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Dubai BIS4430 Web-based Information Systems Management 2015/2016 Coursework Final Paper Student Number Student Name M00558341 Glen Coutinho M00549948 Adam Lalani M00549944 Ranjan Mazumder Tutor: Dr. Krishnadas Nanath Base Campus: _________________________________________ The number of words in the article 7205 (excluding appendices)

BIS4430 - Endorse Me Back

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Page 1: BIS4430 - Endorse Me Back

Dubai

B I S 4 4 3 0 Web-based Information Systems Management

2015/2016 Coursework – Final Paper

Student Number Student Name

M00558341 Glen Coutinho

M00549948 Adam Lalani

M00549944 Ranjan Mazumder

Tutor: Dr. Krishnadas Nanath Base Campus: _________________________________________ The number of words in the article

7205

(excluding appendices)

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“Endorse me back”

Should recruiters be considering endorsements when using LinkedIn to recruit candidates?

Glen Coutinho Adam Lalani Ranjan Mazumder

[email protected] [email protected] [email protected]

Abstract

Recruitment has evolved dramatically over the last few decades from the early days

of job posting in windows and newspaper sections. The dawn of the World Wide Web,

followed by social media networks, revolutionised the recruitment industry, providing

a richer experience for both the recruiter and candidates. The use of LinkedIn as a

social recruiting platform has gained widespread acceptance globally as it primarily

features a professional network. Traditionally, word of mouth recommendations and

reference letters were sought out to accredit a candidate’s skills. Keeping in line with

these practices, LinkedIn features a skill endorsements and recommendations

section - which are the digital equivalents in this e-recruitment era. While

recommendations tend to be generally accepted as meaningful information, the

perceived value of LinkedIn skill endorsements vary extensively. Some argue that

LinkedIn endorsements serve as an alternative option for acknowledging a

connection’s skills, without the time-consuming task of writing a recommendation,

while others claim they have little or no perceived value due to their relatively

simplistic one-click approach in acknowledging a person’s skills. With a user base of

332 million LinkedIn members and over a billion documented endorsements thus far,

this paper presents a quantitative and qualitative study on the perceived value of

LinkedIn skill endorsements in the recruitment process and, focuses on establishing

whether or not recruiters should consider LinkedIn endorsements as a first pass filter

in screening prospective job candidates.

Keywords: Online recruitment, LinkedIn recruitment, LinkedIn endorsements,

Social media recruitment, Recruitment methods, Recommendation

letters.

1. Introduction Recruitment is an important function for acquiring talent and “includes those practices and activities

carried out by the organisation with the primary purpose of identifying and attracting potential

employees” (Breaugh & Starke, 2000).

The origins of recruitment actually date back to 55 B.C. when Roman Emperor Julius Caesar offered

a finder’s fee to any member of his army who could convince one of their associates to sign up and

join Rome’s army (Anand, 2010). After 25 years of service, a serving officer could retire - receiving

either a cash lump sum or a plot of land (The Benefits of Enlistment In A Roman Legion, no date) -

which one could argue was an early form of employment contract with reciprocal responsibilities to

be adhered to by both employer and employee.

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Between the 1950’s and the 1980’s, the most common form of recruitment media was through

newspaper publications, with more than 75% of candidates being unearthed through newspaper

advertising (Desormes, 2014). A recruiter or head-hunter in the 1980s was armed with two things -

a telephone and an advertising budget. During this time, searching for a job was a low-tech affair;

employers would post job openings in the classified section of newspapers, whilst recruitment

agencies advertised job openings in the windows of their premises. Prospective job candidates

would then print multiple copies of their Curriculum Vitae (CV) to physically hand out, or require

access to a fax machine to send their CVs for consideration for an open role.

In today’s modern information age, this has all changed. In a research paper written on behalf of the

Rand Corporation it is noted that “...the networking of computers is the defining characteristic of the

information age” (Dewar, 1998). Thanks to the networking of computers and the emergence of

Internet technologies such as Web 2.0 and Social Networks, the recruitment industry has been

dramatically transformed.

The use of technology-enhanced recruitment, or “e-recruitment” as it has been termed, has soared

in the last decade, with over 50 percent of human resource professionals pursuing talent through

social networking sites (Cable, 2013, p. 382) in order to gain a competitive edge. With the dawn of

the Internet, traditional job postings in newspapers started making an appearance on the web

through “electronic job boards”, such as Monster.com which was founded in 1999 (Lamri, 2013).

While these platforms proved to be a cost-effective method over conventional mediums, the rise of

social networking sites (SNS) in the early 2000s propelled e-recruitment to a whole new level,

thereby providing a richer experience for both the recruiter and candidates.

SNSs such as Facebook, MySpace, etc. were originally intended for locating friends and networking

with likeminded individuals that shared similar hobbies and interests. Employers and recruiters

however, soon turned to these platforms as a viable source for screening potential candidates

(Bohnert & Ross, 2010) and sourcing exclusive talent. “Social Recruitment” was now the new

catchphrase and according to a survey by JobVite (2014), the top three most widely used platforms

for social recruiting were LinkedIn (94 percent), Facebook (66 percent) and Twitter (52 percent).

Prior to social media recruiting, employers had limited insight into a candidate’s actual ability, apart

from what was claimed on their CV. Unlike a conventional CV, a LinkedIn profile offers candidates

a feature-rich platform to represent themselves, their credentials and past achievements (Labovich,

2014).

Facebook is undoubtedly the biggest social network with over 1 billion members worldwide. LinkedIn

reports a user base of 332 million members according to its 2015 statistics (Blake, 2015) and was

selected as the platform of study for this research as it principally features a “professional network”,

one that is prominently used by recruiters for online recruitment (JobVite, 2014).

In the past, the traditional process of accrediting a person’s skills were undertaken through reference

letters and/or word of mouth recommendations. Keeping in line with these practices, “Endorsements

and Recommendations are LinkedIn equivalents of reference letters. Instead of a formal referral,

former or current colleagues write a recommendation or endorse a skill.” (Fawley, 2013). It is

important to note that each serve a different purpose and they should not be considered as one and

the same thing.

Basically, LinkedIn skill endorsements are “...a great way to recognize your 1st-degree connections'

skills with one click. They also let your connections validate the strengths found on your own profile.

Skill endorsements are a simple and effective way of building your professional brand and engaging

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your network...” (Skill Endorsements - Overview, 2015). Its simplistic single-click approach however,

has received much criticism (Naughton, 2012), with many perceiving LinkedIn recommendations

from a peer, co-worker, manager, etc. as being far more meaningful. “A recommendation takes more

time and effort on the part of the person endorsing you. It’s not as easy as just clicking a button;

they actually need to write about their experience with you as a professional. That’s what makes

recommendations so powerful.” (Scivicque, 2014).

However, attaining a recommendation is not always viable as it involves the reference source putting

time aside and taking the effort to write the recommendation. In some cases, such as under the UK

law, an employer is not obliged to provide an employee with a reference unless agreed to previously

in writing. Additionally, an employee can legally challenge a reference that they perceive to be

inaccurate or misleading. (References: workers’ rights, 2014).

This research paper focuses on the empirical study of the professional social network LinkedIn and

whether or not recruiters should consider LinkedIn endorsements as a first pass filter in screening

prospective job candidates. Given the widespread use of this platform in social recruiting and, with

over a billion endorsements documented thus far, it is worthwhile researching the extent of influence

endorsements have in the screening process.

The working hypothesis is that the questionnaire feedback would prove that there is a significant

proportion of LinkedIn endorsers providing endorsements without knowing well enough the skills of

the recipient of the endorsement, and therefore endorsements should not be considered in during

the recruitment process.

2. Literature Review To begin with, the pursuit and acquisition of journal papers related to the subject matter of this paper

was focused on Summon, a portal provided by the University of Middlesex to its students that

contains many high quality, well sourced academic articles, journals and literature. Keywords that

yielded the best results for content appropriate to this paper were:

● Online recruitment

● LinkedIn recruitment

● LinkedIn endorsements

● Social media recruitment

What was clear from the initial keyword searches on Summon is that there was a surge in available

articles beginning in the early 2000s, relating particularly to online recruitment and social media

recruitment. Comparatively, the use of LinkedIn Endorsements has yet to be studied in more detail.

This can be seen in Figure 1 below:

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Figure 1. Initial number of papers found when using Summon, and chosen keyword search(es)

In addition to Summon, searches were performed on EBSCO, Researchgate and Google Scholar

to attain a broader view of the research performed on pre-Internet recruitment methods, and the

perception of traditional job references in the hiring/validation process. To accomplish a theoretical

study on the effects of skill endorsements in the recruitment process, the search was expanded to

include the following keywords, and to synthesise the similarities and differences of the prevalent

current versus prior practices.

● Recruitment methods

● Employment screening

● Job references

● Recommendation letters

The World Wide Web surfaced as a recruiting tool in the mid 90s and led to a “recruiting revolution”

because of the many benefits it brought to recruiters (Boydell, 2002). This revolution exploded into

life at the turn of the millennium causing a radical change in corporate recruitment (Cappelli, 2001).

In a research undertaken in 2002 showed that, just 6% of people looking for work were using the

Internet to do so; the same research conducted a year later showed that this figure had increased

to 46%, and then, 97% as of 2014. (Desormes, 2014).

Based on the research gathered, some argue that LinkedIn endorsements serve as an alternative

option for acknowledging a connection’s skills, without the time-consuming task of writing a

recommendation (Memo To LinkedIn: Please Fix Endorsements, 2014). Consequently, this could

help in portraying a person’s area of expertise over a period of time and building social proof. Social

proof and an online presence are key to being discoverable by recruiters; “...those who don’t build

an online presence....will seemingly appear invisible to most employers and get passed over in

favour of more savvy applicants.” (Labovich, 2014). In a separate article, Rangel (2014) highlights

the importance of keywords and phrases from a job seekers perspective. Endorsements populate

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one’s profile with additional keywords and skills, which would increase the probability of their profile

being found.

The general consensus however, is that endorsements provide little or no value, as (unlike

recommendations) it is too easy for anyone to endorse multiple connections simultaneously without

having to put much thought into it (Zapar, 2012; Augusta, 2013; Dayton, 2013). As per Fottrell

(2014), “most recruiters won’t care whether you have 1,000 endorsements...Recruiters are actually

looking for thoughtful recommendations from a well-respected peer or former employer”.

To ascertain the claim of LinkedIn recommendations being a credible source, a study was carried

out on the perceived value of references traditionally. Interestingly, past research suggest that

“Letters of Recommendation” (LoR) are actually poor indicators of an employee’s future

performance (Aamodt et al., 1993). According to Browning (1968) and Mosel & Goheen (1958), the

average validity coefficient for references was relatively low (.13) given that applicants ideally

choose individuals who would provide them with a favourable reference, rather than someone who

is familiar with an applicant’s conflicting past or cognizant of the applicant's behaviour (Aamodt et

al., 1993). In fact, Brown (2011) cautions employers, stating that written LoRs are generally limited

to what an applicant does well, rather than the complete story. Online references are also open to

the possibility of fraud and deception. This is evidenced by the proliferation of advertisers on

websites such www.fiverr.com, where one can purchase two LinkedIn recommendations for as little

as US$5 (get You 2 Professional LINKEDIN Recommendation – fiverr).

Research conducted by Baxter et al. (1981) further indicates that the inter-rater reliability of LoRs is

only about .40, alluding to the fact that “there is more agreement between two recommendations

written by the same person for two different applicants than there is between two people writing

recommendations for the same person. Thus, letters of recommendation may say more about the

person writing the letter than about the person being written about.” (Aamodt et al., 1993).

Considering these aspects, a compelling question that now prevails is – when screening applicants,

should 2 or 3 (sourced) recommendations be given more weightage than a 100+ endorsements

received by another for a particular skill?

One exceptional paper was located (Caers and Castelyns, 2011) that provided an investigative study

into whether or not LinkedIn and Facebook was being used by recruiters in Belgium to recruit and

select candidates for available roles. The research was performed by way of an online questionnaire,

and helpfully established that because LinkedIn is perceived to be far more professional than

Facebook, it was much more favoured by recruiters to advertise vacancies or scour for applicants

to fill open roles. That said, it was also established that recruiters also looked at a candidate’s

Facebook profile to gain an insight into the type of personality and/or behaviour that the potential

candidate may advertise to the outside world.

From the literature review undertaken, there appears to be a lack of in-depth research, to the best

of our knowledge, that studies LinkedIn endorsements specifically, and whether or not recruiters

should be considering endorsements in their search for job candidates. Thus, with the gap in the

literature having been exposed, the aim of the research is of importance and would be a valuable

addition to the currently published body of work.

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3. Conceptual Model & Background Theory Figure 2 illustrates the conceptual model adopted for the proposed research. The model follows a

structural approach based on quantitative and qualitative data in order to establish a hypothesis on

whether or not, a person’s view on the skill endorsements feature has any bearing on their perceived

value of their skill endorsements in the recruitment process.

Figure 2 - Conceptual model of the proposed research methodology

4. Research Methodology “A research method is a strategy of enquiry which moves from the underlying philosophical

assumption to the research design and data collection” (Myers and Avison, 2002)

The research was performed in a two-pronged approach - one using qualitative interviews, and the

other using quantitative data collected using an online questionnaire. The first tranche of data

collection was to be extracted through qualitative based interviews with a clutch of recruiters known

to the researchers - in order to better inform about the recruiters and their use of LinkedIn. It is

presupposed that these interviews will prove that LinkedIn skills endorsements are indeed used as

a recruitment tool (or part of an arsenal of several tools) and if so, in what way they are used -

perhaps through keyword searching or via some other process/procedure, and what value or level

or regard they are held in by the respondents.

In terms of this paper, the qualitative research was based upon the subjective perception of a

respondent within a given situation, which is known as ‘phenomenology’ (Husserl, 1970). The

intention being that the interviewee attempts to be descriptive in their responses without having

preconceived notions or hypotheses, which therefore allows for deeper insights into their actions,

motivation and behaviour without being tainted by the interviewer’s own assumptions and

motivations to ask the questions.

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The qualitative based interviews were planned to provide supporting data that would corroborate

findings from the questionnaire respondents. It was decided that each of three researchers would

carry out one interview each with a recruiter that was personally known to them. Whilst the sample

size was confined to a small number, it was anticipated that recruiters would most likely already

have their own ideas on skills endorsements within a recruitment context, and therefore the

questionnaire data would provide more credence when attempting to answer the research question

at hand.

In contrast, the second portion of data was to be gathered by performing a quantitative questionnaire

based research on as many LinkedIn users possible, and be focused upon the accumulation of

statistical data, which was then to be analysed using IBM’s SPSS predictive analytics software (IBM

SPSS software, no date) in order to find correlations between sets of data to explain specific

phenomenon (Muijs, 2004). The main purpose of the collected data was to comprehend and

understand the views on LinkedIn skills endorsements from the perspective of a sample of the

general LinkedIn user population. Further to that, the questionnaire was designed to drill down into

their views of LinkedIn skills endorsements in the recruitment process.

The target population of the survey was confined to users of LinkedIn, and as of Q4 2015, LinkedIn

had 414 million members (Numbers of LinkedIn members from 1st quarter 2009 to 4th quarter 2015

(in millions), 2015). It was not practical to target every member LinkedIn, so the sample size was

restricted to other members that were known to the researchers. Additionally, those contacts were

encouraged to forward the survey to others that were known to them, but perhaps not to the

researchers, who would potentially be in a position to provide their answers.

As the researchers were unable to uncover any suitable prior research in to the question (Should

recruiters be considering endorsements when using LinkedIn to recruit candidates?), the constructs

and items in tables 1 and 2 below were developed jointly by the researchers during several

brainstorming sessions, based on their existing understanding of LinkedIn.

The design of the quantitative questionnaire was constructed using Google Forms and included a

total of 16 items. A structural approach involving three constructs was adopted in order to establish

a relationship between each, as depicted in the conceptual model (Figure 2). A summary of each of

the constructs is as follows:

Construct A was developed in order to gather the perception and views of an everyday LinkedIn

user on skills endorsements. This construct included a total of 4 items. Items 2 and 3 were measured

on a binary scale (Yes/No), whereas item 1 was frequency based (Never/Rarely/

Sometimes/Frequently). Item 4 was an open-ended question to gain an insight in to endorsements

from a respondent’s perspective.

Construct B was put together to understand and measure the accuracy of skills endorsements (i.e.

are they legitimate and a fair reflection of the recipient), as well as, to establish if there is a reciprocal

“game of strategy” being played out amongst the LinkedIn populace (quid pro quo). The construct

constitutes of a total of 8 items that are predominately binary based. Except for item 1 which is

frequency based, the remaining items yield a yes/no response.

Construct C sought to ascertain if LinkedIn users believed that skills endorsements added value to

their chances of standing out in the recruitment process. This construct comprised of 4 items, in

which items 1-3 are measured on a binary scale and item 4 gathers an open-ended response.

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Table 1 below outlines the constructs and items defined in the quantitative questionnaire.

Table 1 - Quantitative Questionnaire - Definitions and Measurements

Construct A - Users views on skilled endorsements

1 How frequently do you endorse the skills of your connections on LinkedIn?

2 Do you feel having the right skill endorsements can provide credibility and help a person build their professional brand?

3 Do you think endorsements are a fair reflection of your skills and expertise?

4 What do you think about LinkedIn Skill Endorsements?

Construct B - Reciprocal and Accuracy (Fair Usage)

1 Besides being prompted by LinkedIn, how often do you receive requests from your contacts to

endorse them for specific skills they are promoting?

2 Are you more likely to endorse somebody that has endorsed you previously?

3 Do you feel inclined to endorse somebody who has endorsed you (as a form of professional courtesy possibly)?

4 Do you think somebody you have endorsed is more likely to endorse you in return?

5 If somebody you have endorsed does not endorse you back, would you be less likely to endorse them going forward?

6 If endorsed for the wrong skills, would you decline / remove the endorsement so your actual skills

are not overlooked?

7 Have you endorsed someone you know, but for a skill or expertise you were not sure they have?

8 Have you ever endorsed someone you don’t know?

Construct C - Perceived value of endorsements in the recruitment process

1 Do you think recruiters would be interested in the endorsements you have?

2 Do you feel having more endorsements on a skill, could improve your chances of being found by

recruiters, looking for a specific talent?

3 Do you think recruiters would choose somebody with more endorsements for the same skill than you?

The qualitative interview framework (Table 2) was created through a brainstorming session between

the researchers with a total of 11 open ended questions that were created and designed to extract

as much information as possible.

Table 2 - Qualitative Interviews - Definitions and Measurements

Questions Rationale

1. How old are you? 2. Male or Female?

Ascertain demographical information of the interviewees

3. How long have you worked in recruitment for?

4. Can you describe how recruitment methods have changed since you began your career?

Gain an understanding / general overview of the recruiter’s employment background and history, and how recruitment has changed during the

course of their career.

5. Do you use social networking sites to source

potential candidates? Please name all of them. Is LinkedIn one of them?

Developed in order to learn how recruiters are using social media platforms in their recruitment

process. Firstly, looking at all the platforms they might use, and then narrowing down to their use

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6. How long have you been using LinkedIn to source candidates and does it give you access to a wider talent pool than traditional methods of

recruitment? Why else do you use LinkedIn during the candidate search?

7. Which are the industries you work with to source prospective candidates via LinkedIn, such as

Health Care, IT, Hospitality, Education, Oil & Gas, Manufacturing, Government etc?

8. While searching or sifting through prospective candidates, what are the things that you look for in a candidate profile? Please tell us in what

order of importance do you place them?

of LinkedIn. Also, to see what industries the respondents are

responsible for recruiting within. Finally, learning what they are looking for within a

potential candidates profile, how they search for what they are looking for, and how important these are.

9. What are your opinions on LinkedIn skills endorsements?

10. During your searching for a specific skilled

professional, what are the things that you look for within the profile to validate the person is skilled? Please tell us in what order of

importance do you place them? 11. While looking for a specific skilled professional,

do you take in consideration that how many times a person has been endorsed for that specific skill by his or her peers?

12. What are your opinions on LinkedIn

recommendations? Do you take recommendations into consideration?

Learning about recruiter’s opinions on skills endorsements, if they are of value to them during a candidate search.

Additionally, looking at their opinions on recommendations, and seeing if perhaps they hold

more value than skills endorsements within the recruitment process.

At the time of closing, 56 completed questionnaires were received. Additionally, 3 interviews were

undertaken by the researchers with subjects known to them that work as recruiters, in order to better

see if their opinions would correlate (or not) with questionnaire data or the working hypothesis. As

demonstrated below (in Figures 3, 4 and 5), the majority of the survey respondents were aged

between 36 and 45, were primarily male and based in the United Arab Emirates. The details on the

quantitative results gathered are listed in Appendix B of this paper.

Figure 3 - Age Group Summary for questionnaire respondents

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Figure 4 - Gender breakdown of questionnaire respondents

Figure 5 - Location of questionnaire respondents

Additionally, the transcripts of the interviews conducted have been included in Appendix A. The

three interviewees were all female, all from India, and had the ages of 35, 35 and 38 respectively.

It was hoped that the data could be loosely evaluated to see if perhaps the sample of LinkedIn users

that respond are using “game theory” (potentially without realising) - which is a method for analysing

and defining strategies when people are competing with each other in situations where the decision

of a given person is based upon the steps or actions taken by another

(http://www.oxforddictionaries.com/definition/english/game-theory, no date). This is in the hope that

the data might establish that there are “games of strategy” (Neumann and Morgenstern, 1953, p.

46) tacitly taking place when LinkedIn skills endorsements are being made - which would almost

certainly be useful for recruiters to know.

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The overall anticipation was that the two-pronged data collection approach would answer the final

question of - ‘Should recruiters be considering endorsements when using LinkedIn to recruit

candidates?’ For this to be answered, it is a working hypothesis that the questionnaire feedback will

prove that there is a significant proportion of LinkedIn endorsers providing endorsements without

knowing well enough the skills of the recipient of the endorsement - most likely as a form of ‘gaming

the system’ for their own selfish advantage (Golumbia, 2009).

To ascertain the correlation between items within the constructs, a pre-test was conducted using

IBM’s SPSS software to measure the Cronbach's alpha score for reliability after 30 responses were

received. The results of the three constructs have been listed in tables 3 and 4 below. As the survey

model was mainly binary based, a Cronbach’s Alpha > 0.5 was deemed acceptable for use. Two

open-ended questions from constructs A and C, and two frequency-based questions from constructs

A and B were excluded from the pre-test as the main bulk of the survey responses were binary

based, as mentioned previously. In addition, one item from construct B was later removed as the

first pass results indicated the item had a low correlation with other items and yielded a Cronbach’s

alpha lower than 0.3. Details of the items excluded from the pre-test are listed in table 5 below.

Table 3 – Reliability Statistics from pre-test

Construct Description Cronbach's Alpha

Cronbach's Alpha

Based on

Standardized Items

N of Items

Construct A Views on skills endorsements in general .551 .558 2

Construct B Reciprocal and accuracy (fair usage) .525 .523 6

Construct C Perceived value of skills endorsement in the recruitment process

.719 .716 3

Table 4 – Item-Total Statistics from pre-test

Item Scale

Mean if Item

Deleted

Scale

Variance if Item

Deleted

Corrected

Item-Total Correlation

Squared

Multiple Correlation

Cronbach's

Alpha if Item Deleted

Construct A

VIEW1 .5490 .253 .387 .150 -

VIEW2 .7843 .173 .387 .150 -

Construct B

FAIR1 2.4314 1.650 .462 .287 .378

FAIR2 2.5098 1.575 .513 .366 .345

FAIR3 2.3725 1.758 .391 .219 .420

FAIR4 2.7451 2.034 .177 .292 .524

FAIR5 2.4118 2.487 -.160 .189 .669

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FAIR6 2.7255 1.803 .362 .173 .436

Construct C

RCRT1 1.0200 .796 .437 .223 .743

RCRT2 1.2000 .571 .661 .441 .469

RCRT3 1.3400 .637 .536 .351 .635

Table 5 – Items excluded from the tests

Survey Question Construct Action Reason

How frequently do you endorse the skills of

your connections on LinkedIn?

A Excluded Frequency

What do you think about LinkedIn Skill

Endorsements?

A Excluded Open ended

Besides being prompted by LinkedIn, how

often do you receive requests from your contacts to endorse them for specific skills they are promoting?

B Excluded Frequency

Why would you think recruiters would (or would not) be interested?

C Excluded Open ended

Have you ever endorsed someone you don’t know?

B Removed Low Correlation

To test the hypothesis, linear regression was used to determine whether or not a person’s view on

the skill endorsements feature has any bearing on their perceived value of their skill endorsements

in the recruitment process. The linear regression test was carried out using IBM SPSS, which was

provided by Middlesex University - Dubai Campus. The objective of the test was to measure the

degree of relationship between construct A (user’s views on skill endorsements) and construct C

(perceived value of skill endorsements in the recruitment process). Due to the binary based model

(scale 0 – 1), the mean was derived from the variables in construct A and C and enumerated into

two separate variables – ‘avg_view’ being the independent variable and ‘avg_recr’, the dependent

variable. The results of the linear regression test have been outlined in tables 6, 7 and 8 under the

results section of this paper.

5. Results

The results of the linear regression test are as follows:

Table 6 – Model Summary

Model R R Square Adjusted R Square

Std. Error of the Estimate

1 .341a .116 .100 .35733

a. Predictors: (Constant), avg_view

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Table 7 - ANOVAa

Model Sum of Squares df Mean Square F Sig.

1

Regression .907 1 .907 7.102 .010b

Residual 6.895 54 .128

Total 7.802 55

a. Dependent Variable: avg_recr

b. Predictors: (Constant), avg_view

Table 8 - Coefficientsa

Model

Unstandardized Coefficients

Standardized

Coefficients

T Sig. B Std. Error Beta

1 (Constant) .385 .096 4.018 .000

avg_view .336 .126 .341 2.665 .010

a. Dependent Variable: avg_recr

The R-Square details in the Model Summary (Table 6) measures the degree of variance in the

dependent variable that can be explained by the independent variable. Additionally, the ANOVA

table (Table 7) demonstrates the overall significance of the model, while the the Coefficients table

(Table 8) denotes the level of confidence with which the estimate of the dependent variable is

asserted by the independent variable. A Sig. value of 0.1 would indicate that the model or coefficient

estimate is insignificant, while a value of <0.05 signifies the model is a good fit or the dependent

variable is supported by the independent variable with a 95% level of confidence (Gupta, 1999).

Based on the linear regression test results above, we observe that the R2 coefficient of determination

is .116, indicating that only a 11.6% variation in the perceived valued on skill endorsements in the

recruitment process (dependent variable) is explained by a person’s view on skill endorsements

(predictor). The ANOVA significance value (p = .010) establishes that the overall model fit is 99%

statistically significant. The Coefficients p-value of .010 also implies that construct C is of 99%

significance to construct A. Thus the results would confirm the hypothesis that a user’s assessment

of the skill endorsements feature has no bearing on their perceived value of their skill endorsements

in the recruitment process.

6. Discussion & Conclusion

The research question for this paper is ‘Should recruiters be considering endorsements when using

LinkedIn to recruit candidates?’. The recruiter interviews have shown that they do not currently

consider skills endorsements when screening for candidates. Quotes from the three respondents

include:

“No, (I am) not paying attention to endorsements at all”, (see Appendix A)

“We don’t take endorsements seriously as any random person can endorse anyone. They are quite

meaningless”, (see Appendix A)

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“With LinkedIn endorsements sometimes it can get a little quid pro quo - a lot of endorsements given

by random people who don’t even know you. Some connection of mine endorses me for something

that I don’t know or have anything to do with. It is like an eye wash. My team and I don’t look at

endorsements.” (see Appendix A)

That last quote contains the words “it can get a little quid pro quo” feeds rather well into the working

hypothesis which was that the questionnaire feedback would prove that there is a significant

proportion of LinkedIn endorsers providing endorsements without knowing well enough the skills of

the recipient of the endorsement - most likely as a form of ‘gaming the system’ for their own selfish

advantage. What has been established by the survey is that almost overwhelmingly the respondents

(96.4% - refer to Appendix B) have never endorsed someone that they did not know but 28.6% (refer

to Appendix B) of respondents have provided an endorsement for a skill they were not sure the

recipient had.

Mainly because the researchers were unable to uncover any existing research pertaining to the

question asked, the literature reviewed was used to establish a historical context for the research

that was to be undertaken. This context was further strengthened and reinforced by the recruiter

interviews that were performed. One of which showed that “....11 years (ago) ... the role involved

mostly getting resumes into job portals and a CV database.... sourced mainly from adverts in the

Gulf News…”. Further down the line, “more and more recruiters are depending on recruitment using

social media”. What is also clear from the existing body of literature and the interviews is that

generally social media recruitment tends to be more restricted to LinkedIn - “We do not use

Facebook as we are associated with executive level searches only” and “The organisation’s

Facebook page is not primarily used as a career page although sometimes jobs are posted on the

Facebook page”.

The linear regression testing of quantitative data exhibited that the overall model was highly

significant (99%) and the relationship between construct A and construct C was minimal (11.6%).

Furthermore, the correlation between the individual coefficients was highly significant as well (99%),

thus confirming the hypothesis that a user’s assessment of the skill endorsements feature has no

bearing on their perceived value of their skill endorsements in the recruitment process.

To an extent it appears that reciprocation is an influencing factor when LinkedIn users endorse each

other for skills - 64.3% (refer to Appendix B) of respondents would be more likely to endorse

someone that had previously endorsed them and a similar figure (67.9% refer to Appendix B) would

expect an endorsement to be reciprocated in return. Although the respondents are not overly

negatively influenced going forward if they were not endorsed back, as 71.4% (refer to Appendix B)

would still continue to endorse someone else without any reciprocation. Certainly, there is no penalty

for endorsing someone for their skills, only the perceived potential benefit (the hope of being

endorsed back).

It has been demonstrated during the recruiter interviews that recruiters are not interested in using

LinkedIn skills endorsements as a barometer for validating skills of a potential hire, even though the

survey respondents (76.8% - see Appendix B) believe that it has an influencing factor. Recruiters

are using LinkedIn through geographical and industry/job specific filtering, whilst then further filtering

candidates on keywords. However, it may be possible that these skills endorsements are showing

up in keyword searches.

Prior to performing the research, the researchers of this paper viewed the value of LinkedIn

endorsements with scepticism, and based on the data collected that stance appears to be

corroborated that they are not an accurate reflection of a person’s skill set on their profile. This view

was strengthened by the recruiters’ anecdotal evidence when they were interviewed.

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It is entirely plausible that LinkedIn themselves are aware that there is little to no value of their skills

endorsements functionality - certainly LinkedIn would be expected to know that recruiters are aware

of their lack of value, and as LinkedIn provide recruiter accounts they are undoubtedly aware of how

recruiters are using them. LinkedIn probably use the feature to drive traffic to encourage continual

interaction with their platform and as one of the survey respondents said “...it's a bit like gamifying

of professional connections, like Tinder and swipe left or right…” - which is probably addictive to

users in some way.

The managerial implication provided by the data collected shows that recruiters should continue to

ignore LinkedIn endorsements, and job applicants using LinkedIn should focus on improving their

overall profile in terms of using effective keywords relating to their career experience and skills.

As already touched upon in this conclusion, LinkedIn skill endorsements are potentially a method

used by LinkedIn to drive engagement on, and traffic to, their platform. The recruiters interviewed

were guided by their belief in the veracity of LinkedIn recommendations - which are used like an

online version of a job reference. Perhaps, LinkedIn can find a way to leverage the two together to

create a stronger more rounded and accurate profile for its users.

Due to time limitations, the mind-set behind the reasoning of reciprocal endorsements was not

explored in great detail. This would most definitely be a research worth undertaking. Especially the

application of game theory to best analyse and define the differing strategies that are used when

LinkedIn endorsements are being made. The data gathered during this research points towards this

happening, as LinkedIn users believe that skills endorsements do make a difference to their profile.

Also, further research is recommended into whether it may be possible that these skills

endorsements are showing up in keyword searches.

Furthermore, as referred to earlier in the paper, it is possible to purchase counterfeit LinkedIn

recommendations - perhaps some further research into the inner workings of recommendations and

whether or not they are an accurate reflection of a person would be a logical step to follow on from

this research.

Finally, the gamification of the online identity of others appears to be a trend that is in the ascendancy

- whether it be Tinder swiping, or LinkedIn skills endorsements - at the touch of the button one can

press yes or no to make a decision on whether a particular person is attractive or has a skill - surely

this would be an area of further interest to researchers.

The limitations of this research paper are primarily concerned with sample size. First of all, three

recruiters were interviewed and a larger number of interviewees may have led to some different

conclusions, although the researchers do not believe that to be the case, it could be argued

otherwise. Secondly, a sample size of 56 LinkedIn users responded to the survey, and whilst again

the researchers are of the belief that their feedback points to the general tendencies of the LinkedIn

population it could be argued that the sample size was too small. Additional limitations are that most

of the respondents were in the United Arab Emirates, and there may be regional variations in the

dataset, as well as most of the respondents being male.

In conclusion, the researchers who worked on this paper believe that the answer to the research

question is that recruiters should not be using LinkedIn skills endorsements when recruiting - mainly

due to the fact that only 53.6% (refer to Appendix B) of respondents believed that the endorsements

were a fair reflection of their skills and expertise.

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Appendix A: Interview Transcripts

1 - Recruiter’s interview questions/answers summary : “Nina Simpson” conducted on 22

March 2016

Demographics

The recruiter interviewed was given the pseudonym Nina Simpson, and is a 35 year old female,

from India, that works as a recruiter.

General overview of recruiter’s employment background and history

“For 10 years I have worked in recruitment, and over the years the recruitment industry have

changed from the traditional recruiting methods like placing ads in newspapers etc, and now more

and more recruiters are depending on recruitment-using social media etc”.

Recruiter’s use of social media

“I mainly depend on Facebook and LinkedIn. LinkedIn I have used for 4 years for specialised

professionals mainly in the Healthcare industry like Physicians”.

“During a candidate search, i look at their present role, how many years of experience in the specific

field, their preferred country”.

Recruiter’s opinion on LinkedIn skills endorsements

“I never really considered endorsements as the main catalyst. Sometimes its too exhorted. I check

the certifications - for example if I am looking for a Radiologist , first thing I look for is if the candidate

is American Board certified. I don’t pay any attention to endorsements at all”.

“I am not paying much attention to recommendations either as reference checks are done later once

the candidate gets through the interview process”.

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2 - Recruiter’s interview questions/answers summary: “Jane Smith” conducted on 20 March

2016

Demographics

The recruiter interviewed was given the pseudonym Jane Smith, and is a 38 year old female, from

India, that works as a recruiter.

General overview of recruiter’s employment background and history

“I’ve worked as a recruiter for about 15 years now. In the early days, there was no LinkedIn.

Depending on a client’s requirement, we would focus on campus recruitment and job portals such

monster.com and naukri.com. Another popular method was referrals and buddy programs.

Incentives were offered such a pay for a referral. Now, we use LinkedIn extensively to source

candidates for managerial positions.”

Recruiter’s use of social media

“Yes, we use LinkedIn and ZoomInfo primarily to search for candidates. We do not use Facebook

as we are associated with executive level searches only. I have been using LinkedIn for quite a few

years now. Unlike previously, it allows access to a global pool of talent. We can source candidates

based on the geographical requirements of our clients.”

“I source candidates in the Financial and banking sector.”

“When searching for a candidate, in order of importance, the first thing I look for would be skills,

followed by keywords in their profiles. As we recruit primarily for the banking sector, we look for

keywords such as credit cards, products, sales etc. The next would be location of work if a client

has specified a geographical region preference. Product knowledge, the organisation they currently

work for, the industries that they have worked in and language would be next.”

Recruiter’s opinion on LinkedIn skills endorsements

“We don’t take endorsements seriously as any random person can endorse anyone. They are quite

meaningless. Recommendations on the other hand are taken in consideration based on who has

provided the recommendation. We don’t take into account how many times they are endorsed as

any random person could be endorsing them”

“We check what candidates have written in their profile, the organisations they have worked for

previously and look to do a background check if there are any shared (mutual) contacts. If there are

recommendations included in the profile, those are looked into as well.”

“Recommendations are credible and are taken into account. We check who has written the

recommendation, whether it’s a family member or colleague or manager. Overall, they are taken

seriously and are used to validate a candidate”

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3 - Recruiter’s interview questions/answers summary: “Angela Reynolds” conducted on 18

March 2016

Demographics

The recruiter interviewed was given the pseudonym Angela Reynolds, and is a 35 year old female,

from India, that works as a recruiter for a global sportswear brand.

General overview of recruiter’s employment background and history

“I have worked in the recruiting field for 11 years now. When I started doing recruitment in India the

role involved mostly getting resumes into job portals and a CV database. When I moved to Dubai

and worked with Manpower, we still looked to get CVs into our database, sourced mainly from

adverts in the Gulf News, Monster.com, Gulf Talent and Bayt.com”.

Recruiter’s use of social media

“Yes we do use Linkedin, and also we use a site called Xing.com in Germany and to a lesser extent,

Gulf Talent. Twiter is not used much in the MENA region, or our other emerging markets. Twitter is

sometimes used in by our North America recruiters. The organisation’s Facebook page is not

primarily used as a career page although sometimes jobs are posted on the Facebook page”.

“Slowly, by 2008-2009 Linkedin gained momentum. We did not use at first a recruiter account but

we had a premium account so we could contact candidates. By 2011, we started using a Linkedin

recruiter account. We no longer use Gulf News to hire. Now we also have tie ups with major

universities. Companies still use Gulf Talent and Bayt but they also try to do their own career

database. They use adverts posted to LinkedIn, Indeed.ae etc and attract talent into their own

database. Your own database is better for your own metrics – you can see how many applicants

were sourced internally, externally etc. Just yesterday Linkedin published a report into retail

recruitment in 2015 and people in the market. So for example there are 64,000 people in the retail

sector in Morocco. If I have 20 retail positions I can tap that 64k pool. Therefore Linkedin is definitely

a valid tool”.

“In terms of industries, I have recruited for retail, FMCG, the advertising sector, luxury goods, and a

bit for banking, nothing in IT.”

“Depending on the seniority of the role I’m looking to fill, if it’s a senior role we would use Linkedin,

otherwise our in house job board. When using Linkedin, lets say if I’m looking to hire a franchise

manager in Morocco I’d look at the kind of things he talks about on his profile in terms of sales

volumes, sales targets, opening up of stores, footfalls in the stores – I look for certain keywords like

sales and marketing. I wouldn’t look at people in other industries, as they are not relevant and skills

transfer is not there. I am focussed on product knowledge and industry specific skills. If you are

recruiting with a Linkedin recruiter account you can search by region, country, industry etc. you can

also target competitor companies - so we can also look to take talent from our competition.”

Recruiter’s opinion on LinkedIn skills endorsements

“With Linkedin endorsements sometimes it can get a little quid pro quo - a lot of endorsements given

by random people who don’t even know you. Some connection of mine endorses me for something

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that I don’t know or have anything to do with. It is like an eye wash. My team and I don’t look at

endorsements. Only 10 percent of the endorsements I have are people that know me and the kind

of work I do.”

“To validate someone’s skills the candidate would have to put certain keywords I want to see, like

merchandising, sales, franchising etc. I don’t bother going down to see the n number of

endorsements, but for a senior person I would definitely look at recommendations, to see what kind

of a manager he is, his leadership style, how did he like to manage etc. Endorsements or the number

of endorsements have no bearing in our methods”.

“With Linkedin recommendations, we definitely used it to see leadership styles, what kind of person

he/she is to work with, it may also give away personality traits, we also look at who has given the

person recommendations. If it's someone that worked with them, did they manage them, were they

managed by them. Just to stress, all of this is only at senior level, definitely not at mid level or below”.

Appendix B: Quantitative Survey results

Total - 56 responses

Summary

Demographics

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Your views on LinkedIn Skill Endorsements:

Do you feel having the right skill endorsements can provide credibility and help a person build their professional brand?

Besides being prompted by LinkedIn, how often do you receive requests from your contacts to endorse them for specific skills they are promoting?

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If endorsed for the wrong skills, would you decline / remove the endorsement so your actual skills are not overlooked?

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Do you feel inclined to endorse somebody who has endorsed you (as a form of professional courtesy possibly)?

If somebody you have endorsed does not endorse you back, would you be less likely to endorse them going forward?

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Your views on the role of LinkedIn Endorsements in the Recruitment Process

Do you feel having more endorsements on a skill, could improve your chances of being found by recruiters, looking for a specific talent?