THE EFFECT OF COLLABORATIVE ONLINE MEDIA ON RECRUITMENT DECISIONS: AN EXPERIMENTAL STUDY IN THE HOSPITALITY SECTOR

El efecto de los medios colaborativos online en las decisiones de contratación: Un estudio experimental en el sector de hostelería

ABSTRACT

This research aims to determine whether collaborative hypertext dictionaries (CHDs) offer warranties within the scope of the warranting theory. A fictional script based on recruitment processes was used to examine whether the comments about persons in CHDs offer warranties to recruiters. The study was conducted with a posttest-only control group design from amongst true experimental designs. The sample consisted of 359 persons, including board members of five-star accommodation establishments with recruitment privileges, deputy general managers, accounting managers, and human resources staff. The study concluded that positive or negative comments about applicants in CHDs significantly impact the recruiters’ perspective of them. Also, the research considered important resources in recruitment processes when it comes to offering warranties. The research findings provide a practical contribution by revealing the effect of applicants’ social media content on the recruiter’s choice.

Keywords:
collaborative hypertext dictionary; warranting theory; social media; recruitment decisions; hospitality industry

RESUMEN

Esta investigación tiene como objetivo determinar si los diccionarios colaborativos de hipertexto (CHD) ofrecen garantías en el ámbito de la teoría de la garantía. Se utilizó un guión ficticio basado en procesos de contratación para examinar si los comentarios sobre las personas en CHD ofrecen una garantía o no. El estudio se lleva a cabo con un diseño de un solo grupo con postest de entre diseños experimentales verdaderos. La muestra constó de 359 personas, incluidos miembros de juntas directivas de establecimientos de alojamiento de cinco estrellas con privilegios de contratación, directores generales adjuntos, directores de contabilidad y personal de recursos humanos. El estudio concluyó que los comentarios positivos o negativos en los CHD sobre los candidatos a un empleo tienen un impacto significativo en la perspectiva de los reclutadores hacia dichos candidatos y se consideraron recursos importantes en los procesos de reclutamiento para brindar garantías. Los hallazgos de la investigación brindan una contribución práctica al revelar el efecto del contenido de las redes sociales de los candidatos en la selección realizada por el reclutador.

Palabras clave:
diccionario colaborativo de hipertexto; teoría de la garantía; redes sociales; decisiones de reclutamiento; industria de la hospitalidad

RESUMO

Esta pesquisa tem como objetivo determinar se os dicionários colaborativos de hipertexto (DCHs) oferecem garantias no âmbito da teoria da garantia. Um roteiro fictício baseado em processos de recrutamento foi usado para examinar se os comentários sobre pessoas em DCHs fornecem uma garantia ou não. O estudo foi conduzido com um desenho pós-teste único com grupo de controle em meio a delineamentos experimentais verdadeiros. A amostra para o estudo foi composta por 359 pessoas, incluindo membros do conselho de administração de estabelecimentos de hospitalidade cinco estrelas com privilégios de recrutamento, subgerentes gerais, responsáveis pela contabilidade e pessoal de recursos humanos. O estudo concluiu que comentários positivos ou negativos sobre candidatos a um emprego em DCHs têm um impacto significativo na perspectiva dos recrutadores em relação aos candidatos e são considerados recursos importantes nos processos de recrutamento para fornecer garantias. Os resultados da pesquisa oferecem uma contribuição prática ao revelar o efeito do conteúdo de mídia social de candidatos na escolha feita pelo recrutador em um processo seletivo.

Palavras-chave:
dicionário de hipertexto colaborativo; teoria da garantia; mídias sociais; decisões de recrutamento; indústria hoteleira

INTRODUCTION

Many companies nowadays have been hesitant regarding social media recruitment, while others have embraced platforms such as Facebook, LinkedIn, Twitter, and Hyves as complementary tools to assist traditional recruitment methods or to replace them (Brown & Vaughn, 2011; Chang & Madera, 2012; Gibbs et al., 2015; Melanthiou et al., 2015; Nikolaou, 2014; Sameen & Cornelius, 2013, Muduli & Trivedi, 2020). These authors suggest that companies use social media a) to attract suitable employees by targeting and messaging potential applicants and b) to screen and cross-check resumé information. They obtain further information through content and comments shared on applicants’ social media accounts, supporting their decisions regarding promotion or hiring, for example.

The results of the recruiting survey conducted with human resources specialists in various industries by Jobvite (2014) - a recruitment software company - 73% of employers recruit via social media, and 93% stated that they check applicants’ social media accounts before making a hiring decision. CareerBuilder’s (2017) Social Media Recruiting Report revealed that 70% of employers investigate the applicants’ social media accounts before hiring. According to the report, 54% of employers found content on social media that led them not to hire an applicant.

The individuals’ social media accounts display content they generate and comments usually made by close friends or acquaintances (which is content individuals not always can limit or delete). The warranting theory by Walther and Parks (2002) states that observers trust and attribute more warranting value to information in a person’s social media account when third parties produce such information, and the account holder has no control over it (see also DeAndrea et al., 2018). In other words, if the observer knows that the sender can manipulate the information, its warranting value decreases (Walther, 2011; Walther & Parks, 2002), whereas the value increases if the sender cannot influence it (DeAndrea, 2014).

Collaborative hypertext dictionaries (CHDs), quite popular in Turkey, are deemed the very first examples of social media in the Web 2.0 era (Üngüren, 2019). CHDs are Web 2.0 projects based on interaction and host entries and comments from its members only. Once an entry is posted, members can share objective and subjective information and opinions about any topic, person, concept, or event. The content shared is unfiltered, and members can use nicknames, which may lead to the publication of erroneous or wrongful content that readers are responsible for filtering and checking. Also, the system does not allow a person to reply to a comment on their entry, so wrongful comments cannot be rectified. Thus, CHDs host various information about a single topic, which can be objective and true, just as it can be erroneous and manipulative (Yıldırım & Başer, 2016). These social media have been very popular in Turkey since their creation and have played a significant role in influencing public opinion when examining the patterns around people’s views on specific issues and considering the system’s self-regulation.

The identity of CHDs members is unknown and hidden under nicknames, which encourages them to comment more freely and triggers the online disinhibition effect (Suler, 2004), or the individuals’ tendency to express and do things online that they would not do in face-to-face situations. Suler (2004) examined this effect in six dimensions. One of these dimensions, dissociative anonymity, adequately reflects the status of CHD members since it is based on the idea that “as people move around the Internet, others they encounter can’t easily determine who they are” (Suler, 2004, p. 322). In addition, members can comfortably post and comment expressing negative feelings since their identity is protected. In this respect, CHDs differ from social media platforms like Facebook and LinkedIn. Although it is possible to open accounts using fake identities on these platforms, the individuals’ anonymity is much lower than that of CHD members.

CHDs are considered an informal source of information (Erdem & Bardak, 2010). However, it is a source widely used in Turkey to acquire information about people and events. The recruiters’ attitudes and decisions can lead to opinions about applicants, influenced by comments and views shared on CHDs. This study seeks to answer the question: Can CHDs offer warranties for recruiters within the scope of warranting theory? An experimental method (Fraenkel et al., 2012) was selected to identify the cause-and-effect relationship between variables. It was designed to evaluate the potential applicants via a fictional script. The impact on recruiters of reading positive or negative comments found on CHDs about the applicants was investigated in this study within the scope of a recruitment process. The findings of this research offer a theoretical contribution by strengthening the warranting theory and a practical contribution by revealing the effects of an applicant’s social media content on the perception of recruiters in the recruitment and selection process.

THEORETICAL PERSPECTIVE AND HYPOTHESES

Collaborative hypertext dictionary

CHDs are considered to be early examples of Web 2.0 and social media. CHDs are interactive dictionaries where member-writers can note their ideas or feelings in descriptions of events, persons, concepts, or comments (Bozkurt & Biroğul, 2012). On such platforms, there is a particular procedure and period where one can become a member and assume the status of member-writer. All member-writers on CHDs can share their opinions with others in a structure that favors the diversity of viewpoints (Duman & Özdoyran, 2018). Portraying information, news, comments, and other similar statements about any topic, event, or person, without any limitations of concepts, CHDs continuously develop thanks to entries posted by their members and the comments under the entries. However, this information and comments are not quite objective. They are subjected to personal bias, the comments are shared under nicknames and without identification, and the information may be erroneous, fragmented, or wrongful. Moreover, a person cannot reply to comments people make about them or establish a dialogue through the system, which ultimately leads to biased impressions and a lack of rectification when comments are incorrect or lack precision.

Ekşi Sözlük is a popular CHD in Turkey, being the most visited website daily and listed among the top 20 websites in the country. Its founder, Sedat Kaptanoğlu, warns that no filter guarantees that the information shared on the platform is accurate and trustworthy. According to Kaptanoğlu, the reader is responsible for checking the information and has the discretion to attribute value to the entries in the CHD (Telli, 2011). The former manager of İnci Sözlük (another popular CHD in Turkey), Gürkan Dündar, reinforced that the purpose of the platform is to provide entertainment and founders, employees, and members-writers do not really care about including impartial and accurate information (Bozkurt & Biroğul, 2012). Despite being a repository of unreliable information, these CHDs play an important role by influencing how individuals perceive a particular event. Furthermore, they are quite visible sources for those seeking information on a particular concept or person, contributing to forming public opinion.

Hypotheses development

Walther and Parks (2002) developed the warranting theory after Stone (1995) posited the concept of warranting for the first time within the scope of electronic communications. Walter (2011, p. 466) states that “warranting pertains to the perceived legitimacy and validity of information about another person that one may receive or observe online.” The warranting theory argues that the information in social network sites where the account owner has little control has higher warranting value and is more trustworthy for observers.

According to the warranting theory, information about a person is more reliable when produced by third parties (DeAndrea et al., 2018). People tend to trust more and attribute more warranting value to information that cannot be changed easily, and tend to attribute warranting value to information people produce about themselves only when the individual’s network of relationships verifies this content (DeAndrea & Carpenter, 2018; Walther, 2011; Walther & Parks, 2002). The basic tenet of the warranting theory states that online information about a person loses its unique value when the person controls such information (Walther et al., 2009).

Many studies explore the use of social media in recruiting, the recruiters’ criteria for selecting the social media platform they consult when screening and checking information about an applicant, and the recruiters’ purpose in using this strategy in the selection processes. Sameen and Cornelius (2013) identified that Social Networking Sites (SNSs) are common means to screen applicants during recruitment processes in small and medium enterprises. Recruiters stated that they could observe the applicants’ communication and occupational skills, their fit with the organization’s values, and examine many other factors to help decide to hire a professional by checking social media accounts. Melanthiou et al. (2015) also observed that SNSs are used to attract and screen potential applicants. Hoek et al. (2016) studied employers’ use of SNSs in selection processes. They found that Facebook is used to assess the applicants’ soft skills and to determine their organizational fit, whereas LinkedIn is used to evaluate professional qualities and determine whether the applicant is suitable for the job. The study, overall, concluded that SNS accounts became significant elements in recruitment processes; thus, what applicants share on SNS may have positive or negative impacts in the world of work. Another study conducted by Roulin and Bangerter (2013), on the other hand, found that LinkedIn was used to evaluate the applicants’ professional qualities and the person-job fit, and Facebook was used to evaluate the applicant’s personal qualities and person-organization fit

Bozkurt and Trıki (2016), in a study conducted in Tunisia, found that the applicant’s content on social media significantly influences the recruitment decisions of human resources managers. Becton et al. (2019) also concluded that unprofessional content and information shared on social media platforms might harm the applicants’ evaluation scores, regardless of their qualities. Hartwell (2015) also investigated how HR employees evaluate information about the applicant on social media assessment (SMA) during recruitment in the US. The author found that HR personnel considers the information on SMAs beneficial to assess the individuals’ attitudes, influencing hiring decisions. Wade (2015), on the other hand, used demographic similarity theory to examine how the applicants’ accounts on social media impact managers’ attitudes toward potential employees. The study concluded that recruiters are influenced by professional information the applicants share on social media, and information showing the applicants’ positive differential in the labor market improves the chances of hiring them. HR professionals tend to positively evaluate applicants when examining social media accounts reveals that the applicant is similar to them. Kluemper and* Rosen (2009), in a study conducted in the USA, revealed that applicants’ evaluations of five-factor personality traits, intelligence, and performance, are interpreted in line with the information found on their social media accounts.

Walther et al. (2009) set up a Facebook account for their research on the warranting theory. They observed that when there was a conflict between information disclosed by the account holder and information in a comment from a friend on the platform, observers make their decisions based on third-party comments rather than the information the account holder offers. In addition, Liu and Zhang (2020) conducted a study on bias toward ethnic groups within the framework of the warranting theory. Content shared by a Chinese international student on Facebook, and the posts shared by the student’s friends about them, were presented to the users. The research found that users evaluate the student by emphasizing the comments the others made about them. Overall, these studies show that warranties play important roles in shaping individuals’ attitudes toward others.

Moreover, what others say about a particular individual has more warranting value than what the person says about themselves. This research shows the same dynamic, where positive or negative information about individuals on Social Networking Sites (SNSs) impacts decision-makers. In this context, negative information is even more determinant. Based on these statements, we propose the following hypotheses:

• H1: Negative comments about the applicants on CHDs have a negative impact on hiring decisions.

• H2: Positive comments about the applicants on CHDs have a positive impact on hiring decisions.

METHOD

Procedure and sample

This quantitative study adopted an experimental method, which is the best fit to identify cause-effect relationships between variables (Fraenkel et al., 2012). The study employed a posttest-only control group design (PTOCGD), which randomly assigned subjects to either the experimental or control group. This design allows for manipulation of the independent variable and measurement of the dependent variable, making it suitable for identifying cause-and-effect relationships between variables. With sufficiently large sample sizes, the PTOCGD can effectively control threats to both internal and external validity.

The research model and relevant groups (Table 1) comprised three groups - one control group and two experimental groups.

Table 1
The experimental design of the study

Groups	Treatment	Posttest
R-C	-	O1
R-E1	X1	O2
R-E2	X2	O3

₁₂Source: Elaborated by the authors.

The sample consisted of board members, general managers, HR deputy general manager, accounting managers, and HR staff responsible for recruiting personnel to work in five-star accommodation companies in the Turkish regions of Alanya, Side, and Manavgat. The study was conducted during the COVID-19 pandemic between May 15, 2021, and October 30, 2021. Therefore, convenience sampling and snowball sampling methods were used to collect data. Research data was collected through face-to-face interviews, and interviewees were appointed to control and experimental groups randomly. In the first phase of the data collection, preliminary interviews were conducted with board members, general managers, and HR managers of companies selected based on the ease of access criterion. A total of 35 companies were approached and invited to participate, and 27 of them accepted the invitation, each one represented by one professional. The interviews occurred in their office after making an appointment and informing them of the nature of the study. After the interview, each participant was asked to suggest a maximum of three managers that he/she could direct within the scope of the research, and the contact information of the managers of the suggestions was obtained. Then, the interviews were continued by making an appointment with the people to whom the interviewed participants were directed. A total of 359 data were collected using the snowball sampling method.

The research comprises a fictional scenario and questions that are related to it. In the first stage of the study, respondents were informed about the experiment in written and oral forms. The fictional scenario posed to respondents was that they needed to hire a front-office manager for their company. They were handed two resumes; one referred to a highly qualified applicant (Applicant A) and the other to an applicant with standard competencies to perform the position (Applicant B). Respondents in the first experimental group were given the resumes of the applicants, along with the information that there were (negative) comments on CHDs about Applicant A. These comments were presented to them in written form. Respondents in the second experimental group were given the resumes, along with the information that there are (positive) comments on CHDs about Applicant B (also presented in written form). Later, respondents were asked to evaluate the resumes and answer questions about the applicant. The participants in the control group were not given positive or negative comments about the applicants they evaluated.

Materials and measures

Data was collected via questionnaires. The study uses a perceived person-organization fit assessment scale (α = 0.96) comprising four questions in order to measure respondents’ subjective perceptions of the applicants, which was developed by Kristof-Brown (2000) upon Cable and Judge’s (1997) work. The scale consists of four statements and adopts a 7-point Likert scale (1=not fit at all; 7=Completely fits). Front-office Manager (Level: 5) national (Turkey) occupational standards accepted by Vocational Qualifications (VQA), are used as bases to determine the required competence for front-office manager position (VQA, 2021). Accepted by VQA, national occupational standards represent the minimum norm, designating the required knowledge, skills, attitudes, and behavior for an occupation to be successfully performed. The statements in the scale were evaluated on a 7-point Likert scale (1=Not competent at all; 7=Very competent). Respondents’ intentions to hire were evaluated with three items from the scale Becton et al. (2019) adapted from the work of Cable and Judge (1997) (α = 0.93). High scores on this scale indicate the respondents’ likelihood of hiring the applicant. A 7-point Likert scale was also used to assess the statements in this scale. Two resumes were developed to evaluate two applicants applying for a front-office manager position at a five-star accommodation company. The first resume (Applicant A) represents a highly qualified applicant with competencies that exceed the standards for a front-office manager (FOM). The second resume (Applicant B) represents a qualified applicant with standard competencies for the position. Each version of the resume was prepared in a uniform shape and style. The manipulation variable was tested to determine whether positive or negative comments about the applicants on CHDs have an impact on how respondents evaluate the applicants’ resumes in the experiment group. Positive and negative content about the applicants was taken from content written about other people on another Turkish CHD, which is the most visited website daily in the country. A personal information form was used to determine the demographical attributes of participants.

Data analysis

The respondents’ demographic data were analyzed with frequency and percentage distributions. The measurement model, on the other hand, was tested with confirmatory factor analysis (CFA). Cronbach alpha internal consistency coefficients were calculated to determine the reliability of scales. Convergent validity and discriminant validity measurements were carried out to test whether the structures in the research model support the division. The relations between variables were used with correlation analysis. Experimental and control groups were compared via pairwise t-tests and one-way multivariate analysis of variance (MANOVA). For the evaluation of the results of the pairwise t-tests, Cohen’s d effect size values were used. Post Hoc tests were used for multiple comparisons of variables that yielded significant differences in MANOVA analysis.

RESULTS

Sample characteristics

Table 2 details the respondents and their distribution by control group, experimental group 1, and experimental group 2. A total of 367 individuals participated in the study as a result of the snowball sampling method (A more detailed description of the process of data collection is presented in the section on the procedure and the sample). There were 120 respondents in the control group, 139 in Experiment 1, and 108 in Experiment 2. A relatively homogeneous distribution with respect to the number of respondents in the groups was observed. All three groups comprise mostly male and married respondents. The majority of respondents are between the ages of 25 and 44. The respondents’ positions show that most respondents across the three groups are HR employees. Other positions also reveal a similar distribution according to groups. Nearly 90% of respondents in all three groups reported having a social media account.

Table 2
Demographic characteristics

	Control Group (n=120)	Experiment Group 1 (n=139)	Experiment Group 2 (n=108)	Total (n=367)
Gender (%)
Female	23.3%	33.8%	35.2%	30.8%
Male	76.7%	66.2%	64.8%	69.2%
Marital Status (%)
Single	32.5	33.1	33.3	33.0
Married	67.5	66.9	66.7	67.0
Age (%)
25-34 age	36.7	43.9	35.2	39.0
35-44 age	38.3	41.7	41.7	40.6
45-54 age	23.3	12.2	14.8	16.6
55 age and above	1.7	2.2	8.3	3.8
Education (%)
Primary education	2.5	0.70	-	1.1
High school	24.2	19.4	12.0	18.8
Associate's degree	26.7	33.8	21.3	27.8
Bachelor's degree	43.3	44.6	65.7	50.4
Postgraduate's degree	3.3	1.4	0.9	1.9
Departments/Positions (%)
HR Manager	18.3	10.1	14.8	14.2
HR Department employee	30.8	34.5	33.3	33.0
General manager	10.0	7.9	8.3	8.7
Deputy general manager	10.0	9.4	8.3	9.3
Board member	10.0	6.5	6.5	7.6
Front-office manager	6.7	12.2	10.2	9.8
Sales and marketing manager	7.5	9.4	9.3	8.7
Accounting and finance manager	6.7	10.1	9.3	8.7
Social media account (%)
Yes	90.0	93.5	88.9	91.0
No	10.0	6.5	11.1	9.0

Source: Elaborated by the authors.

Measurement model

Missing values and outliers were checked within the data set before the execution of the confirmatory factor analysis. Consequently, four data were excluded on the grounds of including more than 5% data loss. Mahalonobis’ distance was used to search for any outliers. The examination of Mahalonobis’ distances revealed no outliers, for no value above χ² (p = 0.001, df = 13) = 34,528 was observed (Tabachnick & Fidell, 2013). The measurement model in the study was tested with confirmatory factor analysis via AMOS 23. In order to examine the discriminant validity of the collected data and our structures, a two-step confirmatory factor analysis (CFA) was conducted in line with the recommendation of Anderson and Gerbing (1988). Validity and reliability analyses for each scale comprising the measurement model were conducted first, followed by testing the effects between structures in the model. According to the CFA results in Table 3, all standardized factor load values concerning scale items used to evaluate both applicants were between 0.632 and 0.961. All standardized loads were larger than 0.50, and all t-values were statistically significant (p < 0.05). Overall, the statistics of model goodness of fit for Applicant A (x² = 113,254, df = 62, x²/df = 1,827, p < 0.000, RMSEA= 0.048, CFI = 0.988, IFI= 0.988, NFI= 0.973, RFI= 0.966, SRMR = 0.0316) and statistics of model goodness of fit for Applicant B (x² = 113,780, df = 62, x²/df = 1,835, p < 0.000, RMSEA= 0.048, CFI = 0.985, IFI= 0.985, NFI= 0.967, RFI= 0.958, SRMR = 0.0280) reveal that the measurement model is acceptable. Skewness and kurtosis values of scale items in Table 3 were between +1.5 and -1.5; which shows that the data is suitable for the multivariable normality assumption (Tabachnick & Fidell, 2013). The statistical results reveal that the measurement model has acceptable values.

Table 3
Result of measurement model

	Applicant A				Applicant B
	Std. Fac. Load	t values	Skewness	Kurtosis	Std. Fac. Load.	t Values	Skewness	Kurtosis
Evaluation of Competence
Industry experience	0.78	Fixed	-0.65	-0.31	0.87	Fixed	-0.09	-0.36
Managerial experience	0.74	14.495*	-0.55	-0.74	0.87	22.793*	0.00	-0.27
Education level	0.72	14.082*	-0.91	-0.14	0.81	19.961*	0.21	-0.60
Field of education	0.73	14.178*	-0.85	-0.25	0.78	18.765*	0.11	-0.41
Foreign language knowledge	0.63	12.101*	-0.49	-0.38	0.75	17.614*	-0.08	-0.56
Competence in using front-office information technologies	0.72	14.012*	-0.69	-0.30	0.82	20.295*	-0.09	-0.51
Person-Organization fit assessments
This applicant fits with your organization.	0.86	Fixed	-0.52	-0.34	0.77	Fixed	-0.43	-0.25
This applicant is similar to other managers.	0.88	22.959*	-0.44	-0.42	0.72	13.783*	-0.68	-0.62
Other department managers will think this applicant fits well in your organization.	0.90	24.261*	-0.49	0.10	0.83	17.051*	-0.50	-0.38
This applicant would be compatible with your organization.	0.91	24.797*	-0.31	0.51	0.91	17.431*	-0.52	0.26
Recommendation to hire
I think he can work as a front-office manager in our company.	0.93	Fixed	-0.35	-1.03	0.86	Fixed	-0.45	-0.32
I invite him for the first interview.	0.94	34.212*	-0.17	-1.18	0.84	19.848*	-0.21	-0.87
I believe that if he is hired, he will perform successfully.	0.96	37.815*	-0.24	-1.12	0.90	21.438*	-0.22	-0.52

Source: Elaborated by the authors.

Convergent validity and discriminant validity

In addition to the goodness of fit indexes, convergent validity and discriminant validity values must be examined in testing the scales’ structural validity. As observed in Table 4, AVE and CR of the structures within the measurement tool to evaluate convergent validity and MSV and ASV values for discriminant validity were calculated. All AVE values regarding the scales must be greater than 0.50 for convergent validity, and CR values must be greater than 0.70 and than AVE values (Hair et al., 2010). According to the data in Table 4, AVE values are greater than 0.50, CR values are greater than 0.70, and AVE values. Therefore, all measurement models fulfill the requirement of convergent validity (Anderson & Gerbing, 1988). AVE values of factors being greater than MSV and ASV values, all MSV values being greater than ASV values, and the square root of AVE values being greater than the interdimensional correlation (> correlation between factors) points to the existence of discriminant validity. Table 4 shows that these conditions are met (ASV < MSV < AVE). Consequently, discriminant validity was acquired (Fornell & Larcker, 1981). The Cronbach Alpha values of the scales, greater than 0.70, show that scales are within the limits of high reliability.

Table 4
Convergent validity and discriminant validity

	Applicant A								Applicant B
	1	2	3	α	AVE	CR	MSV	ASV	1	2	3	α	AVE	CR	MSV	ASV
(1)EVACOM	[0.72]a			0.86	0.52	0.87	0.49	0.39	[0.82]a			0.92	0.67	0.92	0.36	0.27
(2) PORFIT	0.55**	[0.89]a		0.93	0.79	0.94	0.69	0.49	.44**	[0.81]a		0.87	0.66	0.88	0.21	0.20
(3)RECTOH	0.70**	0.83**	[0.94]a	0.95	0.89	0.96	0.69	0.58	.60**	.46**	[0.87]a	0.89	0.75	0.90	0.36	0.28

(1) Evaluation of Competence; (2) Person-Organization fit assessments, (3) Recommendation to hire,
• ^**
  p < 0.01, α = Cronbach, a = The square root of the AVE = Average Variance Extracted, MSV = Maximum Shared Variance, ASV = Average Shared Squared Variance
Source: Elaborated by the authors.

Hypotheses testing

Paired sample t-tests were used to determine whether or not respondents’ evaluation of applicants statistically differed according to control and experimental groups. According to the paired sample t-test results (Table 5), respondents’ scores for Applicant A and Applicant B for occupational competence [t₍₁₁₉₎ = 39.03 p < 0.01, Cohen’s d = 4.91), person-organization fit [t₍₁₁₉₎ = -9.59, p < 0.01, Cohen’s d = 2.65) and recruitment intentions [t₍₁₁₉₎ = 28.13 p < 0.01, Cohen’s d = 2.98) differed in a statistically significant way. Even though the paired sample t-tests results were statistically significant, Cohen’s d effect size values were calculated to understand the effect size. It would be weak when Cohen’s d value is less than 0.2, medium when it is 0.5, and strong when greater than 0.8. Accordingly, important differences can be observed in evaluating applicants in the control group. Respondents in the control group evaluated Applicant A more positively than Applicant B in occupational competence [M_(A) = 6.83, M_(B) = 4.39], and recruitment intentions [M_(A) = 6.37, M_(B) = 4.40]. Applicant A was also evaluated with lower scores concerning person-organization fit [M_(A) = 4.59, M_(B) = 5.51] in the control group. In Experimental 1 group, where negative manipulation concerning Applicant A was provided, applicants’ occupational competence [t₍₁₃₈₎ = 9.74, p < 0.01, Cohen’s d = 1.23), person-organization fit [t₍₁₃₈₎ = -40.47, p < 0.01, Cohen’s d = 4.60), and recruitment intentions [t₍₁₃₈₎ = -27.30, p < 0.01, Cohen’s d = 2.79) differed in a statistically significant way. There are great differences between the applicant evaluations in the Experimental 1 group, which can be interpreted with the negative impact manipulation has on the respondents. Respondents in Experiment 1 group positively evaluated Applicant B for person-organization fit [M_(A) = 2.65, M_(B) = 6.17], deemed Applicant B adequate in terms of occupational competence [M_(A) = 5.93, M_(B) = 5.23] and favored Applicant B in their recruitment intentions [M_(A) = 2.98, M_(B) = 5.88]. Finally, in the Experimental 2 group, positive manipulation was provided concerning Applicant B. According to the paired sample t-tests results, which can be found in Table 5, evaluations of respondents in Experimental 2 group differed in a statistically significant way for Applicant A and Applicant B concerning occupational competence [t₍₁₀₇₎ = 8.35, p < 0.01, Cohen’s d = 1.18), person-organization fit [t₍₁₀₇₎ = -29.88, p < 0.01, Cohen’s d = 3.81] and recruitment intentions [t₍₁₀₇₎ = 19.87, p < 0.01, Cohen’s d = 2.74). Respondents in the Experimental 2 group evaluated Applicant B positively for person-organization fit [M_(A) = 4.13, M_(B) = 6.25], deemed Applicant B occupationally competent [M_(A) = 6.26, M_(B) = 5.76] and favored Applicant B in their recruitment intentions [M_(A) = 4.63, M_(B) = 6.17]. Varying evaluations concerning Applicant A and Applicant B in control and experiment groups reveal the influence of comments about applicants that can be found on CHDs on how they are evaluated.

Table 5
Paired-sample t-tests results to compare applicants in control and experiment groups

	Control Group (n = 120)				Experiment Group 1 (n = 139)				Experiment Group 2 (n = 108)
	Applicant A	Applicant B			Applicant A	Applicant B			Applicant A	Applicant B
	Mean	Mean	t	d	Mean	Mean	t	d	Mean	Mean	t	d
EVACOM	6.83	4.39	39.03*	4.91	5.93	5.29	9.74*	1.23	6.29	5.76	8.35*	1.18
PORFIT	4.59	5.51	-9.59*	1.32	2.65	6.17	-40.47*	4.6	4.13	6.25	-29.88*	3.81
RECTOH	6.37	4.4	28.13*	3.38	2.98	5.88	-27.30*	2.79	4.63	6.17	-19.87*	2.74

EVACOM: Evaluation of Competence; PORFIT: Person-Organization fit assessments, RECTOH: Recommendation to hireSource: Elaborated by the authors.

In order to determine whether the occupational competence, person-organization fit, and recruitment intention scores of Applicant A and Applicant B differ significantly between the control group and the experimental groups, a one-way MANOVA analysis was executed. According to MANOVA results (Table 6), respondents evaluated Applicant A and Applicant B differently in both control and experimental groups, while the evaluation scores of applicants revealed statistically significant differences by groups (Pillai’s Trace = 1.322, F _(6,359) = 116.947, p < 0.001, partial ƞ² = 0.661). Taking into consideration the effect value levels (0.01 = low, 0.06 = moderate, 0.14 = high), argued by Tabachnick and Fidell (2013), respondents’ groups (control and experimental groups) can be claimed to have a substantial effect (partial ƞ² = 0.661) on the applicant evaluations. The highest effect by groups in the evaluation of Applicant A, who had a very qualified resume, was observed on recruitment intention (F = 430.666, p < 0.01, η2 = 0.703), followed by person-organization fit (F = 250.315, p < 0.01, η² = 0.579) and occupational competence (F = 58.577, p < 0.01, η2 = 0.466). The highest effect by groups in the evaluation of Applicant B, who had the qualified resume, on the other hand, was observed on recruitment intention (F = 288.275, p < 0.01, η2 = 0.613), followed by occupational competence (F = 174.942, p < 0.01, η2 = 0.490) and person-organization fit (F = 48.413, p < 0.01, η² = 0.210). Differing evaluations of the same applicants in experimental and control groups indicate that the manipulation effect worked. The results (Tables 5 and 6) showed that positive or negative comments about the applicants on CHDs significantly impact how respondents evaluate the applicants, supporting hypotheses H1 and H2.

Table 6
Multivariate Analysis of Variance (MANOVA) results

Applicant	Dependent Variable	GROUP	n	Mean	Std. Error	95% Confidence Interval		F	η2	Post Hoc
						Lower Bound	Upper Bound
Applicant A	EVACOM	Control Group (a)	120	6.83	0.04	6.76	6.90	58.58*	0.466	ab.c. ba.c. ca.b
		Experiment Negative (b)	139	5.93	0.03	5.87	6.00
		Experiment Positive (c)	108	6.29	0.04	6.21	6.36
	PORFIT	Control Group (a)	120	4.59	0.07	4.46	4.72	250.32*	0.579	ab.c. ba.c. ca.b
		Experiment Negative (b)	139	2.65	0.06	2.53	2.77
		Experiment Positive (c)	108	4.13	0.07	3.99	4.27
	RECTOH	Control Group (a)	120	6.37	0.09	6.20	6.53	430.67*	0.703	ab.c. ba.c. ca.b
		Experiment Negative (b)	139	2.98	0.08	2.83	3.14
		Experiment Positive (c)	108	4.63	0.09	4.45	4.80
Applicant B	EVACOM	Control Group (a)	120	4.39	0.05	4.28	4.49	174.94	0.490	ab.c. ba.c. ca.b
		Experiment Negative (b)	139	5.29	0.05	5.19	5.38
		Experiment Positive (c)	108	5.76	0.06	5.65	5.87
	PORFIT	Control Group (a)	120	5.51	0.06	5.40	5.63	48.41	0.210	ab.c. ba. ca
		Experiment Negative (b)	139	6.17	0.05	6.07	6.28
		Experiment Positive (c)	108	6.25	0.06	6.13	6.37
	RECTOH	Control Group (a)	120	4.40	0.06	4.29	4.51	288.26	0.613	ab.c. ba.c. ca.b
		Experiment Negative (b)	139	5.88	0.05	5.78	5.98
		Experiment Positive (c)	108	6.17	0.06	6.05	6.29

EVACOM: Evaluation of Competence; PORFIT: Person-Organization fit assessments, RECTOH: Recommendation to hireSource: Elaborated by the authors.

DISCUSSION AND CONCLUSION

CHDs have become some of the most visited websites in Turkey, offering a structure that allows interaction and access to original content. It is an environment to discuss and criticize any daily life issue, and comments on the platform play a significant role in forming public opinion. For example, member-writers of the platform Inci Sözlük, one of the most popular CHDs in Turkey, nominated the kiosk operator Ahmet Yılmaz from Eskişehir in the 2011 general elections offering financial support for him to run as an independent parliamentary candidate (Üngüren, 2019).

The literature on social recruiting showed that LinkedIn and Facebook are platforms often used (Becton et al., 2019; Caers & Castelyns, 2011; Hoek et al., 2016; Koch et al., 2018; Liu & Zhang, 2020; Melanthiou et al., 2015), but this study explores the CHDs seeking to answer the research question: “Can CHDs offer warranties for recruiters within the scope of warranting theory?” The section on theoretical perspectives started to answer the question, suggesting that CHDs may offer a warranty value like other social media tools. In these platforms, only members can make comments under entries, and the system does not allow replying to comments - different from the features observed in other social media platforms such as Facebook and LinkedIn. Since all the comments are made by people other than the member-writer that produced the entry, the warranting value would be high. Based on this characteristic of the platform, the study suggests that the warranting value is generated by third parties’ comments on content a person (in this case, an applicant for a job going through a selection process) shared on CHD about themselves. According to the warranting theory, what others say and comment about a person has a much more significant impact than what this person says about themselves (Carr, 2019; DeAndrea, 2014; DeAndrea et al., 2018; Peterson & High, 2021; Walther & Parks, 2002).

The study concluded that positive and negative comments about the applicants on CHDs significantly impact hiring decisions, supporting the hypotheses. Therefore, negative comments negatively impact the recruiter’s hiring decision, whereas positive comments positively impact hiring decisions. The findings of this study corroborate the literature. Chang and Madera (2012) found that 50% of HR managers in accommodation companies use social media to check applicants for managerial positions and reception. The study concluded that HR managers deem negative information on social media more important than positive information. Alarcon et al. (2019) also found that positive information about the applicant on social media is associated with crucial elements for hiring, such as compatibility, perceived interpersonal skills, and recruitment recommendations. Consequently, positive and negative information and comments about applicants on social media affect hiring decisions, and negative information and comments are more influential than positive ones.

As a result of the study, negative and positive comments about applicants on CHDs are considered warranties in recruitment processes. Posited for the first time by Walther and Parks (2002), the warranting theory claims that information about a person on social media has higher warranting value and is considered more trustworthy when the person has no control over it. The system of the CHDs does not allow an individual to reply to a comment made by a third party (Üngüren, 2019). Thus, the individual cannot change people’s comments about them on the platform. From this perspective, this study views CHDs as significant sources aligned with the warranting theory.

It is deceiving to think that information on social media always reflects the truth. The literature shows that information about an applicant collected from social media, may yield some issues, when they are used in important decisions such as recruitment, which can significantly impact the future of both the company and the applicant. To name a few; negative information may not be assessed in the right context and may give way to making quick decisions (Brown & Vaughn, 2011). Another reason is that information about the applicant on social media may be rearranged within the scope of the qualities employers expect and can hence be deceptive (Kroeze, 2015; Suder, 2014). Moreover, as employers use social media for recruitment purposes, it may lead to negative consequences such as the violation of privacy - a concept that has been approached within the context of negative consequences of recruitment via social media (Kroeze, 2015). Slovensky and Ross (2012), in addition, argued that applicants may regret social media content they posted in the past; these posts may not reflect their personalities today and the personalities applicants display on social media networks may be different than their true personalities. Wade (2015) also stated that legal debates have become more visible, as people may be disregarded in a hiring process due to images or comments on Twitter, Facebook or other social media platforms or due to firms screening throughout the job seekers’ Facebook pages. Applicants, who apply for a job, cannot always control information about them on social media. Consequently, they may suffer losses because of others’ comments about them (Van Iddekinge et al., 2016). In this context, individuals must be careful in evaluating positive or negative comments about others on CHDs. Checking whether or not comments reflect the truth by consulting with other information sources would yield better results.

Theoretical and practical implications

The results of this study contribute to the warranting theory. Warranting theory has been examined before within the context of various social media tools such as social networks, online dating sites, e-commerce sites and hotel review sites. Considered as informal sources of information in this study, CHDs can also provide warranties value during the recruitment process with the comments they contain. Online information today significantly impacts individuals. From this perspective, CHDs can be claimed to serve to an importance purpose in forming opinions without any formal value for people (Erdem & Bardak, 2010). At the same time, positive or negative impression about a person contributes to the social perception theory, halo and horn effect, which is described as the tendency to generalize all the qualities of the analyzed subject. This study also explores coming to a general opinion about a person with the help of positive and negative comments and making a decision. Within the scope of this study, it was observed that positive comments about an applicant on CHDs give way to a positive evaluation of all qualities of an individual, whereas negative comments cause an overall negative evaluation of the person’s qualities.

Comments on social media do not always reflect the truth. Therefore, when comments about applicants on CHDs or other similar sites are read, the truth behind them must be questioned. This is why recruiters must be careful when using social media profile content to screen applicants. Especially today, when using social media in recruiting is inevitable, recruiters should be trained in social media use or informed about which information to take into account, as they evaluate applicants, which would contribute to the making of right decisions.

Limitations and future directions of research

The study was conducted during the COVID-19 pandemic and was limited by its circumstances. The study was carried out within the framework of a fictional recruitment scenario, and comments about the fictional applicants were collected from CHDs, originally directed to other people. Respondents in the experimental group were only offered positive or negative content concerning an applicant within the scope of the manipulation effect. Further studies focus on testing the impact of mixed content with positive and negative comments about an applicant can contribute to understanding the impact of CHDs in warranting. Furthermore, the fictional applicants were male. Walther et al. (2008) stated that the evaluation of a person based on the information about them on social media accounts differs according to gender. In another study conducted by El Ouirdi et al. (2016), on the other hand, it was found that the recruiter’s gender and nationality may also impact the evaluation of applicants by way of social media content. Future studies focusing on individual characteristics such as personality, social characteristics such as culture, and the evaluator’s demographics such as gender and nationality, would substantially enrich the relevant literature.

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Publication Dates

• Publication in this collection
  31 July 2023
• Date of issue
  2023

History

• Received
  22 Oct 2022
• Accepted
  13 Mar 2023