E-recruitment Systems Research Articles

Online vs Traditional Recruitment Approaches: Preferences of Saudi Employers and Employees

Purpose: This study analyses and compares traditional and e-recruitment methods for job applications from the perspectives of employees and employers. Research Design: The study collected data from employees and employers in business organizations located in Yanbu Industrial City, Kingdom of Saudi Arabia. An internet-mediated approach was used, and a survey questionnaire was designed. The sample size was determined to be 328 using an unknown population sample size formula. Data were gathered from 103 employees and 53 employers. Descriptive statistical analysis was conducted, and Chi-square was used to analyze the approaches of Traditional and e-recruitment for the job application process. Findings: The findings indicate that a high percentage of employees and employers’ preference for online methods in job applications. However, the chi-square test reveals a discrepancy between the perspectives of employees and employers. Employees support the use of online methods, while employers reject the hypothesis that online application methods are effective. Implications: One of the implications of online recruitment systems is that managers who use e-recruitment systems may have concerns about the accuracy and accountability of applicant data. Additionally, the lack of in-person interactions during the online application process can lead to frustration for job seekers and missed opportunities for employers to obtain or share more information. Originality: This study is arguably one of the leading studies that investigates the perceptions of employers and employees regarding the e-recruitment process in Saudi Arabia. Its findings would be of great help to employers in improving the e-recruitment system.

New Perspectives for Human and Artificial Intelligence Interactions for Leadership e-Recruitment

In order to adapt to the post-pandemic era, e-recruitment systems should change their requirements to search for a more competitive leader profile. These systems currently search for individual skills specific to leaders, taking into consideration whether a leader has the required skills and abilities for a certain job. The aim of this study is to improve e-recruitment searches for capable leaders in this new environment. In this regard, the study proposes to search for combinations of complementary skills. These skills, to be effective, should necessarily support each other in order to create successful management. The author’s proposal is to call this combination of skills: Leadership Complementary Skills (LCS). Understanding that some skills should be complementary in order to be viable, the LCS’ new insight into the hiring process was developed to comply with the aim of a performant organization. The idea was drawn from the author’s half a century of real-world experience and from several discussions with employers, employees, consultants and MBA students, debating cases along working and teaching. Statements are presented regarding proposals of appropriate combinations of skills to be implemented in the software of e-recruitment systems, their influence on employees’ behavior and the possible consequences on organizational outcomes. Consistent with the proposals, the author has also developed the Honeycomb Complementary Skills Model for Leadership as a first step in this endeavor, inviting future researchers to find other LCS to be added to the model and accomplish the actual ideal profile of a leader, opening as such a new field of research.

Electronic Recruitment (E-Recruitment) and Organizational Performance in Selected Commercial Banks in Nakuru City, Kenya

Organizations across the globe are now operating in a dynamic environment with stiff competition which calls for improved performance for survival and continuity. Every department in these organizations is continuously improving its ways of operation in order to maintain a competitive edge. Human Resource Management department is not an exception and being the backbone of every organization, is doing everything possible to embrace new technology in delivering its services for enhanced effectiveness and efficiency. The objective was to compare the relationship between recruitment and organizational performance of selected commercial banks in Nakuru City before and after the adoption of technology. The study was guided by the Resource Based View theory and adopted a comparative research design on a target population of 105 employees from selected banks that have embraced electronic human resource management. The Census method was used which involved using the entire population as this is considered suitable for a small population. A self-administered questionnaire was adopted to collect primary data. The validity of the instrument was enhanced through professional expert opinion while reliability was achieved using the Cronbach Alpha coefficient where all items scored above 0.70. Inferential and descriptive statistics with the aid of SPSS software was used to analyse data. The hypotheses of the study were tested at a 0.05 significance level. The findings indicated that recruitment had a negative significant correlation with organizational performance before automation (β = -0.361, p = 0.000<0.05) whereas after automation, there was a positive correlation (β = 0.907, p = 0.000<0.05). The study recommended the integration of technology in organizational processes as a worthwhile undertaking that has positive returns on investment. Organizations should design and implement e-Recruitment systems for more efficiency and effectiveness in their HR activities. The findings may benefit both financial and non-financial institutions, policymakers, and the government. The findings may also add to the available literature

The March of Chatbots into Recruitment: Recruiters’ Experiences, Expectations, and Design Opportunities

Organizations’ hiring processes are increasingly shaped by various digital tools and e-recruitment systems. However, there is little understanding of the recruiters’ needs for and expectations towards new systems. This paper investigates recruitment chatbots as an emergent form of e-recruitment, offering a low-threshold channel for recruiter-applicant interaction. The rapid spread of chatbots and the casual nature of their user interfaces raise questions about the perceived benefits, risks, and suitable roles in this sensitive application area. To this end, we conducted 13 semi-structured interviews, including 11 interviews with people who are utilizing recruitment chatbots and two people from companies that are developing recruitment chatbots. The findings provide a qualitative account of their expectations and motivations, early experiences, and perceived opportunities regarding the current and future use of chatbots in recruitment. While chatbots answer the need for attracting new candidates, they have also introduced new challenges and work tasks for the recruiters. The paper offers considerations that can help to redesign recruitment bots from the recruiter’s viewpoint.

Elucidating the role of gender differences via TAM in e-recruitment adoption in India: a multi-group analysis using MICOM

PurposeThis paper aims to answer two research questions: first, to study the factors that directly and indirectly influence the intentions of job-seekers and second, to examine the moderating role of gender differences in e-recruitment adoption through the application of technology acceptance model (TAM) in India.Design/methodology/approachA convenience sampling technique was used to collect online data via GoogleDocs through various online channels such as social media, LinkedIn and email. The final data was collected from 364 final-year graduates and postgraduate students to confirm the impact of female and male differences, measurement invariance in composite models (MICOM) and multi-group analysis (MGA).FindingsThe results indicated that perceived usefulness (PU) and perceived ease of use (PEOU) have a direct impact on attitude (AT), whereas PU influenced behavioral intentions (BI) of job-seekers, but PEOU did not. AT directly leads to the BI. The outcomes of mediation analysis show that AT partially mediates the relationships between PU to BI and PEOU to BI. Further, the findings of MICOM and MGA showed that gender significantly moderates all the relationships between the constructs except for the influence of AT on BI.Research limitations/implicationsThis study contributes to the current literature, revealing that the original TAM model is still pertinent and effective in prevailing periods in emerging markets. The significance of PEOU and PU on AT and BI implies that job-seekers will strongly adopt e-recruitment when it is user-friendly and assist them to accomplish their tasks easily and efficiently. Moreover, gender has a vital moderating influence in e-recruitment adoption. In the case of females, the effect of PEOU is stronger, and for males, PU has a substantial impact on adoption.Practical implicationsDevelopers and recruiters should provide significant information related to salary, location and job profile on e-recruitment to enhance the adoption rate of online recruitment. Further, the usefulness of e-recruitment systems was more significant for males compared to females, whereas female job-seekers prefer the e-recruitment system, which is easy to use and operate.Originality/valueThis research fills a gap in the literature by examining the essential factors affecting the BI of job-seekers as well as empirically testing the impact of gender differences to adopt TAM for e-recruitment – an under-explored subject in developing countries like India.

A Study on factors affecting Job Seekers’ Perception and Behavioural Intention towards E- Recruitment

Technology has played a vital role in education not only in enhancing the students’ academic excellence, improving teacher’s professional quality but also had proved pertinent in the recruitment of the students once they become job seekers. Where education makes them ready to be recruited in the industry, technology eases the process of recruitment through E-Recruitment (Tong, 2019)1. With technological development, the modern way of recruitment (E-recruitment) is used in majority of the corporates and the present generation with the strong inclination towards technology are dominating the work sphere and increasing efficiency and effectiveness at workplace. E-Recruitment is the latest trend and has been adopted by many large and small corporations. Augmented use of e-recruitment methods and systems facilitates this trend by eliminating much of the routine administrative work involved in recruiting and allowing human resource manager to more easily monitor and track recruitment related activities. (Holm, 201).2 The purpose of this study is to examine the impact of factors on perception of Job Seekers, who are millennial students in this study, and their behavioural intention (BI) towards E-Recruitment. The type of research employed in this study is exploratory cum descriptive. Factor Analysis and regression are used as tools of analysis. In the conclusion, this study will enable one to understand that there is a significant effect of perception of job seekers on intention towards e-recruitment.

Understanding User Perceptions of Trustworthiness in E-Recruitment Systems

Algorithmic systems are increasingly deployed to make decisions that people used to make. Perceptions of these systems can significantly influence their adoption, yet, broadly speaking, users understanding of the internal working of these systems is limited. To explore users perceptions of algorithmic systems, we developed a prototype e-recruitment system called Algorithm Playground where we offer the users a look behind the scenes of such systems, and provide how and why explanations on how job applicants are ranked by their algorithms. Using an online study with 110 participants, we measured perceived fairness, transparency and trustworthiness of e-recruitment systems. Our results show that user understanding of the data and reasoning behind candidates rankings and selection evoked some positive attitudes as participants rated our platform to be fairer, more reliable, transparent and trustworthy than the e-recruitment systems they have used in the past.

A New Approach to Information Extraction in User-Centric E-Recruitment Systems

In modern society, people are heavily reliant on information available online through various channels, such as websites, social media, and web portals. Examples include searching for product prices, news, weather, and jobs. This paper focuses on an area of information extraction in e-recruitment, or job searching, which is increasingly used by a large population of users in across the world. Given the enormous volume of information related to job descriptions and users’ profiles, it is complicated to appropriately match a user’s profile with a job description, and vice versa. Existing information extraction techniques are unable to extract contextual entities. Thus, they fall short of extracting domain-specific information entities and consequently affect the matching of the user profile with the job description. The work presented in this paper aims to extract entities from job descriptions using a domain-specific dictionary. The extracted information entities are enriched with knowledge using Linked Open Data. Furthermore, job context information is expanded using a job description domain ontology based on the contextual and knowledge information. The proposed approach appropriately matches users’ profiles/queries and job descriptions. The proposed approach is tested using various experiments on data from real life jobs’ portals. The results show that the proposed approach enriches extracted data from job descriptions, and can help users to find more relevant jobs.

Analysis and shortcomings of e-recruitment systems: Towards a semantics-based approach addressing knowledge incompleteness and limited domain coverage

The rapid development of the Internet has led to introducing new methods for e-recruitment and human resources management. These methods aim to systematically address the limitations of conventional recruitment procedures through incorporating natural language processing tools and semantics-based methods. In this context, for a given job post, applicant resumes (usually uploaded as free-text unstructured documents in different formats such as .pdf, .doc or .rtf) are matched/screened out using the conventional keyword-based model enriched by additional resources such as occupational categories and semantics-based techniques. Employing these techniques has proved to be effective in reducing the cost, time, and efforts required in traditional recruitment and candidate selection methods. However, bridging the skill gap - that is, the propensity to precisely detect and extract relevant skills in applicant resumes and job posts - and highlighting the hidden semantic dimensions encoded in applicant resumes are still challenging issues in the process of devising effective e-recruitment systems. This is due to the fact that resources exploited by current e-recruitment systems are obtained from generic domain-independent sources, therefore resulting in knowledge incompleteness and the lack of domain coverage. In this article, we review state-of-the-art e-recruitment approaches and highlight recent advancements in this domain. An e-recruitment framework addressing current shortcomings through the use of multiple cooperative semantic resources, feature extraction techniques and skill relatedness measures is detailed. An instantiation of the proposed framework is proposed and an experimental validation using a real-world recruitment dataset from two employment portals demonstrates the effectiveness of the proposed approach.

On the predictive analysis of behavioral massive job data using embedded clustering and deep recurrent neural networks

The recent proliferation of social networks as a main source of information and interaction has led to a huge expansion of automatic e-recruitment systems and by consequence the multiplication of web channels (job boards) that are dedicated to job offers disseminating. In a strategic and economic context where cost control is fundamental, it has become necessary to identify the relevant job board for a given new job offer has become necessary. The purpose of this work is to present the recent results that we have obtained on a new job board recommendation system that is a decision-making tool intended to guide recruiters while they are posting a job on the Internet. Firstly, the Doc2Vec embedded representation is used to analyse the textual content of the job offers, then the job applicant clickstreams history on various job boards are stored in a large learning database, and then represented as time series. Secondly, a deep neural network architecture is used to predict future values of the clicks on the job boards. Third, and in parallel, dimensionality reduction techniques are used to transform the clicks numerical time series into temporal symbolic sequences. Forecasting algorithms are then used to predict future symbols for each sequence. Finally, a list of top ranked job boards are kept by maximizing the clickstreams forecasting in both representations. Our experiments are tested on a real dataset, coming from a job-posting database of an industrial partner. The promising results have shown that using deep learning, the recommendation system outperforms standard multivariate models.

E-Recruitment through Job Portals and Social Media Network: Challenges & Opportunities

The rapid development of modern Information and Communications Technology (ICT) has resulted in an increasing number of job-seekers turning to the Web for information. This has motivated the use of electronic recruitment (e-recruitment) systems, also known as online recruitment which is one of the emerging worldwide trends in electronic human resource management (E-HRM) functions. E-HRM is a way of implementing HRM strategies, policies and practices in an organization through a directed support of Web technology based channels. The Internet can facilitate the selection of employees and other HR functions related to recruitment, especially where long distances are involved. This has dramatically changed the way business is conducted and this use of technology is clearly demonstrated by the number of organizations and individuals who utilize the Internet and electronic media. In terms of HR management, the Internet has changed the recruitment perspective for both organizations and job seekers. This paper helps to identify the merits and demerits of HR Portals and Social Media Network for recruiting the suitable candidates and the challenges faced by it.

The Role of E- Recruitment in Attracting Potential CandidatesEvidence from Fresh Graduate Job Seekers

The study aims to investigate the effectiveness of an online recruitment system and its impact on organizational attraction among fresh graduate job seekers. A sample comprised of 302 fresh graduate job seekers from well-known HEC recognized business schools in the Lahore region is selected using Stratified Random Sampling. Since the data is not normal, the Kruskill Wall is test of mean differences is applied to compare the effectiveness of e-recruitment with traditional methods of recruitment. Furthermore, the Macro process tool of Regression analysis is used to examine the matter of cost-effectiveness, easy to use and website quality. Findings of regression results confirm that e-recruitment has a positive influence on organizational attraction and cost-effectiveness and easy to use mediate the relationship between e-recruitment and organizational attraction. However, the positive relation between e-recruitment and organizational attraction depends on the quality of the recruitment website which depicts that Sitequal (Website Quality) moderates the relationship between e-recruitment and organization attraction. Thus, this study offers valuable findings for managers that aim to adopt E-recruitment systems in their hiring process.

Assessing Electronic Recruitment Implementation in State Governments: Issues and Challenges

In this study, we assessed the status of electronic recruitment for U.S. state government employees and analyzed the issues and challenges state governments faced while they implemented e-recruitment systems. All of the 23 state personnel agencies that responded to a phone survey either offered downloadable application forms or allowed candidates to submit applications online. Ten states had adopted options for assessing applicants and selecting job candidates online, but only three states reported that they had adopted online testing. The number of applications received online increased from 2002 to 2003, and the most common implementation challenges that states faced when introducing e-recruitment were budget constraints, technical difficulties, and HR staff adapting to using a new system. While 15 states reported that they evaluated their electronic recruitment system, only three said they measured the cost per hire. Based on the survey responses, we conclude this article by presenting lessons and implications for effectively implementing e-recruitment for state government employees.

An XML-Based Multiagent System for Supporting Online Recruitment Services

In this paper, we propose an Extensible Markup Language (XML)-based multiagent recommender system for supporting online recruitment services. Our system is characterized by the following features: 1) it handles user profiles for personalizing the job search over the Internet; 2) it is based on the intelligent agent technology; and 3) it uses XML for guaranteeing a light, versatile, and standard mechanism for information representation, storing, and exchange. This paper discusses the basic features of the proposed system, presents the results of an experimental study we have carried out for evaluating its performance, and makes a comparison between the proposed system and other e-recruitment systems already presented in the past.