Attaining sustainable business performance via eco-innovation under ecological regulatory stringency and market turbulence

dc.contributor.authorLarbi-Siaw O.
dc.contributor.authorXuhua H.
dc.contributor.authorOfori Donkor D.
dc.date.accessioned2025-03-04T04:25:15Z
dc.date.accessioned2025-03-04T06:21:47Z
dc.date.issued2023
dc.description.abstractThe study examines approaches wherein two external factors spur Ghanaian firms to eco-innovate: ecological regulatory stringency and market turbulence. The study's conceptual framework is evaluated using survey data from 513 Ghanaian manufacturing firms using a hybrid Partial Least Square-Structural Equation Model and Arttificial Neural Network technique, which provides support to the proposed hypothesis. Thus, by dividing eco-innovation into product eco-innovation and process eco-innovation, we infer that ecological regulation stringency improves sustainable business performance primarily through process eco-innovation instead of product eco-innovation and market turbulence has a greater impact on sustainable business performance through product eco-innovation as opposed to process eco-innovation. Our research adds to the literature on eco-innovation and green economy by providing a comprehensive framework for measuring a firm's pursuit of eco-innovation and sustainability in response to government and market pressures. We conclude by providing theoretical, methodological and practical implications. � 2023 Elsevier Ltd
dc.identifier.issn9596526
dc.identifier.uri10.1016/j.jclepro.2023.136404
dc.identifier.urihttp://162.250.124.58:4000/handle/123456789/198
dc.language.isoen
dc.publisherElsevier Ltd
dc.subjectArtificial neural networks
dc.subjectEco-innovation
dc.subjectEcological regulation stringency
dc.subjectMarket turbulence
dc.subjectSustainable business performance
dc.titleAttaining sustainable business performance via eco-innovation under ecological regulatory stringency and market turbulence
dc.typeArticle

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