Scope:
Nowadays, with the unprecedented and exponential growth of information communication technologies (ICTs), all types of businesses have been impacted by digital transformation. This frequently implies new strategies, new business models, and new and dynamic capabilities, mainly to create data-driven businesses. In this context, organizations are being challenged to understand and create value using cutting-edge technologies like a prominent, highly disruptive technology, artificial intelligence (AI) (Enholm et al., 2022; Fosso Wamba et al., 2021). In this outlook, AI is defined as "the ability of machines to mimic intelligent human behavior, and specifically refers to "cognitive" functions that we associate with the human mind, including problem-solving and learning" (Syam & Sharma, 2018, p. 136) is changing, reshaping and challenging scholars, industry practitioners and governments worldwide. In addition, firms are investing in AI tools, like Generative AI (Gen-AI), to empower their capabilities, innovate, and leverage their competitiveness (Brown et al., 2024; Kusiak, 2020). With the use of Gen-AI, organizations strengthen several processes and their decision-making capabilities for a vast of activities (e.g., customer support in a call center, interaction in social media, product and price recommendations, pattern recognition, email writing, travel recommendations, follow-up activities, etc.) (Fosso Wamba et al., 2024). Gen-AI is an artificial intelligence related to algorithms capable of building new content (i.e., text, images, equations, articles, music, etc.). Since the recent emergence of ChatGPT in November 2022, all types of businesses have been shaken. Thus, Gen-AI, an AI-based on large language models (LLMs), Generative adversarial networks (GANs), Variational autoencoders (VAEs), etc., the operations' efficiency, challenges, transparency, and security of the transactions are being reshaped (Bengesi et al., 2024). In this context, organizations and their supply chain management (SCM) are experimenting with significant challenges to applying Gen-AI effectively into their business models (Fosso Wamba et al., 2023). On the one hand, Gen-AI promises to remodel the traditional business models, bringing more agility, efficiency, and productivity. On the other hand, there are many concerns about Gen AI, mainly related to ethical issues, safety, transparency, and trust. Despite the recent progress made by the literature exploring Gen-AI in business management, empirical studies are still in their infancy. Consequently, they require an urgent discussion involving academia, industry practitioners, government, and society. Therefore, this Workshop aims to invite scholars, researchers, practitioners, and managers to shed more light, unlock, and identify at the organizational, inter-organizational, and SCM levels the dynamics in capturing business value from Gen-AI and the interplay with other emerging technologies, in terms of improved performance, innovative business models, improved decisions making improved interaction with customers, and competitive advantage.
List of topics of interest:
Topics of interest include (but are not limited to):
- Gen-AI innovative approaches to support organizations and SCMs during and after disruptive crises and geopolitical tensions.
- Gen-AI innovative approaches to improve social good in a disrupted world.
- Determinants of Gen-AI adoption and use in operations at the organizational and inter-organizational levels.
- Gen-AI and intelligent agents supporting business process management.
- The role of Gen-AI for the digital transformation: awareness and knowledge challenges in emerging and developed countries.
- Gen-AI, data analytics, and intelligent sensors supporting optimization for smart manufacturing and Industry 4.0.
- Gen-AI and the interplay with cutting-edge technologies (e.g., Blockchain, BDA, IoT, Metaverse, among others) enabled business process innovation at the firm and supply chain levels.
- Determinants of the Gen-AI diffusion stages (intention, adoption, and routinization) in organizations and supply chains.
- Gen-AI initiatives for creating value and competitive advantage.
- Assessment of facilitators and inhibitors of Gen-AI adoption for SCM processes.
- Gen-AI initiatives report improved performance, competitive advantage, and business value at the organizational and inter-organizational levels.
- Implementation of IT infrastructure to support Gen-AI initiatives for improved operations management.
- Gen-AI and the human interaction collaboration within organizations.
- Facilitate innovative electronic business models and operations using Gen-AI techniques in various sectors (e.g., transportation, fashion, healthcare, retail industry, and manufacturing).
- Ethics issues, governance, and the security of Gen-AI at the organizational and SCM levels.
Organizing Committee:
- Samuel Fosso Wamba, TBS Education, Information, Operations and Management Sciences, Toulouse, CO 31068 France,
This email address is being protected from spambots. You need JavaScript enabled to view it. - Maciel M. Queiroz FGV EAESP, Production and Operations Management, Sao Paulo, CO 01332-000 Brazil,
This email address is being protected from spambots. You need JavaScript enabled to view it.
Program Committee:
- Samuel Fosso Wamba,
This email address is being protected from spambots. You need JavaScript enabled to view it. , TBS Business School, France - Maciel M. Queiroz,
This email address is being protected from spambots. You need JavaScript enabled to view it. , FGV EAESP, Brazil - Shahriar Akter,
This email address is being protected from spambots. You need JavaScript enabled to view it. , Sydney Business School, Faculty of Business, University of Wollongong, Australia - Hossana Twinomurinzi,
This email address is being protected from spambots. You need JavaScript enabled to view it. , University of Johannesburg, Department of Applied Information Systems, Johannesburg, South Africa - Bendavid Ygal,
This email address is being protected from spambots. You need JavaScript enabled to view it. , Département de management et technologie, UQAM, Canada - Rameshwar Dubey,
This email address is being protected from spambots. You need JavaScript enabled to view it. , Montpellier Business School, France - Yulia Sullivan,
This email address is being protected from spambots. You need JavaScript enabled to view it. , Hankamer School of Business, Baylor University, USA
