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The era of work 4.0 demands organizations to expedite their digital transformation to sustain their competitive advantage in the market. This paper aims to help the human resource (HR) department digitize and automate their analytical processes based on a big-data-analytics framework.

The methodology applied in this paper is based on a case study and experimental analysis. The research was conducted in a specific industry and focused on solving talent analysis problems.

This research conducts digital talent analysis using data mining tools with big data. The talent analysis based on the proposed framework for developing and transforming the HR department is readily implementable. The results obtained from this talent analysis using the big-data-analytics framework offer many opportunities in growing and advancing a company's talents that are not yet realized.

Big data allows HR to perform analysis and predictions, making more intelligent and accurate decisions. The application of big data analytics in an HR department has a significant impact on talent management.

This research contributes to the literature by proposing a formal big-data-analytics framework for HR and demonstrating its applicability with real-world case analysis. The findings help organizations develop a talent analytics function to solve future leaders' business challenges.

Purpose: The study aims to analyse and discuss the effect of COVID-19 on businesses. The chapter discusses the various machine learning (ML) tools and techniques, which can help in better decision making by businesses in the present world.

Need for the Study: COVID-19 has increased the role of VUCA elements in the business environment, and there is a need to address the challenges faced by businesses in such environment. ML and artificial learning can help businesses in facing such challenges.

Methodology: The focus and approach of the chapter are in the context of using artificial intelligence (AI) and ML techniques for decision making during the COVID-19 pandemic in a VUCA business environment.

Findings: The key findings and their implications emphasise the importance of understanding and implementing AI and ML techniques in business strategies during times of crisis.

Practical Implications: The chapter’s content is in the context of using AI and ML techniques during the COVID-19 pandemic and in a VUCA business environment.

This study investigates the impact of mentoring on real estate students' entrepreneurial intentions with a focus on Nigeria, an emerging African economy. Specifically, the study assessed the influence of mentoring on the entrepreneurial intentions and career preferences of real estate students and analysed the influence of having a real estate mentor on the respondents' perception of the motivators and inhibitors to their entrepreneurial intentions.

The study adopted a descriptive research approach using closed-ended questionnaires. The study population comprise final year real estate students selected from three federal universities offering Real Estate in southwest Nigeria. Total enumeration was adopted for the study. From a total population of 231 students, a response rate of 69.26%, representing 160 questionnaire were retrieved and found suitable for the analysis. Descriptive and inferential statistical techniques were employed for data analysis.

The result shows that the factor structure of the motivators for students who have real estate mentors clustered into four constructs; in order of influence are personal fulfilment/satisfaction, flexibility/financial motives, mentoring/economic influences and personal preferences/prestige and status. Meanwhile, economic/independence, personal preference/fulfilment, financial motives/self-perception and mentoring were the factor clusters influencing intention for real estate enterprise by students who have no real estate mentor. Predominant debacles across both categories of respondents relate to the lack of support and market uncertainty.

There is a growing body of knowledge exploring the linkages between mentoring and the development of entrepreneurial intentions. However, scant empirical investigations have examined the impact of mentoring on real estate students, especially from the perspectives of emerging markets which are usually characterised by low economic opportunities and where issues of graduate unemployment appear endemic and yet to be appropriately resolved.

This study explores the implications of mentoring on the entrepreneurial intentions of real estate students' from the perspective of an emerging market.

The purpose of this paper is to analyze accounting research developments in the area of corporate social responsibility (CSR) in Indonesia for the period 2012-2016. The focus of CSR literature review is on disclosures and not to examine CSR activities or programs.

This study applied a descriptive approach to provide evidence on the major variables that have been examined in CSR research and what is the measurement used to measure CSR disclosures. The CSR research development was traced through mapping articles published in the international journal with the subject of category accounting (Schimago Journal rank quartile Q3 and Q4), and national journal (national accredited accounting journals, as well as the proceedings of National Symposium on Accounting [NSA]). A total of 5,971 articles were reviewed and resulted in 31 Indonesian CSR articles in accounting which are dominated by quantitative methods (93.5 per cent), and as many as 28 articles were analyzed.

The analyses result showed that (1) 75 per cent of CSR research were in the areas of financial accounting and capital markets, followed by tax accounting and corporate governance; (2) The most widely used variable associated with CSR was financial performance; which (3) More than 80 per cent of the CSR research used annual reports as the source of data with only 19.23 per cent using sustainability reports; (4) 65.38 per cent of the CSR disclosure measurement referred to used other CSR disclosure lists, other than the Global Reporting Initiative (GRI).

The study results are important as a basis for future studies to provide a platform for the analysis to cover the gap between CSR studies in the academic and business areas for not only Indonesia but also other countries. Comparative studies between countries will be essential for future research to provide empirical evidence on the development of CSR research in accounting fields.

The study provides comprehensive pictures in how CSR disclosures have been analyzed in academic area so that practitioners in business field are able to understand the results on which variables are associated with CSR. Further, the practitioners could enhance their CSR implementations and reports to gain the utmost benefits for their business.

This study is considered as the first CSR literature review analyzed in accounting research publications. As CSR topics have been emerging developed in many field of studies, reviewing this topic in the accounting area resulted interesting findings. These findings are useful for not only Indonesia but also other countries. Further, this study provides platform to fill many gaps for future research in the topic of CSR in accounting field.

The purpose of this paper is to attempt to shift away from an exclusive probabilistic viewpoint or a pure network theory-based perspective for vulnerability assessment of infrastructure networks (INs), toward an integrated framework that accounts for joint considerations of the consequences of component failure as well as the component reliability.

This work introduces a fuzzy inference system (FIS) model that deals with the problem of vulnerability analysis by mapping reliability and centrality to vulnerability. In the presented model, reliability and centrality are first fuzzified, then 16 different rules are defined and finally, a defuzzification process is conducted to obtain the model output, termed the vulnerability score. The FIS model developed herein attempts to explain the linkage between reliability and centrality so as to evaluate the degree of vulnerability for INs elements.

This paper compared the effectiveness of the vulnerability score in criticality ranking of the components against the conventional vulnerability analysis methods. Comparison of the output of the proposed FIS model with the conventional vulnerability indices reveals the effectiveness of the vulnerability score in identifying the criticality of components. The model result showed the vulnerability score decreases by increasing reliability and decreasing centrality.

Two key practical implications for vulnerability analysis of INs can be drawn from the suggested FIS model in this research. First, the maintenance strategy based on the vulnerability analysis proposed herein will provide an expert facilitator that helps infrastructure utilities to identify and prioritize the vulnerabilities. The second practical implication is especially valuable for designing an effective risk management framework, which allows for least cost decisions to be made for the protection of INs.

As part of the first contribution, we propose a novel fuzzy-based vulnerability assessment model in building a qualitative and quantitative picture of the vulnerability of INs. The second contribution is especially valuable for vulnerability analysis of INs by virtue of offering a key to understanding the component vulnerability principle as being constituted by the component likely behavior as well as the component importance in the network.

This paper aims to systematically find the main research differences and similarities between social media and social networks in marketing research using the bibliometric perspective and provides suggestions for firms to improve their marketing strategies effectively.

The methods of co-word analysis and network analysis have been used to analyze the two research fields of social media and social networks. Specifically, this study selects 2,424 articles from 27 marketing academic journals present in the database Web of Science, ranging from January 1, 1996 to August 8, 2020.

The results show that social networks and social media are both research hotspots within the discipline of marketing research. The different intimacy nodes of social networks are more complex than social media. Additionally, the research scope of social networks is broader than social media in marketing research as shown by the keyword co-occurrence analysis. The overlap between social media and social networks in marketing research is reflected in the strong focus on their mixed mutual effects.

This paper explores the differences and similarities between social networks and social media in marketing research from the bibliometric perspective and provides a developing trend of their research hotspots in social media and social networks marketing research by keyword co-occurrence analysis and cluster analysis. Additionally, this paper provides some suggestions for firms looking to improve the efficiency of their marketing strategies from social and economic perspectives.

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.

Governance can often be assessed as one part of directing companies’ action toward something better. This study examines how governance quality at the country level and firm level can affect sustainability performance that aligns with sustainable development goals (SDG). Prior academic literature explains that if a country has a low institutional condition, it is a great challenge to implement sustainability. However, the internal awareness of the company to implement sustainability plays an important role as well. To examine the research question, this study uses the banking sector as a research sample with an observation period from 2017 to 2019. Prior literature overlooks research in the banking sector and does not feature country-level governance with firm-level governance. The data were collected either from the annual report or sustainability report, which comprises 141 companies, with the total observation of 423 firm-year. This study used panel data regression analysis and was based on the Hausman Test; it shows that random effect is used to test the hypothesis. This research finds that good quality governance at the country level, results in good sustainability performance. However, contrary to expectations regarding the quality of firm-level governance, which is thought to be positively related to sustainability performance, this study found a negative relationship. The argument that might answer the finding is the existence of governance conditions at the state level and at the firm level that mutually subsidize each other. This research contributes to policymakers continuing to provide counseling and improve institutional conditions to motivate companies to support the achievement of the SDGs. Companies should also pay attention to the effectiveness of their internal governance and strive to use stakeholder opinions as a guide in the realization of SDGs.

Facilitating members' continual participation in a community is crucial for ensuring the community's long-term survival. However, knowledge regarding whether member similarity is related to member participation and the mechanism underlying this relationship is limited. Drawing on similarity–attraction, social exchange and social identity theories, this study explored the influences of different facets of similarity (i.e. value, personality and goal similarity) on group norm conformity, group identity and social participation.

Data were collected from 444 Taiwanese members of social networking sites (SNSs), and structural equation modeling was employed to examine the hypothesized relationships.

The results revealed that value similarity directly affected group norm conformity but did not directly affect group identity; personality similarity influenced group identity but not group norm conformity. Goal similarity had positive influences on group norm conformity and group identity. Moreover, group norm conformity had direct and positive influences on group identity and social participation; group identity also had a positive influence on social participation.

On the basis of the aforementioned findings, this study contributes to the understanding of factors facilitating SNS members' participation from the perspective of similarity. These findings can serve as a reference for SNS administrators to facilitate social participation by emphasizing member similarity.