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Virtual reality (VR) offers unprecedented immersion and interactivity in education, and working and learning from home have become the norm during the COVID-19 pandemic. This study empirically investigated the factors affecting the use of a VR online learning system (VROLS).

To explore factors affecting users’ continuance behavioral intentions toward using VROLSs, a research framework was formed comprising factors that constitute benefits (i.e. pull factors) and costs (i.e. push factors); these factors included perceived value, flow and social influence. The data for this study were collected via online survey questionnaires. A total of 307 valid responses were used to examine the hypotheses in the research model, employing structural equation modeling (SEM) techniques.

Perceived value, flow experience and the number of peers using VR primarily affect the decision to adopt a VROLS. The pull factors of spatial presence, entertainment and service compatibility, along with the push factors of complexity and visual fatigue, affect perceived value. Therefore, we conclude that perceived value is a primary factor positively influencing both flow experience and the decision to adopt the service.

This study contributes to a theoretical understanding of factors that explain users’ intention to use VROLSs.

This study aims to explore customer perceived value (CPV) dimensions in the context of free mobile educational applications (EduApps) which are paramount in learning-based digital start-ups and are essential for the implementation of circular economy (CE). The purpose of the present study is to identify dimensions of CPV specifically for EduApps and propose a conceptual model that would assist the digital start-up decisions which in turn can be a catalyst in navigating to a CE.

The study uses the Netnography approach by analyzing online user-generated content. A total of 13,147 reviews posted on the Google play store after using top free education apps were coded using ATLAS.ti 9 software.

Major dimensions of context-specific CPV are identified as technical value, content value, pedagogical value, gamification value and learning value. Subdimensions and items are extracted for each of these dimensions.

The larger subscriber base drives sponsorships, advertisements and donations which underpin the business model of free EduApps. This can be obtained through an attractive value proposition. Identifying context-specific value dimensions would aid entrepreneurs in optimal value mix development decisions. The proposed framework can be utilized by both researchers (for scale creation, comparative studies and quantitative studies) and practitioners (for entrepreneurial decisions on better value propositions).

CPV successfully describes consumer decision-making, but less attention is paid to linking the theory to the setting of mobile learning apps, where the bulk of research is focused on techniques like TAM, UTAUT, etc. In addition, studies identifying CPV from mobile apps with a specific focus on EduApps are sparse. Extant literature in this context is either based on a foundation of in-store business value dimensions or dominated by technical aspects when focused on the context of mobile apps. The current study bridges this gap.

This study aims to examine the moderating effect of media exposure and media legitimacy on the environmental audit committee (EAC) regarding environmental disclosure quality as measured by voluntary and timely disclosure.

This paper was based on a sample of 81 French nonfinancial companies listed on the SBF 120 index and covered a six-year period; from 2014 to 2019. To test the hypotheses, a feasible generalized least squares regression was applied. Moreover, the authors checked the results using an additional analysis and the generalized method of moment model for endogeneity problems.

The results obtained show that for 482 French firm-year observations during the period 2014–2019, the media exposure does not play a moderating role between the EAC and the voluntary environmental disclosure; However, it plays a moderating role between the EAC and the timely environmental disclosure. The results also show that media legitimacy plays a moderating role between the EAC and the quality of environmental information. After testing for endogeneity problems, the findings remain unchanged.

The findings of this study may be of interest to academic researchers, practitioners and regulators who are interested in determining the quality of environmental disclosure by considering the role of the EAC while giving a role to media exposure and media legitimacy in the French context. Considering the EAC as a powerful source of effective corporate governance to improve the quality of environmental disclosure for decision-making, the research provides valuable insights for policymakers and managers on the importance of this mechanism and the importance of the environmental media and its tone in making environmental reporting useful and relevant.

The originality of the work lies in the fact that it is one of the first works that deal with the moderating effect of media exposure on the relationship between the EAC and the quality of environmental information disclosure measured by voluntary and timely disclosure. To the best of the authors’ knowledge, no previous empirical studies have been conducted on this relationship in the French context or in other contexts.

With more cities aiming to achieve climate neutrality, identifying the funding to support these plans is essential. The purpose of this paper is to exploit the present of a structured green bonds framework in Sweden to investigate the typology of abatement projects Swedish municipalities invested in and understand their effectiveness.

Marginal abatement cost curves of the green bond measures are constructed by using the financial and abatement data provided by municipalities on an annual basis.

The results highlight the economic competitiveness of clean energy production, measured in abatement potential per unit of currency, even when compared to other emerging technologies that have attracted the interest of policymakers. A comparison with previous studies on the cost efficiency of carbon capture storage reveals that clean energy projects, especially wind energy production, can contribute to the reduction of emissions in a more efficient way. The Swedish carbon tax is a good incentive tool for investments in clean energy projects.

The improvement concerning previous applications is twofold: the authors expand the financial considerations to include the whole life-cycle costs, and the authors consider all the greenhouse gases. This research constitutes a prime in using financial and environmental data produced by local governments to assess the effectiveness of their environmental measures.

This paper aims to examine the Canadian financial sector’s reaction to opportunities and risks created by the green bond market in a low-carbon and climate-resilient (LCR) economy.

The authors used a concurrent mixed methodological approach that undertakes an online survey and semistructured interviews with critical green bond market stakeholders.

The most significant market driver in Canada is the reputational benefit for stakeholders, i.e. its ability to meet the high demand for sustainable finance and the marketing potential of its green credentials. The major market barriers are transactional costs, i.e. additional tracking required for reporting purposes, lack of market liquidity and identification of environmental impact or additionality. Canadian green bonds are also more likely to be evaluated on their green impact than their global market peers.

Limitations of this study include its focus on Canada, which may exclude or not apply to drivers and barriers in other green bond markets.

The paper helps create an accounting-based conceptual framework for key motivations and barriers that affect financial decision-making regarding green bonds.

The authors identify economic and policy-related barriers and drivers for green bonds, addressing the financing gap for the LCR economy.

To the best of the authors’ knowledge, this study is the first to identify and compare Canadian green bond market drivers and barriers and to examine relevant stakeholder- and policy-related approaches that can be targeted to scale this market effectively.

This study aims to examine the perceived values of the metaverse when adopting it in the luxury hospitality business. Based on the cost–benefit perspective, this research provides solid theoretical contributions and actionable managerial recommendations.

An exploratory sequential mixed-method design was used. For the qualitative phase, 21 hotel managers and 24 hotel guests (who often stay in four-star and five-star hotels and resorts) were interviewed after showing them a series of videos about using the metaverse in the hotel business. Based on the results of the qualitative phase, the analytic hierarchy process method was used, and 476 valid questionnaires were analyzed.

The results highlight the perceived benefits (personalized services, immersive experience and positive brand image) and costs (lack of human touch, time and effort and security and privacy) of metaverse adoption for hotel managers and their guests. In addition, the study determines the weight of each value attribute of metaverse adoption for each travel stage (pre-travel, during travel and post-travel).

Regarding metaverse adoption, the research offers practical suggestions for luxury hotels. For instance, the cost of equipment and the time and effort required are perceived costs of metaverse adoption. To address these challenges, hotels may offer free equipment (e.g. VR headsets) and training to their guests to stimulate the use of the metaverse.

This study addresses a gap in the literature by presenting a conceptual framework for examining metaverse adoption in the luxury hotel scenario. Unlike using conventional models like the technology acceptance model or the unified theory of acceptance and use of technology to investigate a technology’s adoption, this study stands out by unraveling the topic through the lens of value proposition. The latter often comes from an efficient value co-creation process, which is indeed shaped by an adequate appreciation of the congruence of perceived values (i.e. perceived benefits and costs) of metaverse from hotel manager and guest perspectives.

This study aims to explore the internationalization of multinational enterprises (MNEs) from China and aims to examine the relationship between Chinese MNEs’ duration of internationalization and export intensity, and the contingent roles of the home country government.

By extending the springboard theory with institutional and cost-benefit analyses, the authors elaborate a two-phase framework of internationalization to explain how Chinese MNEs develop their international business under the influences of the home country government. Furthermore, the authors apply the Heckman two-stage method based on a panel data set of 19,994 firm-year observations of Chinese listed firms in 2008–2018 to test the hypotheses.

The research findings demonstrate an inverted U-shape relationship between the duration of internationalization and the export intensity of MNEs from China. The export intensity of MNEs from China increases during the initial phase of internationalization, and decreases during the subsequent. A further study reveals that the inverted U-shape of Chinese non-SOEs is steeper than that of SOEs, and this moderating effect is more salient after the Belt and Road Initiative. These results highlight the influence of the home government through state ownership and policies on the inverted U-shaped relationship.

This study helps to refine the understanding of Chinese MNEs’ global expansion by addressing time as an explicit dimension and revealing the mechanism of state ownership and the home country governmental policy in the dynamic internationalization process.

Turn-taking is beneficial to conversational search success, but the increase in turns and time can also increase the cognitive load of the user. Therefore, in this research paper, the authors view conversational search sessions through the lens of economic theory and use the economic models of search to analyze the various costs and benefits of information-seeking interactions.

First, the authors built a cost-benefit model for conversational search sessions by defining action types and performing an intellectual mapping of actual sessions into sequences of these actions (using thematic analyses). The authors used the hypothesized cost and benefit actions (obtained from the user-system dialogs), along with the number of turns, utterances and time-related parameters, to propose the mathematical model. Next, the authors tested the model empirically by comparing the model scores to the user satisfaction and task success scores (collected through questionnaires). By representing each session as a bag of actions, the authors developed linear regression models to predict task success and user satisfaction.

Through feature analysis and significance testing, the authors identify the different parameters that contribute significantly to user satisfaction and task success scores. Error analysis shows that the model predicts task success and user satisfaction reasonably well, with the average prediction error being 0.5 for both (on a 5-point scale).

The authors' research is an initial step toward building a mathematical model for predicting user satisfaction and task success in conversational search sessions.

This study aims to analyze why listed Taiwanese firms uniquely rejected the early adoption of International Financial Reporting Standards (IFRS) in 2012. It investigates the underlying decision-making processes behind this policy reluctance to further understand the continuous phenomenon of rare voluntary IFRS adoption.

It reports on fieldwork evidence obtained in situ by in-depth interviewing in Mandarin. It uses qualitative methods, complemented by quantitative cost-benefit metrics of IFRS adoption. It presents five diverse illustrative case-study vignettes, using a judgment sample based on expert opinion.

While the net-benefits of implementing IFRS varied across firms, this study’s unanimous finding was that no firms (in the sample or population) adopted IFRS early, despite stated intentions to the contrary. The key reasons for shunning early IFRS adoption were found to be frequent changes in regulations, insufficient benefits from adopting IFRS and the undermining of comparability across companies, compounded with scarce preparation time. Further, this study found that the Taiwanese accounting regulator’s reluctance toward IFRS adoption, partly caused by a long-standing US influence, contributed to this anomalous outcome.

This study recommends two critical policy changes: more realistic timelines and less frequent regulatory changes.

To the best of the authors’ knowledge, this is the first study to investigate the reasons behind the anomaly of no early adoption of IFRS in Taiwan, using new primary data and illustrative case studies. Its novelty lies in extending understanding beyond the existing quantitative literature on accounting standards, using new “thick” qualitative evidence on motives for such choices and decision-making processes, which have been neglected in previous work.

In recent decades, infrastructure has continued to develop as an important basis for social development and people's lives. Resource management of these large-scale projects has been immensely concerned because dozens of construction enterprises (CEs) often work together. In this situation, resource collaboration among enterprises has become a key measure to ensure project implementation. Thus, this study aims to propose a systematic multi-agent resource collaborative decision-making optimization model for large projects from a matching perspective.

The main contribution of this work was an advancement of the current research by: (1) generalizing the resource matching decision-making problem and quantifying the relationship between CEs. (2) Based on the matching domain, the resource input costs and benefits of each enterprise in the associated group were comprehensively analyzed to build the mathematical model, which also incorporated prospect theory to map more realistic decisions. (3) According to the influencing factors of resource decision-making, such as cost, benefit and attitude of decision-makers, determined the optimal resource input in different situations.

Numerical experiments were used to verify the effectiveness of the multi-agent resource matching decision (MARMD) method in this study. The results indicated that this model could provide guidance for optimal decision-making for each participating enterprise in the resource association group under different situations. And the results showed the psychological preference of decision-makers has an important influence on decision performance.

While the MARMD method has been proposed in this research, MARMD still has many limitations. A more detailed matching relationship between different resource types in CEs is still not fully analyzed, and relevant studies about more accurate parameters of decision-makers’ psychological preferences should be conducted in this area in the future.

Compared with traditional projects, large-scale engineering construction has the characteristics of huge resource consumption and more participants. While decision-makers can determine the matching relationship between related enterprises, this is ambiguous and the wider range will vary with more participants or complex environment. The MARMD method provided in this paper is an effective methodological tool with clearer decision-making positioning and stronger actual operability, which could provide references for large-scale project resource management.

Large-scale engineering is complex infrastructure projects that ensure national security, increase economic development, improve people's lives and promote social progress. During the implementation of large-scale projects, CEs realize value-added through resource exchange and integration. Studying the optimal collaborative decision of multi-agent resources from a matching perspective can realize the improvement of resource transformation efficiency and promote the development of large-scale engineering projects.

The current research on engineering resources decision-making lacks a matching relationship, which leads to unclear decision objectives, ambiguous decision processes and poor operability decision methods. To solve these issues, a novel approach was proposed to reveal the decision mechanism of multi-agent resource optimization in large-scale projects. This paper could bring inspiration to the research of large-scale project resource management.