E-ISSN:2583-1747

Research Article

Digital Employability

Management Journal for Advanced Research

2026 Volume 6 Number 4 August
Publisherwww.singhpublication.com

Understanding Job Search Behaviour on Career-Oriented Social Networking Sites: An Integrative Systematic Literature Review

Malakar A1*, Sharma A2
DOI:10.54741/MJAR/6.4.2026.328

1* Abhijit Malakar, Assistant Professor, Institute of Leadership, Entrepreneurship and Development (iLEAD), Kolkata, West Bengal, India.

2 Archana Sharma, Professor, Indian Institute of Social Welfare and Business Management (IISWBM), Kolkata, West Bengal, India.

Career-Oriented Social Networking Sites (CSNS) have revolutionized job searching process by offering access to professional networks, career information, and job opportunities. As these platforms grow in popularity, research on their impact on job search behaviour has expanded significantly with time. However, much of the existing research are fragmented in different disciplines and focuses primarily on individual factors, limiting a full understanding of how CSNS influence job search behaviour. This study addresses this gap by systematically reviewing the literature and integrating findings into a cohesive conceptual framework.

The review synthesises evidence from more than fifty peer-reviewed studies published in internationally indexed journals. Using a structured and systematic literature review approach, it critically examines the theoretical foundations, research trends, and empirical results related to job search behaviour on CSNS. The findings reveal that job search behaviour is influenced by four interconnected dimensions: technological factors (like perceived usefulness and platform engagement), behavioural factors (such as networking orientation and career motivation), psychological factors (including personal branding and professional identity), and social factors (such as trust, social capital, and digital competencies). The review further shows that education, career stage, generation, and labour market conditions influence these relationships.

By integrating fragmented evidence in research, this review offers a clearer conceptual picture of job search behaviour on CSNS, identifies key gaps in theory and methodology, and suggests future research directions. The findings also provide valuable insights for researchers, employers, educational institutions, policymakers, and CSNS developers aiming to enhance digital employability and improve recruitment practices.

Keywords: career-oriented social networking sites (CSNS), job search behaviour, digital employability, personal branding, professional networking, linkedin

Corresponding Author How to Cite this Article To Browse
Abhijit Malakar, Assistant Professor, Institute of Leadership, Entrepreneurship and Development (iLEAD), Kolkata, West Bengal, India.
Email: 		Malakar A, Sharma A, Understanding Job Search Behaviour on Career-Oriented Social Networking Sites: An Integrative Systematic Literature Review. Manag J Adv Res. 2026;6(4):42-51.
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https://mjar.singhpublication.com/index.php/ojs/article/view/328

Manuscript Received Review Round 1 Review Round 2 Review Round 3 Accepted
2026-07-11 2026-07-26 2026-08-18
Conflict of Interest Funding Ethical Approval Plagiarism X-checker Note
None Nil Yes 3.48

© 2026 by Malakar A, Sharma A and Published by Singh Publication. This is an Open Access article licensed under a Creative Commons Attribution 4.0 International License https://creativecommons.org/licenses/by/4.0/ unported [CC BY 4.0].

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Download PDFBack To Article1. Introduction2. Research Objective3. Research Methodology4. Results and Literature
Review Synthesis5. Theoretical Foundations6. Methodological Trends7. Integrated Conceptual
Framework8. Research Gaps and
Future Research Agenda
(Table 2)9. Practical and Policy
Implications10. Limitations of the
Study11. ConclusionReferences
Malakar A, et al. Understanding Job Search Behaviour

1. Introduction

Digital technology has fundamentally transformed how individual jobseeker discover and pursue jobs. Professional CSNS platforms like LinkedIn, combine networking, information sharing, and recruitment in a single platform. Comparative evidence suggests that traditional job boards remain more widely used than CSNS in overall context, though CSNS have a unique advantage in reaching passive candidates who are open to new opportunities without actively searching for jobs (Nikolaou, 2014). CSNS are a part of the broader spectrum toward e-recruitment, where organizations increasingly use social media and algorithms to attract and evaluate candidates (Frasca & Edwards, 2017; Hosain, 2020; Melanthiou et al., 2015). For job seekers, this changes job searching into a continuous digital self-presentation rather than an episodic activity: usage frequency, more than network size, predicts tangible career benefits on LinkedIn (Davis et al., 2020), and experiments show the platform’s algorithm design influences the flow of job-related information through weak ties (Rajkumar et al., 2022). However, the literature remains fragmented across disciplines that tend to isolate single constructs, often treating factors like technology acceptance, social capital, and personal branding separately instead of integrating them. The outcomes are not always positive—greater LinkedIn use for job searching has been associated with declining job search self-efficacy due to ego depletion and social comparison (Johnson & Leo, 2020), complicating any simple narrative conclusive of unambiguous benefit. This review addresses these gaps by synthesizing direct and indirect evidence across four dimensions, mapping theoretical approaches to CSNS job search behaviour, and proposing a structured agenda for future research.

The review is guided by the following research questions (RQ):

  • RQ1: What technological, social, psychological, behavioural factors influence job search behaviour on CSNS?
  • RQ2: Which theoretical frameworks have been used to explain job search behaviour within CSNS environments?
  • RQ3: What methodological patterns and limitations are evident in the existing literature?

  • RQ4: What research gaps and future prospects emerge from the integrated evidence?

2. Research Objective

This review aims to synthesise interdisciplinary, fragmented, diverse evidence on how CSNS, such as LinkedIn, influence job search behaviour. It integrates direct evidence from CSNS-specific studies with indirect evidence involving related constructs (such as social capital, career adaptability, and technology acceptance) into a unified four-dimensional framework that covers technological, psychological, behavioural, and social factors. The review’s specific goals include mapping the influencing factors, analyzing theoretical frameworks (TAM, UTAUT, TPB, Social Capital, Signalling, and Career Construction Theory), examining methodological patterns to assess an integrative conceptual framework, and identifying research gaps to guide future research on digital job search behaviour and employability.

3. Research Methodology

3.1 Review Design

This review adopts an integrative systematic literature review approach, guided by the PRISMA 2020 reporting principles. It combines direct evidence (CSNS/LinkedIn/social-media job search or recruitment) with supporting/indirect evidence (theoretically relevant constructs such as social capital, career adaptability, personal branding, and technology acceptance).

This review synthesises evidence from 55 peer-reviewed studies, retrieved through structured, academic search into how CSNS shape job search behaviour. Included studies are classified as direct evidence (CSNS/LinkedIn/social-media job search and recruitment; n = 24) or supporting evidence (theoretically relevant constructs such as social capital, career adaptability, and technology acceptance; n = 31). Findings are organised around four dimensions — technological, behavioural, psychological, and social factors — and mapped onto seven theoretical frameworks [The Technology Acceptance Model (TAM), UTAUT, Theory of Planned Behaviour (TPB), Social Capital Theory (SCT), Signalling Theory, Social Cognitive/Career Theory, and the Career Construction Theory].


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3.2 Inclusion and Exclusion Criteria (Table 1)

Selective CriterionInclusionExclusion
Publication typePeer-reviewed journal articles; peer-reviewed conference proceedingsBlogs, news, commercial sites, Wikipedia, unpublished student work, Non peer-reviewed opinion pieces
LanguageEnglishNon-English content with no available English translation
Topical relevanceCSNS/LinkedIn/social-media job search or recruitment (direct); social capital, career adaptability, TAM/UTAUT, personal branding (indirect)No conceptual link to job search, recruitment, employability, or professional networking
Timeframe≈2009 onward; seminal earlier works retained for theory (Davis, 1989; Granovetter, 1973)Outdated studies superseded by later replications with no remaining theoretical value
Journal qualityScopus/Web-of-Science-indexed outlets; recognised HRM, IS, vocational-behaviour and psychology journalsJournals with no discernible peer review or indexing
Evidentiary sufficiencySufficient method/theory detail for synthesisAbstract-only or insufficiently reported records

3.3 Literature Review and Study Selection

The 361 entries were scanned manually in Google scholar and also by using the systematic review software Rayyan. Each entry consisted of meta-data (e.g. title, authors, journal) and an abstract. The selection process is shown as a PRISMA flowchart in Fig. 1.

mjar_328_01.PNG
Figure 1: The Selection process, PRISMA flowchart

The Inclusion criteria that are needed to fulfil for an article to be included and eligible are as follows:

  • the research was original (empirical), peer-reviewed, and published in English.
  • the population studied were from diversified geographic segment but primarily the jobseeker is been considered in the systematic literature review
  • regular employment was investigated on the review
  • employees considered here are in regular employment and work alongside colleagues without disabilities, though they may receive various types of support.
  • the employment opportunities had the potential to be long-lasting. (e.g. not seasonal jobs or temporary jobs in nature)

The exclusion criteria, where meeting any one was sufficient to exclude an article, were that


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  • the studied groups included other diagnoses such as intellectual disability (ID) and other conditions (e.g., autism) without co-occurring ID.
  • other groups (e.g., family members or staff) were the ones employed.
  • the studies focused on interventions.

During the initial selection phase, decisions were made using Rayyan based on titles and abstracts. This step (see Fig. 1) led to the exclusion of articles for several reasons: duplicates (n = 76), irrelevance (n = 195, such as medical studies on working memory that appeared due to search terms like “keeping work memory”), non-empirical content (n = 16, including book reviews, debates, or editorials), wrong population focus (n = 19, e.g., studies on autism without co-occurring intellectual disability or cases where parents were the employed individuals), and lack of focus on direct employment (n = 31, such as mentions of work as part of daily life without direct study).

After this, 24 articles supporting direct CSNS or job-search evidence were downloaded in full for further review. Beyond the initial inclusion and exclusion criteria (Fig. 1), additional exclusions were made for articles not addressing employment sustainability. The total articles reviewed in full text numbered 55 (see Fig. 1). Some seminal foundational theoretical articles were also retained in this study, including the works by Davis (1989) and Granovetter (1973).

3.4 Data Extraction and Synthesis

For each study, authorship, year, country, journal, sample/method, theory, variables, and findings were extracted where reported. Data were synthesised thematically around the four dimensions that emerged inductively from convergent patterns across the evidence, consistent with an integrative rather than purely descriptive review.

4. Results and Literature Review Synthesis

4.1 Descriptive Characteristics

The 55 studies span HRM, vocational/organisational psychology, information systems, communication, sociology, and labour economics, concentrated in the 2016–2025 window.

Designs are dominated by cross-sectional surveys and SEM, with a smaller set of longitudinal panels (Guan et al., 2013; Haenggli et al., 2021), field/natural experiments (Rajkumar et al., 2022), and qualitative studies (Jacobson, 2020; Priyadarshini & Premchandran, 2017). Samples range from students to working professionals and executives (Chen & Cheng, 2021).

4.2 Technological Factors

Perceived usefulness is a more robust predictor of e-recruitment/CSNS adoption than ease of use across Iranian (Kashi & Zheng, 2013) and Indian samples (Sathyanarayana et al., 2024; Kaur et al., 2024). The Media richness and the source credibility enhance organizational attraction (Frasca & Edwards, 2017), while marketing recruitment as merely 'trendy' can backfire (Esch et al., 2018). Candidates perceive hiring driven by algorithms as less fair in procedure compared to human-led processes (Acikgoz et al., 2020; Lavanchy et al., 2023), and AI support at later selection stages reduces perceived opportunity to perform (Köchling et al., 2022); algorithmic bias from limited training data is a recurring concern (Chen, 2023). Limited experimental evidence indicates that LinkedIn's own recommendation algorithm causally increases job applications via weak-tie exposure (Rajkumar et al., 2022).

4.3 Behavioural Factors

Factors influencing CSNS use differ between active and passive job seekers: while information provision drives both groups, but trendiness matters more for active seekers whereas image plays a bigger role for passive seekers (Subbarao et al., 2022). Engagement frequency, not network size, predicts career benefits (Davis et al., 2020) and interview invitations (Mowbray & Hall, 2020). Generation Z prefers online/social-media job search over traditional channels (Karácsony et al., 2020); students remain comparatively passive users whose behaviour follows the Theory of Planned Behaviour (Carmack & Heiss, 2018). Cross-platform search is an emerging construct shaped by platform reputation and involvement (Meng et al., 2025).

4.4 Psychological Factors

Personal branding activity is linked to increased visibility and career advancement (Kanasan et al., 2024; Rahman et al., 2025; Vițelar, 2019), and measurable executive labour-market performance (Chen & Cheng, 2021).


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However, intensive use of LinkedIn for job searching has been associated with decreased job search self-efficacy due to ego depletion and social comparison (Johnson & Leo, 2020). Career adaptability and self-perceived employability consistently act as mediators between competencies and self-efficacy (Gerçek, 2023; Guan et al., 2013; Matijaš et al., 2021), with job search self-efficacy best explained by the Social Cognitive or Career Theory (Pirsoul et al., 2023).

4.5 Social Factors

Weak-tie theory (Granovetter, 1973) finds strong platform-experimental support, with the weak ties increasing on the job mobility non-linearly (Rajkumar et al., 2022). Yet a single strong tie can outweigh many weak ties at the margin (Gee et al., 2017), and strong-tie communication better predicts post-job-loss re-employment (Burke & Kraut, 2013) — a pattern echoed among the older workers (International Journal of Sociology and Social Policy, 2019). Chinese data show direct-effects methodology overstates weak-tie benefits relative to more robust social-capital methodology (Obukhova & Kleinbaum, 2017). Networking behaviour itself predicts perceived employability (Batistič & Tymon, 2017) and career outcomes, with gender differences in effectiveness (Forret & Dougherty, 2004). Digital competencies and inequality moderate all of the above (Karaoglu et al., 2021).

5. Theoretical Foundations

Seven theoretical traditions recur across the evidence base. The Technology Acceptance Model (TAM) and its TAM2 extension (Davis, 1989; Venkatesh & Davis, 2000) explain CSNS/e-recruitment adoption driven by usefulness and ease of use., the former consistently dominant. UTAUT (Venkatesh et al., 2003) adds social-influence processes but was designed for organisational rather than voluntary, identity-laden contexts. The Theory of Planned Behaviour (Ajzen, 1991) directly underlies LinkedIn-intention research (Carmack & Heiss, 2018) and offers an under-used bridge to self-efficacy research. Social Capital Theory, rooted in Granovetter's (1973) weak-ties thesis, dominates the social-factors literature but requires contextual qualification given genuine weak-tie/strong-tie contradictions (Gee et al., 2017; Burke & Kraut, 2013; Obukhova & Kleinbaum, 2017).

Signalling Theory (Spence, 1973) helps explain why profile and platform signals matter to recruiters, and appears alongside TAM in e-recruitment research (Kashi & Zheng, 2013). Social Cognitive and Social Cognitive Career Theory (Bandura, 1986) underpins the job search self-efficacy research (Pirsoul et al., 2023; Gerçek, 2023). Career Construction Theory (Savickas, 2005) anchors adaptability research across diverse populations in Chinese graduates (Guan et al., 2013), Togolese job seekers (Atitsogbe et al., 2019), and Turkish vocational students (Gerçek, 2023) offers a natural bridge between psychological and behavioural factors.

Cross-sectional, self-report survey designs analysed via SEM/PLS-SEM dominate, raising common-method-bias concerns. Longitudinal panel studies (Guan et al., 2013; Haenggli et al., 2021) and large-scale field experiments (Rajkumar et al., 2022) remain comparatively rare but generate the field's robust causal evidence. Research predominantly relies on student and early-career convenience samples, with a geographic focus on Europe, East/Southeast Asia, and increasingly South Asia, limiting the generalizability of findings. Regions such as Africa, Latin America, and the Middle East are largely underrepresented except for a few isolated studies (Atitsogbe et al., 2019). Qualitative and mixed-methods designs (Jacobson, 2020; Meng et al., 2025; Priyadarshini & Premchandran, 2017) remain a minority but add mechanism-level insight.

7. Integrated Conceptual Framework

Synthesising the evidence, this review presents a layered model where technological factors (perceived usefulness, algorithmic exposure) influence platform engagement intensity; psychological factors (self-efficacy, adaptability, branding investment) affect the quality and confidence of self-presentation; social structures (weak/strong ties) determine the reach of that self-presentation; and employer-side signalling processes interpret it. Behavioural factors (networking intensity, job search activity) are the observable output connecting engagement to job search outcomes (leads, interviews, offers), ultimately impacting digital ultimately impacting digital employability.


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This process is moderated by variables like education, career stage, generation, and labour-market conditions. The model is grounded in the evidence cited in Section 4, revealing real tensions, particularly the weak-tie versus strong-tie paradox—rather than presenting a false consensus.

8. Research Gaps and Future Research Agenda (Table 2)

Twelve recurring gaps have been identified and are translated below into specific research questions, theoretical frameworks, and methodological approaches as depicted in the following Table 2.

Table 2. Future Research Agenda for CSNS and Job Search Behaviour

Research GapProposed Research QuestionRecommended TheorySuggested Methodology
Fragmented single-construct modelsHow do technological, behavioural, psychological and social factors jointly predict CSNS job search behaviour?Integrated TAM–Social Capital–Career Construction frameworkCross-sectional SEM, then longitudinal replication
Overdependence on LinkedInHow does job search behaviour differ across CSNS platforms?Uses and Gratifications TheoryComparative multi-platform survey
Scarce longitudinal/
experimental designs		Does sustained CSNS engagement causally improve job search self-efficacy over time?Self-regulation theoryPanel study; field experiment
Algorithmic transparency and fairnessHow does perceived algorithmic transparency affect trust and search persistence?Organisational justice theoryVignette experiment
Limited non-Western evidenceHow do labour-market and cultural context moderate CSNS effectiveness?Institutional/
cross-cultural theory		Multi-country comparative survey
Digital inequalityHow does CSNS-specific digital literacy mediate access to opportunity across SES groups?Digital divide theoryStratified survey with skills assessment
Psychological costs of useWhen does CSNS job searching undermine job search self-efficacy?Social-cognitive/self-regulation theoryExperience-sampling / diary study
Personal branding as causal mechanismDoes branding training causally improve employability outcomes?Symbolic interactionismRandomised controlled training intervention

Weak-tie/strong-tie contingenciesWhen do weak versus strong ties dominate CSNS job search success?Strength-of-ties theoryNetwork-analytic study with platform data
Gig-economy and platform-mediated careersHow do freelancers use CSNS differently from traditional job seekers?Protean career theoryComparative qualitative/quantitative study
Generational/career-stage moderationHow does CSNS job search effectiveness vary across career stages?Career construction theoryMulti-cohort comparative survey
Employer-side and bidirectional dynamicsHow do recruiter behaviour and algorithmic curation jointly shape job seekers' behaviour?Signalling theoryDyadic employer–applicant study

9. Practical and Policy Implications

  • Researchers: adopt integrative, multi-theory designs and prioritise longitudinal/platform-data methods over single-wave surveys.
  • HR managers/recruiters: combine profile-based screening with structured, validated assessment to address documented concerns around algorithmic-fairness (Acikgoz et al., 2020; Kochling et al., 2022; Lavanchy et al., 2023); and be transparent about the use of AI in hiring processes.
  • CSNS developers: focus on creating demonstrably useful and explainable matching algorithms rather than just simplifying interfaces, as algorithmic design’s has a proven causal impact on outcomes (Kashi & Zheng, 2013; Rajkumar et al., 2022).
  • Universities/career services: prioritize resources that enhance career adaptability and self-efficacy, not just platform usage skills, through structured training programs (Gerçek, 2023; Guan et al., 2013; Leo et al., 2024).
  • Job seekers: prioritise active engagement over passive profile maintenance, while managing the documented psychological cost of intensive, comparison-driven use (Johnson & Leo, 2020).
  • Policymakers: address digital-inequality risk in CSNS-mediated labour markets (Karaoglu et al., 2021) and monitor algorithmic hiring tools for discriminatory effects (Chen, 2023).

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10. Limitations of the Study

This review is evidence base, though exceeding 50 studies, remains concentrated in a few countries and disciplines, limiting it’s generalisability. Here the most included studies rely specifically on the cross-sectional, self-report survey designs, restricting on causal inference, while longitudinal and experimental evidence remains scarce. Only English-language, peer-reviewed sources were included, potentially excluding relevant non-English or grey literature. Finally, thematic synthesis, while integrative, involves interpretive judgement that could introduce reviewer bias despite structured extraction procedures.

11. Conclusion

This integrative systematic review consolidates fragmented and cross-disciplinary literature into four-dimensional areas of how technological, behavioural, psychological, and social factors jointly shape job search behaviour on CSNS, mapped onto seven theoretical frameworks. Use of CSNS is not always uniformly beneficial or uniformly efficient; while engagement and strategic self-presentation often increase access to opportunities, their impact depends on factors like tie strength, platform usage intensity, algorithm design, and psychological resources, and can undermine rather than support job search self-efficacy under some conditions. No single theory fully explains CSNS job search behaviour alone, motivating the integrated framework proposed here. The field remains dominated by cross-sectional, single-platform designs concentrated in few countries, leaving longitudinal, experimental, and cross-cultural evidence disproportionately valuable and scarce. Addressing the identified gaps, especially the algorithmic transparency, longitudinal causal research design, and non-Western contexts will be crucial for advancing both theory and practice in this rapidly evolving domain.

Master Evidence / Citation Table

55 studies forming the evidence base (Category A/Direct, n = 24; Category B/Indirect, n = 31). Category “A/Direct” is represented as “A” and Category “B/Indirect” is represented as “B” only and both the categories (“A” and “B”) are independently verified in this session (Rajkumar et al., 2022; Johnson & Leo, 2020);

Master Evidence / Citation Table is available in the Supplementary File.

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