Examining Firms’ Green Information Technology Practices: A Hierarchical View of Key Drivers and Their Effects

Abstract

This study examines key drivers of firms’ green information technology (IT) practices. A hierarchical view, premised in institutional theory and competitive dynamics, leads to a model that explains firms’ practices. This model includes factors that pertain to the environment (environmental awareness and government regulations), industry (industry norms and competitors’ green practices), and firm (customers’ and equity holders’ attitudes and internal readiness) levels. Survey data collected from 304 major firms in Taiwan are used to test the model and hypotheses. In particular, attitudes of a firm’s customers and equity holders, as well as its internal readiness, directly influence its green IT practices, while also channeling the effects of important contextual factors. Among the contextual factors considered herein, environmental awareness and industry norms influence firms’ practices both directly and indirectly. The overall results highlight the significance of contextual factors and underscore the mediating roles of firm-specific considerations. According to our findings, firms should implement strategic goals and make resource allocations toward green IT practices that are aligned with the industry-wide atmosphere and general public’s awareness of environmental protection.

Key words and phrases:

• competitive dynamics
• environmental actions
• firms’ green practices
• green information technology
• green IT
• institutional theory
• nomological network
• sustainability

Supplemental File

Supplemental data for this article can be accessed on the publisher’s website at http://dx.doi.org/10.1080/07421222.2016.1267532

Notes

^1. We acknowledge the potential, subtle differences between internal readiness and organizational readiness [42] but do not differentiate them in this study; instead, we consider internal and organizational readiness mostly interchangeable [46].

^2. Seven firms agreed to participate but could not complete the entire survey for various reasons; these firms were not included in our sample.

^3. We still acknowledge that all existing statistical remedies for common method variance have weaknesses; therefore, we cannot completely rule out this possibility [50].

Additional information

Notes on contributors

Paul Jen-Hwa Hu

Paul Jen-Hwa Hu ([email protected]; corresponding author) is David Eccles Chair Professor at the University of Utah. Hu received his Ph.D. in management information systems from the University of Arizona. His research interests include the deployment of information technology in health care, technology implementation and evaluation, e-commerce, digital government, and knowledge management. He has published in Journal of Management Information Systems, MIS Quarterly, Information Systems Research, Journal of the AIS, Communications of the ACM, and various other journals.

Han-fen Hu

Han-fen Hu ([email protected]) is an assistant professor of management information systems in the Department of Management, Entrepreneurship and Technology, University of Nevada, Las Vegas. She received her Ph.D. in information systems at the David Eccles School of Business, University of Utah. Her research interests include e-commerce, behavioral issues in online settings, and organizations’ information technology strategies. She has published in Journal of Management Information Systems, Information and Management, Journal of the American Society for Information Science and Technology, Communications of the AIS, and other journals.

Chih-Ping Wei

Chih-Ping Wei ([email protected]) is a Distinguished Professor in the Department of Information Management at National Taiwan University. He received his Ph.D. in management information systems from the University of Arizona. His work has appeared in Journal of Management Information Systems, European Journal of Information Systems, Decision Sciences, Decision Support Systems, and other journals.

Pei-Fang Hsu

Pei-Fang Hsu ([email protected]) is an associate professor at the Institute of Service Science, College of Technology Management, the National Tsing Hua University (Taiwan, ROC). She received her Ph.D. in information systems from the Paul Merage School of Business at the University of California, Irvine. Her research focuses on the adoption and value of enterprise systems, information technology (IT) service quality measurement, impact of IT on service innovation, and multinational corporations. She has published in Decision Sciences, Decision Support Systems, Information and Management, International Journal of Electronic Commerce, and other journals.