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.

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.