Analysis of Online Recruitment Process With TAM

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1) S.Munzarin, 2) A. Manimegalai

3) G. Latha, 4) B. Sindhuja


Today, online recruitment has become a major tool for many organizations. However, little is known about jobseekers’ reactions to this new technology. This article is aimed at developing a web-based and central recruitment Process system for the HR Group of the company. Some features of this system will be creating vacancies, storing application data, and Interview process initiation, Scheduling interviews, storing Interview results for the applicant and finally Hiring of the applicant. This online website provides jobseekers to register themselves by attending the registration exam. Reports may be required to be generated for the use of the HR group. This paper provides an insight for jobseekers on the effective use of e-recruitment website and strategy to attract potential jobseekers for employment in reducing the manual work of HR correcting the Test, Short-listing the candidates, Informing the candidates etc. Data gathered from 332 job applicants at System Group Corp. shows usefulness and perceived ease of use – as core constructs of TAM model – are two main factors that predict jobseekers’ behavioral intentions to use recruitment websites.

Keywords:, Technology Acceptance Model, online recruitment, e-recruitment efficient usage, jobseekers, behavioral intentions.

Nowadays, e-recruitment is a method to recruit potential employees; with over 90% of Fortune 500 companies using some form of online recruiting (Feldman & Klaas, 2002). Job seekers are also conducting their searches online; with over 52 million Americans have used online job searches (Jansen, Jansen, and Spink, 2005). Online recruiting and hiring as a business tool has not only changed the way companies recruit employees and how job seekers search for jobs, it has also impacted both parties involved.

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If the effectiveness of an organization’s web site in attracting potential employees is considered to be a crucial determinant of an organization’s ability to generate qualified applicants (Willianson et al., 2003), identifying the factors that influence jobseekers’ attraction to organization website has to be a high priority.This fact was highlighted by a recent study of college students reporting that 26% of students rejected potential employers from job search consideration because of the poor design of their web sites (Karr, 2000). This paper attempts to use Technology Acceptance Model (TAM) introduced by Davis, (1989) – as one of the most successful models explaining the user/technology adaption – to identify some factors influencing jobseekers’ behavioral intentions in using e-recruitment websites. The findings of the current paper not only provides an insight for managers on the effective use of organizations’ recruitment websites but also, by providing a sound theoretical framework, would help to eliminate the shortcomings associated with former studies in the area of online recruitment. To begin our discussion, we first review the existing online recruitment literature. We then explain Technology Acceptance Model as our research framework, and introduce the related hypotheses. Finally, we explain the practical implications of the research, as well as our study limitations.


In IT literature, the TAM is the most influential model use to measure technology acceptance. This model is the extension of Ajzen and Fishbein’s Theory of Reasoned Action (TRA), by Fred Davis and Richard Bagozzi (Bagozzi et al., 1992; Davis et al., 1989) to explain the computer-usage behavior. The main purpose of TAM was: to provide an explanation of the determinants of computer acceptance that is generally, capable of explaining user behavior across a broad range of end-user computing technologies and user populations, while at the same time being both parsimonious and theoretically justified (Davis et al., 1989, p. 985). Numerous empirical studies have found that TAM consistently explains a substantial proportion of the variance (about 40%) in usage intentions and behavior (Venkatesh and Bala, 2008), and TAM compares favorably with alternative models such as the Theory of Reasoned Action (TRA) and Theory of Planned Behavior (TPB) (Venkatesh and Davis, 1996). As of December 2007, the Social Science Citation Index listed over 1,700 citations to the two journal articles that introduced TAM (Davis, 1989; Davis et al., 1989). TAM theorize that an individual’s behavioral intention to use a system is determined by two beliefs: perceived usefulness, defined as the extent to which a person believes that using a system will enhance his or her job performance, and perceived ease of use, defined as the extent to which a person believes that using a system will be free of effort (Venkatesh and Davis, 1996). According to TAM, perceived usefulness is also influenced by perceived ease of use because, other things being equal, the easier the system is to use the more useful it can be(Venkatesh and Davis, 1996).Many researchers’ empirical studies have replicated and tested the model under different conditions for TAM’s extended variables as general measures by explicitly including IT acceptance variables (e.g., Davis et al., 1992; Compeau and Higgins, 1995; Ma and Liu, 2004). However, Davis et al. (1989) TAM assumes that perceived ease of use and perceived usefulness are of primary relevance for computer acceptance. In the next section, with a full introduction of these two core constructs of TAM – perceived ease of use and perceived usefulness – the research hypotheses are presented and the research framework is explained.

2.1.1. Perceived Usefulness (PU)

Perceived usefulness is defined here as “the degree to which a person believes that using a particular system would enhance his or her job performance.” Within an organizational context, people are generally reinforced for good performance by raises, promotions, bonuses, and other rewards (Pfeffer, 1982). A system high in perceived usefulness, in turn, is one for which a user believes in the existence of a positive use-performance relationship. Organizations’ recruitment websites often support jobseekers with comprehensive job information including, salary information, benefits, rewards, and organizational programs (Cober et al., 2000). Perceiving system usefulness as antecedent of e-recruitment utilization, such as using these information and tools to enhance the effectiveness of job application, would draw the attention of many employed jobseekers into adopting the technology for job search (Tong, 2008).

2.1.2. Perceived Ease of Use (PEU)

Perceived ease of use, in contrast, refers to “the degree to which a person believes that using a particular system would be free of effort.” This follows from the definition of “ease”: “freedom from difficulty or great effort.” All else being equal, we claim, an application perceived to be easier to use than another is more likely to be accepted by users. On the contrary, a complex system, that is difficult to use, is less likely to be adopted since it requires significant effort and interest on the part of the user (Teo, 2001). As perceived ease of use has an inverse relationship with the perceived complexity of use of the technology, it affects perceived usefulness. TAM thus posits that perceived usefulness is influenced by perceived ease of use (Sanchez- Franco and Roldan, 2005). Similarly, in the e-recruitment context, jobseekers would prefer the system if it is easy to use compared to other methods of job applications.

2.1.3. Behavioral Intention

Bagozzi et al. (1992), believe that new technologies (e.g., recruitment websites) are complex, Thus, people form attitudes and intentions toward trying to learn to use the new technology prior to initiating efforts directed at using (Tong, 2008). Sanchez- Franco and Roldan (2005) study found that the relationship between perceived usefulness and behavioral intention was strong among goal-directed users. Consequently, this study relates PEOU to PU and PU to BI with the following hypotheses:

H1: Perceived Ease of Use (PEU) positively influences Perceived Usefulness (PU) in Erecruitment adoption.

H2: Perceived Usefulness (PU) positively influences Behavioral Intention (BI) to use organization’s e-recruitment website. Therefore, given empirical tested studies of modified TAM and the significant causal link among the three constructs by previous researchers, the author attempts to use Structural Equation Modeling (SEM) to test these highly validated studies with PEOU, PU, as independent variables and BI as the dependent variable for this study. The research framework is also illustrated in Figure 1.

Research framework forjobseekers e-recruitment technology adoptionFigure1. Research framework forjobseekers e-recruitment technology adoption


3.1. Participants

The participants of the study were 347 applicants for System Group Corp. While having more than 1200 employees, System Group Corp. is considered to be the biggest active organization in manufacturing software technologies in Iran. The data was gathered in a two-month period, during which 421 applicants

logged on to the organization’s website. From among these applicants, 347 questionnaires were gathered by the researcher, and at the end, a number of 332 questionnaires were analyzed (response rate 82%). The respondents of the study included 63 percent male, 73 percent single, and the majority of them ranged between 21 to 25 years old. Participation was completely anonymous and on a voluntary basis.

3.2. Procedure

The researchers did not have access to the actual application data due to stringent privacy regulations. Rather, data on the measures were collected using an online questionnaire that was administered subsequent to the online application procedure. we will first describe the data that were collected as part of the application procedure followed by a description of the research questionnaire.

3.2.1. Application Procedure

Applicants could search for positions on the System Group official website. Here, candidates could find general information on the organization and its conditions of employment. More specifically, information could be found on the organization’s culture, structure, development opportunities, and benefits. All applicants had to fill out an online form after they had accepted a privacy statement. The form consisted of information on contact details, date of birth, gender, education, and qualifications obtained from college, work experience, and skills. In addition, applicants had the opportunity to give additional information and to upload personal documents such as a curriculum vitae.

3.2.2. Research Questionnaire

After completion and submission of the online application, a questionnaire was presented in a pop-up window on a separate web page. This questionnaire was also accessible via a link which could be found in an email confirming the receipt of the applicant’s online application. The confirmation email was sent immediately after the online application had been submitted. A short introductory text accompanied the link to the online survey.

3.2.3. Measures

The questionnaire was preceded by a short introductory text. Anonymity and confidentiality of the participants’ responses were emphasized. It was explicitly mentioned that responses could not affect the selection process in any way and that the company did not have access to individual responses. It took respondents approximately 5 min to complete the questionnaire. The questionnaire was offered in both Farsi and English languages. Translations were made from English to Farsi, which were checked by native speakers. All responses were assessed on the following five-point Likert scale (1=completely disagree, 3=neutral, and 5= completely agree), with the exception of items on general background information. The questionnaire was consist of 18 items. To assess behavioral intentions (BI) the measure of Tompson et al., (2008) were obtained. This construct was assessed by five items. Example item is “I would like to work for this organization”. Perceived ease of use and perceived usefulness each assessed using five (Williamson et al., 2003) and eight (Palmer, 2002) items scales, respectively. Where applicable, the original wording ‘computerized process’ was replaced by ‘online application process’ for consistency throughout the questionnaire. Example items are “My interaction with online application processes was clear and understandable”; and “The organization’s recruitment website provides all the information required to apply for job”. At the end of the survey, space was provided for remarks or suggestions and respondents were thanked for their participation.

3.2.4. Analysis

The descriptive characteristics of the sample (Table 1) were assessed using SPSS 11.0 statistical package, based on the guidelines provided by Dimitriadis (2003). The research model (Figure 1) was tested using structural equation modeling (SEM) using LISREL 8.7. As it has been suggested, the structural equation approach has several advantages over traditional analyses (Bagozzi and Yi, 1989). Data were analyzed using the two-step approach suggested by Anderson and Gerbing (1998) and. In the first step, a confirmatory factor analysis (CFA) was performed, which helps assess the adequacy of the measurement model (Chang, 1998), or in other words, “[. . .] the measurement models (or confirmatory factor models) specify how hypothetical constructs are measured in terms of the observed variables” (Lin and Lee, 2004). In the second step of the data analysis, the structural model is tested using SEM; structural equation models specify causal relationships among latent variables (Lin and Lee, 2004).


In recent days, staffs are monitoring the candidates during the recruitment process which is nearly the waste of time. Currently all the jobseekers register for their jobs in prior which are stored in the database of the company due to which more space is consumed. After registration all the jobseekers attend the aptitude test and proceed further but only certain candidates are selected for the further process.

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Presently recruitment is done manually. That is if a company or organization needs employees they make an announcement through newspaper or websites. People who are eligible send application to the organization or company. From these applications they are called for interviews or tests. After tests company has to do short listing manually. From these shortlisted candidates, they are called for interviews. After interview short listed candidates are employed. So it’s all a time consuming procedure too.

It may take one month or long. People around the world cannot apply. This is very convenient because in the manual system there are lot of difficulties in conducting and managing a recruitment exam, short listing, maintaining staff etc


Online Recruitment is aimed at developing a web-based and central recruitment Process system for the HR Group for a company. Some features of this system will be creating vacancies, storing application data, and Interview process initiation, Scheduling Interviews, Storing Interview results for the applicant and finally hiring of the applicant. Based on the outcome of the exam the jobseekers will be shortlisted. The details of the examination & Date of the examination will be made available to them through the website. People all around the world can apply and register. It has made all the process easy. System Analysis is the detailed study of the various operations performed by the system and their relationships within and outside the system. Here we are using the TAM model for analysing the system performance.


This paper enables the users to have the typical examination facilities and features at their disposal. It resolves typical issues of manual examination processes and activities into a controlled and closely monitored work flow in the architecture of the application. This multi platform solution brings in by default, the basic intelligence and immense possibilities for further extension of the application as required by the user. The system makes it friendly to distribute, share and manage the examination entities with higher efficiency and easiness. It is a comprehensive resource for finding a job online.


In the final model of the study, perceived usefulness and perceived ease of use have strong path coefficients( 0.71 and 0.82 respectively) in relation with behavioral intentions. Thus, from a causal point of view, the results of structural equation modeling confirm a strong causal relation between PEU and PU in one hand, and PU and BI on the other hand. The linear relation between PU and BI suggests that the perceived usefulness construct has a direct positive effect on applicants’ behavioral intentions to use recruitment websites.


In today’s competing world, the success of recruitment efforts in organizations is bound with attracting an appropriate group of qualified job applicants using the least possible sources. E-recruitment – as a growing recruitment tool – is not an exception. Therefore, identifying factors that influence e-recruitment success in attracting the qualified group of applicants should be a high priority. Using a TAM model in the area of erecruitment, this study tried to identify two of the most influential factors on the applicants’ behavioral intentions to use organization recruitment website and the consequent employment decisions.


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  2. Chatzoglou, P.; Vraimaki, E. (2009), Knowledge-sharing behavior of bank employees in Greece, Business Process Management Journal, 15 (2), 245-266.
  3. Venkatesh, V., & Bala, H. (2008). Technology accpetance model 3 and a research agenda on interventions. Decision Science , 39 (2), 273-315.
  4. Tong, D. (2008). A study of e-recruitment technology adoption in Malaysia. Industrial Management & Data Systems , 109 (2),281-300.
  5. Thompson, L., Braddy, P., & Wuensch, K.E-recruitment and the benefits of organizational web appeal. Computer in Human Behavior , 24, 2384-2398.
  6. Bock, G.; Kim, Y. (2002), Breaking the myths of rewards: an exploratory study of attitudes about knowledge sharing, Information Resources Management Journal, 15 (2), 14-21.
  7. Bock, G.; Kim, Y, Breaking the myths of rewards: an exploratory study of attitudes about knowledge sharing, Information Resources Management Journal, 15 (2), 14-21.


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