Fang-Ming Hsu

Measuring relative efficiency of government-sponsored R&D projects: A three-stage approach

Without considering differences in operating environment, traditional methods of efficiency evaluation are suffering from external environmental influences. This study presents an alternative approach for assessing the relative efficiency of government-sponsored research and development projects (GSP). A three-stage approach employing data envelopment analysis to evaluate efficiency and Tobit regression to control external variables was applied to 110 projects over 9 years. This study finds that firm size, industry, and ratio of public subsidy on research and development (R&D) budget of recipient firm significantly influences the technical efficiency of GSP in Taiwan. After controlling these external variables, the mean value of technical efficiency in the third stage increases and becomes significantly different to that in the first stage. Most GSPs increase their returns when their projects are scaled up. Furthermore, government policy makers must establish the upper-limit ratio of subsidies on R&D budgets of recipient firms to avoid inefficient use of public funds.

Design and implementation of an intelligent recommendation system for tourist attractions

Highlights? Based on the EBM model, we develop a decision support system for tourist attractions. ? The probability of a tourist attraction is calculated utilizing a Bayesian network. ? The accuracy of the prediction is validated by a ROC curve test. ? The recommended routes and tourist attractions are presented by Google Maps. Selecting tourist attractions and collecting related site information is one of the most crucial activities for a tourist when making decisions for a trip. Although various recommendation systems have been discussed over the last decade, rarely do such systems take individual tourist preference information into consideration. Based on the Engel-Blackwell-Miniard (EBM) model, this study used data published by the Tourism Bureau of Taiwan to develop a decision support system for tourist attractions. The probability of a tourist attraction appealing to a particular tourist is calculated utilizing a Bayesian network, and the accuracy of the prediction is validated by a ROC curve test. Finally, recommended routes and tourist attractions are presented through an interactive user interface using Google Maps. This study confirms that by combining the EBM model with a Bayesian network to propose a decision support system called the Intelligent Tourist Attractions System (ITAS). It has demonstrated good prediction of tourism attractions and provides useful map information to tourists.

Segmenting customers by transaction data with concept hierarchy

The segmentation of customers is crucial for an organization wishing to develop appropriate promotion strategies for different clusters. Clustering customers provides an in-depth understanding of their behavior. However, previous studies have paid little attention to the similarity of different items in transaction. Lack of categories and concept levels of items, results from item-based segmentation methods are not as good as expected. Through employing a concept hierarchy of items, this study proposes a segmentation methodology to identify similarities between customers. First, the dissimilarity between transaction sequences is defined. Second, we adopt hierarchical clustering method to segment customers by their transaction data with concept hierarchy of consumed items. After segmentation, three cluster validation indices are used for optimizing the number of clusters of customers. Through the compassion of normalized index, the segmentation method proposed by this study rendered better results than other traditional methods.

Efficiency and satisfaction of electronic records management systems in e‐government in Taiwan

Purpose – The purpose of this paper is to investigate the efficiency and satisfaction of electronic records management systems (ERMS), which has been of interest to archivists and records managers, in electronic government (e‐government) agencies in Taiwan.Design/methodology/approach – Using the measures from information systems (ISs) success model, this study applies data envelopment analysis to measure the relative efficiency and satisfaction in different types of e‐government agencies. After conducting a large‐scale survey of e‐government agencies in Taiwan, a matrix of efficiency and satisfaction is developed.Findings – Research results show that the efficiency of ERMS in central agencies exceeds that in local agencies, and the efficiency in upper level agencies exceeds that in lower level agencies. The efficiency in business agencies exceeds that in administration agencies and public schools. Additionally, ERMS users satisfaction in e‐government agencies is linearly related to ERMS efficiency.Resear...

Agency satisfaction with electronic record management systems: A large-scale survey

A huge number of informal messages are posted every day in social network sites, blogs, and discussion forums. Emotions seem to be frequently important in these texts for expressing friendship, showing social support or as part of online arguments. Algorithms to identify sentiment and sentiment strength are needed to help understand the role of emotion in this informal communication and also to identify inappropriate or anomalous affective utterances, potentially associated with threatening behavior to the self or others. Nevertheless, existing sentiment detection algorithms tend to be commercially oriented, designed to identify opinions about products rather than user behaviors. This article partly fills this gap with a new algorithm, SentiStrength, to extract sentiment strength from informal English text, using new methods to exploit the de facto grammars and spelling styles of cyberspace. Applied to MySpace comments and with a lookup table of term sentiment strengths optimized by machine learning, SentiStrength is able to predict positive emotion with 60.6p accuracy and negative emotion with 72.8p accuracy, both based upon strength scales of 1–5. The former, but not the latter, is better than baseline and a wide range of general machine learning approaches.

Business-Technology Alignments in e-Government: A Large-Scale Taiwan Government Electronic Record Management Systems Study

Associate Professor and Chairman, Department of Information Management, National Dong Hwa University, Taiwan, R.O.C. (fmhsu@mail.ndhu.edu.tw); Associate Professor and David Eccles Faculty Fellow, Accounting and Information Systems, David Eccles School of Business, University of Utah, U.S.A. (actph@business.utah.edu); McClelland Professor, Department of Management Information Systems, University of Arizona, U.S.A. (hchen@eller.arizona.edu)

Factors affecting the satisfaction of an online community for archive management in Taiwan

Purpose – The purpose of this paper is to investigate the relationship between the richness of information and the satisfaction of participants in an online community regarding archive management in Taiwan. Design/methodology/approach – An investigation was deployed to attendants in 20 training courses created by the National Archives Administration (NAA) in Taiwan for records staff on the topic of digital preservation. The responses were collected from respondents who were participating in an online community for archive management. Through structural equation modeling method, this study examined the effects of channel richness, information transparency and accessibility of archive to brand image and trust and then continued to the satisfaction of professional participants to archive management in an online community. Findings – Appropriate disclosure of information regarding archiving can effectively improve the satisfaction of participants in the online community to archive. Channel richness of communi...

Examining Agencies’ Satisfaction with Electronic Record Management Systems in e-Government: A Large-Scale Survey Study

While e-government is propelling and maturing steadily, advanced technological capabilities alone cannot guarantee agencies’ realizing the full benefits of the enabling computer-based systems. This study analyzes information systems in e-government settings by examining agencies’ satisfaction with an electronic record management system (ERMS). Specifically, we investigate key satisfaction determinants that include regulatory compliance, job relevance, and satisfaction with support services for using the ERMS. We test our model and the hypotheses in it, using a large-scale survey that involves a total of 1,652 government agencies in Taiwan. Our results show significant effects of regulatory compliance on job relevance and satisfaction with support services, which in turn determine government agencies’ satisfaction with an ERMS. Our data exhibit a reasonably good fit to our model, which can explain a significant portion of the variance in agencies’ satisfaction with an ERMS. Our findings have several important implications to research and practice, which are also discussed.

The innovation strategies of government agencies in implementing information systems

Innovation strategies for deploying information services have arisen from the concern of internal resources and external supports. Agencies with different resources may respond differently in fulfilling the rules and regulations. Through conducting a large-scale survey, this study examines the relationship between the nature of organizations, resources and the innovation strategies of agencies. From the empirical findings, outsourcing has been the major innovation strategy adopted by most large agencies with sufficient resources in implementing IS.

Efficiency and advantage of government-sponsored R&D projects: An inter-industry comparison

In this study, data envelopment analysis (DEA) was applied to investigate the relative efficiencies of government-sponsored R&D projects (GSPs) in different industries in Taiwan. The longitudinal data of 110 GSPs belonging to 4 distinctive industries between 1997 and 2005 were examined. Empirical results showed that aggregated efficiency, technical efficiency and scale efficiency in different industries were significantly different. Besides, we present a Two-Model approach that allows decision-makers to evaluate two models simultaneously-one technical efficiency of intellectual property (IP)-based measures and the second one of application (AP)-based measures. This new method selects only DMUs that are efficient in both IP-based and AP-based measures to be members of the benchmark set. This study show that the two-model approach DEA method of analysis can better indicate managerial efficiency and can help the policy maker at various stages to understand their specific advantages and disadvantages more thoroughly and clearly. This will aid each GSP in the industry to gain a greater understanding of the gap between the outputs of GSPs and improve their operational efficiency by providing future operational strategies analysis.