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The purpose of this paper is to investigate the association between CEO narcissism and corporate risk taking.

The authors provide a novel and unobtrusive measure of CEO narcissism based on LinkedIn profiling. The authors investigate the relationship between CEO narcissism and corporate risk taking (stock return volatility) for a sample of 475 US manufacturing firms in the period 2010-2014.

The authors find an inverse U-shape relationship between CEO narcissism and stock return volatility. The inverse U-shape relationship (the “humpback”) is caused by the paradoxical nature of the narcissistic personality in which the self-esteem is high but at the same time fragile with a combination of self-admiration and a constant need of having this positive self-view confirmed. The results are robust to alternative specifications of CEO narcissism and corporate risk taking. The results are economically meaningful. Thus, a moderate degree of CEO narcissism – as compared to a very low or a very high level of CEO narcissism – is associated with an increase in corporate risk taking of approximately 12 percent.

Previous literature provides multiple analyses on the association between managerial overconfidence and corporate decisions. As opposed to overconfidence, narcissism is a personality trait having both cognitive and behavioral dimensions. This paper provides a novel contribution to the growing literature on the association between managerial biases/traits and corporate decision-making.

This paper aims to investigate relationship conflicts and creative idea endorsement to develop the understanding of managerial reactions towards ideas of those who develop relationship conflicts with managers/supervisors at work. Taking a contingency perspective, the authors also investigated role subordinates’ political skills and implementation instrumentality play in determining supervisors’ endorsement of subordinates’ creative ideas.

The authors used two sources of data collected from 243 subordinates and their respective 41 supervisors of a multinational software company operating in an emerging economy (Pakistan) and analyzed the hypothesized model with Mplus using random coefficient modeling.

With this research, the authors contributed to management literature by investigating how the effects of relationship conflicts on creative idea endorsement depend on subordinates’ political skills and implementation instrumentality. They postulate a negative relationship between relationship conflict and creative ideas endorsement and predict that this negative relationship is augmented by subordinates’ implementation instrumentality but attenuated by subordinates’ political skills. They also give directions to decision makers in organizations that they must inform the managers/supervisors about negative effects of their relationship conflict with their subordinates and train supervisors and subordinates about reducing their relationship conflicts with each other for mutual benefits.

Organizations should take a relationship perspective when creating an environment for creativity: an environment based on mutual trust and respect so that exchange relationships can foster. With this research, the authors extended the list of potential detriment associated with relationship conflicts, that is the endorsement of creative ideas by supervisors. The authors also extended creativity literature by investigating social relationships for selection-focused creativity (idea endorsement) instead of variance-focused creativity (idea generation).

LinkedIn is a popular and maybe the best job-oriented social networking site (SNS) around the world. Numerous individuals (mostly, jobseekers), as well as the companies (mostly, hiring organizations) have LinkedIn accounts. This study intends to reveal the roles of LinkedIn-based skill endorsements (LSEs) as well as LinkedIn-based hiring recommendations (LHRs) on the hiring preferences (HPs) of Bangladeshi employers.

The authors purposefully selected 388 valid respondents (employers) from different Bangladeshi job sectors. Based on their responses, the authors applied SPSS 25 for explanatory statistics and a “Covariance-based Structural Equation Modeling (CB-SEM)” (with AMOS 25) to measure the hypothesized associations.

After appropriate analysis, the authors revealed a momentous positive role of LHR on HP, whereas LSE was identified to have an inconsiderable role on HP.

In this empirical study, the authors tried to highlight the relatively unattended area of Bangladeshi employers' HPs that can be affected by LSEs and LHRs. The authors believe that this study will encourage the researchers to unveil the impacts of LinkedIn-based profile characteristics on job candidates' employability. This empirical study can also aid the employers and policymakers to look for a new avenue for hiring competent talents.

Why do K-12 schools not perform better in educating English Language Learners (ELLs)? Part of the problem lies with higher education: We continue to produce pre-service teachers who are not prepared for today’s multilingual student population and, more importantly, most currently practicing teachers lack any such preparation.

This study aims to assess higher education students’ interest in learning sustainability competencies and their pro-ecological worldviews at a large research-intensive university in Finland to provide a background information for developing a sustainability science course.

In total, 797 students participated in the study. The data were collected through an online survey that measured students’ interest in learning sustainability competencies and their pro-ecological worldviews. Participants were classified into five categories based on field of study. The data were analysed by using Pearson’s correlation, independent samples t-tests, and analysis of variance.

The participating students perceived learning of critical thinking and values thinking most interesting. Interest in learning sustainability competencies and pro-ecological worldview appeared to differ across fields of study. Participants studying humanities expressed lower interest in collaborative use of digital technology compared to the participating students in science and agriculture. Participating students in health and welfare scored lower on interest in learning values thinking than students in other study fields.

The response rate was low. It is likely that the participants felt strongly about sustainability challenges, therefore making them more interested in sustainability competencies. The limited number of sustainability competencies studied does not allow generalisation to all sustainability competencies.

The differences in interest in learning sustainability competencies and pro-ecological worldview should be understood and considered when planning sustainability education.

These results provide new insights into the interlinkage of students’ interest in learning sustainability competencies, their pro-ecological worldviews and their field of study.

This paper aims to explore expanded uses for LinkedIn.com as a teaching tool, beyond introductory assignments, for in-demand and emerging marketing techniques.

This paper reviews the current use of LinkedIn as a teaching tool for marketing educators and presents sample assignments that can be used to introduce students to content marketing, SEO, and online reputation management.

Marketing educators have found LinkedIn to be a valuable resource for teaching professional development in the business curriculum. But the site can also provide a platform for the exploration of emerging specializations including content marketing and search engine optimization (SEO).

As a general review, this paper provides an overview of techniques. Research is needed to test and further explore the use of these techniques.

This paper provides rationale and recommendations for marketing educators who wish to better prepare students for a competitive job market, in which employers expect students to be well versed not only in social media but also in emerging techniques like content marketing and SEO.

Researchers have explored the use of various social media platforms for marketing education, including LinkedIn. This paper addresses the future potential of LinkedIn to teach various marketable skills and shows the versatility of social media platforms as pedagogical tools.

The paper aims to studiy social recruiting for finding suitable candidates on social networks. The main goal is to develop a methodological approach that would enable preselection of candidates using social network analysis. The research focus is on the automated collection of data using the web scraping method. Based on the information collected from the users' profiles, three clusters of skills and interests are created: technical, empirical and education-based. The identified clusters enable the recruiter to effectively search for suitable candidates.

This paper proposes a new methodological approach for the preselection of candidates based on social network analysis (SNA). The defined methodological approach includes the following phases: Social network selection according to the defined preselection goals; Automatic data collection from the selected social network using the web scraping method; Filtering, processing and statistical analysis of data. Data analysis to identify relevant information for the preselection of candidates using attributes clustering and SNA. Preselection of candidates is based on the information obtained.

It is possible to contribute to candidate preselection in the recruiting process by identifying key categories of skills and interests of candidates. Using a defined methodological approach allows recruiters to identify candidates who possess the skills and interests defined by the search. A defined method automates the verification of the existence, or absence, of a particular category of skills or interests on the profiles of the potential candidates. The primary intention is reflected in the screening and filtering of the skills and interests of potential candidates, which contributes to a more effective preselection process.

A small sample of the participants is present in the preliminary evaluation. A manual revision of the collected skills and interests is conducted. The recruiters should have basic knowledge of the SNA methodology in order to understand its application in the described method. The reliability of the collected data is assessed, because users provide data themselves when filling out their social network profiles.

The presented method could be applied on different social networks, such as GitHub or AngelList for clustering profile skills. For a different social network, only the web scraping instructions would change. This method is composed of mutually independent steps. This means that each step can be implemented differently, without changing the whole process. The results of a pilot project evaluation indicate that the HR experts are interested in the proposed method and that they would be willing to include it in their practice.

The social implication should be the determination of relevant skills and interests during the preselection phase of candidates in the process of social recruitment.

In contrast to previous studies that were discussed in the paper, this paper defines a method for automatic data collection using the web scraper tool. The described method allows the collection of more data in a shorter period. Additionally, it reduces the cost of creating an initial data set by removing the cost of hiring interviewers, questioners and people who collect data from social networks. A completely automated process of data collection from a particular social network stands out from this model from currently available solutions. Considering the method of data collection implemented in this paper, the proposed method provides opportunities to extend the scope of collected data to implicit data, which is not possible using the tools presented in other papers.