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The purpose of this paper is to examine the factors that significantly affect the prediction of fake news from the virality theory perspective. The paper looks at a mix of emotion-driven content, sentimental resonance, topic modeling and linguistic features of news articles to predict the probability of fake news.

A data set of over 12,000 articles was chosen to develop a model for fake news detection. Machine learning algorithms and natural language processing techniques were used to handle big data with efficiency. Lexicon-based emotion analysis provided eight kinds of emotions used in the article text. The cluster of topics was extracted using topic modeling (five topics), while sentiment analysis provided the resonance between the title and the text. Linguistic features were added to the coding outcomes to develop a logistic regression predictive model for testing the significant variables. Other machine learning algorithms were also executed and compared.

The results revealed that positive emotions in a text lower the probability of news being fake. It was also found that sensational content like illegal activities and crime-related content were associated with fake news. The news title and the text exhibiting similar sentiments were found to be having lower chances of being fake. News titles with more words and content with fewer words were found to impact fake news detection significantly.

Several systems and social media platforms today are trying to implement fake news detection methods to filter the content. This research provides exciting parameters from a viral theory perspective that could help develop automated fake news detectors.

While several studies have explored fake news detection, this study uses a new perspective on viral theory. It also introduces new parameters like sentimental resonance that could help predict fake news. This study deals with an extensive data set and uses advanced natural language processing to automate the coding techniques in developing the prediction model.

Informal entrepreneurship challenges sustainable economic performance and is a barrier to productive entrepreneurship. In this context, the level of development of formal and informal institutions and their impact on informal entrepreneurship is crucial. This chapter examines the informal sector entrepreneurship in Kosovo using institutional theory lenses. Using a survey with 500 owners/managers of private companies, the study finds that the service industry has the highest participation in the informal economy compared to other sectors. On average small firms, compared to larger ones, report a higher percentage of unreported incomes. Our findings also suggest that when informal entrepreneurs perceive penalties for tax avoidance from tax authorities as high, they tend to have higher compliance with reporting their income. In addition, our findings indicate that the higher the vertical (trust in formal institutions) and horizontal distrust (trust in business partners), the higher the involvement in the informal economy. The chapter concludes with some policy implications for tackling the informal economy in Kosovo and similar institutional contexts.

Drawing on institutional theory, this paper seeks to untangle the relationship between university support for entrepreneurship and students’ entrepreneurial intentions. Specifically, this study aims to examine whether entrepreneurial climates within universities mediate the relationship between university support for entrepreneurship and students’ entrepreneurial intention.

Empirical data is drawn from 195 students across three Malaysian higher education institutions. Partial least squares procedures are used to test the proposed hypotheses.

Findings show that no element of university support for entrepreneurship had a direct effect on students’ entrepreneurial intentions. However, the entrepreneurial climate was found – to mediate the relationship between perceived business and concept development support and students’ entrepreneurial intentions.

This study represents one of the few efforts in the literature considering the role of entrepreneurial climates within universities in influencing students’ entrepreneurial intention. In considering the mediating role of entrepreneurial climate, in the relationship between university support for entrepreneurship and students’ entrepreneurial intentions, this study provides a complementary and contextualised perspective, to existing studies, which have traditionally focussed on the mediating role of individual attributes. Doing so provides further evidence of entrepreneurial universities in fostering entrepreneurship.

The purpose of this study is to provide a nuanced explanation of the linkage between entrepreneurial motivations, job attractiveness and growth of family-owned small and mid-sized enterprises (SMEs) using expectancy and institutional theories.

The data was collected from small family business owners and job seekers in the same companies during interview time using a simple random technique.

The study found that three EMs among small business owners play a pivotal role in family SME business growth in underdeveloped trade regions like China–Pakistan Economic Corridor. These firms are interested in investing in seaport-related commerce, restaurants or hotels and real estate business.

The government, small family business owners, universities and regional youth can use this applied research for their benefits alike.

The study contributes in multiple ways. First, the authors brought a unique context in the emerging economies context of an informal economy like Pakistan. Second, the authors have uniquely tested the moderating role of job attractiveness in the least developed regions. Finally, the authors have integrated family SMEs’ expectancy theory and institutional perspective.

The purpose of this paper is to investigate the effect of heuristic biases, namely, availability bias and representativeness bias on investors’ investment decisions in the Pakistan stock exchange, as well as the moderating role of long-term orientation.

Using a structured questionnaire, a total of 374 responses have been collected from individual investors trading in PSX. The relationship was tested by applying the partial least square structural equation model using SmartPLS 3.2.2. Further, Henseler and Chin’s (2010) product indicator approach for moderation analysis was applied to the data set.

The results revealed that availability bias and representativeness bias have a significant and positive influence on the investment decisions of investors. Furthermore, a significant moderating effect of long term orientation on the effect of representativeness bias on investment decision is observed. This suggests that investors’ long term orientation weaken the effect of representativeness bias on investment decision. However, no significant moderating effect was observed for availability bias.

The paper provides novel insights on the role of heuristic-driven biases on the investment decisions of individual investors in the stock market. Particularly, it enhanced the understanding of behavioral aspects of investment decision-making in an emerging market.

Relying on the stakeholder view, this study investigates the role of CSR committee in moderating the association between CSR and firm performance (FP). Further, the authors examine whether country-specific governance and institutional factors drive the effect of CSR committee on the CSR-FP association.

The study's sample includes 4405 firms from 39 countries over the period 2002–2020. For analysis, ordinary least squares (OLS) regression with year and firm fixed effects is employed as the primary econometric model. Two-step generalized method of movement (GMM) is employed to address the endogeneity issues.

This study provides international evidence that the existence of a CSR committee enhances CSR's contribution to FP. Moreover, the benefits of CSR committees in terms of enhancing the positive impact of CSR on FP are significantly greater in strong governance countries and in environmentally less sensitive industries. The findings are further checked through endogeneity and robustness tests and remain unchanged.

CSR committee is a key governance mechanism that assists firms in generating value from their CSR activities. It strengthens a firm's relations with the stakeholders via an effective CSR channel, which translates into improved FP and long-term value.

The study is the first attempt to investigate the role of CSR committee, as a corporate governance mechanism, in explaining the relationship between CSR and FP in the international context. Further, the study also found that the role of CSR committee in enhancing CSR's outcomes largely depends on country-specific governance factors and the nature of industries.

Despite burgeoning interest in knowledge hiding (KH), there are still significant gaps in the understanding of the boundary conditions under which KH is more or less likely to occur. To address this research gap, the researchers examined abusive supervision as an interpersonal antecedent of KH. In addition, this paper aims to investigate the moderating roles of negative reciprocity beliefs (NRB) and moral disengagement (MD) in the relationship between abusive supervision and KH.

Two-wave data using a non-experimental face-to-face method was collected from 257 service employees in Pakistan, which supported the hypothesized model. Considering minimum sample size requirements (i.e. n = 208) in partial least squares structural equation modeling, the researchers analyzed a two-stage approach to test the measurement model and the structural model.

The study found that abusive supervision was positively related to evasive hiding and playing dumb but not associated with rationalized hiding. Further, the results confirm the moderating roles of NRB and MD. The positive relationships between abusive supervision and evasive hiding and playing dumb are intensified at high levels of NRB and MD.

Given the complicated nature of KH, this is one of the few efforts that outstretch the boundary conditions of KH.

This study aims to use dynamic capability theory to investigate the effect of entrepreneurial orientation and dynamic capabilities (DC) on the firm’s entrepreneurial performance through strategic entrepreneurship (SE).

To address the research objective, the authors obtained data from larger organisations operating in an emerging Pakistani economy.

Findings reveal that, in emerging markets, DC are essential elements that influence the organisation’s opportunity-seeking and advantage-seeking behaviours to ensure the firm’s entrepreneurial performance.

The present study implies that training is needed for the managers and team leaders of emerging market corporates to think entrepreneurially by revising the strategic goals of the corporate.

SE-based executive training should also be compulsory for the top management teams, including the board of directors for larger firms.

SE is a critically important business concept and should be taught in the emerging market’s business schools as a course at the graduate level.

This paper strengthens entrepreneurship literature by using a unique context of an emerging market and suggests a unique SE-based framework for the firms operating in emerging markets.

This paper aims to enhance the existing literature on adaptive market hypothesis (AMH) as this study first time links the month of Ramadan with AMH that permits the performance of well-known Ramadan effect to fluctuate over time.

To fulfill the purpose, the authors inspect the daily returns of 107 individual firms listed at Pakistan Stock Exchange over the period of 20 years. To explore the varying degree of return predictability during Ramadan, the authors use four different subsamples comprising equal length of observations of five years each. The authors use a GARCH (1,1) regression model which facilitates for time varying nature of volatility in equity returns. To facilitate the non-normal nature of stock return data, the authors use Kruskal–Wallis test statistic.

The authors find that behavior of Ramadan effect evolves over time, as performance of this effect varies from time to time and consistent with AMH. Finally, the paper proposes that AMH is well elucidation of behavior of Ramadan effect than traditional efficient market hypothesis.

First limitation is related to the choice of sub-sample as the study uses a sub-sample of five years. Second, the authors ignore transection cost (commissions, fee and taxes) as it is freely negotiated and varies between 4 and 10% (Khan, 2013). Due to such varying information we ignore the transaction cost. It is suggested that a sub-sample analysis of long period may be a more appropriate method to elucidate the idea of AMH in future research and suggest the current method could be adapted and helpful to examine other calendar and market anomalies in different equity markets.

The paper includes implications for investors to choose a better model for investment. Investors can exploit greater returns in future month of Ramadan periods. Furthermore, the researchers can easily extend the methodology used in the study to address multiple issues like adaptive behavior of returns from bonds, real estate investment trusts, cryptocurrencies and trading rules of strategies.

Study confirms from sample t-test and GARCH (1,1) model that Ramadan effect is present in the full and in certain sub-samples; therefore, based on these discrepancies investors can earn abnormal returns by developing specific investment strategies as investors usually make investments in share according to the religious context of Islamic Calendar. The results provide good references for suitable time of investment in stock market. The findings of this study will be helpful to investors and brokers as well as portfolio managers to capture favorable returns across the Islamic calendar.

The paper identified need to study why behavior of Ramadan effect varies over time. The data set comprises daily returns of 107 individual companies over the period of 20 years to better investigate the varying nature of anomalous effect of month of Ramadan. The findings are valuable for international investors and portfolio managers.

This study aims to short-therm forecasting of power generation output for this purpose, an adaptive neuro-fuzzy inference system (ANFIS) is designed to forecast the output power of power plant based on climate factors considering wind speed and wind direction simultaneously.

Several methods and algorithms have been proposed for systems forecasting in various fields. One of the strongest methods for modeling complex systems is neuro-fuzzy that refers to combinations of artificial neural network and fuzzy logic. When the system becomes more complex, the conventional algorithms may fail for network training. In this paper, an integrated approach, including ANFIS and metaheuristic algorithms, is used for increasing forecast accuracy.

Power generation in power plants is dependent on various factors, especially climate factors. Operating power plant in Iran is very much influenced because of climate variation, including from tropical to subpolar, and severely varying temperature, humidity and air pressure for each region and each season. On the other hands, when wind speed and wind direction are used simultaneously, the training process does not converge, and the forecasting process is unreliable. The real case study is mentioned to show the ability of the proposed approach to remove the limitations.

First, ANFIS is applied for forecasting based on climate factors, including wind speed and wind direction, that have rarely been used simultaneously in previous studies. Second, the well-known and more widely used metaheuristic algorithms are applied to improve the learning process for forecasting output power and compare the results.