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Due to the rapid pace of development and innovation in information technology, the dedicated electronic book (e‐book) reader has become a new trend in reading. However, at present there is only a limited understanding of what factors drive user attitudes/willingness to use this new device for reading. Hence, this paper aims to explore what factors drive users to use dedicated e‐book readers for reading.

The study proposes a causal model that explores how convenience, compatibility, and media richness affect users' attitudes towards the dedicated e‐book readers for reading.

The results of this study suggest that convenience, compatibility, and media richness all significantly contribute to dedicated e‐book reader acceptance.

The study extends previous theories: the Technology Acceptance Model, Innovation Diffusion Theory, media richness theory and convenience. This helps one to better understand what factors affect usage of the dedicated e‐book readers, an important topic for current and future research.

The findings outline and describe how the dominant factors affect users' attitudes towards adoption of the dedicated e‐book readers for reading. By considering factors such as ease‐of‐use, usefulness, convenience, compatibility, media richness, etc., in the stage of product development, practitioners can provide dedicated e‐book readers that customers will readily accept.

These findings will enable development of a more robust understanding of attitudes toward dedicated e‐book readers and will be helpful to developers researching e‐book hardware and software as well as to researchers interested in testing related theories.

Although scholars have paid considerable attention to the relationship between technological diversification and firm performance, research on this relationship has produced mixed findings. To reconcile these inconsistent findings, this study, thus, aims to revisit the performance effect of technological diversification by considering two organizational characteristics as crucial moderators, namely, firm size and financial slack.

To test the research hypotheses, the research sample covers manufacturing firms in the 2008 Standard & Poor (S&P) 500 index. Data regarding the characteristics and patent information of the sample firms were obtained from Compustat and the US Patent and Trademark Office. The hypotheses were tested by using hierarchical regression models.

In a sample of 168 S&P 500 manufacturing firms, this study finds that technological diversification has a positive effect on firm performance. The relationship between technological diversification and firm performance is also found to be positively moderated by firm size, financial slack and their configuration.

The findings of this study further suggest that firms should be aware that the effect of technological diversification on performance can be enhanced or hindered in specific contexts.

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.

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.

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.

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.

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.

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.