BUS 271: Business Communication

Resumes - Applicant Tracking Systems in Today's World: Bibliography

Bafna, P., Shirwaikar, S., & Pramod, D. (2019). Task recommender system using semantic clustering to identify the right personnel. VINE Journal of Information and Knowledge Management Systems, 49(2), 181-199. https://doi.org/10.1108/VJIKMS-08-2018-0068

• Text mining is growing in importance proportionate to the growth of unstructured data and its applications are increasing day by day from knowledge management to social media analysis. Mapping skillset of a candidate and requirements of job profile is crucial for conducting new recruitment as well as for performing internal task allocation in the organization. The automation in the process of selecting the candidates is essential to avoid bias or subjectivity, which may occur while shuffling through thousands of resumes and other informative documents. The system takes skillset in the form of documents to build the semantic space and then takes appraisals or resumes as input and suggests the persons appropriate to complete a task or job position and employees needing additional training. The purpose of this study is to extend the term-document matrix and achieve refined clusters to produce an improved recommendation. The study also focuses on achieving consistency in cluster quality in spite of increasing size of data set, to solve scalability issues.

Faliagka, E., Tsakalidis, A., & Tzimas, G. (2012). An integrated e-recruitment system for automated personality mining and applicant ranking. Internet Research, 22(5), 551-568. https://doi.org/10.1108/10662241211271545

• The purpose of this paper is to present a novel approach for recruiting and ranking job applicants in online recruitment systems, with the objective to automate applicant pre‐screening. An integrated, company‐oriented, e‐recruitment system was implemented based on the proposed scheme and its functionality was showcased and evaluated in a real‐world recruitment scenario.

Köchling, A., Wehner, M. C., & Warkocz, J. (2022). Can I show my skills? affective responses to artificial intelligence in the recruitment process. Review of Managerial Science, https://doi.org/10.1007/s11846-021-00514-4

• Companies increasingly use artificial intelligence (AI) and algorithmic decision-making (ADM) for their recruitment and selection process for cost and efficiency reasons. However, there are concerns about the applicant’s affective response to AI systems in recruitment, and knowledge about the affective responses to the selection process is still limited, especially when AI supports different selection process stages (i.e., preselection, telephone interview, and video interview). Drawing on the affective response model, we propose that affective responses (i.e., opportunity to perform, emotional creepiness) mediate the relationships between an increasing AI-based selection process and organizational attractiveness. In particular, by using a scenario-based between-subject design with German employees (N = 160), we investigate whether and how AI-support during a complete recruitment process diminishes the opportunity to perform and increases emotional creepiness during the process. Moreover, we examine the influence of opportunity to perform and emotional creepiness on organizational attractiveness. We found that AI-support at later stages of the selection process (i.e., telephone and video interview) decreased the opportunity to perform and increased emotional creepiness. In turn, the opportunity to perform and emotional creepiness mediated the association of AI-support in telephone/video interviews on organizational attractiveness. However, we did not find negative affective responses to AI-support earlier stage of the selection process (i.e., during preselection). As we offer evidence for possible adverse reactions to the usage of AI in selection processes, this study provides important practical and theoretical implications.

Lacroux, A., & Martin-Lacroux, C. (2022). Should I trust the artificial intelligence to recruit? recruiters' perceptions and behavior when faced with algorithm-based recommendation systems during resume screening. Frontiers in Psychology, 13, 895997-895997. https://doi.org/10.3389/fpsyg.2022.895997

• Resume screening assisted by decision support systems that incorporate artificial intelligence is currently undergoing a strong development in many organizations, raising technical, managerial, legal, and ethical issues. The purpose of the present paper is to better understand the reactions of recruiters when they are offered algorithm-based recommendations during resume screening. Two polarized attitudes have been identified in the literature on users’ reactions to algorithm-based recommendations: algorithm aversion, which reflects a general distrust and preference for human recommendations; and automation bias, which corresponds to an overconfidence in the decisions or recommendations made by algorithmic decision support systems (ADSS). Drawing on results obtained in the field of automated decision support areas, we make the general hypothesis that recruiters trust human experts more than ADSS, because they distrust algorithms for subjective decisions such as recruitment. An experiment on resume screening was conducted on a sample of professionals (N = 694) involved in the screening of job applications. They were asked to study a job offer, then evaluate two fictitious resumes in a 2 × 2 factorial design with manipulation of the type of recommendation (no recommendation/algorithmic recommendation/human expert recommendation) and of the consistency of the recommendations (consistent vs. inconsistent recommendation). Our results support the general hypothesis of preference for human recommendations: recruiters exhibit a higher level of trust toward human expert recommendations compared with algorithmic recommendations. However, we also found that recommendation’s consistence has a differential and unexpected impact on decisions: in the presence of an inconsistent algorithmic recommendation, recruiters favored the unsuitable over the suitable resume. Our results also show that specific personality traits (extraversion, neuroticism, and self-confidence) are associated with a differential use of algorithmic recommendations. Implications for research and HR policies are finally discussed.

Laumer, S., Maier, C., & Eckhardt, A. (2015). The impact of business process management and applicant tracking systems on recruiting process performance: An empirical study. Zeitschrift Für Betriebswirtschaft, 85(4), 421-453. https://doi.org/10.1007/s11573-014-0758-9

• This research focuses on the effects of different business process management components in combination with information technology on recruiting process performance. The results of a study of Germany’s largest 1,000 business enterprises (response rate 13.1 %) reveal that business process analysis, business process improvement and the usage of applicant tracking systems reduce recruiting process costs. Specifically, the cycle time of the recruiting process can be shortened significantly through business process controlling and process analysis, and by using an applicant tracking system that supports the design and evaluation of key performance indicators. Business process standardization combined with applicant tracking systems and business process documentation as well these systems used together with business process controlling have a significant positive impact on stakeholder satisfaction with the recruiting process. The general quality of the process can be improved through business process controlling as well as through a combination of applicant tracking systems and business process controlling. Our results reveal that several components of the business process management in conjunction with a supporting applicant tracking system have differing impacts on recruiting process performance. This paper discusses these diverse effects of business process management on process performance and draws implications for information systems success research.

Nikolaou, I. (2021). What is the role of technology in recruitment and selection? The Spanish Journal of Psychology, 24, e2-e2. https://doi.org/10.1017/SJP.2021.6

• We explore a number of new developments in the field of employee recruitment and selection with a focus on recent technological developments. We discuss examples of technological developments across the four stages of the recruitment and selection process. In the attraction stage we discuss how on-line/internet recruitment and especially social networking websites have changed dramatically the focus of attracting candidates effectively. In the next stage of screening, we discuss how cybervetting and applicant tracking systems offer opportunities but also threats for recruiters and candidates. In the third stage of employee selection, we focus especially on two new selection methods; the asynchronous/digital interview and gamification/games-based assessment, along with the critical role and impact applicant reactions have on the selection process. Finally, we briefly discuss the main technological developments in on-boarding and socialization, and we conclude with a few suggestions for future research in this field.

Novak, J. (2017). Making the cut when applying for jobs online. Journal of Vocational Rehabilitation, 46(3), 293-299. https://doi.org/10.3233/JVR-170864

• BACKGROUND: Companies are increasingly moving toward the use of web-based hiring practices. Unfortunately, job applicants with disabilities may encounter barriers to accessing and submitting online job applications. Recent research reveals that nearly half of job seekers with disabilities who applied for a job online found the experience to be difficult or impossible. OBJECTIVE: This article provides job seekers with intellectual and developmental disabilities and those who support them with winning strategies for navigating the online application process. CONCLUSION: Strategies focus on getting your application through automated filters in applicant tracking systems, making a good first impression, requesting assistance, leveraging your personal connections, and standing out from the crowd.

Russell, D. P. (2007). Recruiting and staffing in the electronic age: A research-based perspective. Consulting Psychology Journal, 59(2), 91-101. https://doi.org/10.1037/1065-9293.59.2.91

• Although the consulting psychology profession tends to focus on assessment and development, effectiveness in these domains is strongly influenced by how effective the recruiting process has been. The continuing widespread acceptance of Web-based recruiting systems presents both opportunities and challenges for consulting psychologists. An overview of recent research in this area, along with implications for the practicing consulting psychologists, is presented.

Diassi, T. (2016). Why automation is the next step in HR?s evolution: Why automation is the next step in HR?s evolution. Employee Benefit Adviser (Online). http://umiss.idm.oclc.org/login?url=https://www-proquest-com.umiss.idm.oclc.org/trade-journals/why-automation-is-next-step-hr-s-evolution/docview/1911977035/se-2

• [...]many organizations are embracing technology to orchestrate and streamline all types of HR administration processes. Tech tools vital for HR success Implementing a centralized HR platform provides real-time information for executives to understand personnel trends and gives employees more control of the services offered to them, including self-service options. If you?re looking into starting this process today, consider automating the following five priority tasks first to ensure a smooth transition: · Applicant tracking and onboarding · Time and attendance · Records management and reporting · Benefits enrollment · Payroll Applicant tracking and onboarding Finding the right employees can be the difference between company failure and success. [...]by providing a centralized platform to post jobs and then screen and score resumes, an automated system can help HR departments easily weed out unqualified candidates during the initial recruiting process. [...]tracking time and attendance can be a difficult process, rife with regulations and strict compliance guidelines. From an HR perspective, it reduces paperwork and data entry while giving companies the ability to integrate payroll into benefits administration; combining these two functions allows HR departments to accurately track withholdings and contributions.

Dysart, J. (2022). AI recruiting: Businesses get a boost from automation. Business NH Magazine, 39(4), 14-15. http://umiss.idm.oclc.org/login?url=https://www-proquest-com.umiss.idm.oclc.org/trade-journals/ai-recruiting-businesses-get-boost-automation/docview/2655172694/se-2

• Kevin Parker, CEO of Hire Vue, another candidate interviewing tool that uses AI, says the pandemic has "created a unique opportunity for employers to redesign their hiring processes-leveraging technology that complements the capability of employees at a speed and scale not otherwise possible."

Hipps, C. (2019, December). can ai reduce bias in talent selection? Training Journal, 22-24. http://umiss.idm.oclc.org/login?url=https://www-proquest-com.umiss.idm.oclc.org/trade-journals/can-ai-reduce-bias-talent-selection/docview/2410492657/se-2

• [...]more consistent disparate impact scores of close to 1.0 (ie no disparate impact observed) are recorded in hiring predictions undertaken in this way, providing better hired prediction performance. By being built on thousands of data points derived from candidates resumes/CVs and profiles/applications to foster diversity and accelerate candidate selection, the intelligent algorithm is optimised to ensure no adverse selection in compliance with established EEOC selection rates. [...]recruiters can monitor anonymised data insights on gaps in diversity pools and focus attraction efforts on obtaining better representation without sacrificing quality. * Sources - increase uncovering strong candidates from new sources, who are typically overlooked by the manual process, with algorithms scouring broader pools to look at all candidates regardless of source. In so doing, it is feasible that technology could effectively free up months of recruiter resource each year - time which could be spent on adapting better engagement techniques to ensure a leading candidate with many offers at their disposal is more likely to buy into the culture, mission and vision of our clients ahead of market competitors with equally tempting offers on the table.

Sachar, S. (2019, April 8). Why is it becoming so difficult to get A job? Business World (India). http://umiss.idm.oclc.org/login?url=https://www-proquest-com.umiss.idm.oclc.org/magazines/why-is-becoming-so-difficult-get-job/docview/2204783723/se-2

• According to a white paper published by CV library 68% of the hiring of talent is done directly. While humans can never be replaced for many assessment factors related to the hiring of talent, AI-backed by automation of data and social media is supporting the recruitment activity. Option 2 is to outsource the entire job search activity right from developing your ATS friendly Resume to receiving interview calls to being coached for an interview through one of it's kind job assistance service offered by Aspiration.

Technology and adaptability: How HR professionals are navigating the unique talent demands? (2022, May 19). Business World (India). http://umiss.idm.oclc.org/login?url=https://www-proquest-com.umiss.idm.oclc.org/magazines/technology-adaptability-how-hr-professionals-are/docview/2666699071/se-2

• According to a recent study, a third of the HR leaders surveyed said that they are altering how they hire by building better candidate experiences for new joiners. Advanced technological domains such as Data Science, AI, and ML are being deployed by organizations to plan, execute, monitor, measure, analyze business challenges and manage talent more effectively. [...]these tech adoptions were due to the need for quick and simple solutions for all kinds of problems faced during virtual recruitment processes like slow internet or hours of video conferences for interviewing candidates. AI-powered résumé assessments, candidate ranking, recruitment bots to pre-screen and video-based interviews that use facial/emotion recognition streamline the recruitment process and help the recruiter understand just how well the candidate can fit the role.

Applicant Tracking Systems Among Global Top 500

• https://www.appsruntheworld.com/applicant-tracking-systems-among-global-top-500/

8 Things You Need To Know About Applicant Tracking Systems

• https://mckelveyconnect.wustl.edu/blog/2022/02/04/8-things-you-need-to-know-about-applicant-tracking-systems/

99% of Fortune 500 Companies use Applicant Tracking Systems

• https://www.jobscan.co/blog/99-percent-fortune-500-ats/