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This study aims to advance a behavioural approach towards understanding how managerial perception impacts the enactment of responses to risk management during the implementation of digital technologies in industrial operations and supply chains. The purpose is to investigate the influence of (digital) technology and task uncertainty on the risk perception of managers and how this impacts risk responses adopted by managers.

Following an exploratory theory elaboration approach, the authors collected more than 80 h of interview material from 53 expert interviews. These interviews were conducted with representatives of 46 German companies that have adopted digital technologies for different industrial applications within manufacturing, assembly and logistics processes.

The findings provide nuanced insights on how individual and combined sources of uncertainty (technology and task uncertainty) impact the perception of decision makers and the resulting managerial responses adopted. The authors uncover the important role played by the interaction between digital technology and human being in the context of industrial operations. The exploratory study shows that the joint collaboration between humans and technologies has negative implications for managerial risk responses regardless of positive or negative perception, and therefore, requires significant attention in future studies.

The empirical base for this study is limited to German companies (mainly small and medium size). Moreover, German culture can be characterised by a high uncertainty avoidance and this may also limit the generalizability of the findings.

Managers should critically revise their perception of different types of digital technologies and be aware of the impact of human-machine interaction. Thereby, they should investigate more systematic approaches of risk identification and assessment.

This paper focuses on the managerial risk responses in the context of digitalisation projects with practical insights of 53 expert interviews.

This study aims to explore and conceptualize metaverse adoption using a systematic literature review (SLR). It also aims to propose a conceptual model that identifies significant factors affecting metaverse adoption in the entertainment, education, tourism and health sectors.

A SLR was conducted using the “preferred reporting items for systematic reviews and meta-analyses” report protocol and the “theory, context, characteristics, methods” framework to include all relevant articles published up to March 2023, which were sourced from the Scopus and Web of Science databases.

The reviewed literature revealed that the countries with the highest publications in the field of metaverse were China and the USA. It was also found that the technology acceptance model was the most used theoretical framework. Survey-based research using purposive and convenience sampling techniques emerged as the predominant method for data collection, and partial least square-structural equation modeling was the most used analytical technique. The review also identified the top six journals and the variables that help to develop a proposed model.

This review presents a novel contribution to the literature on metaverse adoption by forming a conceptual model that incorporates the most used variables in the entertainment, education, tourism and health sectors. The possible directions for future research with identified research gaps were also discussed.

This study aims to examine the effect of the different forms of attitudes on the behavioural intentions to adopt solar energy technologies (SETs) in Uganda. Although commonly examined, the effect of attitudes on people’s behavioural intentions to adopt SETs ought to be more distinctively examined to have a clear picture of how each of the identified sets of attitudes influences the adoption of SETs.

Based on a sample of 360 households from three urban districts in Uganda sampled using a multi-stage sampling technique, data were collected using a self-administrated structured questionnaire. The data were then analysed using partial least square–structural equation model with SmartPLS 3.0 software.

The study establishes that more specific attitudes affect behavioural intentions to adopt SETs than general pro-technology attitudes. Results reveal that both pro-environment and application-specific attitudes matter for behaviour intentions to adopt SETs amongst households. However, the general pro-technology attitudes are not significantly associated with behavioural intentions to adopt SETs.

The results are important for producers and promoters of solar technology to craft appropriate promotion campaigns intended to increase the acceptance and usage of SETs. This means focussing on creating positive attitudes specific to particular applications and popularising specific uses of solar technologies.

The study provides an alternative approach to the general representation of the attitudes–intentions relationships by examining the differences in the attitudes developed towards the different aspects of these technologies as a substantial source of variations in adoption behaviour, which is rarely addressed.

Digitalization accelerates the need of tourism and hospitality ecosystems to reframe business models in line with a data-driven orientation that can foster value creation and innovation. Since the question of data-driven business models (DDBMs) in hospitality remains underexplored, this paper aims at (1) revealing the key dimensions of the data-driven redefinition of business models in smart hospitality ecosystems and (2) conceptualizing the key drivers underlying the emergence of innovation in these ecosystems.

The empirical research is based on semi-structured interviews collected from a sample of hospitality managers, employed in three different accommodation services, i.e. hotels, bed and breakfast (B&Bs) and guesthouses, to explore data-driven strategies and practices employed on site.

The findings allow to devise a conceptual framework that classifies the enabling dimensions of DDBMs in smart hospitality ecosystems. Here, the centrality of strategy conducive to the development of data-driven innovation is stressed.

The study thus developed a conceptual framework that will serve as a tool to examine the impact of digitalization in other service industries. This study will also be useful for small and medium-sized enterprises (SMEs) managers, who seek to understand the possibilities data-driven management strategies offer in view of stimulating innovation in the managers' companies.

The paper reinterprets value creation practices in business models through the lens of data-driven approaches. In this way, this paper offers a new (conceptual and empirical) perspective to investigate how the hospitality sector at large can use the massive amounts of data available to foster innovation in the sector.

This study aims to use a survey to examine the factors encouraging Malaysian government agencies (MGAs) to adopt chatbots, which are a new artificial intelligence technology.

The minimum sample size was 98 according to the complexity model, and the respondents were top MGA management personnel. The questionnaire was emailed to all MGAs, and data were collected using snowball sampling in the technology–organization–environment (TOE) framework. Out of 348 top management personnel contacted, 341 agreed to participate in the study.

Technology readiness (TR), organizational readiness (OR) and citizen demand were all positively related to chatbot use intention. Government support (GS) strengthened the relationship between OR, TR and chatbot adoption intentions. The findings demonstrated the ability of the TOE framework to ascertain the factors influencing MGA chatbot adoption.

This study was limited to Malaysian federal government agencies.

The findings provide useful information for a better understanding of factors influencing the adoption of chatbots among Malaysian government agencies. Related parties, such as the head of department, could use these findings to plan further action to empower counter service by integrating chatbot adoption.

The study revealed the capability of the TOE framework to identify the factors influencing the decision to adopt chatbots among Malaysian government agencies. GS was found to have moderation effect on the relationship between OR and TR toward the intention to adopt a chatbot.

This paper aims to provide a complete analysis framework and prediction method for the construction of the patent securitization (PS) basic asset pool.

This paper proposes an integrated classification method based on genetic algorithm and random forest algorithm. First, comprehensively consider the patent value evaluation model and SME credit evaluation model, determine 17 indicators to measure the patent value and SME credit; Secondly, establish the classification label of high-quality basic assets; Then, genetic algorithm and random forest model are used to predict and screen high-quality basic assets; Finally, the performance of the model is evaluated.

The machine learning model proposed in this study is mainly used to solve the screening problem of high-quality patents that constitute the underlying asset pool of PS. The empirical research shows that the integrated classification method based on genetic algorithm and random forest has good performance and prediction accuracy, and is superior to the single method that constitutes it.

The main contributions of the article are twofold: firstly, the machine learning model proposed in this article determines the standards for high-quality basic assets; Secondly, this article addresses the screening issue of basic assets in PS.

This study aims to explore some perceptions related to the suggestion that external auditors will be replaced by audit technologies that use artificial intelligence (AI) tools to make audit judgements when performing the financial statement audits. Digital transformation is revitalising the technologies used by external auditors and their firms; thus, the authors seek to understand what challenges this creates for the auditing profession in Vietnam.

Through the theoretical lens of new institutionalism theory, this study uses a qualitative approach involving 20 semi-structured interviews conducted with external auditors in Vietnam during 2022. This sample includes the global Big Four, global mid-tier and smaller local Vietnamese audit firms.

The findings indicate that there is resistance or disagreement with the suggestion that in the future audit technologies using AI tools can replace humans (external auditors). The role of external auditors in the professional services sector will gradually be changed by audit technologies; however, external auditors are unlikely to be replaced by audit technologies that use AI tools based on the responses of the participants. Strict institutional rules that exist in Vietnam would prevent the replacement of (human) external auditors. In the future, external auditors may take on new roles as consultants, with unique skills in classifying and processing data for decision-making processes; however, they will not be completely replaced by technology in the audit space.

This study has limitations that it is based on the data collection from a single developing country, Vietnam; therefore, the generalisability of the findings is limited to Vietnam. Also, the authors sought insights into the future of external audits in Vietnam.

This study highlights the changing role of auditors and institutions. Thus, policymakers, external auditors and auditees in other developing countries would find the findings helpful.

This study provides new perspectives, particularly from local Vietnamese firms, about audit practices that emerge due to high-level technological advancements and then embed themselves into existing audit practices in an emerging economy. Prior studies tended to focus on the global Big Four firms, thus this study contributes by sharing the perceptions of the smaller practitioners also.

Considering rapid digitalization development, this study examines the impacts of digital technology innovation on social responsibility in platform enterprises.

The study applies the event study method and cross-sectional regression analysis, taking 168 digital technology innovations for social responsibility issued by 88 listed platform enterprises from 2011 to 2022 to study the impact of digital technology innovations for social responsibility announcements of different announcement content and platform attributes on the stock market value of platform enterprises.

The results show that, first, the positive stock market reaction is produced on the same day as the digital technology innovation announcement. Second, the announcement of the platform’s public social responsibility and the announcement of co-innovation and radical innovation bring more positive stock market reactions. In addition, the announcements mentioned above issued by trading platforms bring more positive stock market reactions. Finally, the social responsibility attribution characteristics of the announcement did not have a significant differentiated impact on the stock market reaction.

Most scholars have studied digital technology innovation for social responsibility through modeling rather than second-hand data to empirically examine. This study uses second-hand data with the instrumental stakeholder theory to provide a new research perspective on platform social responsibility. In addition, in order to explore the different impacts of digital technology innovation on social responsibility, this study has classified digital technology innovation for social responsibility according to its social responsibility and digital technology innovation characteristics.

A positive outlook on the impact of Industry 4.0 (I4.0) on sustainability prevails in the literature. However, some studies have highlighted potential areas of concern that have not yet been systematically addressed. The goal of this study is to challenge the assumption of a sustainable Fourth Industrial Revolution by (1) identifying the possible unintended negative impacts of I4.0 technologies on sustainability; (2) highlighting the underlying motivations and potential actions to mitigate such impacts; and (3) developing and evaluating alternative assumptions on the impacts of I4.0 technologies on sustainability.

Building on a problematization approach, a systematic literature review was conducted to develop potential alternative assumptions about the negative impacts of I4.0 on sustainability. Then, a Delphi study was carried out with 43 experts from academia and practice to evaluate the alternative assumptions. Two rounds of data collection were performed until reaching the convergence or stability of the responses.

The results highlight various unintended negative effects on environmental and social aspects that challenge the literature. The reasons behind the high/low probability of occurrence, the severity of each impact in the next five years and corrective actions are also identified. Unintended negative environmental effects are less controversial than social effects and are therefore more likely to generate widely accepted theoretical propositions. Finally, the alternative hypothesis ground is partially accepted by the panel, indicating that the problematization process has effectively opened up new perspectives for analysis.

This study is one of the few to systematically problematize the assumptions of the I4.0 and sustainability literature, generating research propositions that reveal several avenues for future research.

This study aims to use a novel approach, focusing on the manager’s gender, to explore whether it acts as a differentiator in the following aspects of tourist accommodation companies in Extremadura (Spain): the level of information and communication technology (ICT) specialisation of employees, managers’ knowledge of ICTs and the social media and online tourism platform use intensity of managers.

A questionnaire was sent to 238 accommodation companies. The data collected from the questionnaire were analysed using statistical inference techniques and linear and logistic regression.

In general, ICT specialist profiles are more common amongst the employees of male-led companies. Male managers also use Booking and analyse online feedback more intensively. There appear to be no gender-based differences in terms of the ICT knowledge of managers.

These results highlight issues of major practical interest for the sector’s managers and decision makers, especially in Extremadura. They reveal the digital divide in certain aspects between men- and women-led firms in Extremadura. This finding has important consequences for the sector in terms of competitiveness. It highlights the need to continue working to eradicate gender gaps in digital settings.

The study shows the role of the manager’s gender as a differentiating factor in terms of the existence of specialist ICT profiles and ICT use intensity in tourism companies. To the best of the authors’ knowledge, this study provides the first evidence of such a finding for the tourism sector in general, as well as for the specific case of a rural destination such as Extremadura.