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This study, a theoretical article, aims to introduce new institutionalism as a framework through which business and management researchers can explore the significance of artificial intelligence (AI) in organizations. Although the new institutional theory is a fully established research program, the neo-institutional literature on AI is almost non-existent. There is, therefore, a need to develop a deeper understanding of AI as both the product of institutional forces and as an institutional force in its own right.

The authors follow the top-down approach. Accordingly, the authors first briefly describe the new institutionalism, trace its historical development and introduce its fundamental concepts: institutional legitimacy, environment and isomorphism. Then, the authors use those as the basis for the queries to perform a scoping review on the institutional role of AI in organizations.

The findings reveal that a comprehensive theory on AI is largely absent from business and management literature. The new institutionalism is only one of many possible theoretical perspectives (both contextually novel and insightful) from which researchers can study AI in organizational settings.

The authors use the insights from new institutionalism to illustrate how a particular social theory can fit into the larger theoretical framework for AI in organizations. The authors also formulate four broad research questions to guide researchers interested in studying the institutional significance of AI. Finally, the authors include a section providing concrete examples of how to study AI-related institutional dynamics in business and management.

This paper aimed to test a proposed framework highlighting strategic green marketing initiatives and how they drive new technology implementation towards green corporate performance, underpinned by institutional isomorphism.

The study used a quantitative method and convenience sampling approach in gathering data using adapted questionnaires to solicit first-hand information from 225 employees of small and medium-sized enterprises (SMEs) in the tourism and hospitality sector underpinned by the theory of institutional isomorphism.

The study shows that green communication and green strategy alignment have significant predictive effects on new technology implementation. Cultural isomorphism significantly moderated the effects of implementing new technology (i.e. green communication and strategy alignment). In addition, “new technology implementation had a significant predictive effect on green corporate performance”. Meanwhile, the moderation effect of “green creative behaviour on the new technology-green corporate performance dyad was positive but insignificant.”

The study’s novel framework confirms how green communication strategy and green strategy alignment complement cultural isomorphism to explain the impact of new technology implementation on green corporate performance, underpinned by institutional isomorphism.

We conducted a systematic review to explore the potential for the application of blockchain technologies for supply chain resilience in a small-scale agri-food business context.

As part of the research methodology, scientific databases such as Web of Science, Google Scholar and Scopus were used to find relevant articles for this review.

The systematic review of articles (n = 57) found that the use of blockchain technology in the small-scale agri-food business sector can reduce the risk of food fraud by assuring the provenance of food products.

Only a few papers were directly from a small-scale agribusiness context. Key challenges that limit the implementation of blockchain and other distributed ledger technologies include concerns over the disclosure of proprietary information and trade secrets, incomplete or inaccurate information, economic and technical difficulties, low levels of trust in the technology, risk of human error and poor governance of process-related issues.

The application of blockchain technology ensures that the risks and costs associated with non-compliance, product recalls and product loss are reduced. Improved communication and information sharing can increase resilience and better support provenance claims and traceability. Better customer relationships can be built, increasing supply chain efficiency and resilience.

This study aims to use the extended model of goal-directed behavior (EMGB) to examine the interaction between wine purchasing motivations and prior knowledge and their impact on consumers’ wine purchase intentions and decisions.

The survey was conducted in large discount retail stores in South Korea, and structural equation modeling analysis reveals EMGB’s strong predictive ability to understand wine buying behavior.

Notably, the findings reveal that social life and enjoyment motivations play a significant role in shaping consumers' attitudes. In addition, positive emotions, attitudes, prior knowledge, subjective norms and negative anticipated emotions all have a positive effect on desire, while desire, prior knowledge and frequency of past behavior have a significant impact on behavioral intention. Contrary to previous studies, celebration motivation has no significant effect on attitude and perceived behavioral control has no significant effect on desire and behavioral intention.

The findings provide practical insights for marketers to conduct targeted wine marketing campaigns and increase consumers' intention to purchase wine.

This study furthers the understanding of the complex mechanisms involved in shaping the intention to purchase wine using the EMGB framework.

The purpose of this paper is to understand how hospitality companies can best explain controversial corporate social responsibility (CSR) activities to consumers who may not agree with the CSR activity. This research explores message framing through emotional and cognitive appeals to influence consumer perceptions of the Gideon Bible in USA hotel rooms. The study uses the theory of deontic justice to measure the impacts of messaging on consumer perceptions of the morality of the Gideon Bible as suicide prevention in hotels and its relation to controversial CSR initiatives.

The study uses an experimental study design via a self-administered survey to analyze participants’ perceptions of the placement of the Gideon Bible in hotel rooms and participants’ attitudes toward CSR initiatives based on deontic justice and religion using different message framing conditions.

Results show that religion was a major determinant of attitude towards the Gideon Bible, but the sentiment analysis also revealed that negative perceptions can be mitigated through message framing via emotional and cognitive appeals. Additionally, the cognitive appeal did impact CSR perceptions, as did identifying as Christian. Moral outrage emerged as a significant moderator for the relationships between message framing, attitudes toward the Gideon Bible and CSR.

This study provides an extension of deontic justice research to examine justice traits in accepting controversial CSR.

Given the importance of the growing segmentation of ageing consumers and their increasing interaction with the Internet, digital marketing scholars are becoming more interested in this market. Prior research needs to pay more attention to this market in many contexts of digital marketing. This study aims to provide insights into ageing consumers’ content usage, content typology choices, and online brand advocacy (OBA).

Semi-structured interviews were applied, and 16 consumers from Southern Europe aged 55+ were included. The interviews were transcribed and examined following the principles of content analysis.

According to the research, older consumers display their usage and concerns regarding online content. They have different decision-making processes depending on whether they are purchasing products or services. Likewise, their choices of content typology vary based on the utilitarian or hedonic product category.

This study contributes to the literature by providing insights into this growing segmentation and proposing an OBA framework for older consumers related to content marketing. Finally, the study suggests that older consumers are passive online and active offline brand advocates.

This study aims to investigate the bright and dark sides of environmental, social and governance (ESG) during the COVID-19 pandemic, including both the outbreak and recovery periods, for the Chinese hospitality industry.

Using panel data of 564 firm-quarter observations from 2018 to 2020, the authors adopt fixed-effects regression estimation with standard errors clustered at the firm level. To address potential endogeneity concerns, the authors also use the two-stage least squares estimator with instrumental variables.

The results suggest that ESG plays different roles in market- and accounting-based performance during the COVID-19 outbreak and recovery periods. Specifically, ESG practices show a bright side as a reputation builder to mitigate the negative pandemic impact on market-based performance, whereas the dark side of ESG practices consumes firm resources to aggravate the negative pandemic impact on accounting-based performance during the coronavirus outbreak. These results also suggest hospitality companies benefit bountifully from ESG practices during the COVID-19 recovery.

ESG plays a vital role for hospitality firms by providing insurance-like protection during and after the COVID-19 outbreak. Additionally, hospitality firms should evaluate their capability to adapt resource-consuming ESG practices.

Existing hospitality COVID-19 studies have investigated the effect of ESG on firm performance within a short period with mixed results. This study extends the literature by showing the different effects of ESG practices on market- and accounting-based performance during the COVID-19 outbreak and recovery periods.

The purpose of this study is to systematically examine and compare the growth of halal tourism and hospitality in OIC and non-OIC countries based on published literature.

A critical systematic review of 154 academic papers published in the last decade involving halal tourism in OIC and non-OIC countries constituted the sample for this study. The study uses an integrated antecedents, decisions and outcomes and theories, contexts and methods framework, and a coding protocol based on the preferred reporting items for systematic reviews and meta-analyses.

Halal tourism is not developed in non-OIC countries where Islam does not predominate, which represents an opportunity for many countries to incorporate new trends in their tourism offerings. This research increases awareness of non-OIC destinations to welcome a growing halal tourism market, enabling them to foster innovation to meet new demands for Muslim travelers.

This study is different as we compare the pertinent needs that are based on religion in various geographical locations while focusing on tourism and hospitality research in Islamic and non-Islamic nations.

This study aims to propose a risk-induced game theoretic forecasting model to predict average daily rate (ADR) under COVID-19, using an advanced recurrent neural network.

Using three data sets from upper-midscale hotels in three locations (i.e. urban, interstate and suburb), from January 1, 2018, to August 31, 2020, three long-term, short-term memory (LSTM) models were evaluated against five traditional forecasting models.

The models proposed in this study outperform traditional methods, such that the simplest LSTM model is more accurate than most of the benchmark models in two of the three tested hotels. In particular, the results show that traditional methods are inefficient in hotels with rapid fluctuations of demand and ADR, as observed during the pandemic. In contrast, LSTM models perform more accurately for these hotels.

This study is limited by its use of American data and data from midscale hotels as well as only predicting ADR.

This study produced a reliable, accurate forecasting model considering risk and competitor behavior.

This paper extends the application of game theory principles to ADR forecasting and combines it with the concept of risk for forecasting during uncertain times.

This study is the first study, to the best of the authors’ knowledge, to use actual hotel data from the COVID-19 pandemic to determine an appropriate neural network forecasting method for times of uncertainty. The application of Shapley value and operational risk obtained a game-theoretic property-level model, which fits best.