Evaluating the Factors Affecting on Intension to Use of E-Recruitment

Yas A. Alsultanny^*, Mona F. Alotaibi

Technology and Management Innovation Department, College of Graduate Studies, Arabian Gulf University, Manama, Bahrain

Abstract

The Internet has become an important tool for all human matters including e-recruitment. The aim of this paper is to evaluate the factors that affect on the attitude and intention to use the e-recruitment. A questionnaire was designed to examine applicant’s intention to use e-recruitment by obtaining their opinions; data were obtained from 356 job seekers who are e-recruitment actual users. The results revealed that enjoyment, usefulness and ease of use significantly correlate with their attitude while their attitude strongly correlates with their intention to use. Applicants’ demographic variance was tested and found that age, education and Internet experience have no statistically significant differences except for a few sections, while gender and occupation have statistically significant differences. The study recommended is to take the advantages of information technology and continuously update this application by improving the productivity, easy to work with and enjoyable experience for job seekers.

Keywords

E-Recruitment, Job Seekers, Information Technology, Qualified Candidates, Intention to Use

Received: April 5, 2015
Accepted: June 14, 2015
Published online: August 9, 2015

@ 2015 The Authors. Published by American Institute of Science. This Open Access article is under the CC BY-NC license. http://creativecommons.org/licenses/by-nc/4.0/

1. Introduction

Recruitment of employees is a core phase in the Human Resource Management (HRM) process, it plays a major role in enhancing the organization's success, and therefore the human resource departments are facing pressure to deal with the technological changes.

Handlogten (2009) stated that the first introduction of the Internet as a recruiting tool was in the mid-1990s [1]. The terms online recruitment, e-recruiting, cybercruiting, or Internet recruiting, present the formal sourcing of job information online [2]. The use of the Internet has dramatically changed the face of Human Resource (HR) recruitment and the ways organizations think about the recruiting [3]. E-recruitment adopted in many organizations, both large and small ones. It brings the benefits to the organizations; e-recruitment gives more flexibility to the recruitment management in making contact with prospective applicants through online channels like e-mails and Short Message Services (SMS) [4].

Electronic-Human Resource Management (E-HRM) influences the efficiency and the effectiveness of the HR system by minimizes cycle times, increasing data precision and reducing HR crew. E-HRM enables the HR system to create value for the organization in new ways one of these ways is e-recruitment [5]. For e-recruitment, organizations is building their own web sites ever better because of the higher costs of advertising and the ease and speed of finding more qualified applicants [6].

The first section of this paper provides an introduction. The second section is for the motivations for this study. The third section presents the research objectives. The fourth section is for e-recruitment related literature. The fifth section exhibits the research model and methodology. The sixth section describes data analysis. The final section is for discussion and conclusions.

2. Motivations for This Study

The motivations for this study emerge from the recommendations that appeared in the literature on e-recruitment benefit to any organization in different aspects, but many organizations have not fully accepted this method yet [7]. E-recruitment has received limited attention in academic research from an organizational perspective [8]. Researches on adopting Internet technology in recruitment are few despite the wide range of Internet by both job seekers and employers [9]. This method is related to significantly lower costs for both job-seekers and recruiters [10]. Organizations career sites, like Shell, Coca Cola and Nike, don’t even offer the option to apply via email, these organizations work with online recruitment systems because of advantages for the applicants, and for the organization itself [1]. Every day, about 4 million applicants open their browsers to search for jobs on the Internet. Especially among students it is totally normal to use the Internet in order to get informed about possible career perspectives [11]. A study held by Ziesing (2013) [12] conducted a survey of students and graduates in the US, Europe and Asia regarding their attitude towards online, social and mobile recruitment found that 74% of job seekers use companies’ career websites, and 94% of the respondents said that employers should in addition to the organization career website they should have a special page on at least one social network.

3. Research Objectives

The major objectives of this research are concerned with answering the following questions:

•   What is the relationship of the factors (perceived ease of use, perceived usefulness, perceived enjoyment, and attitude towards using) on an intention to use job seekers e-recruitment?

•   Are there statistically significant differences of demographic characteristics of job seekers on intention to use job seekers e-recruitment?

4. Literature of E-Recruitment Intention to Use

The main purpose of recruitment is to identify and attract potential employees. Recruitment performs the basic function of putting an important resource – human capital – into the organization [13]. It is estimated that by using only online recruiting it costs the organization about one-twentieth, as it does to hire through traditional sources [14]. This is similar to the estimation of Maurer and Liu (2007) that web-based recruitment saves cost up to 87% per new employee hired by an organization [15]. Different authors have different concepts of what e-recruitment means [2]. A lot of recruiters and HR employees agree that the social network sites are effective and useful for recruiting and they might become a major method if not in the next generation [16]. Lin in 2011 studied how the social networks (Facebook) help companies to do recruitment and his results showed that the Facebook is a good recruiting channel because it owns many features [17], and if candidates have questions they can use the Question and Answer tool, In this way, they also could save time and cost.

Thompsons et al. In 2008 studied the influence of organizations, web design on prospective jobseekers 182 participants reviewed an online job advertising to rate advertising formatting attractiveness, usability of the website, organization web appeal, impressions of the organization, and willingness to pursue employment and found that both the formatting attractiveness and usability of online recruitment materials influenced participants’ inclinations to pursue jobs, formatting was more important than usability [18].

Brahmana and Brahmana in 2013 [19] conducted a study in Indonesia to examine the variables that influence job seekers intentions to use e-recruitment and used Davis (1989) [20] technology model accepted as a framework for the study and proposed perceived usefulness, perceived ease of use, and perceived of enjoyment as the determinants of the job seekers intention and found that all three variables influenced the decision of job seekers intention to use. Odumeru also conducted in 2012 a study for Nigeria by using modified technology acceptance model to target candidates for the intention to use e-recruitment [7]. Kashi and Zheng in 2013 studied the Job applicants’ intentions to use e-recruitment to apply for a job using modified technology acceptance model in Iran using a sample of 332 job applicants [21]. The results showed that perceived usefulness was found to have a significant impact on applicants’ behavioural intentions to use e-recruitment while perceived ease of use did not have any significant effect on their intention to use.

5. Research Model and Methodology

The research model factors were designed with support of literatures presented in Table (1) that summarizes e-recruitment intention to use related literature that highlights the importance of the chosen factors that influence intention to use e-recruitment for gathering information. The research model that guides this study is depicted in Figure (1). The model examines the relationship between Perceived Ease Of Use (PEOFU), Perceived Usefulness (PU), and Perceived Enjoyment (PE). The model is constructed based on similar research models that appeared in the literature on e-recruitment intention to use. Table (1) summarizes e-recruitment intention to use related literature that highlights the importance of the chosen factors that influence intention to use e-recruitment for gathering information.

Table 1. Literature related factors intention to use e-recruitment.

The hypotheses of this paper are;

H1: Perceived ease of use e-recruitment positively correlates with the perceived usefulness of using it.

H2: Perceived ease of use e-recruitment positively correlates with the attitude towards using it.

H3: Perceived enjoyment of using e-recruitment positively correlates with the perceived usefulness of using it.

H4: Perceived enjoyment of using e-recruitment positively correlates with the attitude towards using it.

H5: Perceived usefulness of using e-recruitment positively correlates with the attitude towards using it.

H6: Attitude towards using e-recruitment positively correlates with the intention to use it.

H7: There are statistically significant differences of demographic characteristics (gender, age, occupation, and Internet experience) on (Perceived ease of use, Perceived enjoyment, Perceived usefulness, and Attitude towards using) towards intention to use e-recruitment.

Figure 1. Conceptual research model.

A Questionnaire was constructed and validated before using it to test the research hypotheses. The questionnaire statements constructed on a five-point Likert scales with end points of strongly disagree and strongly agree.

Several groups contacted to participate; under-graduate students, mostly who are about to graduate or postgraduate students in several universities, also the questionnaire sent to several organizations in order to reach the employees group. The Job seekers respondents entered for data analyses are 356, who are users of e-recruitment.

Cronbach’s alpha was tested the questionnaire reliability. The test was held in each section and for the total. Table (2) shows the results of the test.

Table 2. Cronbach’s alpha reliability test.

The results show that the total for all statements are 0.905, which indicates a high consistency between the statements of the questionnaire because it is higher than 0.6 [26].

6. Data Analysis

Descriptive statistics and advanced techniques were used in this section to test the research hypothesis.

Table (3) shows the research sample consists of 266 (74.7%) males and 90 (25.3%) females.

The results showed that 4 (1.1%) respondents of the study sample ages (less than 20 years); 107 (30.1%) respondents of the study sample ages (20–23 year); 179 (50.3%) respondents of the study sample ages (24–27 year); and 66 (18.5%) respondents of the study sample ages (above 27 years). This relatively believed because most of the job seekers are young.

Regarding the occupation, the results showed that 164 (46.1%) respondents of the study sample were non employees; 67 (18.8%) respondents of the study sample were students; and 125 (35.1%) respondents of the study sample were employees.

Regarding the Internet experience, the results showed that 6 (1.7%) respondents of the study sample have less than 2 years Internet experience; 7 (2%) respondents have a 2-3 years of Internet experience, 40 (11.2%) have a 4-5 years of Internet experience; 77 (21.6%) respondents have 6-7 years of Internet experience and 226 (63.5%) respondents of the study sample have more than 7 years experience in using Internet. Which indicated that most of the job seekers have experience in using Internet, which makes it easier for them use e-recruitment

Table 3. Respondent’s demographic information.

Table 4. Means, standard deviations, and ranks of the dimensions.

SD*: Standard Deviation

The 19 statements of the questionnaire divided into 5 dimensions. For each statement the means, standard deviations (SD), and ranks was calculated according to respondents where rank represents the order of agreement for each statement in the dimensions. Table (4) shows that the average value of the 1^st dimension Ease of use is 3.64 with a standard deviation 0.94, this indicate that the users’ find e-recruitment easy. Ultimately, job seekers exploit e-recruitment because they find it easy to learn and operate this due to the nature of the seekers because all of them are well educated and have a good experience in using the Internet.

The average value of the 2^nd dimension Usefulness is 3.39 with a standard deviation 1.03, which is less than the 1^st dimension, this is due to the fact that some of the organizations don’t offer advanced features and services on their career websites.

The average value of the 3^rd dimension Enjoyment is 3.21 with a standard deviation 1.08, the low average because some of the job seekers don’t care much about the settings in their websites and the long procedures that faces applicants to submit their resume.

The average value of the 4^th dimension Attitude towards using is 3.77 with a standard deviation 1.03, this average indicate the job seekers generally have a positive attitude to using e-recruitment therefore; they are willing to use it in the future and leave the traditional methods.

The average value of the 5^th dimension Intention to use is 4.07 with a standard deviation 0.79, this average indicate the users have the intention to use the e-recruitment technology to search for a job and will use it as a sustainable job search tool.

The hypotheses (H1 to H6) were tested by Pearson correlation and the significant values, the results are shown in Table (5).

Table 5. Job seekers matrix of correlation.

**Means statistically significant at the level of significance (0.05 = α)

The table shows that there is a positive correlation coefficient between the dimensions of the questionnaire at significance level 0.05 because all the values are 0.00; therefore the hypotheses (H1-H6) are accepted. The results showed Perceived ease of use have significant effect on (Perceived usefulness, Perceived enjoyment, Attitude toward using, and Intention to use it) with correlation factors (r= 0.528, r= 0.487, r=0.444, r=0.376) respectively, these are moderate correlation. Users found that the easier the technology is to use the more useful, enjoy, attitude and intention to use e-recruitment increase.

The factor Perceived usefulness have significant effect on (Perceived enjoyment, Attitude toward using, and Intention to use it) with correlation factors (r= 0.539, r= 0.539, r=0.470) respectively, these are moderate correlation. This indicates that users will have a positive attitude toward e-recruitment if they find it useful for them in providing information and offering services.

The factor Perceived enjoyment have a significant effect on (Attitude toward using and Intention to use it) with correlation factors (r=0.620, r=0.486) respectively, these are moderate correlation. This indicates that the e-recruitment creates in users' feelings of enjoyment, fun, and pleasure while they search for a job on the web site; the job seekers will find the technology useful, hence, users who experience immediate pleasure and fun of using e-recruitment they will have a positive attitude toward using it.

The attitude towards using has a strong relationship with the intention to use e-recruitment technology with r= 0.714, this indicates that the more the users have positivity toward e-recruitment the more they intend to use it.

To test hypothesis (H7), two statistical tests were carried out: the independent sample T Test to examine if there are any differences between male and female users in terms of using e-recruitment, and one way ANOVA to test, age, occupation, and Internet experience.

Table (6) shows the gender has a significant effect on the ((Perceived usefulness, Perceived enjoyment, Attitude toward using, and Intention to use it) towards using e-recruitment, because all the values of (t-test) have sig < 0.05, and this means that there’s significant difference between female and male in the respondents according to all dimensions of the questionnaire.

Table 6. Independent sample T test for gender analysis.

df.*: degree of freedom

Sig.**: Significance

Means statistically significant at the level of significance (α = 0.05)***

Table (7) shows the age has no statistically significant effect on all the dimensions. of the questionnaire except perceived usefulness. Where all the sig>0.05, this means that there’s no statistically significant difference between the respondents according to perceived ease of use, perceived enjoyment, attitude toward using, and intention to use e- recruitment. Because most of the respondents are young, job seekers and they are more open to see worldwide career web sites. When they compare it to the local career websites, they find it less useful in terms of providing information about vacancies and in their less advanced features.

Table 7. One way ANOVA test for age analysis.

df.*: degree of freedom

Sig.**: Significance

Means statistically significant at the level of significance (α = 0.05)***

Table (8) shows the educational level has no statistically significant effect on all the dimensions of the questionnaire, where all the sig>0.05.

Table 8. One way ANOVA test for education analysis.

df.*: degree of freedom

Table (9) shows the occupation has a statistically significant effect on all the dimensions of the questionnaire, where all the sig<0.05.

Table 9. One way ANOVA test for occupation analysis.

Means statistically significant at the level of significance (α = 0.05)*

Table (10) shows the Internet experience has no statistically significant effect on all the dimensions of the questionnaire. Where all the sig<0.05, that is, most of the respondents have long Internet experience therefore more aware of the fact that the Internet gives a better chance to reach wider organizations and it becomes more easy to apply for an open position other than going to the organizations.

Table 10. One way ANOVA test for Internet experience analysis.

7. Discussion and Conclusions

The evolution of the e-recruitment industry closely parallels such development worldwide. This trend started in the 90’s and confirmed to be an efficient way to provide better interaction between job seekers and employers. The variables for the study were identified from the literature review. The study evaluates the factors influencing the use of e-recruitment. The evaluation depends on the three factors of technology acceptance model (TAM) developed by Davis in 1989. The three factors towards behaviour attitude are; perceived ease of use, perceived usefulness, and perceived enjoyment, these factors validated as the elements of job seekers attitude to use e-recruitments, and then correlated to intention to use e-recruitment.

The results found that attitude and intention to use have significant association. An increase of job seekers positive attitude will also lead to an increase of intention to use that particular system. The first variable perceived ease of use has moderate correlation with behavioural intentions and perceived usefulness on the other hand, has moderate correlation with intention to use. Perceived enjoyment has strong correlation with behavioural intentions and perceived ease of use has a significant correlation with perceived usefulness. The results were supported by Venkatesh and Davis in 2000 [27]. The success of e-recruitment relies on the good influence of individuals which in turn affect intention. Thus, it’s obvious that individual must have a positive perception in order to motivate them to use e-recruitment in the real world.

For the effect of demographic character of applicants on using e-recruitment, the results show that there are statistically significant differences in the dimensions attributed to gender and occupation. For age, we found that there is no statistically significant difference of age on all factors except for the usefulness factor. For education it was found that the there were no statistically significant differences attributed to all factors. Finally, for the Internet experience there was no statistically significant difference in all factors except for the job seekers’ intention to use the technology.

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