502
Views
4
CrossRef citations to date
0
Altmetric
Articles

Can attention allocation affect firm’s environmental innovation: the moderating role of past performance

, , & ORCID Icon
Pages 1081-1094 | Received 29 Oct 2020, Accepted 17 Jun 2021, Published online: 30 Jun 2021
 

ABSTRACT

Based on the upper echelons theory and the attention-based view of the firm, this study constructed a relationship model between the top management team's attention allocation and the firm's environmental innovation. Given the firm's environmental innovation activities may be influenced by resource factors, we selected the past performance of the firm (measured by profit) as the moderating variable. Three hundred and twelve listed Chinese companies were selected as the research sample, and NVivo11 and SPSS21.0 software were used to analyze the relationships among attention allocation, past performance, and environmental innovation. The results showed that the more attention that the top management team allocated to policies and consumers, the more likely the firm was to adopt an environmental innovation strategy; however, the more attention that top management team allocated to competitors and employees, the less likely it was the firm adopted an environmental innovation strategy. Besides, the past performance of the firm played a positive moderating role between the top management team's attention to consumers and the environmental innovation of the firm.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This work was supported by Major project of National Social Science Fund of China (20ZDA088).

Notes on contributors

Zhongju Liao

Zhongju Liao is a Professor at school of Economics & Management in Zhejiang Sci-Tech University. He earned his PhD degree in business management from Zhejiang University in 2015. His current research includes environmental policy and eco-innovation. His research outputs have been published in major international journals.

Jie Lu

Jie Lu is a master student at the School of Economics & Management, Zhejiang Sci-Tech University. Her current research focuses on eco-innovation.

Yubing Yu

Yubing Yu is an Associate Professor at Logistics and E-commerce School, Zhejiang Wanli University, China. He received his PhD degree in operations management from Zhejiang University. His research interests are supply chain quality and green management. His research has been published or accepted in Supply Chain Management: An International Journal, Production Planning & Control, Journal of Cleaner Production, Total Quality Management & Business Excellence, Journal of Enterprise Information Management, and International Journal of Logistics Research and Applications.

Zuopeng (Justin) Zhang

Zuopeng (Justin) Zhang is a faculty member in the Coggin College of Business at University of North Florida. He was previously an Associate Professor of Management, Information Systems, and Analytics at State University of New York at Plattsburgh. He received his Ph.D. in Business Administration with a concentration on Management Science and Information Systems from Pennsylvania State University, University Park. His research interests include economics of information systems, knowledge management, electronic business, business process management, information security, and social networking. He is the editor-in-chief of the Journal of Global Information Management, an ABET program evaluator, and an IEEE senior member.

Log in via your institution

Log in to Taylor & Francis Online

PDF download + Online access

  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 53.00 Add to cart

Issue Purchase

  • 30 days online access to complete issue
  • Article PDFs can be downloaded
  • Article PDFs can be printed
USD 650.00 Add to cart

* Local tax will be added as applicable

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.