Brenda Mak

A conceptual framework and belief-function approach to assessing overall information quality

We develop an information quality model based on a user‐centric view adapted from Financial Accounting Standards Board,1 Wang et al.,2 and Wang and Strong.3 The model consists of four essential attributes (or assertions): accessibility, interpretability, relevance, and integrity. Four subattributes lead to an evaluation of integrity: accuracy, completeness, consistency, and existence. These subattributes relating to integrity are intrinsic in nature and relate to the process of how the information was created and the first three attributes: (accessibility, interpretability, and relevance) are extrinsic in nature. We present our model as an evidential network under the belief‐function framework to permit user assessment of quality parameters. Two algorithms for combining assessments into an overall IQ measure are explored, and examples in the domain of medical information are used to illustrate key concepts. We discuss two scenarios, online user and assurance provider, which reflect two likely and important aspects of IQ evaluation currently facing information users—concerns about the impact of poor quality online information and the need for IQ assurance.

A confirmatory factor analysis of IS employee motivation and retention

Abstract It is widely recognized that the relationships between organizations and their IS departments are changing. This trend threatens to undermine the retention of IS workers and the productivity of IS operations. In the study reported here, we examine IS employees’ motivation and intent to remain using structural equation modeling. A survey was conducted among existing IS employees and analyzed with LISREL VIII. Results showed that latent motivation has an impact on latent retention, with job satisfaction and perceptions of management on career development as indicator variables for the former, and burnout, loyalty, and turnover intent as indicator variables for the latter. Implications for management in developing strategies for the retention of IS employees are provided.

Rule extraction from expert heuristics: A comparative study of rough sets with neural networks and ID3

Abstract The rule extraction capability of neural networks is an issue of interest to many researchers. Even though neural networks offer high accuracy in classification and prediction, there are criticisms on the complicated and non-linear transformation performed in the hidden layers. It is difficult to explain the relationships between inputs and outputs and derive simple rules governing the relationships between them. As alternatives, some researchers recommend the use of rough sets or ID3 for rule extraction. This paper reviews and compares the rule extraction capabilities of rough sets with neural networks and ID3. We apply the methods to analyze expert heuristic judgments. Strengths and weaknesses of the methods are compared, and implications for the use of the methods are suggested.

A model of customer satisfaction and retention for hotels

ABSTRACT This study was designed to assess the antecedents and consequences of customer satisfaction and retention in the hotel industry. The relationship between customer satisfaction and customer retention has been researched for many years. This study extended that research to look at the antecedent effects of customer satisfaction as well as the effect of added value and gender on customer satisfaction and customer retention, and how they relate to the intent to switch. Customer retention was operationalized in terms of loyalty and intent to switch. Customer satisfaction was operationalized in terms of hotel ambience and hospitality. A survey among hotel customers in the San Francisco Bay Area was conducted. A LISREL structural equation model with confirmatory factor analysis was developed to analyze the data. Results indicated that the latent construct customer retention was dependent on the latent construct of customer satisfaction. Added value was found to have positive effects on customer satisfaction and customer retention. Managerial implications to develop strategies to improve customer satisfaction and enhance retention of hotel customers were discussed.

User participation in knowledge update of expert systems

Abstract Applying the Elaboration Likelihood Model (ELM) of persuasion we conducted an experiment to examine the effect of participation of users in the design process on their acceptance of system recommendations and revision of their original decisions. Results of our study indicate that two different types of information processing occur when subjects are reviewing the expert system recommendations. 1. (i) For users who have a high perceived level of participation in updating the knowledge of the ES, ambiguity of the decision setting is the primary determinant affecting acceptance of the recommendation from the ES. 2. (ii) For users who have a low perceived level of participation in updating the knowledge of the ES, acceptance of system recommendation to revise their original judgment is dependent on the perceived credibility of the experts building the system. We discuss the implications of these findings for the design of expert systems.

A New Look at the Antecedents and Consequences of Relationship Quality in the Hotel Service Environment

Abstract As economic conditions improve, hotels are investing in new ways to improve service quality and perceived value that hopefully will lead to better customer satisfaction and loyalty. This study took a new look, with newly developed scales, at the antecedents and consequences of relationship quality in the hotel service environment to shed new light on the factors hotels have to deal with to achieve their objective of satisfied and loyal customers. Using a structural equation model, it was determined that the tangible and intangible factors of perceived value, timeliness, and hotel facilities are antecedents of hotel quality. Hotel quality, subsequently, is a determinant of both customer satisfaction and loyalty. However, consistent with previous research, customer satisfaction is not a guarantee of customer loyalty.

A multi-national study of attitudes about mobile phone use in social settings

Mobile phones have taken on the role of providing truly portable and individual communications and computing. Unlike many devices, however, mobile phones can be used anywhere and anytime. Consequently, they are used in social situations such as restaurants and theatres where co-located people can be bothered by their use. How people perceive the impact of mobile phones in these situations may vary by user factors such as age, gender and work status, and by the country in which the user is located. This paper presents the results of a multi-national study of attitudes about mobile phone use in social situations.

An empirical measure of element contribution in neural networks

A frequent complaint about neural net models is that they fail to explain their results in any useful way. The problem is not a lack of information, but an abundance of information that is difficult to interpret. When trained, neural nets will provide a predicted output for a posited input, and they can provide additional information in the form of interelement connection strengths. This latter information is of little use to analysts and managers who wish to interpret the results they have been given. We develop a measure of the relative importance of the various input elements and hidden layer elements, and we use this to interpret the contribution of these components to the outputs of the neural net.

Aggregating and updating experts' knowledge: An experimental evaluation of five classification techniques

Abstract Knowledge acquisition consists of eliciting expertise from one or more experts in order to construct a knowledge base. When knowledge is elicited from multiple experts, it is necessary to combine the multiple sources of expertise in order to arrive at a single knowledge base. In this paper, we present and compare five techniques for aggregating expertise. An experiment was conducted to extract expert judgments on new product entry timing. The elicited knowledge was aggregated using classical statistical methods (logit regression and discriminant analysis), the ID3 pattern classification method, the k-NN (Nearest Neighbor) technique, and neural networks. The neural net method was shown to outperform the other methods in robustness and predictive accuracy. In addition, the explanation capability of the neural net was investigated. The contributions of the input variables to the change in the output variable were interpreted by analyzing the connection strengths of the neural net when the net stabilized. We conclude by discussing the use of neural nets in knowledge aggregation and decision support.

A MODEL OF ATTITUDES TOWARDS THE ACCEPTANCE OF MOBILE PHONE USE IN PUBLIC PLACES

Since the first commercial launch of cellular telecoms by NET in Tokyo Japan in 1979 and the launch of the NMT system in Denmark, Finland, Norway and Sweden in 1981, the mobile phone has undergone continual incremental innovation for changing market needs. This study investigates the factors affecting the attitudes towards the social acceptance of mobile phones in public places and how this attitude affects its usage. Theories on innovation and technology acceptance were reviewed, and studies relating demographic factors to technology acceptance were examined. A model was proposed relating the usage frequency and attitudes towards acceptance of mobile phone in public places to demographic factors, such as country, age, education, gender, and work status. A survey was conducted among mobile phone users, and the sample consisted of 1079 respondents in the United States, France, Italy, Turkey, and Finland. A structural equation model was developed to analyze the survey data. Results of the analysis indicate that the attitudes about mobile phone use in public places depend on country, and age factors. This attitude in turn significantly affects the usage frequency of mobile phones. In addition, usage frequency also is affected by gender and work status. Implications of the findings for both academicians and practitioners are discussed