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The purpose of this paper is to provide an explanation of factors influencing online music purchase intention of Taiwanese early adopter of online music, which can help the online music practitioners of Taiwan to develop better market strategies.

An empirical survey was used to test the hypotheses. Data were collected from a total of 302 online Taiwanese early adopters of online music. A structural equation modeling (SEM) is proposed to assess the relationships of the research model.

The findings in this paper show that the perceived value of online music is a significant factor in predicting the purchaser intention of buying online music in Taiwan. Also, the beneficial factor of the perceived usefulness and playfulness are identified in addition to the sacrificing factor of the perceived price for assessing the value. Moreover, purchasers and potential purchasers differ in the determinants underlying the perceptions of value, which customers hold towards online music.

The results in the paper facilitate to understand what encourages and impedes the purchase intention of early adopters of online music in Taiwan.

The value of this paper is to establish a theoretical model incorporating the value‐intention framework into technology acceptance model to investigate the purchase behavior of early adopter of online music in Taiwan. The results of this study help online music practitioners of Taiwan and other Asian countries culture similar to Taiwan to create a success business model.

This study explores the relationship among relationship-selling, celebrity attachment and customer engagement.

Hypotheses were tested, using structural equation modeling on survey responses of 321 participants.

This study determines the connection between relationship-selling factors and customer engagement using the stimulus-organism-response (SOR) theory. Results demonstrate that interactional intensity, mutual disclosure and cooperative intention exert considerable positive effects on celebrity attachment, which, in turn, significantly impacts customer engagement.

The research findings add to the existing body of knowledge through more information on the degree to which relationship-selling factors affect celebrity attachment, and eventually, customer engagement. The study also aims to prompt researchers and organizations to consider effective communication strategies to increase online customer engagement.

The explosion of data due to the sophistication of information and communication technology makes it simple for prospective tourists to learn about previous hotel guests' experiences. They prioritize the rating score when selecting a hotel. However, rating scores are less reliable for suggesting a personalized preference for each aspect, especially when they are in a limited number. This study aims to recommend ratings and personalized preference hotels using cross-domain and aspect-based features.

We propose an aspect-based cross-domain personalized recommendation (AsCDPR), a novel framework for rating prediction and personalized customer preference recommendations. We incorporate a cross-domain personalized approach and aspect-based features of items from the review text. We extracted aspect-based feature vectors from two domains using bidirectional long short-term memory and then mapped them by a multilayer perceptron (MLP). The cross-domain recommendation module trains MLP to analyze sentiment and predict item ratings and the polarities of the aspect based on user preferences.

Expanded by its synonyms, aspect-based features significantly improve the performance of sentiment analysis on accuracy and the F1-score matrix. With relatively low mean absolute error and root mean square error values, AsCDPR outperforms matrix factorization, collaborative matrix factorization, EMCDPR and Personalized transfer of user preferences for cross-domain recommendation. These values are 1.3657 and 1.6682, respectively.

This study assists users in recommending hotels based on their priority preferences. Users do not need to read other people's reviews to capture the key aspects of items. This model could enhance system reliability in the hospitality industry by providing personalized recommendations.

This study introduces a new approach that embeds aspect-based features of items in a cross-domain personalized recommendation. AsCDPR predicts ratings and provides recommendations based on priority aspects of each user's preferences.

This paper provides, first, a historical perspective of accounting research relating to Asian/Pacific countries as seen from the vantage of the leading international journal in the United States and, second, a bibliographical data base and index of twenty‐six years of articles on this region of the world. It accomplishes the first objective by presenting a tabular profile of research in international accounting as it pertains to countries in the Asian/Pacific Rim region as shown in articles published in the International Journal of Accounting (formerly, the International Journal of Accounting, Education and Research) and related publications which appeared from 1965 to 1990. The articles are classified according to country, research methodology, subject, and five‐year time periods. The paper accomplishes the second objective by providing an annotated bibliography of 125 articles on Asian/Pacific Rim countries and indices by country and methodology, and subject.

The purpose of this paper is to investigate the influence of two dimensions of relational risks, namely, opportunism behavior and interest conflict, on knowledge flow and to explore the moderating effect of network power among these untested relationships and to examine the positive effect of opportunism behavior and interest conflict.

This paper adopts survey data collected from 180 enterprises in China's high-technology industry and examines the relationship between relational risks, network power and knowledge flow.

This research empirically shows that opportunism behavior and interest conflict significantly and negatively impact on knowledge flow. Those relationships are positively moderated by network power.

To be more generalized to the high-technology industry, future research should adopt the quantitative research, which can obtain more comprehensive information to explore the nature of phenomenon. The future research can also combine with other variables. In addition, this research extends the current literature by investigating the relationship of so far understudied theorized antecedents.

This research enriches the related network perspective literature by providing new insight combining relational risks and knowledge flow. Especially, the moderating effect of network power is empirically examined.