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This paper aims to understand, in the state of São Paulo academic environment, the differences between the profiles of academic entrepreneurs, nonacademic entrepreneurs and non-entrepreneurs.

The authors collected data from a more comprehensive research, whose objective was to evaluate the scholarship programmes of São Paulo Research Foundation (FAPESP). For data collection, the authors used an online questionnaire, pre-filled with information from the Lattes Curriculum of the sample individuals, as well as information obtained from FAPESP and from coordination for the improvement of higher education personnel. The response rate of the questionnaires was 21 per cent. The authors sought to explore the variables regarding entrepreneurial activities carried out by former scholarship holders, by relating them to other key variables identified in the literature review and explained in the hypotheses.

The results indicate that entrepreneurship rates decrease with the higher academic level of the researcher; in general, academic entrepreneurs come from families with a good financial situation, and applied sciences are the areas of knowledge with more entrepreneurs.

Despite the great number of theoretical and empirical studies found in the literature on entrepreneurship and academic entrepreneurship, there is still a shortage of practical studies on this latter topic in Brazil. This gap is even more evident when the authors consider the significant growth of entrepreneurial activity in the country in the past years. This paper contributes to fill this gap, and it aims to understand, in the state of São Paulo academic environment, the differences between the profiles of academic entrepreneurs, nonacademic entrepreneurs and non-entrepreneurs.

Knowledge sharing in research communities has been considered indispensable to progress in science. The aim of this paper is to analyze the mechanisms restricting knowledge sharing in science. It considers three categories of academia–industry knowledge transfer and a range of individual and contextual variables as possible predictors of knowledge-sharing restrictions.

A unique empirical data sample was collected based on a survey among 212 life science researchers affiliated with universities and other non-profit research institutions. A rich descriptive analysis was followed by binominal regression analysis, including relevant checks for the robustness of the results.

Researchers in academia who actively collaborate with industry are more likely to omit relevant content from publications in co-authorship with other academic researchers; delay their co-authored publications, exclude relevant content during public presentations; and deny requests for access to their unpublished and published knowledge.

This study informs policymakers that different types of knowledge-sharing restrictions are predicted by different individual and contextual factors, which suggests that policies concerning academia–industry knowledge and technology transfer should be tailored to contextual specificities.

This study contributes new predictors of knowledge-sharing restrictions to the literature on academia–industry interactions, including outcome expectations, trust and sharing climate. This study augments the knowledge management literature by separately considering the roles of various academic knowledge-transfer activities in instigating different types of knowledge-sharing restrictions in scientific research.

This study investigates the characteristics of business and management consulting firms (firm size, international affiliation and scope of operation) affecting the adoption rate (i.e. recency of adopting big data analytics (BDA) as a new idea) and usage level of BDA. Ten critical areas of BDA application to business and management consulting were investigated, (1) Human Resource Management; (2) Risk Management; (3) Financial Advisory Services; (4) Innovation and Strategy; (5) Brand Building and Product Positioning; (6) Market Research/Diagnostic Studies; (7) Scenario-Based Planning/Business Simulation; (8) Information Technology; (9) Internal Control/Internal Audit; and (10) Taxation and Tax Management.

Survey data was obtained through a structured questionnaire from one hundred and eighteen (118) consultants in Nigeria from diverse consulting firm settings in terms of size, international affiliation and scope of operation (Big 4/non-Big 4 firms). Data was analyzed using descriptive statistics, cluster analysis, multivariate analysis of variance (MANOVA), multivariate discriminant analysis and multivariable logistic regression.

Whereas organizational characteristics such as firm size, international affiliation and scope of operation significantly determine the adoption rate of BDA, two attributes (international affiliation and scope of operation) significantly explain BDA usage level. Internationally affiliated consulting firms are more likely to record higher usage level of BDA than local firms. Also, the usage level of BDA by the Big 4 accounting/consulting firms is expected to be higher in comparison to non-Big 4 firms.

Contrary to common knowledge that firm size is positively associated with the adoption of an innovation, the study found no evidence to support this claim in respect of the diffusion of BDA. Overall, it appears that the scope of operation is the strongest organizational factor affecting the diffusion of BDA among consulting firms.

The study contributes to knowledge by exposing the factors promoting the uptake of BDA in a developing country. The originality of the current study stems from the consideration that it is the first, to the researchers' knowledge, to investigate the application of BDA by consulting firms in the Nigerian context. The study adds to literature on management accounting in the digital economy.

This study investigates the extent to which a company's usage of open access (OA) literature for R&D activities depends on its size. The authors’ assumption is that smaller pharmaceutical companies have less access to (usually expensive) journal subscriptions.

A fixed-effect Poisson model was used to study a panel dataset of USPTO pharmaceutical company patents. The dependent variable is the count of citations to OA resources in a given company patent.

Results support current anecdotal evidence that many SMEs suffer from high journal prices.

This result justifies the assumption made by policymakers about the potentially positive impact OA mandates have on national innovation activity. It was also shown that collaborating with universities can be a potential coping mechanism for companies that struggle to gain access to the journals they need. In addition to the novelty of its findings, this study introduces a new way to study the impact of OA in nonacademic contexts.

Given the cryptocurrency market boom in recent years, this study aims to identify the factors influencing cryptocurrency pricing and the major gaps for future research.

A systematic literature review was undertaken. Three databases, Scopus, Web of Science and EBSCOhost, were used for this review. The final analysis comprised 88 articles that met the eligibility criteria.

The influential factors were identified and categorized as supply and demand, technology, economics, market volatility, investors’ attributes and social media. This review provides a comprehensive and consolidated view of cryptocurrency pricing and maps the significant influential factors.

This paper is the first to systematically and comprehensively review the relevant literature on cryptocurrency to identify the factors of pricing fluctuation. This research contributes to cryptocurrency research as well as to consumer behaviors and marketing discipline in broad.

Integrated thinking involves a holistic, multi-capital approach to decision-making and operations to promote value creation and sustainability. This paper aims to outline a schematic which can be used to gauge the levels of integrated thinking by organisations.

The researchers partnered with an independent consulting firm (“Sustain-X”) which has developed a tool for evaluating integrated thinking. A two-stage mixed-method design is used to evaluate the tool. Firstly, in keeping with the exploratory nature of the paper, the tool’s integrated thinking principles and indicators are contrasted with findings from an extensive review of the integrated thinking research and interviews with experts on how integrated thinking is understood and operationalised. Secondly, the tool was applied to a sample of South African listed firms’ integrated reports and used to generate integrated thinking scores. These scores are evaluated by testing the strength of their association with other generally accepted proxies for integrated thinking.

The principles of the schematic include integrated awareness and understanding; integrated leadership commitment and capability; integrated structures; integrated organisational performance management; and integrated external communication. Empirical results show that the integrated thinking measures generated using the Sustain-X schematic are aligned with integrated report quality scores and ratings of the sophistication of organisations’ accounting, management and governance structures.

A combination of earlier research findings, detailed interviews (conducted independently of Sustain-X) and a battery of quantitative tests have been used to evaluate the schematic, but more refined testing using additional case studies or ethnographies has been deferred.

The tool offers a practical means for stakeholders to evaluate integrated thinking. It is flexible enough to be used with data collected during private engagements with companies or only publicly available information.

The schematic is one of the first to outline the dimensions of integrated thinking and should be useful for academics and practitioners concerned with the development and application of integrated thinking.

This paper adds to the literature on integrated thinking and answers the call for further research to evaluate integrated thinking practices.

Critics say cryptocurrencies are hard to predict and lack both economic value and accounting standards, while supporters argue they are revolutionary financial technology and a new asset class. This study aims to help accounting and financial modelers compare cryptocurrencies with other asset classes (such as gold, stocks and bond markets) and develop cryptocurrency forecast models.

Daily data from 12/31/2013 to 08/01/2020 (including the COVID-19 pandemic period) for the top six cryptocurrencies that constitute 80% of the market are used. Cryptocurrency price, return and volatility are forecasted using five traditional econometric techniques: pooled ordinary least squares (OLS) regression, fixed-effect model (FEM), random-effect model (REM), panel vector error correction model (VECM) and generalized autoregressive conditional heteroskedasticity (GARCH). Fama and French's five-factor analysis, a frequently used method to study stock returns, is conducted on cryptocurrency returns in a panel-data setting. Finally, an efficient frontier is produced with and without cryptocurrencies to see how adding cryptocurrencies to a portfolio makes a difference.

The seven findings in this analysis are summarized as follows: (1) VECM produces the best out-of-sample price forecast of cryptocurrency prices; (2) cryptocurrencies are unlike cash for accounting purposes as they are very volatile: the standard deviations of daily returns are several times larger than those of the other financial assets; (3) cryptocurrencies are not a substitute for gold as a safe-haven asset; (4) the five most significant determinants of cryptocurrency daily returns are emerging markets stock index, S&P 500 stock index, return on gold, volatility of daily returns and the volatility index (VIX); (5) their return volatility is persistent and can be forecasted using the GARCH model; (6) in a portfolio setting, cryptocurrencies exhibit negative alpha, high beta, similar to small and growth stocks and (7) a cryptocurrency portfolio offers more portfolio choices for investors and resembles a levered portfolio.

One of the tasks of the financial econometrics profession is building pro forma models that meet accounting standards and satisfy auditors. This paper undertook such activity by deploying traditional financial econometric methods and applying them to an emerging cryptocurrency asset class.

This paper attempts to contribute to the existing academic literature in three ways: Pro forma models for price forecasting: five established traditional econometric techniques (as opposed to novel methods) are deployed to forecast prices; Cryptocurrency as a group: instead of analyzing one currency at a time and running the risk of missing out on cross-sectional effects (as done by most other researchers), the top-six cryptocurrencies constitute 80% of the market, are analyzed together as a group using panel-data methods; Cryptocurrencies as financial assets in a portfolio: To understand the linkages between cryptocurrencies and traditional portfolio characteristics, an efficient frontier is produced with and without cryptocurrencies to see how adding cryptocurrencies to an investment portfolio makes a difference.

When we take the lens of race, ethnicity, gender, and class to the collected academic work on women business owners, what does it reveal? What do we really know? Are there differing definitions of success across segments of the women businessowner demographics? Do the challenges faced by African American women entrepreneurs differ from those confronting white female entrepreneurs? Do immigrant female women businessowners face more significant institutional barriers than their counterparts who have been U.S. citizens for at least two generations? Are there similar reasons for starting their businesses?