Social media recruiting and online personal reputation evaluation by recruiters in Israel
收藏Mendeley Data2024-03-27 更新2024-06-26 收录
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Online Reputation (OR) is the public evaluation of an individual, based on his behavior and the information published online by himself or shared by others. The elements of a person's online reputation may include pictures and movies, online résumé and posts or comments in blogs. Online Reputation is an important element when recruiters gather relevant and credible personal information in order to evaluate and screen candidates. Evaluation and screening with Online Reputation is widely used by recruiters in USA and Europe (Haefner, 2009; Cross-Tab, 2010; Madden & Smith, 2010). However, such a study was never performed in Israel. This research examines the attitudes of recruiters and HR professionals concerning online reputation information in their candidate evaluation processes by asking the following questions: Do Israeli recruiters use online reputation in the recruitment process? To what extent online reputation components are perceived as relevant, credible and affecting the decision to screen candidates? What are the goals and online resources used by recruiters in Online Reputation search? Are recruiters willing to pay for such and information? Do organizations use Online Reputation in their formal procedure of recruitment? An innovative approach was required to recruit randomly selected Israeli recruiters thru connections within the LinkedIn Network. This method resulted in a 31.3% (N=104) participation rate (valid answers only). The participants (age: 25 to 58, 87 women) filled an online questionnaire, mainly about the impact of online reputation on candidate screening, the relevance and the credibility of online reputation information, free and paid sources used in their tasks and their goals in social media recruiting. Highlights of the study’s findings show that 85% of the Israeli recruiters use Online Reputation Search in the recruitment process. Means of relevancy and credibility of professional values and norms (like writing about a previous employer or being a member of professional community) were high (M=3.9, SD-0.9) on a Lickert scale of 1-5, compared to pictures and hobbies which were unexpectedly low (M=2.6, SD=1.0). While a positive correlation was found between credibility and relevancy (r=0.32, p < .001, n=97), no significant correlation was found between these variables and the impact on the decision to screen candidates. Other findings show that recruiters use principally free resources like Google (79%) and LinkedIn (96%) for online reputation search and are only 9% are willing to pay for information about candidates (N=8). This study also indicates that only a small number of Israeli companies have made online reputation screening a formal requirement of their hiring process (13%).
线上声誉(Online Reputation,OR)指公众基于个体自身行为、其在网络上发布或他人分享的信息,对其作出的公开评价。个体的线上声誉要素可包含图片、视频、线上简历以及博客中的帖子或评论。当招聘人员为评估并筛选求职者而收集相关且可信的个人信息时,线上声誉是一项重要考量因素。借助线上声誉开展评估与筛选的做法已在美国和欧洲的招聘人员中广泛应用(Haefner, 2009; Cross-Tab, 2010; Madden & Smith, 2010)。然而,以色列尚未开展过此类研究。本研究针对招聘人员与人力资源(Human Resources)专业人士在求职者评估流程中对线上声誉信息的态度展开调研,提出以下问题:以色列的招聘人员是否会在招聘流程中使用线上声誉信息?线上声誉要素在何种程度上被视为与求职者评估相关、可信,且会影响筛选求职者的决策?招聘人员在搜索线上声誉信息时的目标与使用的网络资源有哪些?招聘人员是否愿意为此类信息付费?企业是否将线上声誉纳入正式的招聘流程中?本研究需采用创新方法,通过领英(LinkedIn)网络内的人脉关系招募随机选取的以色列招聘人员。该方法最终实现了31.3%的参与率(仅统计有效答卷,N=104)。参与调研的人员年龄介于25至58岁之间,其中女性87名,他们填写了一份线上问卷,问卷内容主要涵盖线上声誉对求职者筛选的影响、线上声誉信息的相关性与可信度、调研任务中使用的免费与付费信息源,以及他们在社交媒体招聘中的目标。本研究的核心发现显示,85%的以色列招聘人员会在招聘流程中开展线上声誉信息搜索。在1至5分的李克特(Likert)量表中,与职业价值观和职业规范相关的信息(如提及前雇主或加入专业社群的内容)的相关性与可信度得分较高(均值M=3.9,标准差SD=0.9),而图片与个人爱好相关的信息得分则出乎意料地低(均值M=2.6,标准差SD=1.0)。研究发现可信度与相关性之间存在正相关关系(r=0.32, p < .001, n=97),但这两个变量与筛选求职者决策的影响程度之间未发现显著相关性。其余研究结果显示,招聘人员主要使用谷歌(Google)、领英(LinkedIn)等免费资源开展线上声誉信息搜索,仅有9%的受访者愿意为求职者相关信息付费(N=8)。本研究同时表明,仅有少数以色列企业将线上声誉筛选纳入招聘流程的正式要求之中,占比仅为13%。
创建时间:
2024-01-23
搜集汇总
数据集介绍

背景与挑战
背景概述
该数据集是一项关于以色列招聘者使用社交媒体招聘和在线个人声誉评估的实证研究。研究基于104名招聘者的在线问卷调查,发现85%的招聘者利用在线声誉信息评估候选人,主要依赖免费资源如Google和LinkedIn,但仅13%的公司将其纳入正式招聘流程。数据集包含SPSS格式的调查数据,用于分析招聘者对在线声誉相关性、可信度和决策影响的态度。
以上内容由遇见数据集搜集并总结生成



