Terence T. Ow

Modeling attitude to risk in human decision processes: An application of fuzzy measures

Abstract Several models of the human decision process have been proposed, classical examples of which are utility theory and prospect theory. In recent times, the theory of fuzzy measures and integrals has emerged as an alternative meriting further investigation. Specifically, one is interested in the degrees of disjunction and conjunction and the veto and favor indices that represent the tolerance measure of the decision maker. Though several theoretical expositions have appeared in contemporary literature, empirical studies applying these concepts to the real world are scarce. This paper reports two studies based on a model of strategic telecommunication investment decisions from a research work involving a survey of executives. The first study involves building fuzzy models corresponding to each individual decision maker with the results grouped based on the decision makers’ propensity to risk as determined by their degrees of disjunction. The Shapley indices and the interaction effects are determined for each pooled dataset corresponding to each group. To contrast this approach with those of conventional nomothetic comparisons of decision policies, the decision makers are grouped based on a clustering analysis of the individual linear regression models. The data for each cluster are pooled and the fuzzy measures learned from the dataset are analyzed for comparison purposes. The results not only serve as a demonstration of fuzzy measure analysis as a viable approach to studying qualitative decision making but also provide useful methodological insights into applying fuzzy measures to strategic investment decisions under risk.

Does information technology investment influence a firm's market value? a case of non-publicly traded healthcare firms

Managers make informed information technology investment decisions when they are able to quantify how IT contributes to firm performance. While financial accounting measures inform ITs influence on retrospective firm performance, senior managers expect evidence of how IT influences prospective measures such as the firms market value. We examine the efficacy of ITs influence on firm value combined with measures of financial performance for non-publicly traded (NPT) hospitals that lack conventional market-based measures. We gathered actual sale transactions for NPT hospitals in the United States to derive the q ratio, a measure of market value. Our findings indicate that the influence of IT investment on the firm is more pronounced and statistically significant on firm value than exclusively on the accounting performance measures. Specifically, we find that the impact of IT investment is not significant on return on assets (ROA) and operating income for the same set of hospitals. This research note contributes to research and practice by demonstrating that the overall impact of IT is better understood when accounting measures are complemented with the firms market value. Such market valuation is also critical in merger and acquisition decisions, an activity that is likely to accelerate in the healthcare industry. Our findings provide hospitals, as well as other NPT firms, with insights into the impact of IT investment and a pragmatic approach to demonstrating ITs contribution to firm value.

Security Assurance: How Online Service Providers Can Influence Security Control Perceptions and Gain Trust

Security researchers agree that security control is a difficult to observe credence quality of online services that Internet users cannot easily assess through research or experience. Yet there is evidence that users form perceptions of security control that strongly determine how much trust they put in online services. This study investigates whether users’ security control perceptions arise solely from their predispositions or whether online service providers can influence them. The study also examines whether these seemingly undependable perceptions of security control lead to trust or whether more traditional factors might offer a better explanation of trust under security risks. To address these issues, this study proposes a new theory of security assurance that integrates the frameworks of trust and quality signals. The results show that rather than being guided by predispositions, users appear to mainly assess security control based on indirect cues controlled by service providers. Importantly, Internet users do not treat the credence quality of security the same way they treat qualities that can be understood through search and experience. Although returning users develop security control perceptions and trust from the usual heuristics of ongoing relationships, they also continue to evaluate market information about service providers like they do in new relationships. The proposed model offers a new perspective of how users respond to the uncertain and technically challenging qualities prevalent in online services.

Supporting systems analysis and design through fisheye views

Demonstrating the usefulness of integrating context-based views into the systems analysis and design process.

On policy capturing with fuzzy measures

Policy capturing methods generally apply linear regression analysis to model human judgment. In this paper, we examine the application of fuzzy set and fuzzy measure theories to obtain subjective descriptions of cue importance for policy capturing. At the heart of the approach is a method of learning fuzzy measures. The Shapley values associated with the fuzzy measures provide a basis for comparison with the results of linear regression. However, the fuzzy measure-theoretical approach provides additional insight into interaction effects corresponding to the nonlinear, noncompensatory nature of the underlying decision model. To illustrate the methodology, we estimated the importance of factors and the interactions among them that influence decisions related to strategic investments in telecommunications infrastructure and compared the results from the fuzzy approach to those obtained from traditional statistical methods.

WEBVIEW: an SQL extension for joining corporate data to data derived from the web

Using SQL and database technology to seamlessly retrieve information from any corporate or external Web site.

Which online channel is right? Online auction channel choice for personal computers in the presence of demand decay

Electronic commerce has become a viable marketing channel for many companies as they take advantage of the ease of electronic markets to move merchandise quickly and inexpensively. Researchers have investigated the use of an e-commerce channel in conjunction with traditional channels, but less research has been dedicated to choosing which e-commerce channel to use. In this study, we examine the choices made by Dell, a computer manufacturer, about whether to utilize their own proprietary auction site to sell computers or to use eBay, a popular and well-established third-party auction site, to move excess merchandise. We find that Dell receives a price premium over other vendors of Dell computers, and that DellAuction.com receives a price premium over eBay.com auctions. This price premium is drastically reduced as technology ages and is made obsolete by newer technology-based products. We further find that there is little to no price premium for extremely new technology, which is consistent with a contention that the online auction demand is so high for new technology that Dell cannot realize much of a price premium making a more popular third-party channel a more viable option.

Trust and experience in online auctions

ABSTRACT This paper aims to shed light on the complexities and difficulties in predicting the effects of trust and the experience of online auction participants on bid levels in online auctions. To provide some insights into learning by bidders, a field study was conducted first, to examine auction and bidder characteristics from eBay auctions of rare coins. We proposed that such learning is partly because of institutional-based trust. Data were then gathered from 453 participants in an online experiment and survey, and a structural equation model was used to analyze the results. This paper reveals that experience has a nonmonotonic effect on the levels of online auction bids. Contrary to previous research on traditional auctions, as online auction bidders gain more experience, their level of institutional-based trust increases and leads to higher bid levels. Data also show that both a bidder’s selling and bidding experiences increase bid levels, with the selling experience having a somewhat stronger effect. This paper offers an in-depth study that examines the effects of experience and learning and bid levels in online auctions. We postulate this learning is because of institutional-based trust. Although personal trust in sellers has received a significant amount of research attention, this paper addresses an important gap in the literature by focusing on institutional-based trust.

Parallel Implementation of Lemke's Algorithm on the Hypercube

A simple but very effective method for parallelizing Lemkes algorithm for the solution of linear complementarity problems is presented. Implementation details on a 32-node Intel iPSC/2 hypercube for problems of dimension up to 1000 are discussed. A speedup efficiency as high as 76% is achieved with 32 processing nodes for a problem with 500 variables and 250,000 nonzero elements. By combining the effects of concurrency and vectorization the computing time on the Intel iPSC/2 in some cases is reduced by a factor of 100. INFORMS Journal on Computing , ISSN 1091-9856, was published as ORSA Journal on Computing from 1989 to 1995 under ISSN 0899-1499.