Purpose The purpose of this paper is to explore the role of social media in creating an attractive employer brand for any organization. It investigates one of the social media Glassdoor, which is an online employer branding platform, where employees put their reviews which are both positive and negative. Analysis of these reviews can generate a lot of insights into employer branding. Design/methodology/approach The data was collected as 1,243 reviews from Glassdoor, an online crowdsourced employer branding platform for 40 top-rated employers across four different sectors, namely, Pharma, IT, retail and FMCG. Text and sentimental analyses were done using SAS visual analytical for these reviews. Findings Ten themes were generated from the text analytics which is nothing but the employer value propositions (EVPs), and they were social, interest, development and economic value as given by Berthon et al. (2005) and also others, such as work–life, management and brand value emerged. Social value came as a significant EVP followed by interest value and work–life values. Research limitations/implications This research is providing only ways to show that crowdsourced data can also be used to understand the mindset of employees regarding an employer’s image but is not providing any idea regarding how to generate the right employee value proposition. Originality/value The research has shown that employers can use crowdsourced employer branding insights to see where they stand in the employer's attractiveness spectrum. They can use innovative data analytics techniques, such as visualization for text and sentimental analysis to create employer branding intelligence strategies.
PurposeThe purpose of this study is to explore the perception of the users concerning the role of artificial intelligence (AI) in enhancing personal learning profile (PLP), personal learning network (PLN) and personal learning environment (PLE) and their effect on the perceived ease of use, perceived effectiveness and perceived usefulness for enhancing the overall attitude and satisfaction of the e-learning.Design/methodology/approachThe data were collected from students and professionals who have ever used the e-learning module, and smart partial least square-structural equational modeling (PLS-SEM) is used to see relations between the different variables.FindingsIt was seen that the PLE is affecting both perceived ease of use and perceived usefulness. The research has shown that perceived ease of use showed a mediating effect between PLE and attitude and satisfaction. Further satisfaction mediates between perceived ease of use and intention. PLP has come out to significantly impacting perceived effectiveness. The multigroup analysis also showed that the attitude and satisfaction level affecting intention to use the e-learning module differ across the two groups of learners, i.e. gender and type of learners.Research limitations/implicationsThe data are collected from students and professionals who have ever used the e-learning module and wholly based on their perceptions, leading to self-perception bias.Originality/valueThe current research is trying to integrate the user perception of PLP, PLN, PLE into the framework of the technology acceptance model and see how they impact the overall attitude and satisfaction of the learners. AI can be used to improve them and make e-learning more adherent to the users. AI can play an essential role in generating the right environment by matching the profile of the learner.
Purpose The recent COVID-19 pandemic has (triggered) lots of interest in work from home (WFH) practices. Many organizations in India are changing their work practices and adopting new models of getting the work done. The purpose of the study to look at the boundary-fit perspective (Ammons (2013) and two factors, namely, individual preferences (boundary control, family identity, work identity and technology stress) and environmental factors (job control, supervisor support and organizational policies). These dimensions are used and considered to create various clusters for employees working from home. Design/methodology/approach K-mean clustering was used to do the cluster analysis. Statistical package for social sciences 23 was used to explore different clusters based on a pattern of characteristics unique to that cluster, but each cluster differed from other clusters. Further analysis of variance test was conducted to see how these clusters differ across three chosen outcomes, namely, work-family conflict, boundary management tactics used and positive family-to-work spillover effect. The post hoc test also provided insights on how each cluster differs from others on these outcomes. Findings The results indicated four distinct clusters named boundary-fit family guardians, work warriors, boundary-fit fusion lovers and dividers consistent (with previous) research. These clusters also differ across at least two major outcomes like boundary management tactics and positive spillover. The high control cluster profiles like Cluster 3 (boundary-fit fusion lovers) and Cluster 4 (dividers) showed low technostress and higher use of boundary management tactics. Cluster 3 (boundary-fit fusion lovers) and Cluster 1 (boundary-fit family guardians) having high environmental influencers also showed higher positive family-to-work spillover. Research limitations/implications Because this study is very specific to the Indian context, a broad generalization requires further exploration in other cultural contexts. The absence of this exploration is one of the limitations of this study. On the culture continuum, countries may vary from being individualistic on one extreme to being collectivistic on the other extreme. Interaction of these two cultural extremities with the individual and the environmental dimension, as espoused in this research, can be examined further in a different cultural setting. Originality/value This study has extended the work of Ammons (2013) and added external influencers as a dimension to the individual preferences given by (Kossek 2016), and created the cluster for employees in the Indian context. This study has demonstrated the importance of reduced technostress, and the use of boundary management tactics (temporal and behavioral) leads to positive family-to-work spillover. It has also emphasized the relevance of organization policies and supervisor support for better outcomes in WFH.
This article explores the various dimensions of early recruitment activities (ERAs) such as publicity, sponsorship, word of mouth and advertisement, and its impact on employer brand knowledge (EBK) such as employer familiarity, employer image or job association and employer reputation. It further explores the impact of ERAs and EBK on organization attractiveness (OA) and firm performance (FP). The study shows that advertisement, publicity and word of mouth of ERAs impact all aspects of EBK such as employer familiarity, employer image or job association, and employer reputation. Employer reputation and job association are significant for most organization and does impact OA, while brand awareness and job association impact FP. The prominent sources of employment information were the Internet and networking.
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