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The purpose of this paper is to investigate to what extent the amount, information source and the content of the microblog information disclosure of listed companies could impact on innovation from the perspective of financing constraints.

The propensity score matching (PSM) and two-stage least square (2SLS) are used in estimations to deal with the endogeneity problem.

Evidence shows that the amount of we-media information disclosure significantly drives the innovation of enterprises. The mechanism is that we-media information disclosure drives the innovation by easing the financing constraints and bringing funds to the R&D activities. Further research shows that only the original information can drive the innovation. In particular, the R&D information promotes the R&D input and innovation output more significantly.

The conclusion of this paper provides a reference for the listed companies to drive innovation with the help of we-media information disclosure, a new solution for the small and medium-sized listed companies in China which have difficulty in carrying out innovation activities due to financing constrains and also provides useful practical enlightenment for the government and the capital market regulatory authorities to issue relevant policies to regulate we-media information disclosure.

This paper introduces a new information disclosure channel--we-media into the research on influencing factors of innovation and discusses the influence of the amount, different sources and disclosure contents from we-media on enterprise innovation, which enriches the existing research on enterprise innovation influencing factors, providing a new perspective for driving enterprises to innovate.

The purpose of this study is to empirically examine the factors influencing consumer behavioral intention (BI) to use cryptocurrency as a medium of transaction. Constructs from the unified theory of acceptance and use of technology model and an added variable, perceived risk (PR), are examined to predict BI. Age and gender as moderators are retained in this model.

An online survey was used to gather the respondents’ responses on a five-point Likert scale. G * Power was used to calculate the required minimum sample size. A non-probability sampling technique was used to gather data from the 290 respondents based in Malaysia. The final data set was analyzed using the statistical package for the social sciences and SmartPLS software using structural equation modeling.

The results show that three of the five proposed factors (performance expectancy, effort expectancy and facilitating condition) are significant predictors of BI to adopt cryptocurrency as a medium of transaction. Interestingly, PR is not a significant predictor even though prior research studies showed otherwise. Likewise, the relationship between BI and social influence became significant only when age is added as a moderator.

Malaysians are still wary of cryptocurrency, even though global tech firms such as Amazon and Microsoft are already accepting Bitcoin as a payment method. This study aims to provide relevant authorities and businesses (i.e. central bank, retail merchants and cryptocurrency exchangers) insights toward understanding the factors consumers focus on if they were to use cryptocurrency as a medium of transaction.

Most cryptocurrency research are done in developed countries (i.e. USA, UK and EU) perspective. This research addresses the lack of quantitative literature on significant factors influencing BI to use cryptocurrency in developing country context while taking a PR, age and gender into consideration.

Demand foresting significantly impacts supply chain (SC) design and recovery planning. The more accurate the demand forecast, the better the recovery plan and the more resilient the SC. Given the paucity of research about machine learning (ML) applications and the pharmaceutical industry’s need for disruptive techniques, this study aims to investigate the applicability and effect of ML algorithms on demand forecasting. More specifically, the study identifies machine learning algorithms applicable to demand forecasting and assess the forecasting accuracy of using ML in the pharmaceutical SC.

This research used a single-case explanatory methodology. The exploratory approach examined the study’s objective and the acquisition of information technology impact. In this research, three experimental designs were carried out to test training data partitioning, apply ML algorithms and test different ranges of exclusion factors. The Konstanz Information Miner platform was used in this research.

Based on the analysis, this study could show that the most accurate training data partition was 80%, with random forest and simple tree outperforming other algorithms regarding demand forecasting accuracy. The improvement in demand forecasting accuracy ranged from 10% to 41%.

This study provides practical and theoretical insights into the importance of applying disruptive techniques such as ML to improve the resilience of the pharmaceutical supply design in such a disruptive time.

The finding of this research contributes to the limited knowledge about ML applications in demand forecasting. This is manifested in the knowledge advancement about the different ML algorithms applicable in demand forecasting and their effectiveness. Besides, the study at hand offers guidance for future research in expanding and analyzing the applicability and effectiveness of ML algorithms in the different sectors of the SC.

This paper aims to provide a process-driven scientific data quality (DQ) monitoring framework by information product map (IP-Map) in identifying the root causes of poor DQ issues so as to assure the quality of scientific data.

First, a general scientific data life cycle model is constructed based on eight classical models and 37 researchers’ experience. Then, the IP-Map is constructed to visualize the scientific data manufacturing process. After that, the potential deficiencies that may arise and DQ issues are examined from the aspects of process and data stakeholders. Finally, the corresponding strategies for improving scientific DQ are put forward.

The scientific data manufacturing process and data stakeholders’ responsibilities could be clearly visualized by the IP-Map. The proposed process-driven framework is helpful in clarifying the root causes of DQ vulnerabilities in scientific data.

As for the implications for researchers, the process-driven framework proposed in this paper provides a better understanding of scientific DQ issues during implementing a research project as well as providing a useful method to analyse those DQ issues based on IP-Map approach from the aspects of process and data stakeholders.

The process-driven framework is beneficial for the research institutions, scientific data management centres and researchers to better manage the scientific data manufacturing process and solve the scientific DQ issues.

This research proposes a general scientific data life cycle model and further provides a process-driven scientific DQ monitoring framework for identifying the root causes of poor data issues from the aspects of process and stakeholders which have been ignored by existing information technology-driven solutions. This study is likely to lead to an improved approach to assuring the scientific DQ and is applicable in different research fields.

The investigation of pro-environmental behaviors (PEB) among college students is essential for future sustainability endeavors. Existing research seldomly concentrated on college students and their PEB. This study aims to address the gap in understanding PEB among college students.

This study constructed an integrated model combining the theory of planned behavior (TPB) and the value-belief-norm (VBN) theory, with the novel addition of environmental risk perception. Through an empirical study involving 844 college students, this research analyzed the data with the structural model.

The authors identified that environmental values, attitudes, perceived behavioral control, subjective norms and risk perception play crucial roles in shaping PEB. This study also revealed age-related differences, highlighting that older students might be less influenced by attitudes and subjective norms due to more established habits. Findings underscore the importance of fostering PEB through environmental education, promotion of low-carbon lifestyle choices and incentives. This investigation not only enriches the theoretical framework for PEB but also offers practical insights for policymakers and educators to enhance sustainable practices among the youth.

Though the authors offer valuable findings, this research has two key limitations: the use of observational data for hypothesis testing, which weakens causal inference, and the collection of data through questionnaires, which may be biased by social desirability. Respondents of self-report tend to behave in the socially desired ways. Consequently, they usually exaggerate their pro-environmental intention or PEB. To comprehend the influencing aspects more thoroughly, future research should consider incorporating experimental methods and objective data, such as digitalized data.

The findings provide valuable evidence for guiding college students’ PEB, including strengthening environmental education, promoting of low-carbon fashion and providing incentives for PEBs.

First, the authors examine the internal factors influencing PEB among Chinese university students within the “dual-carbon” initiative framework. Second, this research pioneers the use of structural equation modeling to merge TPB and VBN theories, offering a predictive model for university students’ PEB. Third, the authors introduce “environmental risk perception” as a novel variable derived from both TPB and VBN, enhancing the model’s explanatory power.

The chapter details the development of one of the most lucrative professional sports for women in the world, while drawing attention to institutionalised issues of racism and sexism in the sport. We discuss the history of women in professional golf, from the roots of the Ladies Professional Golf Association (LPGA), through the modern-day game where women now play for large sums of money each week. We then shed light on the development of a global tour which started with the likes of Annika Sorenstam, Lorena Ochoa, and Se Ri Pak dominating a once Americentric tour, and how the LPGA struggled to embrace this cultural shift via the Five Points of Celebrity marketing plan and the contentious English-speaking rule. The discussion then moves to focal point of the chapter: the US media's reaction to long-time American professional golf coach and former radio broadcaster Hank Haney's disparaging comments before and at the conclusion of the 2019 Women's US Open. Twenty-five articles were collected from US golf and sport media outlets and coded resulting in four themes: (1) a downplaying of the remarks, (2) ambivalence to the women's game, (3) a privileging of men, and (4) a global tour. The chapter concludes with remarks that highlight the media's struggle to find the appropriate framing and language to cover the incident and how an intersectional approach reveals that oppression of women on the LPGA Tour exists beyond gender.

This paper aims to explore the extent to which social responsibility and social and environmental reporting and disclosure have any relevance in the (so-called) controversial industries. The literature is ambivalent over the extent to which it is expected to see corporate social responsibility and social disclosure employed as active legitimation strategies. However, the apparent importance of “responsible gambling” in both the literature and in gambling industry initiatives suggests, at least a priori, that the international industry is active in some degree of legitimation.

This exploratory study examines the social and environmental disclosures of a sample of large companies in each of five countries over a three-year period using conventional content analysis.

The results are unexpected in that, although disclosure is dominated by employee- and director-related, other areas of social and environmental – and indeed economic – activity feature hardly at all. There is remarkably little disclosure around responsible gambling.

The paper is a research note based on a range of samples across five countries and is, inevitably, tentative. The implications, albeit tentative, include the need to re-theorise corporate disclosure, especially in the controversial sectors.

The note adds to the accounting literature concerned with the controversial industries and contributes to the scarce social accounting research in the gambling sector. The authors hope that the research will be useful in guiding more focused and in-depth studies into this increasingly important and counter-intuitive area.

The purpose of this paper is to investigate the factors influencing the adoption of internet banking services in Mauritius. Drawing from the technology acceptance model, theory of reasoned action, theory of planned behaviour and the extensive literature on demographic profiling of internet banking users, trust and security aspects associated with adoption rate of internet banking, this paper combines various predetermined constructs in one model. The different constructs such as perceived ease of use, perceived usefulness, subjective norms, attitudes, behavioural intentions, security and trust aspects, the level of awareness on internet banking services and demographic variables such as age, income, gender and education into one integrated framework. Hence, the paper will deepen understanding of the specific factors underpinning the adoption of internet banking in Mauritius.

This paper reports upon the empirical findings of the customer survey on the various factors impacting on the adoption of internet banking by the questionnaire method. The Internet Banking Services Acceptance Model (IBSAM) is further validated through a survey instrument administered to 384 respondents visiting various banking institutions across the nine districts throughout Mauritius to ensure proper geographical coverage. The questionnaires were further processed and analysed with the statistical programme SPSS, by using descriptive and inferential analysis.

Data analysis showed that perceived ease of use and perceived usefulness have a direct influence on the adoption of internet banking in Mauritius. Results have also indicated that both trust and security aspects are deemed crucial factors to explaining internet banking adoption in Mauritius. Further examination of the inferential analysis highlighted that level of education and income level of respondents may be a major determinant in influencing the adoption of internet banking.

This research provides banking institutions with significant information on the various aspects that need to be highlighted in their banking communications strategies to increase the adoption rate of internet banking services. Banking institutions need to stress upon the benefits of internet banking services, ease to use, trust and security aspects. The ndings of the research provide valuable insights for the banking industry and also urge upon a reshaping of their e-marketing strategy in relation to internet banking services in Mauritius. The research findings revealed that secured web contents and design are key tools to increase the adoption rate of internet banking. Practical recommendations to increase web usefulness and trust, and guidelines to reduce perceived risk are also provided in the present research paper.

The purpose of the study is to fill up significant gaps in the literature on internet banking landscape in the context of developing countries like Mauritius. The findings are expected to be of significant use to the commercial banks and other financial institutions offering or planning to offer internet banking solutions in the near future. An understanding of the factors influencing the adoption of internet banking services is essential for marketing practitioners so as to capitalize upon the underlying benefits of internet banking and hence, offer banking customers an online experience coupled with a greater level of personalization and customization.

This study aims to construct a theoretical framework that combines the Technology Acceptance Model (TAM) and other variables related to life insurance adoption among customers. This will explain the factors that influence customers’ decisions to use Life InsurTech services in the future.

A hybrid method combining theory-driven analysis and thematic analysis was used for content analysis, allowing for a holistic perspective, and developing a conceptual research model.

The paper contributes significantly by creating a conceptual framework designed to understand and explain the factors that impact customers’ intentions to adopt Life InsurTech services. By emphasizing technology-related factors, behavior-related factors, knowledge-related factors and individual-related factors, one could potentially identify and explain the factors influencing the intention to use Life InsurTech services.

The limitation of the current research is the lack of prior research on InsurTech services. This study contributes to reviewing and organizing earlier knowledge to help researchers address the key factors affecting Life InsurTech services adoption.

The study has suggested a conceptual framework that Life InsurTech managers can use to implement the effective adoption of Life InsurTech services.

With the significant importance of life insurance for consumers as well as for the country’s economic development and the advent of InsurTech innovations, there is a need to understand the online life insurance purchase behavior of consumers.

The outcomes presented in this study will lay the groundwork for future investigations that aim to address the research question regarding the factors influencing customers’ intentions to utilize Life InsurTech services. With very few studies conducted on InsurTech services, this novel study proposes a new conceptual framework to better understand the adoption of Life InsurTech services.