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Information technology changes rapidly, and the market trend flow changes even faster. The information systems (IS) department in a technological oriented environment has to ensure that the plans or solutions made by the IS department can align with organizational strategy to avoid resources waste, and adaptability is a crucial issue for an IS department too. This study believes that adaptability and alignment of the IS department are ambidexterity. The concept of knowledge use effectiveness (KUE), based on the human agency theory, proposed a research model mainly founded on intellectual capital, human agency theory, and contextual ambidexterity, and used intellectual capital (including human, structure and relational capital) as a framework to find the antecedents of knowledge usage.

This study conducts an empirical research method and collects 150 valid cases from the IS department employees in Taiwan.

The results of this study are: (1) KUE in an IS department significantly improves the ambidexterity; (2) intellectual capital has a positive influence on KUE; (3) despite human capital having no influence on iteration, iterational KUE has no influence on adaptability.

For academics, this study has developed KUE through a novel perspective and uses the concept of the human agency to articulate the characteristic of KUE, and thus has combined the intellectual capital, human agency and contextual ambidexterity into a research model. For managers, they should learn that KUE has a positive effect on the IS department ambidexterity, composed of alignment and adaptability. By knowing that, they can understand the concrete elaboration of KUE much better. Therefore, enhancing the process of knowledge usage can be a practical and useful way of improving an IS department performance.

This study aims to empirically analyse the influence mechanism of perceived interactivity in real estate APP which affects consumers' psychological well-being. With the growing application of human–machine interaction in real estate APP, it is crucial to utilize human–machine interaction to stimulate perceived interactivity between humans and machines to positively impact consumers' psychological well-being and sustainable development of real estate APP. However, it is unclear whether perceived interactivity improves consumers' psychological well-being.

This study proposes and examines a theoretical model grounded in the perceived interactivity theory, considers the relationship between perceived interactivity and consumers' psychological well-being and explores the mediating effect of perceived value and the moderating role of privacy concerns. It takes real estate APP as the research object, analyses the data of 568 consumer samples collected through questionnaires and then employs structural equation modelling to explore and examine the proposed theoretical model of this study.

The findings are that perceived interactivity (i.e. human–human interaction and human–information interaction) positively influences perceived value, which in turn affects psychological well-being, and that perceived value partially mediates the effect of perceived interaction on psychological well-being. More important findings are that privacy concerns not only negatively moderate human–information interaction on perceived value, but also negatively moderate the indirect effects of human–information interaction on users' psychological well-being through perceived value.

This study expands the context on perceived interaction and psychological well-being in the field of real estate APP, validating the mediating role and boundary conditions of perceived interactivity created by human–machine interaction on consumers' psychological well-being, and suggesting positive implications for practitioners exploring human–machine interaction technologies to improve the perceived interaction between humans and machines and thus enhance consumer psychological well-being and span sustainable development of real estate APP.

This study aims to develop a conceptual model for GET products that participate in brands’ online communities, based on social cognitive theory (SCT), with environmental factors, personal factors and behavioral factors being used to explore whether users of GET products participate in brand online communities as well as to determine whether participation in a community forum causes users to stick with GET products. In addition, expectancy confirmation is also considered in the research model.

This research examines whether environmental and personal factors have a positive effect on the behavioral factors of Gogoro users, and then further effects on green energy technology (GET) product stickiness for users in online communities. A website was used to distribute links to two Facebook club sites: Gogoro Series 2 Fan Club and the Gogoro Fan Club. The respondents’ qualification criteria were restricted to people who had used Gogoro products and participated in a Gogoro online community. A total of 581 valid responses were collected for structural equation modeling (SEM) analysis, and expectancy confirmation was found to be moderate from a hierarchical regression.

The results of SEM show that virtual interactivity has a positive effect on product-related content, and social norms were found to have significant effects on creating product-related content. Brand community identification, perceived relative advantage and brand knowledge self-efficacy are found to be related to both creating and contributing product-related content. Also, creating product-related content and contributing user participation behaviors influence ET product stickiness.

Online community managers can boost user participation by increasing interaction, and community identification by enhancing users’ perceptions of benefiting from participating in their communities. Companies can also encourage users to create product-related content to increase users’ stickiness to GET products. Further, GET companies can try to enhance users’ intrinsic connection with other community users to increase their brand community identification if they want to increase users’ willingness to participate.

This study adopted SCT to measure the GET product stickiness formation process in an attempt to determine what factors boost user participation based on triadic reciprocality. Also, expectancy confirmation plays an important role in the relationship between community users’ participation behaviors and GET product stickiness. The results indicated that it was appropriate to add virtual interactivity to environmental factors and perceived relative advantage to personal factors to measure users’ participation in an online social community. Actual product users’ online community participation behavior could be a very influential indicator of actual product stickiness formation.

The purpose of this paper is to examine the influence of four organizational culture traits, consistency, cooperativeness, effectiveness and innovativeness, on radical and incremental type of service innovations, which leads to new service market performance (NSMP).

The data are collected through a cross-sectional survey of 171 bank managers in Bangladesh and analyzed through structural equation modelling using SmartPLS software.

The results reveal no impact of “consistency” as a cultural trait on “radical” and “incremental” service innovations. “Cooperativeness” and “innovativeness” impact incremental and radical service innovations positively. “Effectiveness” impacts radical service innovations positively. Radical and incremental service innovations impact NSMP significantly.

These findings add to the knowledge in terms of how organizational culture can make service innovations happen in the growing banking industry in a developing market.

The model links organizational culture traits (internal/external and flexibility/control focussed) with radical and incremental service innovation.

The purpose of this paper is to understand the effect of platform characteristics (i.e. media richness and interactivity) on individual perception (i.e. outcome expectations) and consequent behavioral response (i.e. user participation in online health communities (OHCs)) based on the stimulus-organism-response (S-O-R) model.

This study developed a research model to test the proposed hypotheses, and the proposed model was tested using partial least squares structural equation modeling (PLS-SEM) for which data were collected from 321 users with OHC experience using an online survey.

The empirical results show the following: (1) the three dimensions of media richness significantly affect the three outcome expectations, except that richness of expression has no significant effect on the outcome expectation of health self-management competence. (2) Human-to-human interaction significantly affects the three outcome expectations. Moreover, compared with human-to-human interaction, human-to-system interaction has a stronger impact on the outcome expectation of health self-management competence. (3) The three outcome expectations have a significant influence on user participation in OHCs.

This study extends the understanding about how platform characteristics (i.e. media richness and interactivity) motivate user participation in the context of OHCs. Drawing on the S-O-R model, this study reveals the underlying mechanisms by which media richness and interactivity are associated with outcome expectations and by which outcome expectations is associated with user participation in OHCs. This study enriches the literature on media richness, interactivity, outcome expectations and user participation in OHCs, providing insights for developers and administrators of OHCs.

The purpose of this paper is to develop an evaluation model to determine the relative weights of key factors influencing international market development (IMD) success through analysis network process (ANP) during group decision-making. An empirical case of the Taiwan bulk shipping industry is used to illustrate the feasibility of the proposed approach.

The literature review is performed to generate 20 key success factors (KSFs) along with four factor categories in IMD (such as organizational capability, environmental scanning, international strategy and internationalization behavior). Then, ANP is applied to develop an evaluation model that prioritizes the relative importance linking the above four factor categories with 20 evaluated KSFs.

With respect to the final weights for factor categories, “international strategy” and “environmental scanning” are the two most important criteria, followed by “organizational capability” and “internationalization behavior”. The results also showed that by reviewing the global weights of the 20 KSFs of IMD, “service as competitive advantage”, “market potential” and “risk taking” have the highest rankings.

The findings indicate that firm expansion into international markets typically depends on a successful international strategy. Hence, to enhance their global market competitiveness, Taiwan bulk shipping firms should focus their efforts on planning international market entry strategy and prioritizing shipping services with high-potential target markets.

Theoretically, the study results can provide both theoretical basis and empirical evidence, indicating the relative weights and priorities of KSFs of IMD for the Taiwan bulk shipping industry. From the managerial perspective, the analytical results can help managers focus on main factors and identify the best policy to improve their IMD practice and performance.

This chapter examines herd behavior across national borders. A dynamic latent factor model with Gibbs sampling is used to decompose the national herd behavior into the world, regional, and country-specific components. Testing the daily data from 2000 through 2014 for 47 countries, we find that the impact of world factor on national herd behavior is short-lived. This study indicates that world and regional factors play a significant role in explaining the variations of national herd behavior, constituting 33% of the herding variability. The significance of world and regional components is likely to produce a biased herding estimator.

In the stock market, herding behavior occurs when investors mimic the actions of others in their investment decisions. As a result, the market becomes inefficient and speculative bubbles form. This study aims to investigate the relationship between information, overconfidence, market sentiment, experience and national culture, and herding behavior among Malaysian investors. A total of 400 questionnaires are distributed to bank institutions' investors. The survey design based on cross-sectional data is analyzed using the Partial Least Squares Structural Equation Model. The results indicate that information, market sentiment, experience, and national culture are positively related to herding behavior, while overconfidence has no effect. With this, the government should strengthen regulations to prevent the dissemination of misleading information. Moreover, investors are encouraged to overcome narrow thinking by expanding their understanding of different cultures when making investment decisions.

This paper aims to apply the spacing effect of capacitive imaging (CI) sensors to inspect and differentiate external flaws of the protective module, internal flaws of the protective module and external flaws of the metallic module in oil and gas pipelines simultaneously. Through experimental verification, a method for differentiating three distinct kinds of flaws derived from the spacing effect of CI sensors has been demonstrated.

A 3Dimensions (3D) model for simulating the inspection of these flaws was established by using COMSOL. A novel CI sensor with adjustable working electrode spacing was designed, and a modular CI system was developed to substantiate the theoretical findings with experimental evidence. A method for differentiating three distinct kinds of flaws derived from the spacing effect of CI sensors was established.

The results indicate that the method can successfully discriminate external flaws of the protective module, internal flaws of the protective module and external flaws of the metallic module using CI sensors.

The method for differentiating three distinct kinds of flaws derived from the spacing effect of CI sensors is vital for keeping the transportation safety of oil and gas pipelines.