Open access peer-reviewed chapter

Social Media and Technology Trends in HRM: Cases in Recruitment and Talent Management

By Debolina Dutta

Submitted: February 2nd 2018Reviewed: June 6th 2018Published: October 31st 2018

DOI: 10.5772/intechopen.79342

Downloaded: 955

Abstract

Human resource management practices have evolved over the years to align with shifts in technology, economy, globalization, talent diversity and business strategy, with practices intended to solve business problems. Increased globalization, competition and the pressure for speed and innovation mandates differentiated HR practices which enable attracting, motivating, and retaining a talented workforce, a factor critical to business success. While employees have embraced digital and social media for increased communication and collaboration, opportunities of leveraging the rich information available on social media platforms for HR practices have emerged. The of use of human capital analytics is becoming a powerful tool available to the HR fraternity, as data driven insights have demonstrated impressive business results. The latest of these trends is the leveraging of social media combined with technology solutions and embracing digitization of various HR processes. The present research presents three case studies that illustrate how technology solutions and data insights have transformed talent acquisition, learning and talent management practices within HR functions in India. The cases demonstrate the how the technological advances and increase usage of social media is likely to have significant implications for talent management processes of the firms in the near future.

Keywords

  • talent management
  • social media
  • HR analytics
  • talent development
  • predictive analytics
  • case study

1. Introduction

The rapid pace of technological changes and globalization are simultaneously acting on each other and compounding their effect on the pace of change. The net result has been a pace of change resembling a spiraling vortex that has increasingly challenged individuals’ and organizations’ ability to adapt to the same. With technological changes leapfrogging ahead, the access to Internet also changed the way information was produced, received and consumed over the world. The biggest transformation in media communication was from the unidirectional consumption mode of communication changed to multi-creator and multi-user bi-directional communication. Conventional print media continued to see steady decline with sales reduction from2.1 billion copies in 2000 to less than 1.4 billion copies in 2010 [1]. With commoditization of information and multiple media platforms through which consumers and other stakeholders accessed information, organizations were forced to re-think the way conventional communication could be effected with their relevant stakeholders. While multiple examples exist within the realm of co-creation for product development or marketing, human resource functions still struggled to come to terms with the changing ways communicating with and engaging their current and potential workforce.

Human resource management practices have evolved over the years to align with shifts in technology, economy, globalization, talent diversity and business strategy [2], with practices intended to solve business problems [3]. The resource-based theory has been the guiding paradigm influencing strategic HRM research [4]. Increased globalization, competition and the pressure for speed and innovation mandates differentiated HR practices which enable attracting, motivating, and retaining a talented workforce, a factor critical to business success. This becomes critical, since sustainable competitive advantage obtained from people and people practices, as argued by resource-based theory, have been weakened by globalization and environmental changes [5]. While employees have embraced digital and social media for increased communication and collaboration, opportunities of leveraging the rich information available on social media and technology platforms for HR practices have emerged which indicate a potential to change the dynamic capabilities of organizations [6]. For HR functions, leveraging of technology solutions and embracing digitization of various HR processes therefore becomes critical.

The “war for talent” [7] continues, with organizations trying to identify high quality individuals who not only meet the functional and technical needs of the jobs, but also demonstrate a fit with the organizations values. Simultaneously, research on employee recruitment continues with multiple studies addressing recruitment objective, strategies, intervening job applicant variables and recruitment activities and processes [8]. However, a limitation of some of the recent recruitment method research has been the emphasis on post-hire outcome (e.g. performance, turnover) rather than pre-hire outcomes (which approaches generate better applicants)—something that is of critical interest to organizations seeking high quality talent. In this context, it becomes extremely crucial for HR practices to evolve more broad based recruiting methods to discover skilled applicants required to support organizational growth. Furthermore, targeted recruitment (whom to recruit, where to recruit, etc.) has also attracted little attention from researchers, and the need for research on targeted recruitment [9] and the use of data science and intelligence tools within human resources has been emphasized [10].

In the present chapter, the case studies of three firms of India are discussed which are aiding and enabling talent management. Two of the cases demonstrate how people analytics utilizing predictive analysis measures is transforming talent acquisition and workforce planning in the emerging markets of the world and the resulting impact on HR functions within organizations. The third case discusses new approaches in leveraging technology for building efficiencies in the recruitment process. While there has been considerable research on e-recruitment and its drivers, there is need for research documenting the latest trends in the use of technology, artificial intelligence and machine learning for supporting external recruitment. These cases demonstrate the state-of-the-art technology available to recruiters to enhance the operational efficiency, agility, and quality of applicant hired in their recruitment process, and illustrate the way social media and technology is being used to hire both efficiently, in terms of reduction in resources consumed, and effectively, in terms of finding a fit between the person and the organization. The new ways of communicating with talent, quantifying and systematizing through technology, the complex human decision making process related to employee-organization fit, are demonstrated. The implications that emerge from these trends in talent acquisition is that technology is likely to revolutionize the HR organization by possibly creating redundancies within the applicant attraction process of recruitment or at an extreme view, disintermediate the talent acquisition function as a whole.

2. E-recruitment and talent acquisition using social media

Electronic recruitment processes which involve hiring of candidates over the internet, talent management techniques for identification, tracking, evaluation, and selection of personnel increasingly are being adopted widely for acquisition of human resources in organizations today. These practices have been a matched by an exponential increase of social networking sites for recruitment purposes, which may have been prompted by cost efficiencies or talent scarcity [11]. The advantages of e-recruitment over traditional channels have been well documented, such as economy of time and money, larger candidate pool, and ease of use for both the recruiter and the candidate. E-recruitment led to improvement in time to hire and quantity of hire, by improving outreach to potential candidates, and scanning information across a wide range of sources, to lead to a better fit with the organization.

Online recruitment has the advantage of reciprocal communication, where the candidate and the recruiter may communicate with each other at minimal cost. While the advantages of the e-recruitment processes are significant, there are also several challenges that online hiring brings. The launch and maintenance costs of online hiring systems are high, and it requires hiring of personnel competent in dealing with the technology. Secondly, the number of candidates obtained through job boards is often extremely large, making optimal scanning difficult. Thirdly, there are also concerns of breach of confidential data and security, as platforms might store resumes for later references.

Various organizations may adopt differentiated strategies and tactics while embracing social media and e-recruitment. These are broadly classified under the pillars of building employer brand, building relationships (for current or future requirement), active recruitment for vacancies or new job roles, and finally cost optimization [12]. Lastly, we assess the influence of these emerging trends on the pillars defining strategies and tactics adopted for social media and e-recruitment.

3. Method

Case study research focuses on the latest practices in a field, to better understand processes not well explored and to generate theories out of them. The present research incorporates three case studies on use of social media, E-recruitment and big data analytics for facilitating talent acquisition. All three organizations selected are involved in providing recruitment services to firms—using online resources. Each study demonstrates a different approach and demonstrates the latest trends in the e-recruitment domain in the emerging markets of the world.

3.1. Cases

  • Case 1: This case focuses on the people analytics solutions marketed by the firm Belong.co, with reference to recruitment, the unique features of these offerings and their implications.

  • Case 2: This case focuses on asynchronous recruitment solution offered by Talview which brings in efficiencies into the recruitment process through better pipeline management, keeping actively engaged applicants refreshed and enable better fit with the organization.

  • Case 3: This case deals with a job portaliimjobs.com, positioned to attract high caliber applicants. The organization then used the large data pool of applicants to build intelligence around talent availability. The intelligence made available to HR enables better talent management.

A total of 22 semi-structured interviews were conducted in all, with 7 interviews each spanning over 2 hours conducted at firms 1 and 2. In firm 3, 8 semi-structured interviews were conducted, each spanning about 1.5–2 hours. The interviewees selected were either key position holders in the firms and subject matter experts on the product offering and value demonstrated or were members of the founding team of these firms. The author also interviewed seven members of the user community (HR and Talent acquisition heads), who had subscribed to the offering of these firms, three who were subscribing to Belong and two each who were using Talview andiimjobs.comsolution offerings. The purpose of these interviews was to understand both the acceptance of the new solutions being offered and also their perceived value. These interviews spanned between 45 minutes to 1 hour each.

3.1.1. Case 1: Belong.Co

Belong.co [13] is a Bangalore based startup, which provides hiring solutions using predictive analytics and personalized engagement, which enable firms to identify, meaningfully engage, and recruit top, relevant talent in optimum time. The typical V-funnel of recruitment—represented by large number of applicants sourced through conventional channels, reduced number of candidates deemed fit for the role, and a much smaller number clearing the interview process and final candidate being hired—was found to be tedious and time consuming, with a lot of effort invested to screen, interview and filter out potential fits. Additionally, most applicants were active job seekers, which constituted only 20% of the available talent pool. Discussion with recruiters of multiple organizations reinforced the painstaking process of candidate filtration undertaken by each one.

The organizations unique value proposition was to identify, connect with, and engage the passive talent pool which resulted in hires that were more engaged. Such candidates, selected through individualized consideration and matching, felt that they truly belonged to the organization. Calling this approach “Outbound hiring”, there was also the realization that the best talent was not always available on popular job boards. The founders created a product offering based on machine learning and artificial intelligence, which allowed organizations to “Google Search” not just for skill fit, but also for ideology fit was born. The outbound hiring process is presented in Figure 1.

Figure 1.

Flipping the recruitment pyramid by Belong.co. Source: https://belong.co/outbound-hiring/ last accessed on 07-01-2018.

In the Belong system, artificial intelligence and predictive algorithms are used to scan publically available information on talent on the internet, to map and suggest profile fits. The data scanned include information that potential candidates put out on a blog, updates on Linkedin or other professional networking profiles, tweets sent, updates on social networking sites like Quora [14] or Kaggle [15] (a domain where data scientists hang out), contribution to sites like Github [16] or Stack overflow [17], personal websites, or any other public reference to the candidates. The analytics thus helped generate data that was far more comprehensive than a resume, and helped the recruiter identify which pools of talents were to be engaged. Again, based on information such as a potential candidate’s prior employment tenure, or the average duration in the current organization before they would be considered for a role change/promotion, the tool was able to predict their likelihood of responding to an interest eliciting mail. The search results were therefore always customized for a particular job positing or organization, unlike a key-word search for skills, which would throw up the same set of candidate names, irrespective of the organization that was searching for it (Figure 2).

Figure 2.

Prospective resume shortlist, probability of candidate interest and potential fit indication. Source: Company provided information.

The predictive analytics at Belong.co ensured that, unlike the normal talent funnel, the search identified 8–10 potential passive candidates. The recruiter would then shortlist out of these limited set of suggested candidates, thereby freeing up recruiter time and improving their effectiveness. Next, a recruitment bot would send out personalized relevant emails on behalf of the recruiter which would elicit the interest of the passive talent for initiate a conversation with the recruiter and enhance engagement. The customers of Belong.co reported that candidate feedback on the personalized mail reflect the delight in the degree of personal attention and detail demonstrated in the approach. At the same time, recruiters, who saw a significant reduction in their manual effort in sourcing profiles (estimated to be 40% to their time), were delighted in the quality of candidates brought for interviewing, the higher conversion ratio, and the reduction in time to fulfill recruitment mandates.

The effectiveness of outbound hiring were demonstrated in multiple customer success stories [18], which documented instances of 50% reduction in sourcing time and significant reduction in overall recruitment time, better candidate engagement and better fit in terms of skills, interests and motivations. The value demonstrated by the offering was measured by different industries in terms of fit of hire, cost per hire and quicker demand fulfillment.

3.1.2. Case 2: Talview

Most organizations receive a large volume of unsolicited applicants, most of whom do not find matching opportunities within the organization. The applications of these potential recruits invariably lie unutilized and unscreened within the applicant tracking system or mailboxes of recruiters within organizations. Additionally, each job application tends to receive a large volume of potentially suitable candidates, as deemed by their resume, experience and skill sets. However, most recruiters experience a selection ratio between resumes received and final selection of candidates which could range from 20:1 to 1000:1. A lot of time and effort of recruiters and managers are spent in filtering through the potential set of candidates. Energy is dissipated in trying to arrange mutually convenient schedules for a face to face interview between candidate and interviewer, which could be arranged through technology enabling platforms such as Skype/Facetime, etc. In case physical meeting is to be arranged, travel delays add to the inefficiencies built into the selection process, which could also involve efficiency loss due to scheduling time/effort, synchronizing interview times, travel time and wait for interviews etc.

To solve both these issues and address efficient use of resumes and efficient use of applicant and hiring manager time, a Bangalore based technology firm Talview [19] introduced an asynchronous cloud based mobile enabled video interviewing platform. Candidates deemed as potential fit for current/future role are sent a link through the platform. Potential applicants could log onto the platform and pre-defined set of questions sequentially from any location and at any time. Once completed, the recorded interviews were then screened by the recruiter and hiring manager at their convenience. The platform also enabled psychometric, aptitude testing and coding testing for potential applicants. Additionally, the gamification feature of assessments made the process engaging for applicants and helped in enhancing employer brand (Figure 3).

Figure 3.

Example of competency based asynchronous video interview using Talview platform.

Organizations using this platform were able to effectively build and manage a passive talent pipeline, efficiently filter through a larger number of applicants and quickly check for fit parameters. With the recorded interviews saved on the cloud, the convenience of candidates and recruiters was aided, ensuring better candidate experience. With over a million applicants assessed through the platform, Talview has an impressive clientele of a large number of fortune 500 companies over 102 countries. The benefits of the platform range from 40% reduction in poor performance of new hires, 50% reduction in cycle time for recruitment and a 70% reduction in campus recruitment costs.

3.1.3. Case 3:iimjobs.com

iimjobs.com[20] had started as a job portal with a differentiated proposition. The founder Tarun Matta possessed qualification of engineering and management from some of the top institutes of India. Like a lot of his peers from these institutes, he found access to challenging and aspirational jobs difficult. Recruiters typically received a large volume of resumes and found it challenging to sift through and identify good talent. Additionally, candidates were more successful in obtaining desired jobs through referral process. To disintermediate this asymmetry between high caliber talent availability seeking jobs and recruiters looking for high caliber talent,iimjobs.comwas born. The name alluded to talent pedigreed from IIMs (Indian Institutes of Management), which were considered the most premier management institutes within India. While a large segment of the applicants on this portal were from these institutes, applicants from other prestigious institutes also started applying on this portal. It additionally allowed applicants to only apply for jobs posted on the portal, and maintained the confidentiality of applicants who applied on it. Resumes of applicants were not openly visible to other recruiters for many years. Wheniimjobs.comfinally opened resume search access, it was restricted only to corporate accounts and not made available to recruitment consultants and search firms. This helped maintain applicant confidentiality, which was a key requirement of high caliber talent.

By 2017,iimjobs.comhad built a repository of over a million registered users as job seekers and over 70,000 recruiters using the platform to interact and find suitable fits. While working on database and listings,iimjobs.comgot inputs from the clients about the challenges faced in taking talent decisions and discovered opportunities in leveraging this database to yield important job market trends. For instance, when a seeker registered and applied for a job, the system captured everything about their educational background, CVs, salaries (current and expected), etc. This provided an opportunity to synthesize this information and provide recruiters a clear understanding of the trends in the talent landscape for a particular segment or skillset.

A comprehensive visibility of the talent landscape continued to present a challenge for HR professionals, who struggled to identify key talent. Most HR professionals based their understanding of talent trends from some of peers in the industry to get a qualitative sense of the trends in their respective firms. However, organizations desiring quantitative data for decision making desired exact data. This was usually obtained through job market analyses conducted by consulting firms. Obtaining meaningful data tended to be painstaking, costly and a voluminous task for most organizations. Obtaining this kind of data meant mapping an entire industry or associated industries where such talent could be hired from. Additionally, the problem with these kinds of surveys was that the reports they generated were static, while, on the other hand, the actual workforce and talent trends changed dynamically. Finally, most organizations resorted to compensation benchmarking exercises, where specific job families were pegged against market compensation rates to understand and correct internal pay equity. These, compensation benchmarking reports tend to be highly expensive, putting the updated reports out of the reach of many small and mid-sized firms and start-ups.

While planning talent requirements for current/future state of business, the internal factors of talent availability, training capability and reward philosophy were also key factor influencing HR leaders decisions to build or buy talent. While demand/supply of labor presented the external market information, the planning and administering of compensation and reward systems would be influenced by the talent strategy adopted. For instance, inducting new skills/capabilities into the organization would influence the organizations’ definition of key labor competitors, pay positioning with respect to the market, choice and/or expansion of the market basket used for compensation benchmarking, which in turn could dilute the benchmark relevance etc. The HR function was expected to provide informed decisions around costs of hiring/re-locating talent/upskilling talent/attrition trends and costs of attrition for future state talent needs of the organization. Absence of clear and dynamic data made these decisions challenging.

Detailing the offering being made available byiibjobs.com, Matta said.

‘Recruiters and hiring managers are often pushed to fill vacancies, that too with unrealistic specifications and targets. So this tool enables them to know and talk about expectation of talent availability, in a more meaningful manner. They can now say that by relaxing a few parameters we can increase our supply side. It helps them to understand the industry trends and calibrate expectations accordingly’.

The Calculus platform was created by theiimjobs.comteam from the data available within the within the job portal The aim was to provide recruiters an interface where they could examine the trends reflected in the existing database ofiimjobs.com, to answer their own specific requirements about the talent horizon. The interface of the Calculus was almost similar to that of database search so that recruiters were able to use it easily (Figure 4). All the recruiter needed to do was to define a query—using keywords, position looked for, or/short form/long (bullion operator), company, industry, and other search parameters, such as target, college (Tier 1/2/3), type of course (e.g., full time/part time), batch (e.g., 2010–2014), and notice period (e.g., 3 months).

Figure 4.

Talent demographics of salary, gender and availability on Calculus. Source: Company data.

The automation tool generated a sample set, based on the specifications, and studied the trends reflected in the sample in terms of the query generated. To make the sample representative, the tool removed all the outliers (extremes). Also, to keep the sample set recent, the search results were limited to profiles updated in the last 6 months, thereby revealing the dynamic trends and shifts within technologies, skills and domains.

The Calculus tool let HR examine five dimensions related to hiring (Figure 5):

  1. Compensation: This data point allowed talent management functions to view the current and expected salary trends and understand the range, the mean and median salary; The compensation analytics also indicated gender, age, or experience-wise distributions of salary

  2. Geographical location: This functionality used to determine the talent density in a particular location. It provided visibility to how many professionals of a certain profile are present in a geographical area). This enabled the manager to decide where to open a new branch. It also shows how salaries change as per locations, helping in zone-wise compensation management

  3. Gender diversity: This reflects the gender-related distribution of talent, and its interaction with other factors such as experience, salary, location, notice period, etc.

  4. Average tenure: For most recruiters, tenure of employment was a surrogate measure of expected stability and future attrition. Hence trends information in along skills/functions/age groups helped talent management teams calibrate talent expectations.

  5. Availability index: Based on information provided by the applicant, the expected notice period across different roles/seniorities and functions was also indicated.

Figure 5.

Talent availability basis experience, current and expected compensation and geographical distribution on Calculus. Source: Company data.

Since its launch in mid-2017, Calculus has been well received by the industry. The head of marketing, Amandeep Singh enthused:

‘The feedback, in general, is highly positive for our offerings. HR heads have been telling me that Calculus simplifies their HR decision making a lot and also aids in realistic planning’.

4. Discussion

Key analytical ability and developments in technology are enabling organizations to meet competitive threats and adapt to changing business and technology conditions. The use of machine learning and predictive analytics, combined with large information available on social media is clearly changing the ways recruitment is being done across organizations. With economies arising from large scale enterprise systems, globally connected networks and data available on the cloud, mobile devices enhancing connectivity and greater internet connectivity, globally connected networks and economies arising from large scale enterprise systems, online social graphs, mobile devices and enhanced connectivity, internet of things and open data/public data, Big Data has emerged as a potential solution to disintermediating talent requirement and availability. The ability of the platforms to “link various data streams using appropriately defined unique identifiers” [21] enables better understanding of candidates behaviors, motivations and expected fit with the organization.

Talent is operationalized into two components: ability component (innate abilities and systematic development) and affective component (which constitutes the motivation to invest and the interest areas). The difference in the various approaches of defining talent is presented in Table 1.

Classification approachSubject approachObject approach
InclusiveIn this approach, talent is defined as the entire workforce and human capital is considered as interchangeable.This approach allows each employee to reach his or her potential. The research on “talent management’ as a whole looks at talent through this perspective. This is similar to HR development or competency management across the organization
ExclusiveThis approach is based on segmentation or differentiation of the workforce in terms of capability, performance and the ability to make a significant different to current and future organization performance. This is the approach taken in our research study.This approach concentrates on exceptional, above-average ability employees in the organization. This is a focus of talent development and retention within organizations using HR practices for high performance and high potential individuals.

Table 1.

Talent classification through various approaches.

Talent has also been conceptualized through the exclusive approach is based on the notion of segmentation of the workforce, and proposed talent as an elite subset of the organizations’ population [22]. The exclusive subject approach focuses on specific employees “who are exceptional in terms of skills and abilities, either in a specific technical area, a specific competency, or a more general area” [23]. Since talent acquisition focuses on hiring individuals based on their differentiated abilities, skills, competencies and fit to the role and organization, the exclusive subject approach to talent definition becomes relevant.

SHRM literature has no clear theory or principle to guide when and on which organizational pools should be targeted or classified but align with the view that “pivotal talent pools are vital targets for HR investment and leader attention” [24]. Thus it is important to develop some system of identification and segmentation of talent as it facilitates the ability to strategize organizational actions to attract or develop the talent pool [25]. All three cases demonstrate the ability to support recruitment functions in identifying talent.

While proposing that changes in technology produce changes in the quality of talent required by organizations, a classification was developed of talent along the dimensions of difficulty-to-replace and value-added [26]. The difficulty-to-replace dimension is thus linked with the labor market factors and the value-added dimension is a customer related factor [25]. This framework essentially makes it possible to do the segmentation of talent specific to each organization and the environment it operates in and takes into account the “economic geography of talent” [27]. The Calculus platform support talent management decisions by providing real time insights on talent availability and cost, thus supporting tactical recruitment decision or decisions in investment of capability development for certain skills required by the organization. Furthermore, it reinforces the “outside/in” approach that talent functions are adopting, creating value by integrating outside context to support decision making [3].

Lastly, we evaluate the impact of the three organizations under the lens of strategy for social media (Table 2).

StrategyPhilosophyTactical outcomeBelong.coTalviewIimjobs
Relationship strategyTrust building & collaboration through personalized engagementStrategic talent inducted into the organization
Employer brandingEstablishing credibility, gaining attention, demonstrating employer value propositions.Organization perceived as “preferred employer of choice”
Active recruitmentReactive demand fulfillmentActive recruitment positions closed
Cost optimizationReducing costs of recruitment channelsReduce recruitment spend on more expensive channels

Table 2.

Strategic and tactical outcomes of social media recruitment for the three organizations.

Source: Adapted from [12]—alignment of strategy, philosophy out outcome of social media recruitment.

The perceived supportive environment of the hiring organization would induce candidates hired through the Belong platform to utilize their efforts, skills and abilities to embrace organizational objectives. Belong’s approach was also of keen interest to recruiters in all industries, who saw this tool as a potential ally in “hunting” passive talent. A longitudinal study along the lines of value of human capital through human capital metrics appreciated by the business functions [10] would help cement the perceived value delivered, apart from speed of hiring or the ability to find passive talent.

Technology has been found to increase efficiency and reduce administrative burden in HR [2]. The recruitment solution offered by Talview was able to contribute to first level efficiency metrics of improved productivity, reduced costs and improved recruitment cycle time [10]. Further, the offering of assessments by the system was able to set the decision criteria for effective filtering to support the decision making discretion, which build agility within the organizations utilizing this offering. By having a repository of potentially suitable talent available when commensurate opportunities arise, better candidate experience and agility in recruitment is demonstrated. This agility would be valuable to organizational seeking to build this dynamic capability through quickly acquiring key talent faster than competitors [28, 31]. The organizations using and benefitting from Talview’s offering grappled with large volumes of recruitment, where the demonstrated agility was keenly appreciated.

While the above mentioned cases illustrate the impact of social media and technology in disrupting candidate search, attraction and recruitment process, the emerging trends and their impact on recruitment approaches have the potential of reinforcing recruitment biases and discriminatory hiring practices. Big data algorithms used to screen and filter are based on specific patterns of social behavior. This approach presents a fundamental limitation in promoting a non-discriminatory approach to recruitment. With algorithms built on people characteristics rather than on job requirements, the algorithms are trained to predict desired behavioral outcomes and filter out candidates not meeting the criteria. For example, while publically posted photos of inappropriate behavior or offensive language are some of the obvious filtering logics used, spelling mistakes in resumes are also used as a measure of communication skills. These flout the norms of equal opportunity recruitment practices advocated and open up avenues for exposing organizations to lawsuits for discriminatory hiring practices.

Social media and technology also have the ability to influence employer brand. A few examples of employees demonstrating inappropriate behavior or even posting about unfair treatment at the workplace have resulted in huge social media backlash and poor PR for organizations [29]. Both journalists and media also leverage social media trends to promote and rank topics of interest. Websites like Glassdoor allow for anonymous reviews of companies, their management, the recruitment experience and provide a feel of the culture. Managing the social media PR has become increasingly important for HR functions. While an erstwhile approach adopted by organizations was to provide gated access to internet, with mobile access freely providing access, the approach of organizations to manage the social media engagement of their employees and thus the impact on employer brand has got changed. Social media allows individuals to meet social needs but with plausible deniability [30]. Most organizations have adopted social media and digital strategies and code of conduct to educate employees on desired social behaviors and consequences of inappropriate behaviors.

The illustrative cases are a demonstration of the morphing social media and digital trends shaping HRM practices in organizations. For practitioners looking for synergies with their strategic and tactical outcomes in recruitment, these illustrative cases suggest the relevant appropriateness of each case. These cases also open avenues for further research on multitude of dimensions in the domain of recruitment such as efficiency and effectiveness of the new trends as well as the unconscious bias of big data in recruitment [31, 32, 33]. Additionally, theoretical linkages of social media tactics and their alignment with organization strategy could further be explored. The emerging trends in social media and technology uses in recruitment are allowing for correlation between individuals’ social media behaviors and recruitment outcomes. However, these trends are contributing to the development of societal norms for technology and social media adoption by organizations and also the socially accepted behaviors of individuals on these platforms, thereby having influences beyond HRM principles.

© 2018 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution 3.0 License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Debolina Dutta (October 31st 2018). Social Media and Technology Trends in HRM: Cases in Recruitment and Talent Management, Social Media and Journalism - Trends, Connections, Implications, Ján Višňovský and Jana Radošinská, IntechOpen, DOI: 10.5772/intechopen.79342. Available from:

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