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This study aims to explore subsidiaries' diversification strategies, both internationally and with regard to their product offerings. The study seeks to examine, at the subsidiary level, the relationships between subsidiary size, internationalization, production diversification, and performance.

Based on the archival data of an officially conducted survey, the study used ordered logit regression analysis to test its hypotheses using data from 920 Taiwanese subsidiaries in China.

The study's results revealed: larger subsidiaries tend to engage in internationalization and product diversification activities to a greater degree, and, as a result, tend to exhibit superior performance; and subsidiaries that pursue outward internationalization and that reinvest in related businesses enjoy enhanced performance.

This study examines Taiwanese firms that have one foreign subsidiary in China. Future research should examine larger firms with numerous foreign subsidiaries in developed countries, and should employ more fine‐grained measurements of subsidiary size to provide a clearer picture of subsidiary‐specific advantages.

Unlike the existing literature, which has tended to take the perspective of the multinational corporation, this study examines internationalization and product diversification at the subsidiary level. By extending the resource‐based view to the subsidiary level, larger subsidiaries might be able to exploit their advantages so as to more successfully implement international and product diversification strategies and improve their performance in a host country.

Drawing on the resource-based theory and dynamic capability view, this paper aims to examine the mechanisms by which business analytics (BA) capabilities (i.e. the effective use of data aggregation, analytics and data interpretation tools) in healthcare units indirectly influence decision-making effectiveness through the mediating role of knowledge absorptive capacity.

Using a survey method, this study collected data from the hospitals in Taiwan. Of the 155 responses received, three were incomplete, giving a 35.84 per cent response rate with 152 valid data points. Structural equation modeling was used to test the hypotheses.

This study conceptualizes, operationalizes and measures the BA capability as a multi-dimensional construct that is formed by capturing the functionalities of BA systems in health care, leading to the conclusion that healthcare units are likely to obtain valuable knowledge through using the data analysis and interpretation tools effectively. The effective use of data analysis and interpretation tools in healthcare units indirectly influence decision-making effectiveness, an impact that is mediated by absorptive capacity.

This study adds values to the literature by conceptualizing BA capabilities in healthcare and demonstrating how knowledge absorption matters when implementing BA to the decision-making process. The mediating role of absorptive capacity not only provides a mechanism by which BA can contribute to decision-making practices but also offers a new solution to the puzzle of the IT productivity paradox in healthcare settings.

The purpose of this paper is to review existing literature on users’ digital learning acceptance behavior and to identify gaps in the current body of knowledge and suggest future research directions. The paper also includes identification of motivating as well as inhibiting factors previously explored by academicians in the acceptance of digital learning.

The systematic literature review based on PRISMA methodology was conducted, and 200 articles from peer-reviewed journals on digital learning acceptance behavior using technology adoption theories were examined.

The study found an overall rise in the number of papers published yearly during 2002–2017. Most of the studies were published in two journals, i.e. Computers & Education and Computers in Human Behaviour and were carried out in Asia followed by Europe, North America, Africa, Oceania and South America. It was also noted that most of the studies have used the technology acceptance model and were empirical in nature. The study also found that prominently students’ digital learning acceptance behavior was investigated. The review also indicates a lack of qualitative and mixed method (qualitative and quantitative) approaches to study digital learning acceptance behavior.

The study identified gaps in the current body of knowledge by reviewing published articles that will suggest future directions for further research. The top three determinants of digital learning acceptance that have been analyzed were the behavioral intention, perceived usefulness and perceived ease of use, followed by attitude and user behavior. The study articulates the implications for providers in marketing digital learning products, for higher education institution in expanding digital content, for students seeking digital education tools, for educators in motivating students to accept digital learning and for governments in delivering cost-effective public education by utilizing digital learning.

The paper analyzes 200 publications on digital learning acceptance through technology adoption theories. To the best of the authors’ knowledge, this is the first initiative to provide systematic and exhaustive summarization of the knowledge in this subject. It further explores the various factors influencing digital learning adoption behavior and provides avenues for future research. The paper is useful for researchers working on digital learning acceptance behavior.