No abstract

No abstract

Although online complaint forms have long been used in the online environment, the problem of identifying the best of the prevalent theoretical models has been relatively ignored until a few studies recently attempted to examine this issue using the integrated model. This study explores the various advantages of online complaint forms in order to establish a positive factor named perceived value and the study further integrates the model of the theory of planned behavior (TPB) and the acceptance model (TAM) with the aim of explaining consumer acceptance of online complaint forms. Empirical data were obtained from a questionnaire survey fielded in Taiwan. A confirmatory factor analysis (CFA). using AMOS 19.0, was conducted to test the causal relationships. Notable among the findings was that an integrated model with perceived value is superior to the TPB and the TAM in terms of its ability to explain user acceptance of online complaint forms. Moreover, the predictors of the TPB and the TAM as well as perceived value have had different significant effects in predicting the intention of using an online complaint form. The findings also suggest that marketers need to formulate implementation strategies that enhance the likelihood of a user’s seeing online complaint forms as a useful tool in lodging their complaints.

Purpose The purpose of this study is to explore the pivotal role that collective teaching plays in knowledge transfer between new product development teams. This study develops a theoretical model of collective teaching, where team intelligence is its consequence and learning orientation cognitive skills are moderators. Design/methodology/approach Based on a questionnaire survey of 156 pairs of new product development project teams of information technology firms, the authors used partial least squares to test the study’s hypotheses. Findings The findings reveal that the use of collective teaching is positively related to team intelligence of recipient teams. In addition, T-shaped skills of source teams exert positive moderating influence on this relationship and so does a learning orientation of recipient teams. Research limitations/implications First, the sample firms used in the study are from the IT industry, which is characterized by extremely short product life cycles, thereby limiting the generalizability of the study’s findings. Second, the authors did not examine whether the effect of T-shaped skills is different at various NPD stages; the contributions of each functional expertise may vary depending on the NPD stage (e.g. the idea generation or pre-launch stage). Third, the use of cross-sectional design precludes a causal inference. The role of focal constructs and moderators and their consequent effects would benefit from more stringent, longitudinal research. Finally, the authors controlled for only a limited set of factors of team intelligence because other potential antecedents of this variable still await identification by future studies. Practical implications This study suggests that the implementation of collective teaching can enhance the capacity of a project team as a whole to manage and innovate information, namely, team intelligence. The study’s findings also suggest that the management must recognize the significance of teams’ learning orientation and thereby proactively develop teams’ learning culture by redesigning work, reward systems or performance evaluation to promote learning. Additionally, it is prudent for managers to reconsider their recruitment criteria to incorporate T-shaped skills. Originality/value This study represents the first step in developing an empirically grounded framework linking collective teaching with team intelligence. Additionally, the authors confirm that team intelligence is a four-dimensional construct.

In recent years, users have increasingly focused on the privacy of social networking sites (SNS); users have reduced their self-disclosure intention. To attract users, SNS rely on active platforms that collect accurate user information, even though that information is supposed to be private. SNS marketers must understand the key elements for sustainable operation. This study aims to understand the influence of motivation (extrinsic and intrinsic) and self-disclosure on SNS through soft computing theories. First, based on a survey of 1108 users of SNS, this study used a dominance-based rough set approach to determine decision rules for self-disclosure intention on SNS. In addition, based on 11 social networking industry experts’ perspectives, this study validated the influence between the motivation attributes by using Decision-Making Trial and Evaluation Laboratory (DEMATEL). In this paper, the decision rules of users’ self-disclosure preference are presented, and the influences between motivation attributes are graphically depicted as a flow network graph. These findings can assist in addressing real-world decision problems, and can aid SNS marketers in anticipating, evaluating, and acting in accord with the self-disclosure motivations of SNS users. In this paper, practical and research implications are offered.