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This study examines shareholder and board motivations regarding corporate social responsibility (CSR) to understand boards' stewardship approaches to environmental issues.

Using content analysis, the authors classify CSR motivations in all environmental shareholder proposals and board responses of Fortune 250 companies from 2013 to 2017 from do little (a shareholder primacy perspective) to do much (a stakeholder pluralism perspective). The authors calculate the motivational dissonance for each proposal-response pair (the Talk Gap) and use cluster analysis to observe evidence of board stewardship and subsequent environmental disclosure and performance (ED&P) changes.

Board interpretations of stewardship are not uniform, and they regularly extend to stakeholders beyond shareholders, most frequently including profit-oriented stakeholders (e.g. employees and customers). ED&P changes are highest when shareholders narrowly lead boards in CSR motivation and either request both action and information or information only. The authors observe weaker ED&P changes when shareholders request action and the dissonance between shareholders and boards is larger. When shareholders are motivated to do little for CSR, ED&P changes are weak, even when boards express more pluralistic motivations.

The results show the important role that boards play in CSR and may aid activist shareholders in determining how best to generate change in corporate CSR actions.

This study provides the first evidence of board stewardship at the proposal-response level. It measures shareholder and board CSR motivations, introduces the Talk Gap, and examines relationships among proposal characteristics, the Talk Gap, and subsequent ED&P change to better understand board stewardship of environmental issues.

This is a general review study aiming to specify the key customer-based factors and technologies that influence the value co-creation (VCC) process through artificial intelligence (AI) and automation in the hospitality and tourism industry.

The study uses a theory-based general literature review approach to explore key customer-based factors and technologies influencing VCC in the tourism industry. By reviewing the relevant literature, the authors conclude a theoretical framework postulating the determinants of VCC in the AI-driven tourism industry.

This paper identifies customers' perceptions, attitudes, trust, social influence, hedonic motivations, anthropomorphism and prior experience as customer-based factors to VCC through the use of AI. Service robots, AI-enabled self-service kiosks, chatbots, metaversal tourism and new reality, machine learning (ML) and natural language processing (NLP) are technologies that influence VCC.

The results of this research inform a theoretical framework articulating the human and AI elements for future research set to expand the models predicting VCC in the tourism industry.

Few studies have examined consumer-related factors that influence their participation in the VCC process through automation and AI.