Feng Ji, Yonghua Zhou, Hongjian Zhang, Guiqing Cheng, Qubo Luo
{"title":"数字奥德赛导航:工业 4.0 中人工智能驱动的商业模式","authors":"Feng Ji, Yonghua Zhou, Hongjian Zhang, Guiqing Cheng, Qubo Luo","doi":"10.1007/s13132-024-02096-4","DOIUrl":null,"url":null,"abstract":"<p>In the era of Industry 4.0, characterized by the convergence of digital technologies and physical systems, the transformation of business models is paramount for sustainable industrial growth. This research explores the critical role of AI-driven data analytics in shaping digital business models within this dynamic landscape. The study investigates the interplay between technology readiness, innovation potential, automation and control, and privacy and security considerations in the context of Industry 4.0. Our findings reveal that technology readiness serves as a catalyst for innovation potential, emphasizing the importance of a robust technological infrastructure. Moreover, innovation potential plays a substantial mediating role in the linkage between technology readiness and privacy and security dynamics, highlighting the symbiotic relationship between innovation and security in the digital business arena. The study underscores the significance of automation and control in safeguarding privacy and fostering security, emphasizing the need for automated, data-driven approaches in crafting innovative and secure business models. Furthermore, it advocates for a multifaceted approach that fosters synergies between technological advancements and ethical considerations. Policy implications include the promotion of collaboration between industries, academia, and governments to catalyze innovative solutions grounded in feasibility and sustainability. Regulatory frameworks should encourage automation and control measures to protect consumer privacy, and policies must remain adaptable to the fast-paced developments in AI and Industry 4.0. This research illuminates the pivotal role of AI in shaping digital business model innovations in Industry 4.0. It emphasizes the importance of technology readiness, innovation potential, and ethical considerations in creating a dynamic and secure digital business ecosystem. The study envisions a future where digital business model innovations drive growth, efficiency, and resilience in Industry 4.0, shaping a sustainable and progressive industrial sector.</p>","PeriodicalId":47435,"journal":{"name":"Journal of the Knowledge Economy","volume":"11 1","pages":""},"PeriodicalIF":4.0000,"publicationDate":"2024-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Navigating the Digital Odyssey: AI-Driven Business Models in Industry 4.0\",\"authors\":\"Feng Ji, Yonghua Zhou, Hongjian Zhang, Guiqing Cheng, Qubo Luo\",\"doi\":\"10.1007/s13132-024-02096-4\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>In the era of Industry 4.0, characterized by the convergence of digital technologies and physical systems, the transformation of business models is paramount for sustainable industrial growth. This research explores the critical role of AI-driven data analytics in shaping digital business models within this dynamic landscape. The study investigates the interplay between technology readiness, innovation potential, automation and control, and privacy and security considerations in the context of Industry 4.0. Our findings reveal that technology readiness serves as a catalyst for innovation potential, emphasizing the importance of a robust technological infrastructure. Moreover, innovation potential plays a substantial mediating role in the linkage between technology readiness and privacy and security dynamics, highlighting the symbiotic relationship between innovation and security in the digital business arena. The study underscores the significance of automation and control in safeguarding privacy and fostering security, emphasizing the need for automated, data-driven approaches in crafting innovative and secure business models. Furthermore, it advocates for a multifaceted approach that fosters synergies between technological advancements and ethical considerations. Policy implications include the promotion of collaboration between industries, academia, and governments to catalyze innovative solutions grounded in feasibility and sustainability. Regulatory frameworks should encourage automation and control measures to protect consumer privacy, and policies must remain adaptable to the fast-paced developments in AI and Industry 4.0. This research illuminates the pivotal role of AI in shaping digital business model innovations in Industry 4.0. It emphasizes the importance of technology readiness, innovation potential, and ethical considerations in creating a dynamic and secure digital business ecosystem. 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Navigating the Digital Odyssey: AI-Driven Business Models in Industry 4.0
In the era of Industry 4.0, characterized by the convergence of digital technologies and physical systems, the transformation of business models is paramount for sustainable industrial growth. This research explores the critical role of AI-driven data analytics in shaping digital business models within this dynamic landscape. The study investigates the interplay between technology readiness, innovation potential, automation and control, and privacy and security considerations in the context of Industry 4.0. Our findings reveal that technology readiness serves as a catalyst for innovation potential, emphasizing the importance of a robust technological infrastructure. Moreover, innovation potential plays a substantial mediating role in the linkage between technology readiness and privacy and security dynamics, highlighting the symbiotic relationship between innovation and security in the digital business arena. The study underscores the significance of automation and control in safeguarding privacy and fostering security, emphasizing the need for automated, data-driven approaches in crafting innovative and secure business models. Furthermore, it advocates for a multifaceted approach that fosters synergies between technological advancements and ethical considerations. Policy implications include the promotion of collaboration between industries, academia, and governments to catalyze innovative solutions grounded in feasibility and sustainability. Regulatory frameworks should encourage automation and control measures to protect consumer privacy, and policies must remain adaptable to the fast-paced developments in AI and Industry 4.0. This research illuminates the pivotal role of AI in shaping digital business model innovations in Industry 4.0. It emphasizes the importance of technology readiness, innovation potential, and ethical considerations in creating a dynamic and secure digital business ecosystem. The study envisions a future where digital business model innovations drive growth, efficiency, and resilience in Industry 4.0, shaping a sustainable and progressive industrial sector.
期刊介绍:
In the context of rapid globalization and technological capacity, the world’s economies today are driven increasingly by knowledge—the expertise, skills, experience, education, understanding, awareness, perception, and other qualities required to communicate, interpret, and analyze information. New wealth is created by the application of knowledge to improve productivity—and to create new products, services, systems, and process (i.e., to innovate). The Journal of the Knowledge Economy focuses on the dynamics of the knowledge-based economy, with an emphasis on the role of knowledge creation, diffusion, and application across three economic levels: (1) the systemic ''meta'' or ''macro''-level, (2) the organizational ''meso''-level, and (3) the individual ''micro''-level. The journal incorporates insights from the fields of economics, management, law, sociology, anthropology, psychology, and political science to shed new light on the evolving role of knowledge, with a particular emphasis on how innovation can be leveraged to provide solutions to complex problems and issues, including global crises in environmental sustainability, education, and economic development. Articles emphasize empirical studies, underscoring a comparative approach, and, to a lesser extent, case studies and theoretical articles. The journal balances practice/application and theory/concepts.