THE INFLUENCE OF AGE, LEVEL OF EDUCATION, AND THE PERSONALITY TRAITS EXTRAVERSION, OPENNESS TO EXPERIENCE AND NEUROTICISM ON THE ATTITUDES TOWARDS RECRUITMENT THROUGH SOCIAL NETWORKING
SITES IN COMPARISON TO TRADITIONAL RECRUITING MEANS
Master’s thesis
MSc. Human Resource Management MSc. Marketing
University of Groningen Faculty Economics and Business
Chantal Hagen Student number: s1768395
Gorechtkade 86
B9713 CG Groningen Tel: +31 (0)6 13 50 94 23 chantalberdinehagen@gmail.com
Supervisor Prof. dr. E. Molleman
Co-assessor Prof. dr. P.C. Verhoef
Acknowledgements:
Helpful comments on earlier versions of this thesis were provided by my supervisor Eric Molleman,
whom I want to thank for his support, time, and input during the process. I also want to thank Peter
Verhoef for his valuable input for making sure this thesis was also acceptable from a Marketing
perspective.
2 ABSTRACT
This study examined the influence of age and level of education on the attitudes towards recruitment through social networking sites and traditional recruitment means by an online survey among 167 individuals. Besides, the personality traits extraversion, openness to experience and neuroticism, which are determined to play a role in technology acceptance, were tested on attitudes towards recruitment through social networking sites. In the second part, the influence of age and level of education on the intent to use online or offline channels is addressed. This study found a negative relation between age and attitudes towards recruitment through social networking sites. A positive relationship was found between level of education and attitudes towards recruitment through social networking sites. The personality trait extraversion had a positive effect on attitudes towards recruitment through social networking sites. The second part showed that elderly individuals and lower educated people intent to use offline channels in their job search, and younger individuals and higher educated people online channels. In addition to the first part, supplementary analyses were performed for a more in-depth understanding of the relation between age and level of education and the different recruiting means. A notable finding is the concern about privacy of recruiting means, especially among elderly individuals and higher educated people.
Keywords: Social networking sites, Traditional recruitment, Recruitment, Multichannel
3 INTRODUCTION
The labor market is changing. Organizations have always been concerned with attracting and selecting the right type of employees, however, due to the aging population it deserves special attention (European Commission, 2010; Rynes & Barber, 1990). Human capital is arguably the most valued asset of an organization and is primarily responsible for adding value to all parts of the organization. Due to the expected labor shortage the importance of applicant attraction for organizations increases. Besides the content of the job advertisement, the channel through which people are recruited can also play a role. Especially as more and more channels emerge, it might be valuable for an organization to know what the attitudes are towards these different channels, what channels individuals intent to use, and which one(s) may be best to focus on for their particular target group.
Besides the importance for companies to know what the attitudes towards the different recruitment means are and through which channel they can reach the kind of employee they are looking for, it is relevant to know whether it is useful to approach them through multiple channels. In marketing a multichannel approach has already proven its relevance. Neslin, Grewal, Leghorn, Shankar, Teerling and Thomas (2006) for example, showed that consumer segmentation is a critical aspect of an effective multichannel strategy design. Numerous researches have already used the channel usage of consumers as a base for segmentation (Konus, Verhoef & Neslin, 2008). In human resource management however, there is hardly any research done concerning this topic. It is often said that recruiters need to think more like marketers when it comes to attracting potential employees. “Job candidates today need to be approached in much the same way as prospective customers: carefully identified and targeted, attracted to the company and its brand, and then sold on the job,” according to Peter Cappelli in Harvard Business Review (2001: 140). However, to my knowledge, there is a lack of academic research concerning this topic.
The recruiting process has changed significantly over the last few decades; a shift to online
recruitment has taken place. Especially the use of social media, which are a hot topic and often used
4 in business nowadays, is an emerging issue. Although the use of the internet for, for example, job- postings and tests has become quite common in human resources (HR), the use of social networks in the process of recruiting and hiring is relatively new (Davison, Maraist & Bing, 2011). A survey conducted in 2008 by the Society of Human Resource Management showed that in 2006 only 21% of the organizations used social networking sites as an HR tool. In 2008 it has grown to 44% of the organizations. Nowadays, about 75% of HR professionals use social networking sites in their recruiting process (Job Doctor Board, 2013). The use of social networking sites like Facebook, Twitter and LinkedIn for recruiting purposes seems to be widely accepted, since it is used so often and is closely related to posting a job advertisement on the internet. From a recruiter’s perspective this tool keeps on rising in popularity and investments in offline tools are decreased (Sinha & Thaly, 2013).
However, feelings of potential employees about this new type of approach is not known. Despite its large use, little empirical research has been conducted on using social networking sites to recruit employees (Davison, Maraist & Bing, 2011). One of the important areas of research is whether applicants consider the posting on the social networking sites for example favourably and reliable, particularly in comparison to more traditional recruiting means like job postings on company websites or print advertisements. Because social networking sites are not publicly accessible (even though most individuals can get an account on the major sites), applicants may evaluate the favourability and reliability of using these sites for job postings differently from postings on company websites or other traditional recruitment means (Davison, Maraist & Bing, 2011).
Thus not much is known about the attitudes towards recruitment through social networking
sites as compared to traditional recruitment means, and the way people would like to be approached
and apply. To come up with segmentation it is important to know what the attitudes of people of
different ages and with different levels of education are towards the different recruiting means. The
variable age is selected, as it plays an important role in understanding human behaviour and
perceptions (e.g. Cole & Balasubramanian, 1993; Goldberg, Finkelstein, Perry & Konrad, 2004; Yoon,
1997). Level of education is related to the adoption of new technology, so might also influence the
5 channel use in the job search of an individual (Porter & Donthu, 2006).
Besides, the main effect of three personality traits, namely extraversion, openness to experience and neuroticism, on the attitudes towards recruitment through social networking sites is tested. These are selected, as they are considered most important in technology acceptance and social media use (Kim, Hsu & Zuniga, 2013; Ross, Orr, Sisic, Arseneault, Simmering & Orr, 2009). This results in the following research question:
What are the attitudes of applicants towards recruitment through social networking sites, particularly in comparison to more traditional recruiting means, and do age, level of education, and the personality traits extraversion, openness to experience and neuroticism, influence their attitudes?
As mentioned above, a shift to online recruitment has taken place. As traditional recruiting means exist of online and offline channels, it is relevant to make a distinction between both and determine the applicants’ intent to use. In multichannel research in marketing, more attention is paid to this distinction and is elaborated on for instance the combination and synchronization of these channels. In HR, there is less research concerning this topic. Investments in offline recruitment such as newspaper advertisements are extremely decreasing (Sinha & Thaly, 2013), but it might be possible that not every type of job seekers shifts to online channels. Therefore, the second question that is addressed concerns the intent to use online or offline channels in the applicants’ job search.
The following question is formulated:
Are people intended to use online or offline channels in their job search?
THEORETICAL BACKGROUND
Employees as brand
Sustainable competitive advantages are no longer derived from the product only; they are
increasingly delivered through memorable, branded experiences. This has established an ‘experience
economy’ where the employees are the brand (Goldberg & Cerullo, 2006). This central role of the
6 employee, especially in the service sector, is often emphasized in the marketing mix by adding a fifth P, namely ‘People’ (Berry, 2000). The employees’ performance plays a vital role in the success of a service brand (Morhart, Herzog & Tomczak, 2009). This makes recruitment an essential aspect of a company’s daily tasks. “Service providers make or break a brand; for the customers’ actual experiences with the service always prevail in defining the brand for them” (Berry, 2000: 135). Not only the way how employees act and what they do influences the brand, but also how they appear to the customer (Davies & Chun, 2010). Take for example Abercrombie and Fitch, who recruits her employees as much as on their abilities to sell as on their physical appearance, and ethnic restaurants who recruit staff from the same ethnicity, because being served by someone of the same culture is inherent to the customer experience (Davies & Chun, 2010). Starbucks prevails to spend even more on partner recruitment and development than it does on advertising (Weber, 2005).
Companies expect their employees to behave as brand ambassadors by communicating the values of the corporate brand in the way they act and interact with consumers (Harris & de Chernatony, 2001).
Finding employees that fit the brand therefore is an important success factor.
Recruitment
Recruitment is a fundamental function of human resource management, which can be
defined as the process of searching the right talent and stimulating them to apply for a job in the
organization. It is the process of finding the right personnel that meets the requirements for a
particular position, and attracting sufficient applicants to make an effective selection (Sinha & Thaly,
2013). The ongoing technological developments influence the several recruiting strategies companies
use. The recruiting process has changed significantly over the last few decades. It has grown to a
multibillion-dollar industry and a shift to online recruitment has taken place; the internet has
become a widely adopted medium by both recruiters and job seekers. Especially the use of social
networking sites is rising. Recruiters nowadays prefer recruitment through social networking sites
above traditional recruitment means, because of the accessibility without costs (Jacobs, 2009) and
7 the provided information by potential employees (Shea & Wesley, 2006; Withiam, 2011), which is perceived as reliable (Kluemper & Rosen, 2009). As mentioned above, 75% of the HR professionals nowadays use social networking sites as a recruitment tool (Job Doctor Board, 2013). However, it is not known if the potential employee values this way of recruiting as much as the HR professionals do. It might possibly seem not reliable or they may be worried about their privacy.
Social networking sites
The first social networking applications started in 1997 (Messinger, Stroulia, Lyons, Bone, Niu, Smirnov & Perelgut, 2009). It has become a global phenomenon and quickly grew in popularity.
Ever since, these sites attracted millions of users, many of whom use it in their daily activities for the most varied purposes. Social networking sites can be defined as web-based services that allow individuals to (1) create a public or semi-public profile within a defined system, (2) compile a list of other users with whom they share a connection, and (3) view the list of their connections and those lists made by other individuals within the system (Boyd & Ellison, 2007).
In HR social networking sites have become a commonly used tool and currently are one of the more widely used methods for organizations to attract employees (Nixon, Ciuca, Venditti, Desormeaux & Dynan, 2012). Social networking sites offer new opportunities from the side of the jobseekers as well. They make it easier for them to approach those who make hiring decisions (Medera, 2012). From the field of recruitment, social networking sites serve two main purposes.
Firstly, they function as a marketing tool. Employers can use it to market themselves to jobseekers,
and vice versa. On Facebook for example, users can ‘like’ or share a vacancy post, also when they are
not going to apply, which raises the overall profile and awareness of the organization (Broughton,
Foley, Ledermaier & Cox, 2013). Secondly, employers use it to conduct online character checks that
includes reviewing information posted on the job applicants’ social networking sites, what can be the
decisive factor in hiring an applicant (Clark & Roberts, 2010). Through these social networking
channels employers can gain a broader image of a potential employee than through the traditional
recruiting means (Broughton, Foley, Ledermaier & Cox, 2013). In the current study, the social
8 networking sites Facebook, Twitter and LinkedIn will be studied, as these are the most popular social media sites used for recruiting (Jobvite, 2014).
Traditional recruitment
As mentioned before, traditional recruitment means are used less and less, because of for instance higher costs and the amount of information provided by alternatives. Some recruiters even expected the end of traditional recruitment tools. Newspaper advertisements for example have decreased from 50% of all applicants applying through this channel, to only 10% in the last 13 years (Sinha & Thaly, 2013). There is much research conducted concerning the attitudes of the recruiter towards online recruitment and the use of social networking sites, but there is not much known about the opinion from the perspective of the applicant. Traditional recruitment means may include both online and offline channels, for instance print advertisements (newspapers, magazines, etcetera), company’s official websites, recruitment agencies and job boards (Sinha & Thaly, 2013).
Attitudes
Throughout the years extensive research is done towards the acceptance of new technology and innovations (for example Gilly & Zeithaml, 1985; Davis, 1989; Morris & Venkatesh, 2000; Chung, Park, Wang, Fulk & McLaughlin, 2010). These studies indicate that attitudes toward technology are critical aspects in accepting and actually using new technologies. Some of the attitudes measured in these researches are also valuable to assess attitudes towards the different recruitment tools.
Perceived ease of use and perceived usefulness for instance, which are determined to be the most fundamental for defining a positive attitude towards technology (Choi & Chung, 2013). Perceived ease of use measures the efforts a person needs to use the system (Davis, 1989; Lee & Tsai, 2010).
Perceived usefulness is defined as the degree to which an individual believes a particular system
would enhance his or her job performance (Davis, 1989). Another factor that could determine the
attitude is the perceived privacy, as this is an important concern for people who engage in online
activities (Chung et al., 2010). Besides, the perceived quality will be measured, because the success
9 of a specific technology is often associated with the quality of information and services it provides (DeLone & McLean, 1992; Chung et al., 2010). Lastly, some variables are added about other general concerns, like reliability and accessibility. First all these factors are measured as one attitude. Then a distinction between the factors will be made to discover underlying reasons and explain the differences. In the method section, the specific questions are discussed.
Age
The attitudes towards the channel through which a job is posted could be influenced by the age of the person. Age differences play an important role in understanding human behaviour and perceptions (e.g. Cole & Balasubramanian, 1993; Yoon, 1997; Goldberg, Finkelstein, Perry & Konrad, 2004). The attitude and actual behaviour with regard to technology adoption are critically linked to a user’s age (Hong, Lui, Hahn, Moon & Kim, 2013).
Research indicates that older individuals, aged 50 and above, prefer to use technological innovations less than those aged between 20 and 49 (Lerouge, Newton & Blanton, 2005). According to Porter and Donthu (2006) it is likely that learning to use innovations would create an anxiety provoking situation amongst the higher aged potential users, since they have limited experience in using computers and the internet in comparison to their younger counterparts. Although admitting the relevance of the internet in their lives; they perceive it as difficult to use.
Besides, privacy may play a different role in the various age groups. Research of Peluchette and Karl (2009) showed that ‘Generation Y’ is less concerned about privacy than prior generations.
Generation Y is the group of individuals aged from 14 to 32 years old that is crowned as digital natives, a generation who has never known a world without internet (Jones, Ramanau, Cross &
Healing, 2010; Palfrey & Gasser, 2008; Prensky, 2005; Small & Vorgan, 2009). These people are more
digitally connected than any other generation, and it is expected that they remain connected this
way in the future, in all aspects of their lives (Davis, Deil-Amen, Rios-Aguilar & Gonzalez Canche,
2012). The older generation, however, did not grow up with this kind of technology and these kinds
10 of websites, or has more limited access to the technology. From that point of view they may consider recruiting through these sites to be less acceptable. So it might be the case that younger individuals are more accepting towards recruiting through social networking sites than older individuals.
Hypothesis 1a
Age is negatively associated with the applicants’ attitudes towards recruitment through social networking sites.
Due to the privacy concerns mentioned above and the possible anxiety elderly individuals experience, they might prefer tools they are more familiar with. Because of the expectation that elderly individuals may consider recruitment through social networking sites less acceptable, it is likely that they prefer traditional recruiting means above social networking sites.
Hypothesis 1b
Age is positively associated with the applicants’ attitudes towards recruitment through traditional recruiting means.
Level of education
Another factor that could influence the attitudes towards a recruitment channel is the level of education. Social networking sites are relatively new and there is not much investigated concerning this topic and different educational levels. However, there is more known about the relation between the use of innovations and the level of education. According to Porter and Donthu (2006) the decision to adopt a new technology is related to the amount of knowledge an individual has with respect to how to use technology appropriately. Early adopters of new technologies generally have higher educational levels and better knowledge, which might be related to their ability to understand new technologies quicker than those who are less educated.
Besides that, more specific research regarding the internet and the level of education shows
that people with less education address insufficient knowledge as one of the main reasons for not
using the internet (National Telecommunications and Information Administration, 2002). They also
11 may perceive more computer anxiety and have less sophisticated cognitive structures that hinder their capability to learn in new environments (Hilgard & Bower, 1975; Porter & Donthu, 2006).
Furthermore, research also found a positive relationship between the level of education and the perceived ease of using the internet (Agarwal & Prasad, 1999). Those innovations that are perceived to be easier to use, are more likely to be accepted, which might result in a higher likelihood of actual use by higher educated people (Davis, Bagozzi and Warshaw, 1989).
Hypothesis 2a
Level of education is positively associated with the applicants’ attitudes towards recruitment through social networking sites.
Social networking sites, opposed to traditional recruitment, are only online. Since lower educated people use the internet less because they have insufficient knowledge and perceive more computer anxiety (Hilgard & Bower, 1975; Porter & Donthu, 2006), and applying through social networking sites is relatively new, it is likely that lower educated people prefer traditional recruiting means above social networking sites.
Hypothesis 2b
Level of education is negatively associated with the applicants’ attitudes towards recruitment through traditional recruiting means.
Personality
Research showed that personality is related to key dimensions of technology acceptance
(Barrick & Mount, 1991; Barrick, Mount & Judge, 2001; Deng, Liu, Li & Hu, 2013). McElroy,
Hendrickson and Townsend (2007) found that personality is a more superior predictor of internet use
than cognitive variables. Previous research mainly focused on personality and internet use. However,
there is a limited understanding of how personality affects the attitudes towards social networking
sites, especially in recruitment. Therefore, the main effect of personality on attitudes towards
recruitment through social networking sites will be addressed.
12 Personality can be defined as a stable set of characteristics and tendencies which determine commonalities and differences in people’s psychological behavior, such as thoughts, feelings, and actions (Deng et al., 2013). The Big Five personality factors are one of the most used characteristics to investigate human personalities. The model consists of five key factors, namely agreeableness, conscientiousness, extraversion, openness to experience, and neuroticism. The role that extraversion, openness to experience, and neuroticism might play in forming attitudes about recruitment through social networking sites will be highlighted. These three traits are selected, as they are considered most important in technology acceptance and social media use (Zywica &
Danowski, 2008; Ross, Orr, Sisic, Arseneault, Simmering & Orr, 2009; Kim, Hsu & Zuniga, 2013).
First of all, extraversion. Extraversion is defined in terms of being sociable, gregarious, ambitious, outgoing, talkative, and assertive (McCrae & Costa, 1989; Mount & Barrick, 1995; Deng et al., 2013). Besides that, extraverted people place a high value on close and warm interpersonal relationships (Watson & Clark, 1997). Deng et al. (2013) specifically conducted research on the impact of extraversion on individuals’ social networking sites use, and found that extraversion has a significant influence on social networking perceptions and continuance intention. Highly extraverted people are naturally inclined to care about their image and other social consequences of behavior, and therefore more likely to have a social network profile. Besides that, they are less resistant to change and may even welcome it (Oreg, 2003; Saksvik & Hetland, 2009). Because extraverted people are less resistant to change and are more likely to have a social networking profile, it is likely that they will have a positive attitude towards recruitment through social networking sites.
H3: Extraversion is positively associated with the applicants’ attitudes towards recruitment through social networking sites.
Openness to experience refers to the extent to which a person is willing to try new and
different things (Deng et al., 2013). This personality trait is most likely to be associated with trying
new communication methods, and new and innovative experiences (Butt & Philips, 2008) These
persons are actively looking for new and varied experiences, and value change (McCrae & Costa,
13 1997). Individuals high in openness to experience are more likely to hold positive attitudes and cognitions towards accepting new technologies and approaches (Deng et al., 2013). This might implicate that individuals who score high on openness to experience have a positive attitude towards recruitment through social networking sites.
H4: Openness to experience is positively related to the applicants’ attitudes towards recruitment through social networking sites.
People who score high on neuroticism have the tendency to be anxious, self-conscious, and paranoid. They show a lack of psychological adjustment and emotional stability (Lin & Lu, 2011; Deng et al., 2013). Research shows that these individuals prefer communication through social networking sites above face to face contact, because these channels make it easier for them to communicate and gives them time to think of responses (Correa, Hinsley, & de Zúniga, 2010). Therefore it is likely that people who score high on neuroticism have a positive attitude towards recruitment through social networking sites.
H5: Neuroticism is positively related to the applicants’ attitudes towards recruitment through social networking sites.
To summarize, the hypotheses are visualized in a conceptual model below (Figure 1).
14
FIGURE 1Conceptual framework
Age
Level of education
ATTITUDES TOWARDS RECRUITMENT THROUGH SOCIAL
NETWORKING SITES
.
Perceived usefulness Perceived ease of use Perceived privacy Perceived quality 1. Extraversion
2. Openness to experience 3. Emotional stability
ATTITUDES TOWARDS RECRUITMENT THROUGH TRADITIONAL RECRUITING MEANS
Perceived usefulness Perceived ease of use Perceived privacy Perceived quality H1a -
H2b -
15 Multichannel in marketing
In the previous hypotheses a distinction is made between social networking sites and traditional recruiting means. Social networking sites are completely online. Traditional recruiting means however, consist of online and offline channels. Where in marketing research focuses on for instance the combination of channels, the synchronization of online and offline channels and the challenges to use multichannel marketing to strengthen the relationship (Rangaswamy & Van Bruggen, 2005), in recruitment the preference for online or offline is not even known.
From the perspective of human resource management the (potential) employees are the main focus and from the perspective of marketing the customers. The marketing department tries to reach (potential) customers through various channels. This multichannel approach has been going on for years already. It has grown excessively and is likely to grow even further (Neslin & Shankar, 2009).
Multichannel users in marketing can be defined as customers who use more than one channel to interact with firms (Rangaswamy & Van Bruggen, 2005). Research shows that multichannel shoppers are significantly more profitable for companies than single-channel shoppers (Kumar & Venkatesan, 2005). Besides, multiple channel retail strategies enhance customer satisfaction (Wallace, Giese &
Johnson, 2004). It has already proven its added value in the field of marketing. In human resource
management however, there is not much known about the multichannel use and effects. Several
findings in marketing literature concerning multichannel may provoke thought for human resource
management. First of all the finding that customers differ in their channel usage (Neslin & Shankar,
2009). They differ in the number of channels they use, intent to use and response per channel. These
differences may also be there when people are looking for a job. Research of Kushwaha and Shankar
(2008) shows that customers vary on their channel usage depending on several attributes of these
customers, so the influence of characteristics might also be relevant for the attitudes towards and
intent to use a recruitment channel. Besides the attitudes towards social networking sites or
traditional recruiting means as a channel to apply as discussed above, it might also be interesting to
know who relatively uses more channels, and if people actually use online or offline channels, and
16 especially which channels. So in the survey respondents are literally asked whether they would intent to use a certain channel in their job search, yes or no.
In this research, online channels are Facebook, Twitter, LinkedIn, job boards, company websites and mobile applications. Offline channels that are used are print advertisements, employment agencies and own networks.
As argued in hypothesis 1, elderly individuals have limited experience in using computers and internet compared to younger people (Porter & Donthu, 2006). Research of the European Commission (2012) mentions lack of interest as the most cited reason. Besides, elderly individuals perceive more anxiety and generally have more privacy concerns (Porter & Donthu, 2006; Peluchette
& Karl, 2009). This might result in feeling less comfortable online (Montoya-Weiss, Voss & Grewal, 2003). Research concerning online channel use for purchasing financial products shows that age is negatively associated with the use of the online channel for information searches and purchases (Ramaswami, Strader & Brett, 2001). These findings might result in the expectation that age is negatively related to recruitment through online channels.
Hypothesis 6a
Age is negatively related to the intent to use online channels in a job search.
Research of Gomez, Egan and Bowers (1986) shows that age is strongly correlated with the amount of time untrained users need to become familiar with computers. The lack of experience among elderly users prevents them to evaluate the advantages the internet might offer (Trocchia &
Janda, 2000). Besides that, elderly individuals might be less willing to adopt a new channel (Hernández, Jiménez & Martin, 2011). A research on the multi-channel shopper of the University of Pennsylvania (2011) found that the older the consumer, the more likely they are to be a mono- channel shopper. It could be that they hold on to that channel(s) they are familiar with. Because of these reasons, it is expected that elderly people prefer to use offline channels.
Hypothesis 6b
Age is positively related to the intent to use offline channels in a job search.
17 Within the different education levels, there is still a large difference in internet use. Research of the European Commission (2012) shows that almost all higher educated people use the internet (96 percent) against 76 percent of the medium educated and less than half of all lower educated people (47 percent). Lower educated people perceive internet as complex (National Telecommunications and Information Administration, 2002). Higher educated use internet almost daily, because they need it for most of their jobs and studies (European Commission, 2012).
Therefore it might be expected that level of education is positively related to recruitment through online channels.
Hypothesis 7a
Level of education is positively related to the intent to use online channels in a job search.
Besides the complexity of the internet lower educated might experience, they also have more security concerns (Ernst & Young, 2000). This might be an explanation for the finding of the European Commission (2012) that there is a low user rate of internet among lower educated people.
Therefore it is expected that level of education is negatively related to the intent to use offline channels in a job search.
Hypothesis 7b
Level of education is negatively related to the intent to use offline channels in a job search.
FIGURE 2 Conceptual framework
Age
Level of education
.
Intent to use online channels
.
Intent to use offline channels H6a -
H7b -
18 METHOD
Sample and procedure
An online questionnaire was used to gather the data. A face to face approach, Facebook, and email were used to reach the respondents. The survey was in Dutch, because the sample consisted of Dutch individuals. In this survey, participants’ attitudes towards several recruiting means, namely the social networking sites and the more traditional recruiting means, were measured. 183 individuals filled in the survey, a convenience sample of whom 167 people completed the entire survey. Listwise deletion is used to handle the missing data. The respondents were individuals from different ages and with different levels of education. These individuals were people in the last stages of their studies, people who are looking for a (new) job or people who have a job. The average age was 33 years. 32.3 percent of the respondents were lower educated and the remaining 67.7 percent were higher educated individuals. 32.9 percent of the individuals who filled in the survey were male. Most of the respondents (89.2 percent) have an account on Facebook, Twitter or LinkedIn.
Measures
The attitudes of the individuals were measured by statements related to the different recruiting means, using a 5-point Likert scale, ranging from 1, “Totally disagree”, to 5, “Totally agree”.
The survey was divided into different parts. To compare the attitudes towards the two different kinds of channels, exactly the same questions were asked concerning social networking sites and traditional recruitment methods. Before each set of questions, a definition of social networking sites and respectively traditional recruitment was given, and it was clearly mentioned and repeated before each question set that the respondent had to imagine they were looking for a new job. The dependent variables are composed of the statements on the basis of a factor analysis and literature.
Age Age was measured by means of an open question.
Level of education Respondents could choose from “no education”, “primary school”,
“secondary school”, “MAVO/VMBO” (Middelbaar Algemeen Voortgezet Onderwijs/ Voorbereidend
19 Middelbaar Beroepsonderwijs; prevocational), “HAVO” (Hoger Algemeen Voortgezet Onderwijs;
general secondary education), “VWO” (Voorbereidend Wetenschappelijk Onderwijs; pre-university education), “MBO” (Middelbaar Beroepsonderwijs; secondary vocational education), “HBO” (Hoger Beroepsonderwijs; higher professional education), or “WO” (Wetenschappelijk Onderwijs; university level).
Perceived usefulness The perceived usefulness was measured by four statements. The scale was developed by Choi and Chung (2013). They modified a scale that was initially developed by Lau and Woods (2009) and Davis (1989). Items that were used are: “Social networking sites make it easier to find information”, “Social networking sites improve my information-seeking”, “Social networking sites help me to find information more quickly”, and “I find social networking sites useful in my information seeking” (α = .90). These questions were repeated for traditional recruitment ways, for example, “Traditional recruitment is useful in my information-seeking” (α = .87).
Perceived ease of use The scale that was used to measure perceived ease of use, was developed by Venkatesh and Davis (2000), adapted from Davis (1989). Four items were used to measure the perceived ease of use (α = .88). Items that were used are “My interaction with social networking sites is clear and understandable”, “Interacting with social networking sites does not require much of my mental effort”, “I find social networking sites easy to use”, and “I find it easy to get the system to do what I want it to do”. Again, these questions were repeated for traditional recruitment ways, for example, “Interacting with traditional recruitment does not require much of my mental effort” (α = .75).
Privacy Subsequently three questions were asked concerning privacy of the recruitment means. The scale of Chung et al. (2010) was used to measure this. Items in this scale were “Privacy of users of social networking sites is protected”, “Personal information stored in social networking sites is safe”, “Social networking sites keep participants’ information secure” (α = .83).
The same questions were asked concerning traditional recruitment, for example, “Traditional
recruitment keeps participants’ information secure” (α = .85).
20 Quality Thereafter three questions concerning the perceived quality followed, also measured by the scale of Chung et al. (2010). Items used were “Social networking sites generally function well”, “Social networking sites are well-designed”, and “The overall quality of social networking sites is high” (α = .86). Also these questions were repeated for traditional recruitment. An example is “Traditional recruitment generally functions well” (α = .82).
Other variables After that, more general attitude questions were asked developed by myself, about for instance perception of reliability and favourability. Example questions are
“Applying through social networking sites provides everyone an equal opportunity”, and “Applying through social networking sites is favourable”. Based on the factor analysis, these general attitude questions are divided among the previous mentioned variables (Appendix A).
Subsequently, there was a question concerning what types of channels the respondents would use when looking for a job. Nine channels, for instance Facebook and employment agencies, were mentioned of which they had to indicate whether or not they would actually use it in their job search.
Control variables A control variable that is used is gender.
Personality traits To investigate the effect of the level of extraversion, openness to experience and neuroticism, a five-item personality measure is used (John, 1990). Participants were asked to indicate to what extent the 15 characteristics reflect how they are in daily life. The answers were given on a five point Likert scale, ranging from 1 = ‘not applicable’ to 5 = ‘highly applicable’. The five items that were used to measure extraversion are “Energetic”, “Outgoing”, “Active”, “Talkative”, and “Assertive”. The internal reliability of this personality trait was α = .75. Secondly, questions regarding openness to experience were asked. Again, five items were used, namely “Intelligent”,
“Original”, “Imaginative”, “Wide interests”, and “Insightful”. However, in this case internal reliability
was low, namely α = .58. Even when questions were deleted it did not reach a reliability of α = .70, so
these measures tend not to be very good items to measure openness to experience. However, they
are used to test the possible influence. Lastly, the personality trait neuroticism is measured. Also in
21 this case five items are used, namely “Nervous”, “Anxious”, “Worrying”, “Moody”, and “Tense”. The Cronbach’s alpha was .81.
Statistical analysis
The hypotheses 1 to 5 were tested in two ways. First the relation between the independent variables - age, level of education, extraversion, openness to experience, and neuroticism - and the attitudes towards recruitment through social networking sites and traditional recruitment means were tested with all 20 statements taken together in one variable to measure the overall attitude (α
= .91 for the social networking sites and α = .91 for the traditional recruitment means). Secondly, these attitudes were separated into the different measures mentioned above, based on a factor analysis (see Appendix A), namely ‘perceived usefulness’, ‘perceived ease of use’, ‘privacy’ and
‘quality’ in order to explain the differences and measure more specific attitudes. A correlation analysis was performed to identify the relationships between the variables and a regression analysis to test the potential main effects. The relation between age and level of education, and the intent to use online or offline channels was tested by a correlational analysis.
RESULTS Descriptive statistics
Table 1 represents the means, standard deviations, and the zero-order Pearson correlations among the variables. As is shown in Table 1, both age and level of education are significantly related to attitudes towards social networking sites. Age is negatively related (r = -.25, p < .01) and level of education has a positive relationship (r = .23, p < .01). The personality trait extraversion is significantly correlated with attitudes towards social networking sites (r = .37, p < .01). Neuroticism however, is negatively correlated with attitudes towards traditional recruiting means (r = -.16, p <
.05). Age is negatively correlated to intent to use online channels (r = -.35, p < .01) and positively
correlated to intent to use offline channels (r = .35, p < .01). Level of education is positively
22 correlated to intent to use online channels (r = .45, p < .01) and negatively related to intent to use offline channels (r = -.27, p < .01).
Hypotheses testing
A regression analysis was used to test the hypotheses. First the control variable gender was added to control for relationships with the independent and dependent variables. In the second and third step, direct effects of the standardized variables age and level of education on attitudes towards recruitment through social networking sites and attitudes towards recruitment through traditional recruiting means were tested. These are tested separately as age and level of education are highly correlated (r = -.41, p < .01), which could suppress possible real associations. Subsequently, in the fourth step, the personality traits were added to test for a main effect on attitudes towards recruitment through social networking sites. Table 2 represents the results of the regression analysis.
TABLE 1
Descriptive statistics and Pearson zero-order correlations among the study variables
Variables Mean S.D. 1 2 3 4 5 6 7 8 9 10
1. Gender 1.67 0.47 -
2. Age 32.70 12.77 .05 -
3. Level of education 6.86 1.33 -.10 -.41 ** -
4. Extraversion 3.77 0.53 .01 -.24 ** .10 - 5. Openness to
experience
3.74 0.45 - .18**
-.30** .22** .31** -
6. Neuroticism 2.41 0.68 .12 .15 -.16* -.35** -.14 - 7. Attitudes towards
SNS
3.26 0.55 -.07 .25** .23** .37** .12 -.09 - 8. Attitudes towards
TRM
3.52 0.53 -.06 -.11 -.05 .10 -.04 -.16* .01 - 9. Intent to use online
channels
2.97 1.04 -.04 -.35** .45** .22** .23** -.16* .38** -.10 - 10. Intent to use offline
channels
2.05 0.83 .09 .35** -.27** -.18* -.08 .13 -.11 .08 -.07 -
Note. N = 167. * p <.05, ** p < .01. SNS = Social networking sites, TRM = Traditional recruiting means
23 A correlational analysis was used to test the relation between age and level of education, and the intent to use online or offline channels.
Hypothesis 1a stated that age is negatively associated with the applicants’ attitudes towards recruitment through social networking sites. As shown in Table 2, there is a significant, negative relationship between age and attitudes towards recruitment through social networking sites (β = -.14 and p < .01). Therefore, Hypotheses 1a is supported. Hypotheses 1b stated that age is positively associated with the applicants’ attitudes towards recruiting through traditional recruiting means. As represented in Table 2, there is no significant relation between age and attitudes towards recruitment through traditional recruiting means (β = -.06 and p = n.s.). Therefore, Hypothesis 1b is not supported.
Hypothesis 2a stated that level of education is positively associated with the applicants’
attitudes towards recruitment through social networking sites. The relation between these two variables is significant and positive, as is shown in Table 2 (β = .13 and p < .01). Therefore, Hypothesis 2a is supported. Hypothesis 2b stated that level of education is negatively associated with the applicants’ attitudes towards recruiting through traditional recruiting means. As represented in Table 2, there is no significant relation between level of education and attitudes towards recruitment through traditional recruiting means (β = -.03 and p = n.s.). Therefore, Hypothesis 2b is not supported.
After these variables, the possible effects of the three personality traits were tested.
Hypothesis 3 stated that extraversion is positively associated with the applicants’ attitudes towards recruitment through social networking sites. This main effect is significant (β = .21 and p < .001).
Therefore, Hypothesis 3 is supported. Hypothesis 4 stated that openness to experience is positively
related to the applicants’ attitudes towards recruitment through social networking sites. As shown in
Table 2, there is no significant relation between openness to experience and attitudes towards
recruitment through social networking sites (β = -.04 and p = n.s.). Therefore Hypothesis 4 is not
supported. The last personality trait that is tested, is neuroticism. Hypothesis 5 stated that
24 neuroticism is positively related to the applicants’ attitudes towards recruitment through social networking sites. This main effect is not significant (β = .05 and p = n.s.). Therefore Hypothesis 5 is not supported.
Subsequently, the effects of age and level of education on the intent to use online versus offline channels in the job search were tested. Hypothesis 6a stated that age is negatively related to online channel use in an individuals’ job search. The relation between these variables is significant (r = -.35 and p < .01). Therefore, hypothesis 6a is supported. Hypothesis 6b stated that age is positively related to offline channel use. As shown in Table 1 there is a significant, positive relationship between age and offline channel use (r = .35 and p < .01). Therefore, hypothesis 6b is supported.
Hypothesis 7a expected a positive relationship between level of education and online channel use. As represented in Table 1 there is a significant, positive relation between level of education and online channel use (r = .45 and p < .01). Therefore, hypothesis 7a is supported.
Hypothesis 7b expected a negative relationship between level of education and offline channel use.
As shown in Table 1 there is a significant, negative relationship between level of education and
offline channel use (r = -.27 and p < .01). Therefore, hypothesis 7b is supported.
25 TABLE 2
Results of regression analysis
Steps and predictors Dependent variable
Attitudes towards SNS
Attitudes towards TRMModel 1 Model 2 Model 3
Model 4 Model 1 Model 2 Model 31. Gender -.04 -.03 -.03
-.04 -.03 -.03 -.032. Age -.14**
-.07 -.063. Level of education .13**
.09* -.034. Extraversion
.21***Openness to experience
-.04Neuroticism
.05R
2.00 .07 .06
.20 .00 .01 .01Adjusted R
2-.00 .05 .05
.17 -.00 .00 -.01Note. N = 167. Unstandardized regression coefficients are reported. SNS = Social networking sites, TRM = Traditional recruiting means.
† < .1, *p < 0.05, **p < 0.01, ***p < 0.001
26 Secondary analyses
As discussed in the method section, the variables attitudes towards recruitment through social networking sites and attitudes towards recruitment through traditional recruitment means can be separated into different factors (Figure 1). To get more detailed insight in these variables and to explain the differences, these relations are also tested. Thus, in short, the direct relations between age and level of education to “perceived usefulness”, “perceived ease of use”, “privacy”, and
“quality” of social networking sites and traditional recruiting means are tested. As explained in the method section, the “other variables” were added to previous mentioned variables according to the factor analysis. Also the personality traits were added to test the main effects. Table 3 represents the means, standard deviations, and the zero-order Pearson correlations among the variables related to attitudes towards recruitment through social networking sites and traditional recruiting means. As represented in Table 3, age and level of education are correlated to several attitudes. From the three personality traits, extraversion and neuroticism are most often correlated with the attitudes.
Extraversion is positively correlated to each attitude of recruitment through social networking sites, and neuroticism is negatively correlated to three out of four attitudes towards recruitment through traditional recruitment means. In Table 4 and 5 results of the regression analysis of these variables are represented.
Age – social networking sites Age is negatively related to attitudes towards recruitment through social networking sites (Hypothesis 1a). As represented in Table 4, this is supported for perceived ease of use (β = -.32 and p < .001), quality (β = -.15 and p < .01), and privacy (β = -.19 and p
< .01).
Level of education – social networking sites Level of education is positively related to attitudes towards recruitment through social networking sites (Hypothesis 2a). As shown in Table 4, this is supported for perceived usefulness (β = .24 and p < .001), perceived ease of use (β = .20 and p
< .01), and quality (β = .15 and p < .01) of social networking sites. However, level of education is
negatively related to privacy of recruitment through social networking sites (β = -.12 and p < .05).
27 Age – traditional recruiting means Age has no significant relationship with attitudes towards recruitment through traditional recruiting means when the factors are measured as one attitude. A positive relationship was expected. However, when a distinction is made between the several attitudes, a negative relationship is found between age and privacy (β = -.15 and p < .01), what is against expectations. Results are shown in Table 5.
Level of education – traditional recruiting means There are no significant relations between level of education and any of the measures of attitudes towards traditional recruiting means.
Personality traits – social networking sites Extraversion is positively related to all of the separate factors (perceived usefulness β = .24 and p < .001, perceived ease of use β = .26 and p < .001, perceived quality β = .19 and p < .001, and perceived privacy β = .16 and p < .01).
Neuroticism is positively related to perceived usefulness of recruitment through social networking
sites β = .14 and p < .05. Remarkable is that neuroticism is has a negative correlation with perceived
ease of use (r = -.15 and p <.05), perceived quality (r = -.17 and p <.05), and perceived privacy (r = -.19
and p <.05) of recruitment through traditional recruitment means.
28 TABLE 3
Descriptive statistics and Pearson zero-order correlations among the study variables – secondary analysis
Mean SD 1 2 3 4 5 6 7 8 9 10 11 12 13 14
1. Gender 1.67 0.47 -
2. Age 32.70 12.77 .05 -
3. Education 6.86 1.33 -.10 -.41** -
4. PU SNS 3.43 0.81 -.08 -.10 .29** -
5. PEU SNS 3.55 0.83 .04 -.38** .23** .58** -
6. Privacy SNS 2.46 0.70 -.11 -.16* -.16* .21** .18* -
7. Quality SNS 3.60 0.62 -.10 -.24** .24** .47** .65** .28** -
8. PU TRM 3.40 0.71 .01 -.08 -.06 -.19* -.02 -.05 .04 -
9. PEU TRM 3.47 0.65 -.05 .05 -.08 -.09 -.01 .05 .07 .69** -
10. Privacy TRM 3.62 0.68 -.17* -.23* .07 .13 .24** -.02 .32** .35** .31** -
11. Quality TRM 3.63 0.64 -.06 -.03 -.10 -.09 .08 -.01 .16* .60** .60** .54** -
12. Extraversion 3.77 0.53 .01 -.24** .10 .23** .35** .21** .35** .07 .14 .06 .02 - 13. Openness to
experience 3.74 0.45 -.18* -.30** .22** .08 .12 -.01 .20** -.06 .00 .03 -.09 .31** -
14. Neuroticism 2.41 0.68 .12 .15 .16* .03 -.09 -.11 -.16* -.04 -.15* -.17* -.19* -.35** -.14 -
Note. N = 167. * p <.05, ** p < .01. SNS = social networking sites, TRM = traditional recruiting means
29 TABLE 4
Results of regression analysis secondary analysis social networking sites Steps and
predictors
Dependent variables
Perceived usefulness SNS Perceived ease of use SNS Perceived quality SNS Perceived privacy SNS Model
1
Model 2
Model 3
Model 4
Model 1
Model 2
Model 3
Model 4
Model 1
Model 2
Model 3
Model 4
Model 1
Model 2
Model 3
Model 4
1. Gender -.07 -.06 -.05 -.07 .03 .05 .05 .03 -.06 -.05 -.05 -.04 -.08 -.07 -.09 -.10
2. Age -.08 .04 -.32*** -.25*** -.15** -.05 -.19** -.11†
3. Level of education
.24*** .25*** .20** .09 .15** .10* -.12* -.17**
4. Extraversion .24*** .26*** .19*** .16**
Openness to experience
-.05 -.06 .02 -.08
Neuroticism .14* .06 .00 -.03
R
2.01 .02 .08 .16 .00 .15 .06 .23 .01 .06 .06 .18 .01 .02 .04 .12
Adjusted R
2.00 .00 .07 .13 -.01 .14 .04 .20 .00 .05 .05 .15 .00 .00 .03 .09
Note. N = 167. Unstandardized regression coefficients are reported. SNS = social networking sites
† < .1, *p < 0.05, **p < 0.01, ***p < 0.001
30 TABLE 5
Results of regression analysis secondary analysis traditional recruiting means
Steps and predictors Dependent variables
Perceived usefulness TRM Perceived ease of use TRM Perceived quality TRM Perceived privacy TRM Model 1 Model 2 Model 3 Model 1 Model 2 Model 3 Model 1 Model 2 Model 3 Model 1 Model 2 Model 3
1. Gender .01 .01 .01 -.04 -.03 -.04 -.04 -.04 -.04 -.11* -.11* -.11*
2. Age -.06 .03 -.02 -.15**
3. Level of education
-.04 -.06 -.07 .04
R
2.00 .01 .00 .00 .01 .01 .00 .00 .02 .03 .08 .03
Adjusted R
2-.01 -.01 -.01 -.00 -.01 -.00 -.00 -.01 .00 .02 .07 .02
Note. N = 167. Unstandardized regression coefficients are reported. TRM = traditional recruiting means
† < .1, *p < 0.05, **p < 0.01, ***p < 0.001
31 Channel use
Although it is not part of the conceptual model, elaborating on the multichannel section, more insights have been gathered about the number of channels people use and the specific channels individuals intent to use in their job search, which could be practically relevant for organizations in the recruiting process.
On average, respondents make use of five channels during their job search. As shown in Table 6, higher educated individuals use significantly more channels than lower educated do (r = .20 and p < .05). There is no significant difference between users of different ages (r = -.06 and p = n.s.).
TABLE 6
Amount of channels used in job search
Mean S.D. 1 2 3
4Gender 1.67 0.47 -
Age 32.70 12.77 .05 -
Level of education 6.86 1.33 -.10 -.41** -
Amount of channels 5.02 1.28 .03 -.06 .20*
-Note. N = 167. * p <.05, ** p < .01
Figure 3 shows that people make most use of traditional recruiting means in their job search.
LinkedIn is also used relatively often, especially among higher educated people and younger individuals (29 years on average compared to the average age of 38 among non-users), but Facebook and Twitter stay behind in user rate.
FIGURE 3
Use of channels in job search
0 10 20 30 40 50 60 70 80 90 100
