Conventional case-based reasoning (CBR) does not perform efficiently for high-volume datasets because of case retrieval time. To overcome this problem, previous research suggested clustering a case base into several small groups and retrieving neighbors within a corresponding group to a target case. However, this approach generally produces less accurate predictive performance than the conventional CBR. This paper proposes a new case-based reasoning method called the clustering-merging CBR (CM-CBR). The CM-CBR method dynamically indexes a search pool to retrieve neighbors considering the distance between a target case and the centroid of a corresponding cluster. This method is applied to three real-life medical datasets. Results show that the proposed CM-CBR method produces similar or better predictive performance than the conventional CBR and clustering-CBR methods in numerous cases with significantly less computational cost.

Interpersonal trust has become essential for online communities because people have managed to be in a situation without face-to-face encounters. To identify the structural relationships between interpersonal trust and learning performance, we analyzed the relationship between two types of trust, namely, cognitive and affective, as well as two dimensions of learning performance, namely, learning satisfaction and knowledge application. We also identified the moderating role of social norms in the relationship between trust and learning performance. Results of analysis are as follows. First, cognitive trust significantly affected the two dimensions of performance. Second, affective trust exhibited a significant effect on learning satisfaction, but did not affect knowledge application. Third, the relationships between the two performance factors were significant and direct. Lastly, social norms appeared to moderate the effects of cognitive trust on knowledge application and affective trust on satisfaction. These findings suggest that organizations, which would like to optimize task-oriented performance of their learning communities, should consider linking strategies between community satisfaction and practical knowledge application.

The use of global mobile technology has increased exponentially. In particular, a survey of consumers in the Philippines showed that 83% "could not live" without their mobile phones. We investigated factors, such as ease of use and personal innovativeness, to elucidate the consumer adoption of mobile technologies in the Philippines, to integrate existing adoption theories for academics and provide recommendations to practitioners based on our findings. Our research questions are as follows: (1) What key factors drive adoption of mobile technologies by Filipino consumers?; (2) Are Filipino consumers innovative in their use of mobile technologies?; And (3) How can telecom companies retain their customers? A structural equation model, which was built from a survey of 528 mobile Filipino consumers, showed support for repurchase intention to use mobile technologies. The hypotheses were generally supported by variables related to mobile phone usage with the Philippine consumer sample. Results support all of the hypothesized relationships for consumers using mobile technologies. Personal innovativeness did load on both attitude and repurchase intention for mobile applications as originally hypothesized but was strongly loaded for attitude toward using. This research is a first step in understanding the adoption of mobile applications by Filipino consumers. We initially hypothesized that consumer behavior toward mobile applications would involve constructs of innovativeness, ease of use, and satisfaction; however, we found that ease of use was less significant in understanding repurchase intention to use mobile technologies. Personal innovativeness was more important in explaining satisfaction with mobile application attitudes and repurchase intention. The Filipino context of this study also provides other interesting implications. As the Philippines transitions into a more international market, western products start to guide market behavior, particularly consumer adoption.

The performance of a novel medical question-answering engine called CliniCluster and existing search engines, such as CQA-1.0, Google, and Google Scholar, was evaluated using known-item searching. Known-item searching is a document that has been critically appraised to be highly relevant to a therapy question. Results show that, using CliniCluster, known-items were retrieved on average at rank 2 ($MRR@10{\approx}0.50$), and most of the known-items could be identified from the top-10 document lists. In response to ill-defined questions, the known-items were ranked lower by CliniCluster and CQA-1.0, whereas for Google and Google Scholar, significant difference in ranking was not found between well- and ill-defined questions. Less than 40% of the known-items could be identified from the top-10 documents retrieved by CQA-1.0, Google, and Google Scholar. An analysis of the top-ranked documents by strength of evidence revealed that CliniCluster outperformed other search engines by providing a higher number of recent publications with the highest study design. In conclusion, the overall results support the use of CliniCluster in answering therapy questions by ranking highly relevant documents in the top positions of the search results.

Social networking services provide individuals with an easy approach for exchanging messages with others based on interpersonal relationships. However, why individuals spread marketer-generated content (MGC) in their online social circles remains unclear. Therefore, we develop a theoretical model to examine how social capital, intrinsic motivations, personal perceptions, past behavior, and personal traits influence MGC sharing behavior of social media users in micro-blogging context. Data collected from 319 social networking users support the proposed model. The results from partial least squares analyses show that enjoyment, perceived control, and outcome expectations are significant indicators of individual's MGC sharing intention in the social broadcasting environment. Results also suggest that social capital, users' intention, and past behavior positively influence the MGC sharing behavior of users. Moreover, individual prevention pride exhibits a significant interaction effect on the relationships between users' MGC sharing and its antecedents. Implications for research and practice are discussed.

This study developed a conceptual model that integrated psychological and physical reactions resulting from online tourism reviews through a longitudinal trust-satisfaction model (LSTM) developed based on the extended valence framework and expectation-confirmation theory. Online reviews are essential factor of consumer's purchase decision. This phenomenon is well applied in a tourism context. However, investigations on online reviews in a longitudinal approach in a tourism context are quite limited. Therefore, this study suggests a conceptual model based on LTSM and several propositions about how online tourism reviews, which are divided into factual and experiential reviews, influence the future travelers' perceptions and attitudes, such as expectation, confirmation, and destination loyalty, in a longitudinal format by examining previous related studies. Finally, expected results were discussed and several implications were described theoretically and practically.

Online customer reviews (i.e., electronic word-of-mouth) has gained considerable interest over the past years. However, a knowledge gap exists in explaining the mechanisms among the factors that determine the product sales in online retailing environment. To fill the gap, this study adopts a principal-agent perspective to investigate the effect of customer reviews and customer incentives on product sales in online retail stores. Two customer review factors (i.e., average review ratings and the number of reviews) and two customer incentive factors (i.e., price discounts and special shipping offers) are used to predict product sales in regression analysis. The sales ranking data collected from the video game titles at Amazon.com are used to analyze the direct effects of the four factors and the interaction effects between customer review and customer incentive factors to product sales. Result reveals that most relationships exist as hypothesized. The findings support both the direct and interaction effects of customer reviews and incentive factors on product sales. Based on the findings, discussions are provided with regard to the academic and practical contributions.

This study investigates the effects of a two-sided message on product attitude and purchase intention by using a message structure variable, such as attribute importance in the context of online consumer reviews (OCRs). Study 1 explains the previous inconsistent results of a two-side message by comparing a one-side message and a two-side message by using the attribute importance in negative reviews. Study 2 determines the reasons for the inconsistent results of a refutational two-sided message research by using the attribute importance in negative reviews and website trust. Two experiments are designed to test our hypotheses. The first experiment is a $2{\times}2$ factorial design with 84 participants. The second experiment uses a $2{\times}2{\times}2$ factorial design with 196 participants. In study 1, two-sided OCRs are more credible than one-sided OCRs, and two-sided OCRs that use low important attributes are more effective in making favorable product attitude/purchase intention. In study 2, refutational two-sided OCRs that use high attribute importance render positive effects on product attitudes in trustworthy websites. However, the refutation could negatively affect product attitude/purchase intention in low trustworthy websites.

Online communities are an important source of electronic word-of-mouth (e-WOM). However, few studies have examined the use of such messages within the Middle Eastern context. This study focuses on Saudi women as members of an online beauty forum. Previous work suggested a mediating effect of gender, with women being more likely to trust word-of-mouth and follow it up with a purchase. A conceptual model with a theoretical underpinning from existing contributions in literature provides the basis of a coding framework for the message characteristics that influence members' e-WOM adoption. A total of 310 threads and 2200 messages coded into 5725 units were content analyzed to demonstrate cases where e-WOM was adopted and indicate further continuance intention with members returning to the forum. A new category of 'community bonding' was created from the content analysis given the prevalence of emotional aspects in messages. Emotion expressed in messages, often expressed in religious terms, is as influential and important as the cognitive aspects of community bonding.