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In the past few decades, there has been a lot of literature about trust research for business and management. However, few authors have applied co-citation analysis.

Trust is one of the most discussed issues in management, as it has proved to have an essential role in business operations. In this study, all citation documents are included in Thomson Reuters ISI Web of Knowledge database from 1992 to 2010.

By using statistics analysis including factor analysis, cluster analysis and multidimensional scaling, researchers identified four domains, including organizational behaviour, strategic alliance, marketing and social capital. Directions for future research are discussed.

This study is the first to apply co-citation techniques in the fields of trust. Therefore, the major contribution of this study is to provide an intellectual structure and trends within the field of trust from an objective and quantitative perspective.

Although numerous studies have examined factors that influence smartphone acceptance and use, few have analyzed cognitive age. This study aims to use the unified theory of acceptance and use of technology (UTAUT) to test two models to analyze the moderating effect of cognitive age. This research offers relevant suggestions among different cognitive age groups.

A questionnaire survey was conducted to collect research data in Taiwan and the UTAUT model was used. Model 1 ensures all four antecedent constructs among digital natives (those under 34 years old). Model 2 divides the digital immigrants into two groups to test the influence of cognitive age on the behaviors of smartphone use. This study tests Model 1 using AMOS 20 to examine the measurement and structural model and validates Model 2 using partial least squares (PLSs).

In Model 1, the digital natives have sufficient confidence to accept a new technology with ease and little effort owing to most educational resources and the widespread internet. Group 1 in Model 2 reveals that the behavior of digital immigrants is similar to that of digital natives. For Group 2 in Model 2, they tend to infer that skills or tasks they associate with having higher value are more difficult to learn.

This study provides another dimensional result for different cognitive age groups and it has to consider not only chronological age but also cognitive age in user behavior. The result can enrich the theoretical perspective on technology adoption and use behavior via cognitive age, which is a significant and important self-related factor that can help predict technology adoption and use behavior.

Online video advertisement is a wide-ranging phenomenon on the internet that provides huge opportunities for business enterprises. The revenues of website service providers come primarily from advertisement. However, it is rare to find research focusing on consumer attitudes toward online video advertisement. This study aims to investigate consumer attitudes toward advertisement while they are watching online videos on YouTube.

The paper followed Brackett and Carr’s (2001) Web Advertising Attitudes Model and combined it with the theory of reasoned action (TRA) and the flow theory. This study investigates consideration of the factors affecting attitudes toward advertisement and the influence on shopping intention and purchase behavior.

The findings indicate that entertainment, informativeness, irritation and credibility have a shopping influence on purchase attitudes. Flow, on the other hand, does have an influence on shopping intention and purchase behavior. The discussion and conclusion have been further discussed.

This study provides a comprehensive model for online video advertisement. This model was based on Brackett and Carr’s model, combining the users and gratifications theory, TRA and flow theory to develop an online video advertisement model. Researchers can consider this model as a framework and use it to capture a more complete picture of the relevant phenomena in their works.

The purpose of this research is to describe an efficient search methodology to help improve the search results in the top portion of a lengthy search list. When facing a lengthy search list, people often limit themselves to the top ten items on the list, even though there may be more useful information after the top ten items.

This study proposes an ontology‐based adaptive semantic search to significantly improve the search experience. To capture the semantic difference of search terms, naïve ontology is used to store the relationship among terms. Before a search term is processed by the search engine Lucene, the related words of the search term are selected from ontology structures to form new query phrases in the process of query expansion. The weighting of the expanded query phrases is dynamically learned by observing the users' clicking behaviors.

Research results show that with the aid of ontology the average precision rate of all cases is dramatically higher than the precision rate for the default search result. Even in the worst cases, in some situations, this ontology is still close to the precision rate for the default search result.

This paper shows how it is possible to improve the precision rate of items retrieved after a search and thus avoid information overload.

The purpose of this article is to investigate urban and rural differences for online activities and e‐payment behavior patterns.

This study applied the MLCA model to investigate Internet usage patterns from 11 online applications among 10,909 Taiwan residents in 25 different regions.

The results showed that online behavior patterns exhibited regional differences, as the regional segments affected the individual segments of different use patterns. For instance, the urban area comprised a higher proportion of members who were accustomed to internet applications and skilled in online shopping by using a credit card. The rural area made up a higher proportion of members who only occasionally used online services. Moreover, rural region residents used other payment methods (excluding credit cards) more often than urban region residents. As expected, users’ personal characteristics also dictated the online behavior pattern. For instance, people with higher‐level income spent relatively more money for online shopping and often used various internet applications than others.

The findings herein should help Internet service providers form an applicable guideline for developing service strategies of higher service satisfaction regarding products and users’ needs.

This study implemented a multilevel latent class model to investigate online behavior patterns that exhibited urban and rural differences, with the goal of providing service providers an understanding and mastery of their target users.

Semantic technologies are a potential approach to enhancing the use of the web of knowledge. An experiment was conducted to investigate the roles of two semantic techniques, namely concept recommendation and mind maps, for females and males This paper aims to document this research.

The study compared the searching behaviours and perceptions of searching strategies in the search environment with techniques to reveal the gender difference in the use of semantic technologies. The study further investigated how the techniques influenced female and male students' searching experiences by comparing their searching behaviours and strategies in two different environments, one developed with the semantic technologies and one without.

Although the techniques were helpful for both female and male students in improving their perceptions of searching strategies, there were gender differences in sense of disorientation, problem solving and searching patterns. In particular, the techniques facilitated females to search for information beyond similarity holes, but did not demonstrate such an effect on males. However, they supported males to organize information for better use.

The study is only a small‐scale investigation. Further studies need to be conducted with a larger sample to obtain robust evidence.

In this paper, the effects of semantic technologies are evaluated from the perspectives of education and the human factor, rather than only in terms of technical performance.