The fast-growing use of gamification in e-learning underscores its potential to enhance individuals' learning performance and experience. However, the mechanisms through which key gamification element influences people's learning remain unclear. This study addresses this gap by investigating how distinct leaderboard directions influence individual learning performance and satisfaction. We conduct a randomized experiment to examine these effects and explore the underlying mechanisms. Our results show that upward leaderboard improves learning performance and satisfaction by fostering learning effort and active exploration. In contrast, downward leaderboard enhances learning performance and satisfaction through self-efficacy and self-expansion. Interestingly, the effect of lateral leaderboards on learning satisfaction appears not associated with the development of personal meaning. This study contributes to current research and practice by providing important insights for effective gamified e-learning design, implementation, and use.

Research analyzing the growing, worrisome phenomenon of cyberbullying in social network sites (SNSs) tends to adopt a cognitive perspective. This study instead investigates SNS envy, an essential emotion often experienced by users, and its relationship with cyberbullying intentions. The authors apply appraisal theory of emotion as a framework to conceptualize the effects of SNS envy, then propose two competing views: a direct effect premised in general strain theory and an indirect effect rooted in moral disengagement theory. The examinations of these competing views use survey data gathered from Facebook. The results support the indirect but not the direct effect, suggesting that envy influences cyberbullying intentions through moral disengagement. This study explicates how envious users rationalize their cyberbullying behaviors by cognitively reinterpreting existing perceptions of the advantages exhibited by envied others in a SNS, which reveals the importance of considering negative emotions to explain the unsettling cyberbullying phenomenon more fully.

Cultural considerations could affect individuals' behaviors, including their technology acceptance. This study analyzes the acceptance of computer technology by 1,088 workers in 56 Arabian organizations to reexamine and compare the theory of planned behavior (TPB), technology acceptance model (TAM), and innovation diffusion theory (IDT). The explanatory power of each theory or model seems lower among Arabian workers, as compared with users in Western, developed countries. The IDT appears capable of explaining workers' technology acceptance better than does TPB or TAM. Perceived behavioral control and subjective norms constitute more important acceptance determinants than does attitude. Both perceived usefulness and perceived ease of use remain significant determinants of attitude and intention; however, considering findings reported by previous research, their total effects are comparable in magnitude and statistical significance. The findings are incongruent with the results of several representative prior studies that examine the same theories and models, which in turn offer several implications from a sociocultural perspective.

Abstract Influxes of new documents over time necessitate reorganization of document categories that a user has created previously. As documents are available in increasing quantities and accelerating frequencies, the manual approach to reorganizing document categories becomes prohibitively tedious and ineffective, thus making a system‐oriented approach appealing. Previous research (Larsen & Aone, 1999 ; Pantel & Lin, 2002 ) largely has followed the category‐discovery approach, which groups documents by using a document‐clustering technique to partition a document corpus. This approach does not consider existing categories a user created previously, which in effect reflect his or her document‐grouping preference. A handful of studies (Wei, Hu, & Dong, 2002 ; Wei, Hu, & Lee, 2009 ) have taken a category‐evolution approach to develop lexicon‐based techniques for preserving user preference in document‐category reorganizations, but have serious limitations. Responding to the significance of document‐category reorganizations and addressing the fundamental problems of salient, lexicon‐based techniques, we develop an ontology‐based category evolution (ONCE), a technique that first enriches a concept hierarchy by incorporating important concept descriptors (jointly referred to as an ontology) and then employs the resulting enriched ontology to support category evolutions at a concept level rather than analyzing and comparing feature vectors at the lexicon level. We empirically evaluate our proposed technique and compare it with two benchmark techniques: CE2 (a lexicon‐based category‐evolution technique) and hierarchical agglomerative clustering (HAC; a conventional hierarchical document‐clustering technique). Overall, our results show that the ONCE technique is more effective than are CE2 and HAC, across all the scenarios studied. Furthermore, the completeness of a concept hierarchy has important impacts on the performance of the proposed technique. Our results have some important implications for further research.

Abstract We investigated agency satisfaction with an electronic record management system (ERMS) that supports the electronic creation, archival, processing, transmittal, and sharing of records (documents) among autonomous government agencies. A factor model, explaining agency satisfaction with ERMS functionalities, offers hypotheses, which we tested empirically with a large‐scale survey that involved more than 1,600 government agencies in Taiwan. The data showed a good fit to our model and supported all the hypotheses. Overall, agency satisfaction with ERMS functionalities appears jointly determined by regulatory compliance, job relevance, and satisfaction with support services. Among the determinants we studied, agency satisfaction with support services seems the strongest predictor of agency satisfaction with ERMS functionalities. Regulatory compliance also has important influences on agency satisfaction with ERMS, through its influence on job relevance and satisfaction with support services. Further analyses showed that satisfaction with support services partially mediated the impact of regulatory compliance on satisfaction with ERMS functionalities, and job relevance partially mediated the influence of regulatory compliance on satisfaction with ERMS functionalities. Our findings have important implications for research and practice, which we also discuss.

Abstract Biomedical research is critical to biodefense, which is drawing increasing attention from governments globally as well as from various research communities. The U.S. government has been closely monitoring and regulating biomedical research activities, particularly those studying or involving bioterrorism agents or diseases. Effective surveillance requires comprehensive understanding of extant biomedical research and timely detection of new developments or emerging trends. The rapid knowledge expansion, technical breakthroughs, and spiraling collaboration networks demand greater support for literature search and sharing, which cannot be effectively supported by conventional literature search mechanisms or systems. In this study, we propose an integrated approach that integrates advanced techniques for content analysis, network analysis, and information visualization. We design and implement Arizona Literature Mapper, a Web‐based portal that allows users to gain timely, comprehensive understanding of bioterrorism research, including leading scientists, research groups, institutions as well as insights about current mainstream interests or emerging trends. We conduct two user studies to evaluate Arizona Literature Mapper and include a well‐known system for benchmarking purposes. According to our results, Arizona Literature Mapper is significantly more effective for supporting users' search of bioterrorism publications than PubMed. Users consider Arizona Literature Mapper more useful and easier to use than PubMed. Users are also more satisfied with Arizona Literature Mapper and show stronger intentions to use it in the future. Assessments of Arizona Literature Mapper's analysis functions are also positive, as our subjects consider them useful, easy to use, and satisfactory. Our results have important implications that are also discussed in the article.

Abstract This article examines the determinants of service quality and continuance intention of online services. We proposed and empirically tested a model with both service and technology characteristics as the main drivers of service quality and subsequent continuance intention of eTax, an electronic government (eGovernment) service that enables citizens to file their taxes online. Our data were collected via a two‐stage longitudinal online survey of 518 participants before and after they made use of the eTax service in Hong Kong. The results showed that both service characteristics (i.e., security and convenience) and one of the technology characteristics (i.e., perceived usefulness, but not perceived ease of use) were the key determinants of service quality. Another interesting and important finding that runs counter to the vast body of empirical evidence on predicting intention is that perceived usefulness was not the strongest predictor of continuance intention but rather service quality was. To provide a richer picture of these relationships, we also conducted a post‐hoc analysis of the effects of service and technology characteristics on the individual dimensions of service quality and their subsequent impact on continuance intention and found assurance and reliability to be the only significant predictors of continuance intention. We present implications for research and practice related to online services.

Abstract The importance of Intelligence and Security Informatics (ISI) has significantly increased with the rapid and large‐scale migration of local/national security information from physical media to electronic platforms, including the Internet and information systems. Motivated by the significance of ISI in law enforcement (particularly in the digital government context) and the limited investigations of officers' technology‐acceptance decision‐making, we developed and empirically tested a factor model for explaining law‐enforcement officers' technology acceptance. Specifically, our empirical examination targeted the COPLINK technology and involved more than 280 police officers. Overall, our model shows a good fit to the data collected and exhibits satisfactory power for explaining law‐enforcement officers' technology acceptance decisions. Our findings have several implications for research and technology management practices in law enforcement, which are also discussed.

Management of textual documents obtained from various online sources represents a challenge in emerging e-commerce environments, where individuals and organisations have to perform continual surveillance of important events or trends pertinent to multiple topic areas of interest. Observations of textual document management by individuals and organisations have suggested the popularity of using categories to organise, archive and access documents. The sheer volume and availability of documents obtained from the internet make manual document-category management prohibitively tedious, if practicable or effective at all. An automated approach underpinned by appropriate artificial intelligence techniques has potential for solving this problem. In this vein, a critical challenge is the preservation of the user's perspective on semantic coherence in different documents and thus supports his or her preferred practice for document groupings. Motivated by the significance of, and the need for automated document-category management, the current research proposed and experimentally examined an evolution-based approach for supporting user-centric document-category management in e-commerce environments. Specifically, we designed and implemented the Category Evolution (CE) technique, capable of supporting personalised document-category management by taking into account categories previously established by the user. Our evaluation results suggest that CE exhibited satisfactory effectiveness and reasonable robustness in different scenarios and achieved a performance level better than that recorded by the benchmark technique using complete category discovery.