclopedic article consists of two main sections: methods and applications. The first aims to summarise the up-to-date knowledge and provide an overview of the state-of-the-art methods and key developments in the various subdomains of the field. The second offers a wide-ranging list of areas where Operational Research has been applied. The article is meant to be read in a nonlinear fashion. It should be used as a point of reference or first-port-of-call for a diverse pool of readers: academics, researchers, students, and practitioners. The entries within the methods and applications sections are presented in alphabetical order

Operational research:methods and applications

Throughout its history, Operational Research has evolved to include a variety of methods, models and algorithms that have been applied to a diverse and wide range of contexts. This encyclopedic article consists of two main sections: methods and applications. The first aims to summarise the up-to-date knowledge and provide an overview of the state-of-the-art methods and key developments in the various subdomains of the field. The second offers a wide-ranging list of areas where Operational Research has been applied. The article is meant to be read in a nonlinear fashion. It should be used as a point of reference or first-port-of-call for a diverse pool of readers: academics, researchers, students, and practitioners. The entries within the methods and applications sections are presented in alphabetical order