Abstract
Highlights
•We examine the effect of green technology innovation (GTI) on market value.
•We find an inverted U-shaped link between GTI and logistics companies’ market value.
•Supply chain partner engagement steepens this non-linear link.
•Scientific institution engagement and public attention faltten this non-linear link.
Abstract
Although logistics companies are encouraged to carry out green technology innovation (GTI) to mitigate their carbon footprint and negative environmental impact, the performance effect of GTI still needs more conclusive evidence. Building on the resource-based view and stakeholder theory, we investigate the impact of logistics companies’ GTI on their market value and further explore the moderating effects of stakeholder engagement and public attention. We use panel data from 53 publicly listed Chinese logistics companies between 2011 and 2021 to test our hypothesized model. We find an inverted U-shaped relationship between GTI and market value. Interestingly, supply chain partner engagement steepens the inverted U-shaped GTI–market value linkage, whereas scientific institution engagement flattens this curvilinear linkage. In addition, public attention weakens this inverted U-shaped GTI–market value relationship. Our study extends the logistics literature by untangling the curvilinear GTI–market value relationship and the distinct moderating effects of stakeholder engagement and public attention on this relationship. It also provides managerial advice for managers in the Chinese logistics industry.
•We examine the effect of green technology innovation (GTI) on market value.
•We find an inverted U-shaped link between GTI and logistics companies’ market value.
•Supply chain partner engagement steepens this non-linear link.
•Scientific institution engagement and public attention faltten this non-linear link.
Abstract
Although logistics companies are encouraged to carry out green technology innovation (GTI) to mitigate their carbon footprint and negative environmental impact, the performance effect of GTI still needs more conclusive evidence. Building on the resource-based view and stakeholder theory, we investigate the impact of logistics companies’ GTI on their market value and further explore the moderating effects of stakeholder engagement and public attention. We use panel data from 53 publicly listed Chinese logistics companies between 2011 and 2021 to test our hypothesized model. We find an inverted U-shaped relationship between GTI and market value. Interestingly, supply chain partner engagement steepens the inverted U-shaped GTI–market value linkage, whereas scientific institution engagement flattens this curvilinear linkage. In addition, public attention weakens this inverted U-shaped GTI–market value relationship. Our study extends the logistics literature by untangling the curvilinear GTI–market value relationship and the distinct moderating effects of stakeholder engagement and public attention on this relationship. It also provides managerial advice for managers in the Chinese logistics industry.
| Original language | English |
|---|---|
| Article number | 103227 |
| Number of pages | 15 |
| Journal | Transportation Research Part E: Logistics and Transportation Review |
| Volume | 176 |
| Early online date | 21 Jul 2023 |
| DOIs | |
| Publication status | Published - 1 Aug 2023 |
Bibliographical note
Funding Information:This work was supported by the National Natural Science Foundation of China under Grant No. 72202112, the Research Grants Council of Hong Kong under Grant No. PolyU15502422, and Zhejiang University–The Hong Kong Polytechnic University Joint Center under Grant No. ZUPUC-2022-03LSC. This work was partially the learning outcome of the second author under the Guided Study subject at The Hong Kong Polytechnic University. The authors are grateful to industry experts, including Renqun Jin, Lei Qin, Feng Xiang, and Frank Zhang, for their kind support during the study. The authors also thank the anonymous reviewers for their constructive comments. The responsibility for the content and any remaining errors are exclusively with the authors.
Funding Information:
This work was supported by the National Natural Science Foundation of China under Grant No. 72202112 , the Research Grants Council of Hong Kong under Grant No. PolyU15502422 , and Zhejiang University–The Hong Kong Polytechnic University Joint Center under Grant No. ZUPUC-2022-03LSC. This work was partially the learning outcome of the second author under the Guided Study subject at The Hong Kong Polytechnic University. The authors are grateful to industry experts, including Renqun Jin, Lei Qin, Feng Xiang, and Frank Zhang, for their kind support during the study. The authors also thank the anonymous reviewers for their constructive comments. The responsibility for the content and any remaining errors are exclusively with the authors.
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