The influence of online professional social media in human resource management: A systematic literature review

research boundaries, and derive ways to enrich this area of research further. The study is motivated by the fact that given the short life cycle of social media platforms and information systems, PSMs need to innovate and continuously offer value to their users. The study makes a concrete contribution to PSM literature by generating actionable research avenues for future researchers and providing practical insights for managers and service providers.


Introduction
Traditional recruitment methods follow the pattern of advertising a job, receiving applications, shortlisting candidates, arranging interviews, and employing individuals [1]. Such a recruitment process involves outsourcing, consultancies, referrals, campus recruitment, or selecting a potential in-house employee for a role switch [2]. These methods are now taking a backseat as online job portals and social media platforms take over the screening process and the shortlisting of candidates that fit a job role [3]. Academic literature claims that recruiters use every possible platform to screen talent for employment [4]. This is being proven by the increasing popularity of professional social media platforms (PSMs) in the recruitment and hiring processes. PSMs are rapidly transforming the way people search for new jobs and employers hunt for new employees [5].
The Internet has played a reframing role in the lives of individuals [6]. Social media platforms (SMPs) were originally introduced to facilitate the communication of personal and professional interests [7]. SMPs are expansive, dynamic and enable the sharing of several types of content [8]. DeNardis and Hackl [9] conceptualize SMPs as encompassing the following three technological features: (a) intermediation of the content generated by users; (b) interactivity among users and direct contact with online content; and (c) interconnection of individuals with other users on the network. Different SMPs serve different purposes [10]. For example, Facebook is used for social networking [11], Twitter is used for micro-blogging [12], YouTube for content sharing and viewing [13], Snapchat for image sharing [14], and LinkedIn for professional networking [15].
From a professional perspective, SMPs allow their users to update information on proficiencies, such as qualifications, work experience, and skills, in a representative manner [16]. This significantly increases the probability of employers finding talent that matches the required skills and qualifications. Moreover, the possibility of several positions showing up on professional websites that fit individual users' qualifications also increases significantly. From the organizational perspective, PSMs provide employers with access to a large pool of suitable potential individuals for available vacancies [3]. Attracted by the large database of employable talent while investing less time and money in the employment process than before [17], human resource (HR) professionals have shifted their focus from traditional methods of recruitment to online PSM platforms [18].
Recent years have witnessed an overwhelming increase in the use of PSMs [5,[19][20][21]. For example, in the United States, recruiters have started depending heavily on social networking sites, especially PSMs, to hire suitable candidates [22]. PSMs were created to facilitate the exchange of human interests (both personal and professional) [18]; and these platforms have overtaken conventional methods of recruiting due to the ease of process and the availability of a large pool of candidates [23]. Among the various PSMs that ease the process of employment, several studies have identified LinkedIn as the most convenient and effective website for employers [24,25] and job seekers [26,27]. In fact, LinkedIn (94%) was found to be the best platform among PSMs [28] for hiring individuals for vacant job roles [29], followed by Facebook (65%), Twitter (55%), Google Plus (18%), YouTube (15%), and Instagram (13%). In addition, Grissa [30] included websites such as Viadeo, Xing, YouPeek, and SkilledAfricans, to conceptualize professional networking sites.
Scholars have suggested that PSMs initiate professional careers [31]. Recent studies have argued that online profiles on PSMs are used to assess candidates' suitability for a job role [20,21]. A strong profile is important for job interviews [32]. Due to their rising importance and decisive role in human resource management (HRM) practices, especially employability and recruitment, PSMs have drawn increasing academic attention in the recent past. However, scholarly knowledge on this subject is scattered across various means of publication. Consequently, it is challenging to comprehend the managerial as well as the theoretical applicability of the existing findings and draw pertinent insights. We argue that this is a significant gap in the literature and that a critical synthesis of prior studies is required to systemically foster productive directions for future research on the effectiveness, efficiency, and role of PSMs in HRM practices. Therefore, the current study attempts to organize these interesting yet scattered studies to arrive at a comprehensive and state-of-the-art synthesis of existing knowledge in this domain. This proposed review aims to add value to the literature on the role of PSMs in the recruitment process [33] and takes a step forward by drawing cumulative conclusions for advancing theory and practice.
For this purpose, we undertook a systematic literature review (SLR) of 45 extant studies on PSM and employability, published during the period from 2009 to June 2020. The primary objective of this SLR is to provide inputs for research and practice in order to diffuse PSMs to a wider number of users and create more value for individuals and HRM professionals. Following the rationale set by the study, the review was based on the following research questions (RQs): RQ1. What is the candidate studies' research profile in terms of journals, countries of study, international collaborations, and data-analysis techniques? RQ2.
What key trends and findings emerge from the research themes examined in the reviewed studies? RQ3. What are the key research gaps identified in the research profile and research themes? RQ4. What are the key implications and recommendations for the stakeholders involved in recruitment via PSMs?
The key contribution of the SLR comes from its tripartite focus on methods, theory, and implications. At the methodological level, we have cataloged features such as year-wise progression of publications, crosscountry collaborations, the geographic scope of the studies, and dataanalysis techniques by reviewing the selected studies. We also undertook detailed research profiling to help future researchers in identifying potential collaborators and suitable publications for publishing their work. At the theoretical level, we have identified emergent themes by taking a cumulative view of existing studies. At the implications level, we have gone beyond reporting of a review, to set a broader research agenda in terms of the gaps derived from each theme. Our contribution to scholarship is made concrete by presenting a visual overview of the potential research areas identified through the SLR.

Research methodology
We carried out the synthesis of prior literature on PSMs by using the protocols of recent systematic reviews [34]; [35]. The SLR protocol was crafted in line with prior reviews to ensure the study's precision and replicability [36]. The method used for this study comprised of two stages. First, we selected the pool of review studies, and second, we discussed the outcomes of the review. To select studies for the review, we employed the technique of citation chaining to ensure the maximum coverage of articles. Moreover, the study selection protocol involved pre-specified quality-evaluation criteria [37].

Search criteria and the selection of studies
To initiate the identification of keywords for the subsequent review, we invited a panel of experts, which included three authors, three academicians from the areas of information systems and HRM, and two doctoral students. The panel was presented with the idea of the study and the seminal research on PSMs and HRM [38], and the members suggested appropriate keywords for the database search. "LinkedIn," "professional social network*," and "professional social media" were identified as base keywords. Words such as "social network" and "social media" were discarded to preserve the core of the area under investigation. The base keywords were included in the search along with "job," "career," "recruitment," "selection," "employability," "human resource*" and "HR*." Words like "management," "organization," and "management practices" were excluded to keep the focus of the selected studies narrow. The data timeline was set to be 2009 to June 2020 to ensure the coverage of articles published in the past decade.
Then, the authors independently carried out the following steps to arrive at the final pool of selected articles. Using the abovementioned keywords, 382 research studies were found from the Scopus and Web of Science databases. The search was restricted to "Title, Abstract, Keywords" and "English" language. First, relevant studies falling under the research scope of current study were screened. 102 studies were selected from both the databases. Next, duplicate studies (studies with the same digital object identifier [DOI]) from both databases were eliminated, leaving a pool of 82 studies. Next, based on the inclusion and exclusion criteria (see Fig. 1), the studies were read and shortlisted. Author 1 selected 79 studies, author 2 selected 71 studies, and author 3 selected 77 studies. The expert panel was re-invited, and the articles selected by each author were discussed. Finally, a set of 69 articles was unanimously agreed upon by the panel for inclusion. Furthermore, the citation chaining for the review studies was executed using the forward (assessing the citations of each study) and backward (assessing the references of each study) chaining techniques. This step minimized the chance of missing any relevant studies. Author 1 found 12 studies, author 2 selected 6 studies, and author 3 selected 11 studies. At this point, the panel met and discussed the studies identified through citation chaining to select studies for review synthesis. After the panel established consensus, 7 studies were included in the review process at this step. Additionally, to ensure a robust selection of studies, the 69 articles from the database search and the 7 articles from citation chaining were rated against pre-set quality evaluation (QE) criteria suggested by systematic reviews [37]. The members of the panel individually rated 76 studies, and based on the QE criteria, 45 studies were finally included in the pool of studies for further synthesis. The ratings of all panel members were analyzed for inter-rater reliability using the Kappa statistic. The coefficient was 0.84 [39], implying acceptable agreement [40]. The panel members were financially compensated for their support and feedback. The method is presented in Fig. 1.

Research profiling
We provide descriptive statistics and visualizations for the selected studies in order to present the profile of existing scholarship on Link-edIn. Research profile includes the annual scientific production of research articles, author collaborations, geographic scope, and data analysis methods. Fig. 2 presents the annual scientific production of research articles. The continuous growth of studies on PSM and recruitment is indicative of the importance of this thematic area. Fig. 3 reveals author collaborations between countries, with two studies reporting a comparison among Norway, France, and Germany and one study reporting a collaboration between the United Kingdom and Saudi Arabia. As evident from Fig. 4, the United States and Europe have the highest number of empirical studies that have been published on the current topic. Most articles are not country specific as the data were drawn from profiles on PSM. This suggests the need for a context-based, country-based study of novel dynamics related to recruitment processes that have changed due to PSM platforms, further justifying the rationale of the present study. Fig. 5 describes the various techniques employed for data analysis in the review studies.

Research themes
We performed a thematic analysis of the selected studies' content for a comprehensive evaluation of existing research [41]. The thematic analysis was based on the grounded theory approach [42]. According to the main theme of the study, each author assigned open codes to the articles based on their understanding, and after individual coding, a     employability through PSM. Our thematic analysis led to the development of the following five themes: professional platforms: reasons for distinctiveness, individual use: drivers and barriers, PSM affordances: enhancing professional visibility, organizations' PSM use and the effects of socio-demographic factors in PSM use.

Professional platforms: reasons for distinctiveness
The digital era is characterized by the prolific use of social networking sites (SNSs), including Facebook, LinkedIn, Twitter, and other platforms. For instance, Archambault and Grudin [43] tracked the use of the social networks by Microsoft employees in the 2008-2011 period and found that the employees used LinkedIn on par with Facebook and Twitter. Further, Kim, Kim, and Nam [44] reported the use of SNSs by employees during work hours. Our review suggests that prior literature has focused on the distinctiveness of PSMs. To understand consumers' use motive for these platforms, Microsoft carried out a comparison between Facebook (an SNS) and LinkedIn (a PSM) and reported that LinkedIn was used more for professional networking. In contrast, Facebook was used mainly for social networking [38]. Similar findings regarding LinkedIn's use for professional reasons have been reported by Nikolaou [26]. LinkedIn is more professional compared to Facebook for communicating and verifying job-related information. For instance, while both sites are used for recruitment purposes, decision-makers rely more on LinkedIn for candidates' information than they do on Facebook [24]. This may be attributed to the benefits of LinkedIn (such as connecting with industry professionals, the authenticity of job posts, and online resumes), which are better than those of Facebook in the professional context [25].

Gaps and avenues of future research
While prior research has emphasized the advantages of professional networking through PSMs, particularly LinkedIn, there is a research gap regarding the comparative effectiveness of job boards such as Monster and Xing, to name a few, that serve similar purposes. Our review suggests that while LinkedIn has been sufficiently examined in terms of its benefits and use motives, there is scant information on the benefits that job boards offer to their users. Furthermore, there is also a gap in understanding the specific features that draw users to PSMs in relation to different job boards. We also argue that it would be beneficial to understand the implications of PSM use compared to job boards, especially for the HRM professionals for the recruitment and hiring processes. Existing literature presents inconsistent information on the use of PSMs and job boards by professionals in different countries. For instance, companies in Germany use LinkedIn for posting job vacancies, whereas companies in France and Norway barely use the platform for online selection [45]. Further, Pavlíček and Novák [46] also found that companies in three countries, namely Norway, France, and Germany, did not encourage their employees to use LinkedIn. Addressing these gaps will provide employers and jobseekers with a broader view of the digital recruitment arena, including job boards, PSMs, and even SNSs. This will allow stakeholders involved in the process to devise effective strategies to boost the efficient use of these platforms. Thus, we propose the following RQs for further research: RQ1.1 What are consumers' perceived benefits and motives for using PSMs, such as LinkedIn, compared to other job boards, such as Naukri, Monster, Xing, and Glassdoor? RQ1.2. What are the different features that draw users' attention and drive use intentions for each of these platforms? RQ1.3. What are the cross-cultural and cross-industry differences in the way that HRM professionals effectively use PSMs versus job boards at various stages in the recruitment process?

Individual use: drivers and barriers
Various studies have investigated the usability of PSMs and the benefits that individuals may gain from them. Utz [47] suggested that LinkedIn provides its users with higher informational benefits that pertain to knowledge about job vacancies, what companies are looking for, and how to estimate one's growth potential. Also, our review highlighted the differences in individuals' experiences when using PSMs. For example, Al-Badi et al. [48] found that using LinkedIn was difficult for novice users who found it challenging to utilize the site's features. On the other hand, Peterson and Dover [27] suggested that students may use LinkedIn to create, visit, and refine their profiles. LinkedIn facilitates users by providing job opportunities. PSM accounts can encourage students to think about career paths and future jobs [15]. Different factors may drive this use of PSMs for networking. For instance, Lucero-Romero and Arias-Bolzmann [49] employed the theory of planned behavior and found that perceived ease of use and usefulness of PSMs affected job-search behavior among Ecuadorian millennial users.
Furthermore, Claybaugh and Haseman [50] suggested that trust is an important factor that promotes networking on LinkedIn, however making new connections on LinkedIn is not influenced by a person's disposition to trust. This indicates that individual users' characteristics may affect their perception and use of PSMs, such as LinkedIn. For instance, individual traits have also been found to affect an employee's probability of employment [29] and their ability to use PSMs for networking [30]. A recent study also supported this contention, suggesting that individuals' use of PSMs to search for jobs can indicate a lack of self-efficacy [51]. However, the uses and gratifications theory suggests that the components that enable the use of PSMs comprise of group activities, finding friends with ease, follow-ups, professional networking, profile viewing, job affairs, and self-promotion [28,52]. Moreover, students are motivated to use PSMs due to factors such as interpersonal communication, career development [53], seeking opinions from experts, networking, and updating professional accomplishments [54]. Florenthal [53] found that students refrain from PSM adoption due to lack of knowledge about the platform and perceptions that PSMs should be used after graduating. However, there is limited knowledge of how such individual traits and characteristics affect individuals' adoption and post-adoption use of PSMs.

Gaps and avenues for future research
The current study identified potential gaps in the literature that can be addressed to derive further insights into individual-level factors that drive PSM use. For instance, the influence of individuals' career opportunities on PSMs regarding job pursuit (job commitment, turnover intentions, job motivation, and job performance) can be an area for further exploration [36,55,56]. Moreover, few theories, such as the uses and gratifications theory [57] and the theory of planned behavior [58]; have been employed to understand individuals' reasons for PSM use. However, given that PSM use can be described as a specific part of consumer behavior, a plethora of theories, such as the technology acceptance model (TAM [59]); see also [50] and the information systems (IS) continuance model [60], have been used to understand adoption and pre-adoption behavior, such as the formation of initial trust toward PSMs, intention to use, post-adoption satisfaction, and continuance intention. The SLR findings specifically emphasize the need to explore whether PSM features interact with individuals' use intentions and activities. Future studies can also assess individuals who do not use PSMs despite their advantages by employing theories, such as the innovation resistance theory (IRT) [61,62]. IRT argues that there are users who may show resistance to new features introduced by a PSM due to reasons such as being comfortable with using the existing features of PSM. Furthermore, there may be other features that are introduced regularly that users do not want to learn about or use. We argue that future research may benefit from assessing whether this resistance is due to functional barriers (usability) or psychological barriers (image or traditional risk). Furthermore, we urge scholars to study whether personality characteristics, such as dark personality traits, affect individual use of PSMs in terms of gaining and leveraging opportunities afforded by such platforms. Thus, we propose the following broad RQs to advance this field of research: RQ2.1. What are the barriers (functional or psychological), and the effects of said barriers, on PSM use among different users, such as employers, job applicants, and students? RQ2.2. How do individual traits and characteristics determine the behavior (pre-adoption, adoption, and post-adoption) of individuals on PSMs?
RQ2.3. How can seminal consumer behavior theories, such as TAM, IRT, and the IS continuance model, explain the pre-adoption (formation of trust and intention) and post-adoption (continuance and satisfaction) behavior toward PSMs?
RQ2.4. How do personality characteristics influence gaining and leveraging opportunities on PSMs?

PSM affordances: enhancing professional visibility
Prior literature has especially noted the role of PSMs in the professional visibility (also understood as self-presentation) of professionals. For instance, individuals' information (or profiles) on PSMs has been used as a criterion to screen potential candidates by recruiters [24]. Furthermore, PSM recommendations are more influential compared to other forms of professional recommendations because they are verifiable and facilitate self-representation [63]. Self-presentation is defined as an individual's description of their warmth, competence, analytical skills, social skills, and flexibility [64]. In the context of PSMs, LinkedIn allows individuals to showcase personal information, such as educational qualifications, work experience, skills, and hobbies, that is accessed by recruiters and other professionals from their field [63]. Such self-presentation is important because recruiters on LinkedIn draw inferences of the person-job fit based on the criteria presented [65]. The increasing use of SNSs and PSMs has made students and professionals aware of presentation strategies that entice recruiters. Therefore, users, especially aspiring candidates, devise strategies for building their profiles on PSMs in a way that creates a positive impression among observers through the listed hobbies and interests [66]. For instance, Guillory and Hancock [67] conducted a comparative study of different types of resumes (traditional resumes, private LinkedIn profiles, and accessible LinkedIn profiles). Their study found that public resumes on LinkedIn are deceptive when displaying hobbies, although such deception is comparatively smaller than the kind found in traditional offline resumes in terms of the work experiences and responsibilities handled by an individual (or profile holder). Literature has also suggested that employees' occupation affects the presentation of their information on platforms such as LinkedIn, which, in turn, also provides these individuals in different occupations with diverse benefits (e.g. [3,16]). For instance, Kim and Malek [25] found that employees in the hospitality industry were empowered by LinkedIn to build and maintain professional networks. Sales/marketing professionals share more personal information and are more network-savvy as compared to industrial/organizational psychologists or HRM professionals [16].
Another PSM affordance that its users leverage is the strength of network connections. Users frequently search for jobs on professional job boards, and Garg and Telang [68] have suggested that the strength of connections on PSMs can affect candidates' job outcomes (e.g., job leads, interview calls, and offers). Buettner [69] asserted that 150 is the ideal number of ties that can help individuals gain effective benefits from PSMs. Furthermore, networking via LinkedIn facilitates a plethora of benefits for career development contingent on networking ability [70]. According to Sender and Korzynski [71], news of peers' career advancement escalated job-search behavior among employees. Such news may be acquired through their networking ability and activeness in PSM use [71]. Thus, networking can aid users with job searches, business assistance, career sponsorship, information and ideas, political guidance, social support, and work-related guidance [70].

Gaps and avenues for future research
Our review suggests some fundamental gaps that can be addressed in future research. Literature suggests that self-presentation plays a key role in recruitment. It would be beneficial to understand if specific attributes of PSM self-presentation cause bias or discrimination in the recruitment processes, such as the presence of a digitally enhanced or idealized picture on PSM resumes (i.e., an indication of candidates' physical appearance). Exploration of such potential biases may generate insights into the negative aspects of using PSMs in recruitment processes. Although companies have rigorous background-check policies, the authenticity of the information available on PSMs in terms of qualifications, prior experience, or recommendations has been questioned by scholars [20,21]. Future scholars may examine potential measures of ensuring the authentication of such information through digital means, such as artificial-intelligence (AI) integration, or manual means, such as establishing the veracity of the provided information through the use of organizational resources. Scholars may also explore ways in which PSM users may be encouraged to provide authentic information by PSM service providers and prospective employers. Additionally, while significant research on PSM affordances, such as self-presentation opportunities, centers on LinkedIn, we urge future researchers to examine the role of self-presentation in the context of other platforms and job boards that may be described as PSMs. Therefore, we propose the following RQs: RQ3.1. What are the specific attributes of self-presentation that may cause bias or discrimination in the recruitment and selection processes?

RQ3.2. How can the veracity of the information on PSM users' profiles be determined and encouraged?
RQ3.3. What are the dynamics of platform affordances, such as selfpresentation opportunities, that affect the individual use of job boards and PSMs other than LinkedIn?

Organizations' PSM use
Scholars have argued that organizations use PSM profiles to evaluate a prospective employee's person-job fit and person-organization fit, which can also predict recruiters' intentions to recommend employees seeking employment [65]. Silva, Silva, and Martins [72] also report that LinkedIn can complement traditional recruitment and selection by easing an organization's search for talent that fits job roles. Roulin and Levashina [20,21] asserted that there is consistency in the assessments of LinkedIn profiles in terms of applicants' skills, personality traits, and cognitive abilities. Van de Ven et al. [73] have also claimed that PSM profiles help in assessing individuals' personalities, largely influencing the process of shortlisting candidates for interviews.
Recognizing the potential of PSMs, multinational companies have started actively engaging in LinkedIn-based recruitment across the globe. For example, multinational companies in Pakistan initiated hiring through LinkedIn in 2012 [18]. In the Eurozone, multinational companies are massively engaged in recruiting employees through LinkedIn [74]. PSMs have been found to be an influential means for employment in South Africa [19]. Another study reported that graduates of a chemical engineering program found jobs, largely in the petrochemical and mining sectors, through their LinkedIn profiles [5]. However, there are notable variations in the manner that organizations use different PSMs for recruiting. For example, jobs with low skill requirements or generic responsibilities are posted on job boards (such as Monster and CareerBuilder), whereas vacancies involving high-skill jobs and supervisory positions are posted on LinkedIn [75].
Furthermore, literature has also reported contradictory findings regarding the benefits that PSMs may provide to organizations. For example, Aguado [23] suggested that certain features of PSMs (such as professional experience, social capital, and information updates) influence professional development, absenteeism, and productivity. Contrarily, Pavlíček and Novák [46] stated that LinkedIn is not as impactful in practice as stated in theory. Further, the job offers proposed through PSM platforms lack clarity regarding the required skills and qualifications [76]. Scholars have attempted to examine the ways in which organizations may enhance the effective use of PSMs for recruitment purposes. For example, Chala and Fathi [77] proposed a job-recommendation system based on algorithms to find the right match for a job vacancy, whereas Yan et al. [78] developed a machine-learning framework that validates users' skills on LinkedIn to optimize selection processes.

Gaps and avenues of future research
Although PSM use and its role in recruitment are established facts, there are some aspects of this phenomenon that have yet to be investigated. For instance, the extent to which PSMs can help ascertain the person-job fit of potential and recruited employees may be assessed by examining the variables that highlight individual differences, such as attitude, values, self-esteem, and self-efficacy. Such studies could be conducted over a longer period to assess the long-term success of recruitment through PSMs in terms of the employee-employer fit, employee attrition, job-switching behaviors, and contribution to organizational development. Along similar lines, we propose that the current field of investigation may benefit from studying whether PSMs also contribute to higher employee attrition by enabling ease of discovery and capitalization of employment opportunities for career progression at various levels of an employee's career. Moreover, scholars may focus on advancing the design, development, and testing of effective AI-based algorithms to facilitate organizations' search for suitable talent. In relation to the discussion above, we propose the following RQs: RQ4.1. How, if at all, can organizations attain long-term benefits from the use of PSMs for recruitment processes?
RQ4.2. How, if at all, do PSMs affect employee attrition rates and job-switching behavior across the different levels of an organization's hierarchy?

RQ4.3.
To what extent can AI and related technologies, such as machine learning, facilitate organizations' effective leveraging of PSMs and their information?

The effects of socio-demographic factors in PSM use
The reviewed studies have noted that socio-demographic differences among applicants and HRM managers, such as gender and sector or industry, affect their PSM use. For example, Archambault and Grudin [43] found that older employees (aged between 45 and 55 years) more frequently use PSMs for professional networking compared to younger employees. In the Eurozone, the use of LinkedIn for recruitment and networking by HRM professionals has been found to be directly related to the size of the organizations [74]. Then, in terms of gender, men are more likely to give (and receive) recommendations. They include more of their personal and professional interests on PSM profiles than women [16]. Other studies have found that women expressed more emotions than men on PSMs [79], while men were more likely to keep their professional status updated [79]. Scholars have also observed that social norms and corporate culture influence how individuals present information on their LinkedIn profiles [79]. Lastly, Kim et al. [44] found significant sectoral differences in individuals' LinkedIn use-for example, individuals employed in the financial sector tend to use LinkedIn to find jobs, make connections, or consider business opportunities more regularly than those employed in the manufacturing industry.

Gaps and avenues for future research
Based on the SLR findings, we argue that there is potential to further investigate the influence of socio-demographic factors in terms of the outcomes of PSM use by different users. For example, scholars may focus on understanding factors, such as gender, that are related to individuals' frequency of use and the effects that platform affordances (e.g., the number of networks connections) have on opportunities obtained from PSMs for career commencement or advancement. We argue that communication norms specific to an individual's geographic, sectoral, and organizational culture can also interact with (e.g. moderate) the relationship between an individual's PSM use and career development. Moreover, we believe that there is a need to examine whether educational qualifications, work experience, and age differences can influence the different use and outcomes of individuals' engagement with PSMs. Based on these arguments, we propose that future scholars may focus on the following research questions (RQ): RQ5.1. What is the extent to which cross-national, socio-cultural, and organizational communication norms influence individual engagement with and outcomes of PSM use? RQ5.2. What is the degree of the interactive effect, if any, of age-and gender-related differences in individual engagement with and outcomes of PSM use? RQ5.3. How do individual differences, such as educational qualifications and work experience, influence individual engagement with and outcomes of PSM use? Table 1 presents the summary of the themes and the gaps identified in the themes.

Research framework
We have used the SLR findings and the questions suggested for future research to create a framework that can assist further scholarly endeavors (see Fig. 6). The proposed framework is labelled as PSM execution and capitalization. It highlights lesser-investigated antecedents and consequences of PSM use for both potential employees and employers that need to be explored in the future by adopting a grounded perspective to explain the nuances of consumer behavior in the context of PSMs. We propose that employers' readiness, size, HRM policies, and leadership structure can serve as factors that drive their PSM use. From the perspective of employees, potential antecedents include personality traits (e.g., the Big Five and the dark triad), socio-demographic factors (such as age, gender, educational qualification, and the level of income), hierarchical level in the organization, and present career stage. Additionally, our framework proposes that networking ability, continuance intentions, and career development (career initiation, intention to switch, and career progression) may be key outcomes of PSM use for employees. In terms of outcomes for employers, we argue that there is a need to examine the retention rates of employees recruited through PSMs, their organizational fit, and their contribution towards organizational development. Scholars may also examine how PSM-driven recruitment affects organizational image among potential employees-for example, in terms of the perceived fairness and transparency of recruitment processes. We also argue that the strength of association for these factors would be different for diverse PSMs, such as Xing, Monster, and LinkedIn, to name a few, and that scholars would need to conduct cross-platform studies to derive a generalized framework for investigating the effectiveness of PSMs for organizations as well as individual users.
We claim that certain factors may moderate the associations of these proposed antecedents and consequences of PSM use. We argue that peer use of PSM, the perceived ease of PSM use, and correlates of the dark side of social media, such as fear of missing out and social media-induced jealousy, would moderate the antecedents of PSM use. We also propose that sectoral dynamics, cross-cultural (communication norms), and cross-national differences are proposed as potential moderators for the posited associations [80]. Examining these moderating variables can enrich and deepen the current knowledge of the antecedents and consequences of PSM use, which may help managers and policymakers to effectively manage PSM use and increase the efficiency of PSMs in executing HRM policies.
The proposed framework is based on prominent theories of information systems and consumer behavior. We argue that the antecedents of PSM use may be examined using the technology acceptance model (TAM [59]). TAM measures the acceptance of novel technology among users via determinants grounded in cognitive processes and social influence. Seeing that the antecedents proposed in our framework are related to individual cognitive, sociocultural, and behavioral factors, we argue that TAM would be an appropriate theory to conceptualize future frameworks. Next, the identified consequences are grounded in the IS continuance model [81] that determines the factors that affect the long-term use of technology systems and, in this case, PSMs. Furthermore, seminal consumer behavior theories, such as IRT, can allow scholars to understand the barriers preventing certain users from leveraging PSMs. These theories can help scholars develop a fine-grained understanding of individual behaviors associated with PSM uses, such as motives, expectations, and intentions.

Conclusion
HRM processes have transformed remarkably since the conception of PSMs eliciting considerable interest among researchers in the recent past. The present study carried out a systematic review to report the findings of extant research and investigate existing knowledge in this field. A state-of-the-art research profile we developed presents annual publications, international collaborations, geographic scope, and analytical techniques adopted by prior studies. Furthermore, we used content analysis of the reviewed articles that identifies five broad themes related to PSMs' role in HRM processes. We discussed the research profile and themes to arrive at a comprehensive understanding of the current literature. We also identified a number of research gaps that can be addressed by future researchers. Integrating the review recommendations with the findings, a synthesized research framework is presented in Fig. 6, visually representing the measures that could be adopted by future scholars, including the adoption of rigorous methodology and theoretical grounding. Furthermore, our review presents significant implications for scholars as well as practitioners.

Implications for theory
First, although using PSMs for recruitment purposes has become frequent, research on this practice is in a nascent stage. Our review holistically organizes the existing literature on PSMs and HRM processes and delineates current research boundaries in this field. The state-of-the-  art research profile also indicates the collaborations and analytical techniques of the area being studied. This can facilitate scholars' efforts to advance research in the domain of PSM and HRM. Second, mushrooming research in the current domain indicates growing scholarly interest in this field. Identifying major areas of research and research themes outlines the perspectives adopted by prior studies and allows for the identification of distinct gaps in prior perspectives. The review has the potential to motivate researchers to undertake research to address the gaps highlighted in the study.
Third, the recommendations for future research based on the thematic foci of our review may be used by researchers interested in PSM research. Each theme highlights the major areas for research in a systematic manner. Research along these lines will enable managers and policymakers to make efficient use of PSMs in HRM practices in the future.
Lastly, based on the review, we urge scholars to incorporate seminal theories from the specific disciplines of HRM, psychology, and information systems to provide stronger theoretical grounding for research on PSM and HRM. Adoption of the aforementioned theories may allow scholars to develop more nuanced insights into the behavior, expectations, and post-behavior evaluation of individuals who use PSMs, and specifically LinkedIn, for HRM-related purposes.
At the same time, the SLR findings may foster strategies for managers to devise efficient policies for optimizing the use of professional networks.

Implications for practice
The current review contains four implications for practice that can be adopted by practitioners, such as HRM managers. These implications may optimize the effective and efficient use of PSMs in the occupational realm.
First, the adoption of PSMs by employers and potential employees is driven by various reasons, such as easing the processes related to job applications and talent search, meant to optimize the cost-and timeeffectiveness of the processes for both stakeholders. For example, the findings may be used by organizations and HRM managers to identify the means for easing recruitment and other HRM processes in tandem with technological advancements that are currently transforming the business environment. Similarly, individuals (including those employed by an organization) may use PSMs to search for career initiation or progression, and professionals may benefit from better understanding PSMs in order to use them more effectively for individual motives.
Second, due to the increased use of PSMs for recruitment, we suggest that practitioners would benefit from understanding individuals' employment of deceptive self-presentation tactics on these platforms. HR managers may focus on restructuring AI-based algorithms to efficiently analyze and authenticate potential employees' qualifications and skills in relation to organizational requirements. Optimizing such algorithms and their performance would thus be profitable for recruiters and candidates in maximizing the effectiveness of PSM use and stakeholders' engagement with these platforms.
Third, recruitment through PSM platforms results in a larger pool of talent and eliminates the probability of favoritism or personal preferences, something that could be leveraged by organizations to improve their image as fair, unbiased, and transparent recruiters. We suggest that HR managers may use our findings to optimize PSM use to increase the efficiency of identifying potential talent and ensuring the integration of our findings in an organization. Furthermore, managers' increased understanding of PSMs' online modalities, their specific affordances, and the individual uses of these affordances may enable them to optimize the efficiency of PSM-based recruitment.
Lastly, the findings of the current review provide HR managers with insights into the use of technological platforms, such as PSMs, by prospective and current employees. Such managers may consider examining the sectoral utility of PSMs in their fields in terms of specific consequences regarding the impact on organizations, such as the influence on employee attrition, retention, and performance [82]. Moreover, HR professionals may also consider the potential application of PSMs for other processes, such as head-hunting, succession planning, and continuous recruitment.

Limitations and future research directions
Although we have presented an extensive review of pertinent literature, the conclusions are limited because the review is qualitative and does not provide meta-analytic insights, such as effect size. Research on PSMs and their impact on HR processes is in its nascent stage, and the growth of literature on this topic will pave the way for meta-analytic reviews in the future. Despite this limitation, the extensive coverage of N. Ruparel et al. the contents of the reviewed studies in our SLR overshadows any gaps due to the absence of a meta-analytic view and provides valuable inputs to researchers and managers. Next, our review includes peer-reviewed articles and conference proceedings. There is a possibility of including book chapters, dissertations, and other gray literature in future literature reviews on the current topic to broaden the scope of the study and the findings further. Furthermore, although the review procedure followed a robust protocol for studies to be included in this SLR, it is quite possible that we may not have exhaustively considered all published articles due to reasons such as the unavailability of full texts in the database, the limitations of the search terms used, and the inclusion and exclusion criteria. The present review maintained its scope to PSMs, which could limit the generalizability of the findings to broader social media. Future studies may compare the influences of social networks and professional networks on HR processes to devise effective strategies for the use of various technological platforms.
The progression of research on the current topic calls for further research to explore PSM dynamics in HRM. Such research would aid the development of policies and practices for making the PSM-based HRM processes efficient for managers, students, and job applicants. To widen the scope of the implications, we propose the idea of carrying out crosscultural and cross-industry studies. Seeing that cross-cultural research in the field of PSMs is scarce, doing a multi-country study on PSM use and its effect on professional recruitment may have large-scale implications. Moreover, the employment possibilities for recruiters across countries may be beneficially augmented through the arguments presented in this article, which shed light upon building more effective recruitment practices by using PSMs in conjunction with traditional recruitment processes. Moreover, we argue that PSM-oriented research calls for collaborative work and requires that researchers build teams and work in this area in conjunction with industry-based practitioners to generate state-of-the-art and practical insights on the leveraging of technological platforms, such as PSMs.

Declaration of competing interest
No potential conflicts.

Appendix A. Supplementary data
Supplementary data to this article can be found online at https://doi. org/10.1016/j.techsoc.2020.101335.