This study employs Systematic Literature Review (SLR) and thematic analysis to explore the topics of Artificial Intelligence (AI), Stakeholder Engagement (SE) and social innovation. To enhance methodological rigor, the study integrated literature analysis and social media analysis to recognize topics within texts using Latent Dirichlet Allocation (LDA), an unsupervised machine learning method. The study highlights AI's influence on social engagement, aligning with diffusion theory, stressing the need to emphasize AI's benefits for faster adoption.

In the digital landscape, online gaming has become an integral part of entertainment. This empirical research aims to examine the influence of AI-based emotional attachment-oriented anthropomorphic features and their impact on the online gaming experience. Under the paradigm of cognitive load theory (CLT) and Computers Are Social Actors (CASA) framework, a theoretical model was developed for an empirical investigation. To examine the model, the present study applied a partial least squares structural equation modeling process with 1802 respondents' data from India. The results show that AI-based emotional attachment anthropomorphic features enhance consumer's overall service experience. In addition, trust and engagement partially mediate the relationship between AI-based emotional attachment anthropomorphic features and consumer's overall service experience.

This study explores the use of digital technologies by food supply chain firms to enhance circular practices, aiming to boost the social, economic, and environmental sustainability of food supply chains. The literature on digital technologies in the food supply chain has experienced significant growth in the last few years. Given the critical importance of these technologies, there is an urgent need for a thorough systematic literature review to integrate and reconcile the findings. This research uses SPAR-4 SLR with the theories, context and methods (TCM) framework to synthesize the body of literature on digital technologies for circular and sustainable food supply chain. The study integrates existing knowledge to propose future research directions, while also addressing identified gaps in theories, methods and contexts.

This study aims to identify emerging topics, themes, and potential areas for applying large language models (LLMs) in supply chain management through data triangulation. This study involved the synthesis of 33 published articles and a total of 3421 social media documents, including tweets, posts, expert opinions, and industry reports on utilizing LLMs in supply chain management. By employing BERT models, four core themes were derived: Supply chain optimization, supply chain risk and security management, supply chain knowledge management, and automated contract intelligence, which provides the present status of LLM in the supply chain. The results of this study will empower managers to identify prospective applications and areas for improvement, affording them a comprehensive understanding of the antecedents, decisions, and outcomes detailed in the framework. The insights garnered from this study are highly valuable to both researchers and managers, equipping them to harness the latest advancements in LLM technology and its role within supply chain management.

Digital agility is a critical dynamic capability that is becoming increasingly important in the context of collaborative product development processes (PDPs). This paper aims to address the complexity of today's PDPs by considering various quality aspects including safety, environment, and the entire lifecycle, along with diverse dynamic capabilities such as digital agility and circular economy. The authors employed a semantic web methodology and created an ontology-based knowledge model. The proposed ontology uses Design for X techniques, circular economy, digital agility, and the semantic web under the PDP perspective to increase performance and cooperation between designers and the project team. To validate the ontology, measures for domain ontology evaluation have been used. The paper presents a detailed guide for ontology engineering and evaluation for collaborative smart PDP, which incorporates digital agility as a critical dynamic capability. The proposed ontology can help boost PDP performance and increase customer satisfaction.

The study draws upon the ethical theory of organizing to elucidate the links between ethical climate antecedents, organizational practices, and consequences. We also integrated organizing vision theory to examine the influence of diffusion of big data analytics innovation on sustainable business practices. The results indicate that organizational trust has a significant positive impact on ethics training and ethics audit, which is critical to South Africa's mining industry. Furthermore, the results indicate that ethical leadership is positively related to ethics training and ethics audits. Findings show that ethics training and ethics audit is positively related to sustainable business practices. Findings indicate that the vision constructed by community members is positively related to the diffusion of big data analytics innovation. We also found that the diffusion of big data analytics innovation is positively related to sustainable business practices. Lastly, findings show that sustainable business practices are positively related to firm performance.

Government of India’s ‘Digital India’ initiative intends to build robust digital ecosystem that fosters innovation & entrepreneurship enabling better citizen service & citizen empowerment. Digitization in India involves geo-demographic & socio-economic dependency, choice of smart technologies undergoing rapid innovation, strategic roll-out planning & flawless implementation as prerequisite of technology diffusion & benefit realization. This study identifies technical & non-technical determinants of smart digital framework roll out that can accelerate digital diffusion in urban public services in India. This study follows inductive exploratory method, combining grounded theory & text mining for primary data analysis. Study reveals digitization is an ecosystem of private & public enterprises and citizen participation, identifies integrated use analytics & IoT can enable connected smart city, whereas technology cost, digital literacy & sustainable innovation as non-technological determinant towards resilient urban digital infrastructure in India.