This paper aims to contribute with a literature review on the use of AI for cleaner production throughout industries in the consideration of AI’s advantage within the environment, economy, and society. The survey report based on the analysis of research papers from the recent literature from leading database sources such as Scopus, the Web of Science, IEEE Xplore, Science Direct, Springer Link, and Google Scholar identifies the strategic strengths of AI in optimizing the resources, minimizing the carbon footprint and eradicating wastage with the help of machined learning, neural networks and predictive analytics. AI integration presents vast aspects of environmental gains, including such enhancements as a marked reduction concerning the energy and materials consumed along with enhanced ways of handling the resulting waste. On the economic aspect, AI enhances the processes that lead to better efficiency and lower costs in the market on the other hand, on the social aspect, the application of any AI influences how people are utilized as workers/clients in the community. The following are some of the limitations towards AI adoption as proposed by the review of related literature; The best things that come with AI are yet accompanied by some disadvantages; there are implementation costs, data privacy, as well as system integration that may be a major disadvantage. The review envisages that with the continuation of the AI development in the following years, the optic is going to be the accentuation on the enhancement of the process of feeding the data in real-time mode, IoT connections, and the implementation of the proper ethical approaches toward the AI launching for all segments of the society. The conclusions provide precise suggestions to the people working in the industry to adopt the AI advancements appropriately and at the same time, encourage the lawmakers to create favorable legal environments to enable the ethical uses of AI. This review therefore calls for more targeted partnerships between the academia, industry, and government to harness the full potential of AI for sustainable industrial practices worldwide.
Interest in the impact of environmental innovations on firms’ financial performance has surged over the past two decades, but studies show inconsistent results. This paper addresses these divergences by analyzing 74 studies from 1996 to 2022, encompassing 4,390,754 firm-year observations. We developed a probability-based meta-analysis approach to synthesize existing knowledge and found a generally positive impact of environmental innovations on financial performance, with a probability range of 0.85 to 0.97. Manufacturing firms benefit more from environmental innovations than firms in other industries, and survey-based studies report a more favorable relationship than those using secondary data. This study contributes to existing knowledge by providing a comprehensive aggregation of data, supporting the resource-based view (RBV) and the Porter hypothesis. The findings suggest significant policy implications, highlighting the need for tailored incentives and information-sharing mechanisms, and underscore the importance of diverse data sources in research to ensure robust results.
In today's highly competitive environment, enterprises strive for competitive advantages by actively responding to changes in the network environment through digital technology. This approach fosters continuous innovation and establishes new paradigms by creating new network structures and relationships. However, research on the relationship and transmission mechanisms between digital technology and innovation performance in dynamic environments is still in its early stages, which does not fully address the demands of current social practice. Therefore, exploring the impact mechanisms of digital technology applications on enterprise innovation performance is an important research area. Based on the dynamic capability theory, this paper utilized SPSS 26.0 and AMOS 24.0 software to conduct an empirical analysis of 490 valid samples from the network perspective, exploring the pathways through which digital technology capability influences enterprise innovation performance. The results indicate that (1) digital technology capability is positively correlated with enterprise innovation performance; (2) digital technology capability is positively correlated with network responsiveness; (3) network responsiveness is positively correlated with enterprise innovation performance; (4) network responsiveness plays a mediating role in the impact of digital technology capability on enterprise innovation performance; (5) environmental dynamism positively moderates the relationship between digital technology capability and enterprise innovation performance. This paper enhances the understanding of how digital technology capability influences enterprise innovation performance in dynamic environments, offering new insights for future research. The results suggest that enterprises should focus on enhancing their digital technology capabilities, optimizing network structures, and strengthening network relationships to drive digital innovation.
Increasing populations in cities have created challenges for the urban environment and also public health. Today, lacking sport participation opportunities in urban settings is a global concern. This study conceptualizes and develops a theoretical framework that identifies factors associated with effective urban built environments that help shape and reshape residents’ attitude toward sport activities and enhances their participation. Based on a comprehensive review of literature and by following the Stimulus-Organism-Response (SOR) theory and attitude change theory, a four-factor measurement model is proposed for studying urban built environment, including Availability, Accessibility, Design, and Safety. Further examinations are made on how these factors are channeled to transform residents’ attitudes and behavior associated with participating in sport activities, with Affordability as a moderator. Discussions are centered around the viability of the developed framework and its application for future research investigations.
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