Che-Hui Lien

Investigating the Relationships among E-Service Quality, Perceived Value, Satisfaction, and Behavioral Intentions in Taiwanese Online Shopping

As the online shopping market gradually grows in Taiwan, it is important to understand the diversity in various aspects of consumer behavior among Internet users. This paper examines the relationships among e-service quality, perceived value, satisfaction, and behavioral intentions for Taiwanese online shoppers. Based on a sample of 428 undergraduate students, a two-step structural equation modeling procedure is applied to perform an empirical test of the comprehensive model. The testing results show that, for the direct path, electronic service quality has a significant, positive influence on perceived value, satisfaction, and behavioral intentions. Also, perceived value directly influences customer satisfaction and behavioral intentions and satisfaction is an antecedent of behavioral intentions. For the indirect path, electronic service quality has a significant, positive influence on behavioral intentions through satisfaction and perceived value. Perceived value indirectly influences behavioral intentions via satisfaction. Managerial implications of these results are discussed.

Evaluation approach to stock trading system using evolutionary computation

The past researches emphasize merely the avoidance of over-learning at the system level and ignore the problem of over-learning at the model level, which lead to the poor performance of the evolutionary computation based stock trading decision-making system. This study presents a new evaluation approach to focus on evaluating the generalization capability at the model level. An empirical study was provided and the results reveal four important findings. First, the decision-making system generated at the model design stage outperforms the system generated at the model validation stage, which shows over-learning at the model level. Secondly, for the decision-making system generated either at the model design stage or at the model validation stage, the investment performance in the training period is much better than that in the testing period, exhibiting over-learning at the system level. Third, employing moving timeframe approach is unable to improve the investment performance at the model validation stage. Fourth, reducing the evolution generation and input variables are unable to avoid the over-learning at the model level. The major contribution of this study is to clarify the issue of over-learning at the model and the system level. For future research, this study developed a more reliable evaluation approach in examining the generalization capability of evolutionary computation based decision-making system.

Trust transfer and the effect of service quality on trust in the healthcare industry

Purpose – The purpose of this paper is to examine the effect of service quality (interaction, physical environment, and outcome quality) on trust, to investigate the trust transfer in the healthcare industry, to explore the moderating effects of image congruence and switching costs on the trust transfer, and to assess the effect of trust on patients’ willingness of recommendation. Design/methodology/approach – The research model was tested using data collected from 483 inpatients in 15 medium-to-large hospitals in Taiwan. Structure equation modeling with the latent interaction effect was employed to verify and validate the research model. Findings – The outcomes show that interaction quality and outcome quality positively influence patients’ trust in the original hospital. But the effect of environment quality on trust is not significant. Patients’ trust in the original hospital positively affects their trust in its allied hospitals. Furthermore, image congruence positively moderates the trust transfer. H...

Cosmetics purchasing behavior - An analysis using association reasoning neural networks

The research objective is to propose a novel association analysis approach using association reasoning neural networks (ARNN) to discover the association rules from cosmetics purchasing. ARNN is modified from multi-layered perceptron and back-propagation algorithm. The number of association rules is controlled by the rule threshold and the number of hidden units. To explore the possibility of producing useful and meaningful association rules using ARNN, our study uses the practical cosmetics transaction data. The results show (1) the predicted output values of ARNN are close to their desired confidence values, (2) reducing the number of hidden units of ARNN can inhibit the generation of association rules with low support, and (3) ARNN has the ability of discovering the cohesion and expansion commodities and this information could be used to make pricing strategy. Therefore, ARNN could be a promising alternative approach for association analysis.

The effects of smartphone users’ core self-evaluations and stickiness on intentions to download free social media apps

Abstract This research investigates the influence of core self-evaluations (CSE), stickiness, positive emotion and trust on smartphone users’ intentions to download free social media apps. An online questionnaire was used to collect data, and 477 valid questionnaires were collected. The outcomes show that CSE and the smartphone users’ stickiness significantly influence their positive emotion. Comparing with CSE, stickiness plays a key role in affecting users’ emotion. Smartphone users’ emotions are found to positively influence their trust, which in turn positively influences their intentions to download free social media apps. The findings provide insights into how an app developer can improve users’ emotions and their associated behaviours.

A preliminary consumer study on the beef market in Canada

This study seeks to understand consumers’ attitudes and preferences regarding locally produced beef in British Columbia in Canada. The investigation aims to assess whether developing a new perspective on beef consumption has the potential to provide new opportunities for the beef industry in BC, Canada. Three main research questions have been identified. A qualitative research approach has been adopted. The findings are presented with an analysis of the results. The managerial implications and the limitations of the studies as well as the direction for future studies are discussed.

Anxious attachment, relational embeddedness, trust, co-production, and performance: An empirical study in online business-to-business relationships

Abstract Purpose The online shopping platform serves as an intermediary between online stores and individual online shoppers. The purposes of this study are to examine the influence of anxious attachment and relational embeddedness on trust and to investigate the impact of trust and co-production on performance in the context of online seller-shopping platform relationships. Design/methodology/approach The research is an empirical research using data collected from 308 senior marketing managers of online stores selling products/services in two largest online shopping platforms. Structure equation modeling was employed to verify and validate the research model. Findings The outcomes confirm that online sellers’ anxious attachment plays a key role and is negatively associated with their trust in the online shopping platform. Relational embeddedness positively affects trust of online sellers in the online shopping platform. The effect of trust on co-production and the influence of co-production on performance are statistically significant. However, trust does not appear to positively influence performance. Research limitations/implications This study surveyed targeted online sellers in Taiwan and the research outcomes may not be generalized to other countries. Practical implications The research results provide insights for the online shopping platform in understanding online sellers’ attachment anxiety and developing relational bonds with them to generate a favorable partnership. Originality/value This study represents one of the few that empirically examines the role of anxious attachment in online business-to-business partnerships and the findings provide useful information for the online shopping platform to improve customers’ trust and participation.