The DOI matches its Crossref record; 69 of the 69 references it cites were found in a registry or an index.
The influence of green supply chain integration and environmental uncertainty on green innovation in Taiwan's IT industry
Abstract
Purpose: The purpose of this paper is to explore the relationship between green supply chain integration (GSCI) and green innovation and to analyze the moderating effects of environmental uncertainty. Design/methodology/approach: A multi‐dimensional approach was employed to develop a comprehensive theoretical framework which encompasses various aspects of GSCI, green innovation and environmental uncertainty. To identify the effects of GSCI and environmental uncertainty on green innovation, hierarchical moderated regression analysis was applied using questionnaire data from 211 Taiwanese, information technology (IT) manufacturers. Findings: Supplier, customer and internal integration enhance both green product and process innovations. Demand uncertainty positively moderates each GSCI‐green innovation link. However, the moderating effect of technological uncertainty is insignificant. Research limitations/implications: This study conducted a cross‐sectional investigation of the Taiwanese IT industry. Therefore, it lacks the advantages of a longitudinal case study and its findings cannot be generalized to other industries. Practical implications: This study argues that, to improve green innovation performance, managers should endeavor to integrate resources and capabilities within their organizations, suppliers and customers. It also suggests that managers should constantly follow demand trends in the market and maintain tight technological networks among supply chain partners. Originality/value: This study provides new insights into green supply chain management (GSCM) knowledge: theoretically creating GSCI‐green innovation links with the natural‐resource‐based view, and empirically demonstrating that effective green innovation requires multi‐dimensional GSCI. Furthermore, it develops a valid and reliable scale of environmental uncertainty for future research in GSCM, and presents the characteristics of implementing GSCI in Taiwan's IT industry.
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Cited by
Li, Y., Dai, J., & Cui, L. (2020) · International Journal of Production Economics · doi:10.1016/j.ijpe.2020.107777 · Cited by 922
de Oliveira, U. R., Espindola, L. S., da Silva, I. R., da Silva, I. N., & Rocha, H. M. (2018) · Journal of Cleaner Production · doi:10.1016/j.jclepro.2018.03.083 · Cited by 341
Agyabeng-Mensah, Y., Ahenkorah, E., Afum, E., Nana Agyemang, A., Agnikpe, C., & Rogers, F. (2020) · Supply Chain Management: An International Journal · doi:10.1108/scm-11-2019-0405 · Cited by 282
Analysing supply chain integration through a systematic literature review: a normative perspective
Mustafa Kamal, M., & Irani, Z. (2014) · Supply Chain Management: An International Journal · doi:10.1108/scm-12-2013-0491 · Cited by 139
Golini, R., & Gualandris, J. (2018) · International Journal of Operations & Production Management · doi:10.1108/ijopm-12-2016-0725 · Cited by 49
Metadata
- Authors
- Wu, G.
- Venue
- Supply Chain Management: An International Journal
- Publisher
- Emerald
- Published
- 2013-07-29
- Volume
- 18
- Issue
- 5
- Pages
- 539-552
- ISSN
- 1359-8546 (ISSN-L)
- OpenAlex
- W2005543795
- Cited by
- 324
- References
- 69
- FWCI
- 25.87
- Type
- journal article
- Language
- en
- Open access
- closed
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.