TRAAC: Trust and Risk Aware Access Control

Postprin

Destructive Effects of Constructive Ambiguity in Risky Times

Unclear bailout policy, underinvestment and calls for bankers? responsibility are some of the observations from the recent financial crisis. The paper explains underinvestment as an inefficient equilibrium. Under ambiguous bailout policy agents suffer from a lack of information with regards to the insolvency resolution methods. Beliefs of bankers regarding whether an insolvent bank is liquidated, may differ from those of depositors even if bankers and depositors possess absolutely symmetric information about the economy. It is shown that such an asymmetry in beliefs results in underinvestment if the investment climate is characterized by high aggregate risk. The paper suggests policy implications aimed at the reduction of anxiety of agents and at aligning their beliefs to restore efficiency

Dynamics of banking technology adoption: an application to internet banking

This paper is concerned with examining behaviour of firms (banks) and consumers (banks’ customers) in the event of a new technology (internet banking) introduction. The determinants of consumer adoption of internet banking are characterised using survey data from Korea in both static and dynamic framework. I find evidence that adoption of internet banking is influenced by sex, age, marital status, degree of exposure to internet banking, and the characteristics of the banks. A duration analysis shows no evidence of first mover advantage (order effects) in internet banking whilst the largest bank (rank effects) in commercial banking remains dominant in internet banking. The results imply that the internet banking adoption is dominated by social norm effects

Contributions to modeling with set-valued data: benefitting from undecided respondents

This dissertation develops a methodological framework and approaches to benefit from undecided survey participants, particularly undecided voters in pre-election polls. As choices can be seen as processes that - in stages - exclude alternatives until arriving at one final element, we argue that in pre-election polls undecided participants can most suitably be represented by the set of their viable options. This consideration set sampling, in contrast to the conventional neglection of the undecided, could reduce nonresponse and collects new and valuable information. We embed the resulting set-valued data in the framework of random sets, which allows for two different interpretations, and develop modeling methods for either one. The first interpretation is called ontic and views the set of options as an entity of its own that most accurately represents the position at the time of the poll, thus as a precise representation of something naturally imprecise. With this, new ways of structural analysis emerge as individuals pondering between particular parties can now be examined. We show how the underlying categorical data structure can be preserved in this formalization process for specific models and how popular methods for categorical data analysis can be broadly transferred. As the set contains the eventual choice, under the second interpretation, the set is seen as a coarse version of an underlying truth, which is called the epistemic view. This imprecise information of something actually precise can then be used to improve predictions or election forecasting. We developed several approaches and a framework of a factorized likelihood to utilize the set-valued information for forecasting. Amongst others, we developed methods addressing the complex uncertainty induced by the undecided, weighting the justifiability of assumptions with the conciseness of the results. To evaluate and apply our approaches, we conducted a pre-election poll for the German federal election of 2021 in cooperation with the polling institute Civey, for the first time regarding undecided voters in a set-valued manner. This provides us with the unique opportunity to demonstrate the advantages of the new approaches based on a state-of-the-art survey

A pilot Internet "Value of Health" Panel: recruitment, participation and compliance

Objectives To pilot using a panel of members of the public to provide preference data via the Internet Methods A stratified random sample of members of the general public was recruited and familiarised with the standard gamble procedure using an Internet based tool. Health states were perdiodically presented in "sets" corresponding to different conditions, during the study. The following were described: Recruitment (proportion of people approached who were trained); Participation (a) the proportion of people trained who provided any preferences and (b) the proportion of panel members who contributed to each "set" of values; and Compliance (the proportion, per participant, of preference tasks which were completed). The influence of covariates on these outcomes was investigated using univariate and multivariate analyses. Results A panel of 112 people was recruited. 23% of those approached (n = 5,320) responded to the invitation, and 24% of respondents (n = 1,215) were willing to participate (net = 5.5%). However, eventual recruitment rates, following training, were low (2.1% of those approached). Recruitment from areas of high socioeconomic deprivation and among ethnic minority communities was low. Eighteen sets of health state descriptions were considered over 14 months. 74% of panel members carried out at least one valuation task. People from areas of higher socioeconomic deprivation and unmarried people were less likely to participate. An average of 41% of panel members expressed preferences on each set of descriptions. Compliance ranged from 3% to 100%. Conclusion It is feasible to establish a panel of members of the general public to express preferences on a wide range of health state descriptions using the Internet, although differential recruitment and attrition are important challenges. Particular attention to recruitment and retention in areas of high socioeconomic deprivation and among ethnic minority communities is necessary. Nevertheless, the panel approach to preference measurement using the Internet offers the potential to provide specific utility data in a responsive manner for use in economic evaluations and to address some of the outstanding methodological uncertainties in this field

Dynamics of Banking Technology Adoption: An Application to Internet Banking

This paper is concerned with examining behaviour of firms (banks) and consumers (banks' customers) in the event of a new technology (internet banking) introduction. The determinants of consumer adoption of internet banking are characterised using survey data from Korea in both static and dynamic framework. I find evidence that adoption of internet banking is influenced by sex, age, marital status, degree of exposure to internet banking, and the characteristics of the banks. A duration analysis shows no evidence of first mover advantage (order effects) in internet banking whilst the largest bank (rank effects) in commercial banking remains dominant in internet banking. The results imply that the internet banking adoption is dominated by social norm effects.internet banking, technology adoption, first-mover advantage, pre-emption, social norm

On the treatment of uncertainty in innovation projects

Innovations encounter a relatively high level of uncertainty in their lifecycle path. As innovations are about implementing a new idea, they suffer from a shortage or lack of knowledge dependent on and directly proportional to the radical quality of novelty. They lack information to predict the future and face (high) uncertainty in the background knowledge used for the risk assessment. Incomplete information causes innovation risk analysts to assign subjective assumptions to simplify system models developed for innovation risk assessment. Subjective and non-subjective assumptions as uncertain assumptions are part of the background knowledge and source of uncertainty. This thesis tries to assess and treat innovation assumptions uncertainties by proposing a hybrid model which comprises the semi-quantitative risk assessment (SQRA) approach, extended semi-quantitative risk assessment (EQRA) approach, and knowledge dimension method. SQRA and EQRA highlight the criticality of assumptions and present a systematic approach to assess and treat assumption uncertainties. SQRA applies probabilistic analysis to conduct an assumptions risk assessment, and EQRA provides innovation managers with guidance on developing strategies to follow up uncertain assumptions over the process implementation. The knowledge dimension technique evaluates and communicates the strength of background knowledge applied in assumptions risk assessment to innovation decision-makers expressing whole uncertainty aspects in the background knowledge (assumptions, data, models, and expert judgment). The model can effectively contribute to innovation risks and uncertainties management during the project execution.2021-09-29T16:30:09

DYNAMICS OF BANKING TECHNOLOGY ADOPTION : AN APPLICATION TO INTERNET BANKING

This paper is concerned with examining behaviour of firms (banks) and consumers (banks’ customers) in the event of a new technology (internet banking) introduction. The determinants of consumer adoption of internet banking are characterised using survey data from Korea in both static and dynamic framework. I find evidence that adoption of internet banking is influenced by sex, age, marital status, degree of exposure to internet banking, and the characteristics of the banks. A duration analysis shows no evidence of first mover advantage (order effects) in internet banking whilst the largest bank (rank effects) in commercial banking remains dominant in internet banking. The results imply that the internet bankin g adoption is dominated by social norm effects.internet banking ; technology adoption ; first-mover advantage ; pre-emption ; social norm

Making decisions with evidential probability and objective Bayesian calibration inductive logics

Calibration inductive logics are based on accepting estimates of relative frequencies, which are used to generate imprecise probabilities. In turn, these imprecise probabilities are intended to guide beliefs and decisions — a process called “calibration”. Two prominent examples are Henry E. Kyburg's system of Evidential Probability and Jon Williamson's version of Objective Bayesianism. There are many unexplored questions about these logics. How well do they perform in the short-run? Under what circumstances do they do better or worse? What is their performance relative to traditional Bayesianism? In this article, we develop an agent-based model of a classic binomial decision problem, including players based on variations of Evidential Probability and Objective Bayesianism. We compare the performances of these players, including against a benchmark player who uses standard Bayesian inductive logic. We find that the calibrated players can match the performance of the Bayesian player, but only with particular acceptance thresholds and decision rules. Among other points, our discussion raises some challenges for characterising “cautious” reasoning using imprecise probabilities. Thus, we demonstrate a new way of systematically comparing imprecise probability systems, and we conclude that calibration inductive logics are surprisingly promising for making decisions