Artificial intelligence (AI)‐driven strategic business model innovations in small‐ and medium‐sized enterprises. Insights on technological and strategic enablers for carbon neutral businesses

持续性 碳中和 杠杆(统计) 战略管理 业务 知识管理 回溯 中小企业 营销 可再生能源 计算机科学 工程类 生态学 财务 机器学习 电气工程 生物
作者
Aqueeb Sohail Shaik,Safiya Mukhtar Alshibani,Girish Jain,Bhumika Gupta,Ankit Mehrotra
出处
期刊:Business Strategy and The Environment [Wiley]
被引量:7
标识
DOI:10.1002/bse.3617
摘要

Abstract This study investigates the enhancement of technological and strategic enablers for carbon‐neutral businesses (CNB) through artificial intelligence (AI)‐driven business model innovation (AIDBMI). Drawing upon the insights gained from the literature review, the study employs structural equation modeling (partial least squares structural equation modeling [PLS‐SEM]) as the methodology to examine the relationships between AIDBMI, technological enablers, strategic enablers, and the attainment of carbon neutrality. The sample size consists of 326 small‐ and medium‐sized enterprises (SMEs) in the United States of America. The findings of this study affirm the significant positive relationships between AIDBMI and both technological and strategic enablers for CNB. The utilization of AI technologies proves to be instrumental in fostering the development and implementation of innovative business models that integrate sustainability practices and address environmental challenges. By leveraging AIDBMI, SMEs can harness technological advancements to adopt energy‐efficient processes, embrace renewable energy solutions, and implement effective carbon reduction strategies. Moreover, the study highlights the critical role of strategic enablers in driving the transition towards carbon neutrality. The alignment of sustainability goals with organizational strategies, stakeholder collaboration, and employee engagement emerge as pivotal factors in enabling SMEs to effectively utilize AIDBMI and leverage technological advancements to achieve carbon neutrality. The implications of this study contribute to the existing literature by highlighting the importance of technological and strategic enablers in creating CNB. By integrating AIDBMI, organizations can drive sustainable transformations, optimize their operations, and align their resource management with sustainable practices. These insights provide valuable guidance for SMEs, policymakers, and researchers seeking to foster sustainable practices, promote carbon neutrality, and contribute to the advancement of a low‐carbon economy.
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