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Saleh Bajaba

Other affiliations: Louisiana Tech University
Bio: Saleh Bajaba is an academic researcher from King Abdulaziz University. The author has contributed to research in topics: Personality & Computer science. The author has an hindex of 5, co-authored 13 publications receiving 172 citations. Previous affiliations of Saleh Bajaba include Louisiana Tech University.

Papers
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Journal ArticleDOI
TL;DR: In this paper, the authors expand the concept of entrepreneurial feasibility to include anticipatory thinking and a generative view of entrepreneurial self-efficacy by considering broader forms of selfefficacy that proactive and competitive people are likely to develop.

135 citations

Journal ArticleDOI
TL;DR: In this article, a detailed overview of the existing state-of-the-art methodologies for ML and DL researchers and the wider health community with descriptions of how machine learning and DL and data can improve the status of COVID-19, and more studies in order to avoid the outbreak of CoV-19.
Abstract: With many successful stories, machine learning (ML) and deep learning (DL) have been widely used in our everyday lives in a number of ways. They have also been instrumental in tackling the outbreak of Coronavirus (COVID-19), which has been happening around the world. The SARS-CoV-2 virus-induced COVID-19 epidemic has spread rapidly across the world, leading to international outbreaks. The COVID-19 fight to curb the spread of the disease involves most states, companies, and scientific research institutions. In this research, we look at the Artificial Intelligence (AI)-based ML and DL methods for COVID-19 diagnosis and treatment. Furthermore, in the battle against COVID-19, we summarize the AI-based ML and DL methods and the available datasets, tools, and performance. This survey offers a detailed overview of the existing state-of-the-art methodologies for ML and DL researchers and the wider health community with descriptions of how ML and DL and data can improve the status of COVID-19, and more studies in order to avoid the outbreak of COVID-19. Details of challenges and future directions are also provided.

82 citations

Journal ArticleDOI
TL;DR: In this paper, the authors investigate Amazon s Mechanical Turk Masters perceptions and attitudes related to the data quality (e.g. inattention) and provide recommendations for researchers using crowdsourcing data.
Abstract: Researchers in the social sciences are increasingly turning to online data collection panels for research purposes. While there is evidence that crowdsourcing platforms such as Amazon s Mechanical Turk can produce data as reliable as more traditional survey collection methods, little is known about Amazon s Mechanical Turk s most experienced respondents, their perceptions of crowdsourced data, and the degree to which these affect data quality. The current study utilises both quantitative and qualitative data to investigate Amazon s Mechanical Turk Masters perceptions and attitudes related to the data quality (e.g. inattention). Recommendations for researchers using crowdsourcing data are provided.

60 citations

Journal ArticleDOI
TL;DR: In this paper, the authors investigated the interactive effects of trait mindfulness and proactive personality on job performance and career success and found that high trait mindfulness substitutes the positive influence of proactive personality.
Abstract: Mindfulness research is growing within organizational studies Emerging evidence across many fields demonstrates that mindfulness is related to numerous individuals’ outcomes in the workplace, but this knowledge base has not been investigated enough This study extends previous literature by examining the extent to which trait mindfulness influences individuals’ job performance and career success Also, this study investigates the interactive effects of trait mindfulness and proactive personality on job performance and career success The sample of the study included three hundred subjects with at least of three years of work experience in the United States of America Hypotheses were tested using multiple linear regression The results supported the hypotheses that trait mindfulness would be positively associated with both job performance and career success, measured by career satisfaction Interestingly, trait mindfulness moderated the relationship between proactive personality and both job performance and career satisfaction such that high trait mindfulness substitutes the positive influence of proactive personality Practical implications, possible limitations, and future research directions are briefly discussed

15 citations

Journal ArticleDOI
TL;DR: In this paper, the authors argue that managers with an adaptive personality tend to have increased self-efficacy levels to lead during a crisis, resulting in increased motivation to lead in the COVID-19 crisis.
Abstract: The coronavirus disease 2019 (COVID-19) has taken the world by surprise and has impacted the lives of many, including the business sector and its stakeholders. Although studies investigating the impact of COVID-19 on the organizational structure, job design, and employee well-being have been on the rise, fewer studies examined the role of leadership and what it takes to be an effective leader during such times. This study integrates social cognitive theory and conservation of resources theory to argue for the importance of adaptive personality in the emergence of effective leaders during crisis times, utilizing the crisis of COVID-19 as the context for the study. We argue that managers with an adaptive personality tend to have increased self-efficacy levels to lead during a crisis, resulting in increased motivation to lead during the COVID-19 crisis. Furthermore, managers with increased motivation to lead during the COVID-19 crisis are argued to have enhanced adaptive performance, thereby suggesting a serial mediation model where crisis leader self-efficacy and motivation to lead during the COVID-19 crisis act as explanatory mechanisms of the relationship between the adaptive personality and performance of the manager. In order to test our hypotheses, we collected data from 116 full-time managers in Saudi Arabia during the COVID-19 crisis and used hierarchical linear regression as the method of analysis. The findings support all of the hypotheses. A discussion of the results, contributions, limitations, and future directions is included.

12 citations


Cited by
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Journal ArticleDOI
TL;DR: The use of Amazon's Mechanical Turk (MTurk) in management research has increased over 2,117% in recent years, from 6 papers in 2012 to 133 in 2019.

327 citations

Journal ArticleDOI
TL;DR: In this article, the authors examined the role played by action-oriented personality traits (i.e. trait competitiveness and proactive personality) in the transition from opportunity recognition to entrepreneurial action and found that entrepreneurial alertness significantly influenced entrepreneurial intentions, which subsequently resulted in entrepreneurial action.

117 citations

Journal ArticleDOI
TL;DR: Barabas et al. as mentioned in this paper found that factual manipulation checks (FMCs) can identify individual-level attentiveness to experimental information and, as a consequence, better enable researchers to diagnose experimental findings.
Abstract: Manipulation checks are often advisable in experimental studies, yet they rarely appear in practice. This lack of usage may stem from fears of distorting treatment effects and uncertainty regarding which type to use (e.g., instructional manipulation checks [IMCs] or assessments of whether stimuli alter a latent independent variable of interest). Here, we first categorize the main variants and argue that factual manipulation checks (FMCs)—that is, objective questions about key elements of the experiment—can identify individual-level attentiveness to experimental information and, as a consequence, better enable researchers to diagnose experimental findings. We then find, through four replication studies, little evidence that FMC placement affects treatment effects, and that placing FMCs immediately post-outcome does not attenuate FMC passage rates. Additionally, FMC and IMC passage rates are only weakly related, suggesting that each technique identifies different sets of attentive subjects. Thus, unlike other methods, FMCs can confirm attentiveness to experimental protocols. Replication Materials: The data, code, and any additional materials required to replicate all analyses in this article are available on the American Journal of Political Science Dataverse within the Harvard Dataverse Network, at: https://dataverse.harvard.edu/dataset.xhtml?persistentId=https://doi.org/10.7910/DVN/GSQG1K. Experiments are a popular method for testing hypotheses and advancing theory within the social sciences. Essential for the validity of an experiment is the extent to which a study’s participants are actually “treated” (Oppenheimer, Meyvis, and Davidenko 2009). As a precondition for being treated, respondents must (in most instances) first be attentive to treatments. Ensuring that respondents attend to stimuli, however, presents a challenge, particularly given the growth in online surveys and reliance upon subjects from opt-in panels who may be distracted (e.g., Chandler and Shapiro 2016; Clifford and Jerit 2015). Within a study, therefore, being able to accurately gauge receipt of treatment is paramount. One technique for assessing treatment receipt is that of a manipulation check (MC). Broadly defined, MCs are “used to check whether the manipulation conducted in an experiment is perceived by the subjects as the experimenter wishes it to be perceived” (Morton and John V. Kane is Assistant Professor, Center for Global Affairs, New York University, 15 Barclay Street, New York, NY 10007 (john.kane@nyu.edu).Jason Barabas is Professor, Department of Political Science, Stony Brook University, Social & Behavioral Sciences, 7th Floor, Stony Brook, NY 11794 (jason.barabas@stonybrook.edu). We would like to thank Scott Clifford, Jennifer Jerit, Yanna Krupnikov, David Nickerson, and Christine Peterson for their helpful comments on earlier drafts of this article. Additionally, Ben Carter, Mike Kriner, Michelle lo-Low, and Alecia Nepaul provided outstanding research assistance. Matthew Hitt and Vittorio Mérola graciously provided data and code. Finally, we also appreciate the suggestions that we received from the anonymous reviewers, faculty and graduate students at Stony Brook University, and panelists at the annual conferences of the American Political Science Association and the International Society for Political Psychology. Williams 2010, 108). However, there is much variation in why researchers implement MCs. In practice, scholars sometimes report using manipulation checks to determine whether the latent independent variable of interest has been affected by experimental stimuli (Mutz and Pemantle 2015, 196). More generally, researchers also use MCs to assess respondent attentiveness during a study, such as via specific questions given to participants to judge whether they are reading carefully (e.g., Anduiza and Galais 2016; Crump, McDonnell, and Gureckis 2013; Maniaci and Rogge 2014). MCs therefore provide researchers with leverage on the nature of their experimental findings. As Mutz (2011, 84–85) contends, “Experiments for which manipulation checks can be considered ‘optional’ are relatively few and far between,” primarily because failing to include an MC “undermines what can be learned from any given study.” Perhaps because of the varying functions of MCs, there is widespread heterogeneity in the forms that MCs American Journal of Political Science, Vol. 63, No. 1, January 2019, Pp. 234–249 C ©2018, Midwest Political Science Association DOI: 10.1111/ajps.12396

102 citations

Journal ArticleDOI
TL;DR: This study applied partial least squares structural equation modeling to test the hypotheses on a sample of 346 university students from Jiangsu province, China and showed that entrepreneurial passion positively and significantly influenced entrepreneurial alertness, entrepreneurial self-efficacy to entrepreneurial intention, and entrepreneurial behavior.
Abstract: This study investigated the role of entrepreneurial passion in recognition of opportunity, developing entrepreneurial self-efficacy, and entrepreneurial intention, in the shaping of entrepreneurial actions in the presence of proactive personality. This study applied a partial least squares structural equation modeling (PLS-SEM) to test the hypotheses on a sample of 346 university students from Jiangsu province China. The output of the study showed that entrepreneurial passion positively and significantly influenced entrepreneurial alertness, entrepreneurial self-efficacy to entrepreneurial intention, and entrepreneurial behavior. The findings also showed that a proactive personality positively and significantly moderated the relationship between entrepreneurial intention and entrepreneurial behavior.

102 citations