خودارائه گری و توصیه های روند استخدام در جوامع آنلاین: درسهایی از شبکه اجتماعی LinkedIn
|کد مقاله||سال انتشار||مقاله انگلیسی||ترجمه فارسی||تعداد کلمات|
|38983||2015||9 صفحه PDF||سفارش دهید||7130 کلمه|
Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : Computers in Human Behavior, Volume 48, July 2015, Pages 516–524
Abstract This study investigated how a job seeker self-presentation affects recruiter’s hiring recommendations in an online communities and what categories of self-presentation contribute to fit perceptions for obtaining hiring recommendations. The study participants viewed potential candidates’ LinkedIn profiles and responded to questions regarding the argument quality and source credibility of their self-presentations, fit perceptions, and hiring recommendations. The results show that recruiters make inferences about job seekers’ person–job fit and person–organisation fit on the basis of argument quality in specific self-presentation categories, which in turn predict recruiters’ intentions to recommend job seekers for hiring. Although certain specific categories of self-presentation offering source credibility have positive associations with person–person (P–P) fit perception, there is a non-significant relationship between perceived P–P fit and hiring recommendations.
. Introduction An online community consists of members sharing common interests and purposes administered through guidelines and policies within a computer system (Preece, 2000). Online community life has increasingly become a significant part of our social lives (Burkell, Fortier, Wong, & Simpson, 2014) and has become a new channel through which organisations can connect with stakeholders, including job candidates (Madera, 2012). As increasing numbers of employers utilise these platforms to screen job candidates (Bohnert & Ross, 2010), job candidates are increasingly presenting themselves in online communities to impress employers (Dekay, 2009). Online communities have paved new paths for job seeking in the computer-mediated communication (CMC) environment (Ikenberry, Hibel, & Freedman, 2010), but few studies have examined how cues in the context of an online community affect job seekers’ behaviours, such as impression formation and self-presentation strategies (van der Heide, D’Angelo, & Schumaker, 2012). Although self-presentation in online communities has been previously examined (e.g., Birnbaum, 2013, DeAndrea and Walther, 2011, Labrecque et al., 2011 and Schwämmlein and Wodzicki, 2012), job seeking within online communities is qualitatively different from many other online settings because of the anticipation of face-to-face job interviews (Jansen, König, Stadelmann, & Kleinmann, 2012) and the social script (Gioia & Poole, 1984) for the hiring process in this context. Membership in the LinkedIn (www.linkedin.com) online community has grown exponentially (Gerard, 2011). The University of Massachusetts at Dartmouth released a study finding that 81% of Inc. 500 companies use LinkedIn for talent acquisition (Barnes & Lescault, 2012). LinkedIn is perhaps the most successful and widely used social networking site (SNS) for recruiters and job seekers and is the world’s largest professional network on the Internet (Adams, 2013). Some articles suggest ways that job seekers can enhance their chances of employment by optimising their self-presentation on LinkedIn (e.g., Damnianović, Matović, Kostić, & Okanović, 2012). However, little evidence exists to determine whether job seekers’ efforts to build their professional identity online are merely futile attempts to advance their careers or whether they might actually help job seekers secure opportunities for job interviews (Guillory & Hancock, 2012). As the realm of job seeking in online communities has not been studied extensively (Bohnert and Ross, 2010 and Davison et al., 2011), there is a gap in the current research on job seekers’ self-presentation in online communities. We address this research gap by investigating the following question: How does a job seeker’s self-presentation influence recruiters’ hiring recommendations in an online community? Accordingly, this study also explores the categories of self-presentation that contribute to fit perceptions for obtaining hiring recommendations. To answer our research question, we begin by reviewing a well-known approach in social psychology – self-presentation (Goffman, 1959) – to understand how job seekers present themselves and manage their self-presentations in an online community. Second, we explain how job seekers’ self-presentations lead to recruiters’ hiring recommendations through recruiter multiple-fit perceptions of applicants based on the theory of person–environment fit (Kristof-Brown, Zimmerman, & Johnson, 2005). Finally, we employ an elaboration likelihood model (ELM; Petty & Cacioppo, 1986) to provide a useful framework for making predictions regarding which self-presentation factors influence recruiters’ evaluations of job seekers (Forret & Turban, 1996) and therefore influence recruiter hiring recommendations. We develop the conceptual framework that is shown in Fig. 1 to explain how a job seeker’s self-presentation affects recruiter hiring recommendations and to identify the factors of effective self-presentation in online communities that lead to a hiring recommendation. The hypothesised relationships are based on person–environment fit theory and the ELM. A conceptual model of job seekers’ self-presentation and recruiters’ hiring ... Fig. 1. A conceptual model of job seekers’ self-presentation and recruiters’ hiring recommendations in online communities.
نتیجه گیری انگلیسی
6. Conclusion In conclusion, this study elucidates the mechanisms (ELM persuasion processes with fit perceptions) that link job seekers’ self-presentations to recruiters’ hiring recommendations in online communities. Our findings provide evidence that the argument quality of self-presentation influences recruiter perceptions of P–J and P–O fit and that perceived P–J fit and P–O fit lead to recruiters’ hiring recommendations. Future research might explore additional moderators (such as different types of job vacancies) to further clarify the boundary conditions of the proposed model.