Abstract In chapter 1, the aim and objectives are clearly mentioned along with some research questions that provides a clear concept about the research topic and it is also necessary for achieving the project goal. The discussion about the role of technology within recruitment selection is clearly addressed within the research background along with the Read More
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Abstract
In chapter 1, the aim and objectives are clearly mentioned along with some research questions that provides a clear concept about the research topic and it is also necessary for achieving the project goal. The discussion about the role of technology within recruitment selection is clearly addressed within the research background along with the importance of this topic is addressed within the research rationale part. In the second chapter, a general information about the topic is addressed where the impact of artificial intelligence, example of AI technology along with its role are clearly mentioned. A conceptual framework is created for evaluating the entire information’s that is covered within the literature review chapter.
The data collection method, data analysis, and other aspects that aid in gathering reliable data depending on the research topic are addressed in detail in chapter 3. Thematic analysis is presented in the analysis chapter as a way to help accomplish goals and get outcomes. The recommendation and future scope are explicitly addressed in the conclusion chapter in order to wrap up the research project.
Table of Contents
1.2 Research aim and objectives. 5
Chapter 2: Literature review.. 11
2.1 Introduction to recruitment and selection. 11
2.2 Role of AI technology in the recruitment and selection process. 12
2.3 Factors affecting the role of technology in recruitment 14
2.4 Critical Evaluation of the role of “Artificial Intelligence” technology in recruitment 16
2.5 Impact of “Artificial Intelligence (AI)” technology on the selection and recruitment process 19
2.6 Example of technology in the recruitment process. 21
Chapter 4: Discussion and Analysis. 34
5.2 Linking with Objectives. 46
The use of technology in hiring and selecting candidates has grown in significance. Technology has completely changed how recruiters find and entice candidates for open positions. It is now simpler for both employers and job seekers to interact with prospective employers because of the development of social media, online job boards, and other digital channels. Reaching a larger pool of candidates is one of the main advantages of technology in recruiting and selection. Online job postings allow employers to reach candidates all around the world. In order to save time and resources, they might also screen resumes and applications using digital tools. Moreover, online job fairs and video interviews have grown in popularity as communication tools (Van Esch & Black, 2019). Technology plays an important role in this recruitment process where the applicant tracking system helps to manage the resume and track multiple applications that have been based on their qualifications along with experiences. In that case, the automation technology of AI assists in this recruitment process by applying an initial screening process and sorting resumes based on the candidate’s job requirements. In addition, technology has improved the candidate experience by providing more transparency and communication throughout the recruitment and selection process. Employers can provide real-time updates on the status of applications and use chat bots to answer common questions from candidates.
On the other hand, there are multiple pieces of information and will be addressed in this chapter including “research aim and objectives” that is necessary for setting a clear goal.
Aim
The primary aim of this assignment is to optimize the hiring process by applying AI technology that helps to improve the quality and reduce time and costs of this hiring and recruitment process.
Objectives
This research has been based on “The role of technology in recruitment and selection”. This research has explored various way that has been used in the selection process including “online job posting”, “application tracking system”, “social media recruitment process”, “video interview session” and many others. In addition, the effect of technology on the inclusiveness and diversity of the recruitment process has been the subject of some research. Technology can assist enhance diversity and decrease human biases, but if it is not handled correctly, it can also reinforce biases (Hmoud and Laszlo, 2019). Another area of inquiry looked at how technology affected the hiring process. According to this research, technology can help make candidates for a smooth and effective recruitment process. Generally, research on the use of technology in recruitment and selection points to the possibility that it can improve the hiring process. It must be utilized carefully to prevent the perpetuation of prejudices and to guarantee a favourable candidate experience.
In that case, the automation technology plays a crucial role in the recruitment and hiring process and multiple aspects are present where this AI performs really well such as “increased efficiency”, “provides wider reach”, “improved candidate experiences”, “improved data-driven decision-making process”, along with “eliminate bias”. This technology helps every recruiter in order to conduct automated tasks where it helps to schedule one or multiple interviews easily and quicker than the other offline process. This technology also enables every recruiter for reaching a wider pool of candidates by posting multiple job vacancies through social media platforms and company websites. It helps to create a larger applicant pool and also it has the ability in order to find candidates faster. In addition, the technology is able to enhance the candidates’ experiences by applying seamlessly along with a user-friendly application process where the online applications portals are enables each and every candidate to apply for a job and track their application status. In addition. Recruiters have access to a wealth of data that can be evaluated to help them make wise recruiting decisions (Yarger et al. 2020). Recruitment analytics, for instance, can be used to spot hiring trends, monitor key performance indicators, and forecast candidate success. This automation technique helps to eliminate multiple bias within the recruitment process by applying objective criteria to screen and select candidates. This technology has become an integral part of this recruitment process that helps to improve the business decision for revenue growth.
In recent years, technology has been used more frequently in recruiting and selection processes and the body of studies examining its effects is expanding. This study rationale argues the need for more research into how technology is used in hiring and selecting employees. First, technology has the ability to improve the effectiveness and efficiency of the hiring and selection process. There isn’t enough research, though, looking at the precise ways in which technology might bring about these advantages. Further study is required to determine which techniques work best in certain situations and how different technologies might be employed to improve recruiting and selection outcomes (Johnson et al. 2020). The use of technology in hiring and selecting candidates also raises significant ethical and legal issues that need to be investigated. While there are numerous advantages to technology, it also raises significant concerns about issues like privacy, prejudice, and discrimination. To comprehend the benefits and drawbacks of various technical approaches and to create best practices for their moral and responsible use, more research is required. The impact of technology on the applicant experience must be understood, third. Candidates’ experience throughout the recruiting and selection process could be enhanced by technology, for instance by delivering more timely and individualized communication. Certain individuals, however, who might not have access to technology or who might feel uneasy with virtual contact, may face obstacles as a result. The use of technology to improve candidate experiences and to lessen any negative effects requires more study.
Figure 1: Research structure
This structure has been created based on the chapters that will be covered in this assignment and a brief description of each chapter will be discussed in the below session,
Chapter 1: Introduction
This chapter has stated a clear goal along with the project objectives that are necessary for executing the project work without facing any types of difficulties. Also, the research questions have been already selected in this chapter for generating proper findings by implementing thematic analysis. The importance of technology within the recruitment process has been also addressed in this part that provides a clear understanding of the research topic. A summary portion is given for gathering the entire points that are created within this chapter.
Chapter 2: Literature review
This chapter represents multiple types of general information that help to gather a clear concept about the research topic. Several advantages of the technology that helps in the hiring process will be discussed along with its impact. A gap will be covered that is present within the existing research and a conceptual framework will be created that helps to summarize all points in this chapter.
Chapter 3: Methodology
The data collection method will be discussed here that plays an important role in executing the research work successfully. In addition, a time plan will be also created for maintaining the time schedule.
Chapter 4: Findings
“Thematic analysis” will be conducted in this part that helps to meet the entire requirements of this project work.
Chapter 5: Discussion
Multiple recommendations, future outcomes, and many others will be covered in this part.
The hiring and selection process has undergone a substantial transformation thanks to technology. Organizations can use it to improve candidate experience, expand the candidate pool, promote objectivity and fairness, and make data-driven judgments. Recruiters can target particular demographics, gather and analyse data, and automate repetitive processes like scheduling interviews and evaluating resumes. Organizations may stay competitive in the quick-paced, digitally-driven world by integrating technology into their recruitment and selection methods (Van den Broek et al. 2021). In that case, there are multiple ways are present where AI helps in recruitment and selection process such as “resume screening”, “candidate sourcing”, “chat bot and virtual assistant”, along with “predictive analysis”. The advanced techniques of AI are able to screen resumes along with CVs by using natural language processing algorithms. It helps in predictive analysis where it provides an easier way for analysing candidates’ data and also helps to create a user’s profile that has been based on historical hiring data. On the other hand, this technology helps in analysing video interviews by using facial recognition analysis.
Organizations use recruitment and selection as two key procedures to find, evaluate, and choose qualified applicants for open positions. These procedures are essential for ensuring that businesses employ the best candidates with the knowledge, expertise, and credentials required to meet their objectives. This section will give a summary of the recruitment and selection procedures along with their goals, steps, and difficulties (Abdulrahaman et al. 2020). Recruitment is the process of locating and enticing potential workers to apply for current or upcoming positions within a firm. It involves many activities, such as finding candidates, job analysis, job description, and posting. Building a pool of qualified candidates who can contribute to the development of the company and fulfill the requirements of the job post is the goal of recruitment. Recruitment methods can be internal or external depending on whether a company promotes from within or looks outside. The process of analysing and selecting the best qualified applicant from the pool of candidates for a given employment vacancy is called selection, on the other hand. Numerous processes are involved, including background checks, testing, interviews, and resume screening. Finding the best candidate with the required knowledge, expertise, and qualifications for the position and alignment with the organization’s culture, beliefs, and objectives is the aim of the selection process (Niati et al. 2021). Organizations need to have recruitment and selection procedures in place for a number of reasons. First and foremost, they aid businesses in locating and luring the best talent on the market, which can increase their competitiveness and profitability. The second benefit is that they offer a fair and open hiring procedure that guarantees candidates are judged on their qualifications rather than unimportant ones like colour, gender, or age. Thirdly, they assist businesses in lowering the possibility of selecting the incorrect employee, which may lead to low productivity, high turnover rates, and a toxic work environment (Ore et al. 2022).
This also assists in decision-making that also can be data-driven. The specific technology has offered particular companies for gathering as well as the analysis of the specific data on their particular selection as well as recruitment procedures, offering them to recognise the specific areas of development as well as make specific data-driven decisions.
All over, the specific technology has specifically transformed recruitment as well as selection procedures, making them more effective, efficient, as well as inclusive.
Technology has advanced the selection as well as recruitment procedure in several ways, offering new as well as inventive solutions to streamline the overall procedure as well as making it more effective. “Artificial intelligence” or AI also acts an enhanced significant role in selection as well as recruitment procedures.
Some of the roles of specific technology in the specific recruitment as well as selection procedure are mentioned below.
“Applicant Tracking Systems”: The respective ATS software offers the specific companies to track, receive, as well as manage several resumes and also various online job applications (Hmoud et al. 2019). The particular software utilises specific algorithms to examine resumes as well as recognise the particular candidates that can be most qualified, saving the particular recruiters’ time as well as effort in the specific selection procedures.
Figure 2.2.1: Role of technology in the recruitment procedure
(Albert, 2019)
Video Interviewing: Technology like AI offers for screening specific video interviews, which can be able to save overall time and money compared to specific interviews. The video interviews also offer the particular recruiters to examine the communication skills of the specific candidate and also their specific personality inviting them for a personal interview (Wu et al. 2019).
Artificial Intelligence: The recruitment tools can assist in the specific screen resumes, conducting specific video interviews, as well as even examining the specific behaviour as well as responses of the particular candidate during the selection procedure. It assists in eliminating specific human bias as well as offers a more objective examination of the particular candidates.
Job Posting as well as Advertising: Technology can be made it possible for posting specific job vacancies as well as advertise them on several platforms such as particular job boards, social media, as well as particular company websites. It enhances the particular visibility of specific job postings as well as engages an extended range of specific candidates (Sánchez-Monedero et al. 2020).
Data Analytics: The specific technology offers various companies to gather data on the particular recruitment as well as selection procure, which can be analysed to enhance the specific hiring process as well as make specific data-driven decisions.
Mobile Recruiting: With the enhanced utilisation of various mobile devices, the specific technology has made this possible for the recruitment of specific candidates utilising specific platforms that also can be mobile-friendly, like various mobile job applications as well as particular recruitment portals that also can be mobile-friendly.
Overall, the particular technology acts a crucial role in the specific recruitment as well as selection procedure, offering the respective companies for reaching an extended pool of specific candidates, streamlining the specific procedure of selection, decreasing the bias, and also making the specific data-driven decisions (Yener et al. 2021).
Artificial Intelligence or AI is an ascending specific technology that is the transformation of the specific recruitment procedure, there are various factors that can impact the specific role of AI in specific recruitment procedures.
Complexity: These specific AI systems can be complex as well as need the technical skills for implementation and maintenance. The specific companies are required to be invested in essential training as well as resources for making sure that their staff can efficiently operate as well as manage the particular AI systems (McCartney et al. 2021).
Data Quality: The specific AI algorithms imply high-standard data for making exact predictions as well as suitable recommendations. If the specific data utilised by the specific AI systems are biased or incomplete, this can outcome in incorrect recommendations as well as specific decisions (Sima et al. 2020).
Cost: The particular AI systems can be costly for development as well as implementation, which can be an impediment to the adaption of shorter companies with restricted budgets.
Figure 2.3.1 several factors of the online recruitment process
(Fenech et al. 2019)
Specific Cloud-based recruitment suggests the utilisation of the following cloud computing technology for managing the particular recruitment procedure. This approach offers the respective companies for accessing the particular recruitment data as well as tools online, without the requirements for reliable hardware or software.
Integration with the systems that already existed: The specific AI systems are required to be integrated with the specific recruitment systems that already existed and procedures to be efficient. It may be challenging if the particular systems that already existed are obsoleted or inconsistent with the specific AI technology.
Regulatory Compliance: The particular systems utilised in the specific recruitment procedure are required to comply with legal as well as regulatory conditions, such as “data privacy laws”, and “anti-discrimination laws”, as well as the particular regulations around particular recruitment tools that can be AI-powered. Delinquency in complying with these regulations can outcome in legal as well as reputational risks (Vrontis et al. 2022).
Ethical Concerns: The AI systems are required to be structured as well as executed ethically, with particular measurements to control biases as well as secure the privacy of the particular candidate. There are concerns about the prospect of the particular AI technology reinforcing or intensifying the specific biases that already existed in the particular recruitment process, which can cause intolerance against specific groups of particular candidates.
Overall, the particular role of AI in specific recruitment processes can be impacted by several factors, involving ethical concerns, data quality, complexity, transparency, cost, engagement with the specific systems that already existed, as well as individual regulatory compliance. This is crucial for specific companies to evaluate these respective factors when embracing as well as implementing the particular AI technology in the recruitment process, for making sure that they are efficient, fair, and also appreciative of the legal as well as ethical standards.
From job posting to candidate evaluation and selection, technology has significantly impacted the recruitment process in recent years. There are benefits and drawbacks to using technology in recruitment, despite the fact that it has improved efficiency and effectiveness. We will examine both the advantages and disadvantages of technology’s role in recruiting in this rigorous examination (Ojo et al. 2022). In recent years, artificial intelligence (AI) has become increasingly important in the hiring process. Some of the advantages of “Artificial Intelligence (AI)” have been discussed below:
Figure 2.4.1: Advantages of AI in recruiting
(Influenced from the topic)
Disadvantages:
On the other hand, there may be negative effects of using AI in hiring, such as:
Figure 2.4.2: Advantages of AI in recruiting
(Influenced from the topic)
Ultimately, using AI in hiring can have a lot of advantages, but to ensure fairness and accuracy, it must be used responsibly and in conjunction with human decision-making. The specific role of a particular technology in the recruitment process has remarkably enhanced in recent years. While the particular technology has obtained various benefits to the particular recruitment process, this has also revealed some specific challenges that are required to be evaluated critically (Tschang et al. 2021).
This is to make sure that can be unbiased, and fair, as well as improves the particular candidate’s experience. Particular employers needed to also prioritize specific data privacy as well as be conscious of the particular potential impact of the specific recent technologies on the upcoming future of work.
In recent years, artificial intelligence (AI) technology has had a considerable impact on the recruitment and selection process. The way recruiters find, assess, and choose candidates for job openings has been altered by AI. Here are some examples of how artificial intelligence has changed the recruitment and selection process:
While artificial intelligence (AI) technology has numerous advantages in the hiring process, it also has some potential negatives, such as the possibility of prejudice, a lack of transparency, and blunders. It’s crucial to appropriately use AI technology in conjunction with human judgement in order to reduce these dangers while maintaining the fairness, openness, and efficiency of the hiring process.
These are a few examples of how technology is being used in the hiring process and some of the examples have been discussed below:
These are but a few instances of the numerous ways that technology is being applied to the hiring process. Employers must keep up with the most recent trends and tools to stay competitive in the hiring market as the usage of technology in recruitment is continuously changing.
Figure 2.8.1: Conceptual Framework
(Snipped from the Draw.io online platform)
In the above image, a conceptual framework for the literature review chapter has been developed using the online platform “Draw.io”. The topic is “The role of technology in recruitment and selection” and there are sections related to the literature survey on the topic. The first part is about the general introduction of the literature review chapter. The second part is about the role of AI technology in the process of recruitment and selection. The third part discusses the factors that are affecting the role of technology in recruitment. The fourth part discusses the critical evaluation of the role of “Artificial Intelligence (AI)” technology in the process of recruitment. The fifth part of the literature survey chapter discusses the potential impacts of “Artificial Intelligence (AI)” technology on the selection and recruitment process. The sixth part of the chapter discusses the example of technology in the recruitment process. The seventh part of the chapter discusses the literature gap of the project work and the last chapter discusses the general summary of the literature review chapter.
Regarding the use of technology in hiring and selecting candidates, there are several gaps in the writing. Insufficient study of the long-term effects of AI technology while there has been extensive research on the advantages and disadvantages of AI technology in employment and selection, there hasn’t been as much done on how these technologies will affect the workforce over the long term. There is little study, for instance, on how AI technology may affect career development, job satisfaction, and employee retention (Pham et al. 2020). Lack of research on the effects of AI on the applicant experience is one area where there may be a void in the literature on the subject of technology’s role in recruitment and selection. There has been a lot of research on the advantages and drawbacks of AI for recruiting and selection, but little empirical data exists on how AI influences job candidates’ attitudes and impressions of the hiring process. There is still a need for more study on this subject, even though some studies have addressed the ethical ramifications of AI technology in recruitment and selection. Research is specifically needed to look at how AI technologies can perpetuate prejudice and discrimination as well as how these technologies can be developed and used in an ethical and just way. A lack of study on how technology is affecting various industries and job roles although some research has been done on how technology may affect recruitment and selection in particular industries or job roles, more study is required to look at how these technologies may affect various industries and job roles (Litchman et al. 2019). Candidate experience refers to the overall impression and satisfaction of candidates with the recruitment and selection process, from the initial contact to the final decision. It is a critical factor in attracting and retaining top talent and building a positive employer brand. However, AI can create a perception of impersonality, lack of human interaction, and reduced transparency, which can negatively impact the candidate experience. The adoption of AI technology in recruitment and selection may present both opportunities and challenges, which this study may help to find. Thus, there is a need for research that looks at how candidates react to and interpret AI-based hiring and selection procedures. Such studies can offer important information about the elements that affect applicant engagement and happiness, the effects of AI on diversity, equity, and inclusion, and the best methods for creating candidate-friendly and efficient AI-powered hiring procedures. By filling up this vacuum in the literature, the research can help to create a more thorough understanding of the function of technology in hiring and selecting employees as well as help to create strategies that are based on solid data and are advantageous to both employers and job prospects.
“Methodology” is an essential component that provides a useful systematic along with a structured approach in order to conduct this research work efficiently. A proper enhancement of research methodology ensures the research validation and it is necessary for creating an accurate framework for the research. This helps to ensure that the research has focused and that the research questions are answered in a way that is meaningful and relevant. In that case, it plays an important role in both collecting and analyzing data that has been based on the selected topic area. This methodology part helps to ensure the data reliability and there are multiple types of critical aspects present that is essential in order to complete this research work within the selected time. Different types of information will be addressed in this topic where the stages of the research onion along with the details of the research design will be discussed in this part. Also, the details about the data collection method and details of data sampling will be addressed for enhancing the entire research work. A time plan will be created that is crucial for managing time and saves project costs.
“Research onion” works as a methodological framework that has been widely used in order to summarize the entire research process. Multiple stages are present within this process such as “research philosophy”, “research approach”, “research strategy”, “research methods”, “research analysis” along with “research method”. It helps to conduct research work by following the above steps and helps to conduct clear research approaches that makes research process more efficient rather than the other techniques. The research onion covers all the key elements of research design, including the research philosophy, approach, strategy, methodology, methods, and techniques. By considering each of these elements in turn, researchers can develop a comprehensive research design that is well-suited to their research question and objectives. On the other hand, it is more flexible along with adaptable in order to specify the research needs and helps to choose accurate data collection techniques for conducting the entire research work. Researchers can make sure their study is thorough, well-structured, and in line with the research objectives by using the research onion as a guide. The research onion is used in this study as a framework to direct the investigation. Also, the study’s research design was a descriptive one.
Figure 3.2.1: Research onion
(Seuring et al. 2021)
While a researcher addresses a study issue or hypothesis, they adopt a general plan or method known as research design. It serves as the general outline for the entire research project and contains choices on the research topic, approaches to gathering data, strategies for analysing that data, and other crucial components of the research procedure. In that case, there are different types of research design are present where “descriptive research design” has been selected in order to gather data about the selected research topic. This design works really well for describing and analysing a particular situation where it has been involved in gathering information by applying observation, surveys along with interviews. In addition, it is very crucial for identifying the data relationships and patterns that help to collect more accurate data about the details of technology for the recruitment process (Siedlecki, 2020). It provides a clear analysis and detailed information about recruitment technology. This design plays an important role in maintaining data flexibility and provides a wide range of data for collecting accurate data. Descriptive research design is frequently less expensive than other types of research designs. It can be carried out utilizing straightforward and affordable data collection techniques, such as surveys or questionnaires. In exploratory research, where the objective is to learn more about a phenomenon or circumstance, the descriptive research design is very helpful. It can be useful to pinpoint crucial elements and connections that merit additional, in-depth research. In addition, it provides multiple types of valuable data in order to conduct further research and also helps to identify the gap in the research work that plays an essential role in maintaining consistency of the entire research work.
A key component of conducting research is developing a research philosophy since it offers a framework for comprehending and approaching the research process. The researcher’s worldview or collection of presumptions regarding the nature of reality, knowledge, and the function of the researcher in the research process is known as the research philosophy (Nickerson, 2022). The researcher’s disciplinary training, theoretical perspective, and personal values and views are frequently the foundation of their research philosophy. In that case, “interpretivism research philosophy” has been selected for the research work that helps to emphasize different types of subjective interpretation. Also, it helps to compare multiple pieces of information that have been collected from different scholarly journals. This interpretation is necessary for gathering accurate information about the recruitment process. This process has been selected for collecting data in depth that has been based on subjective experiences along with the perspective of questionnaires. However, it is flexible and allows for a wide range of research methods and techniques. Researchers can adapt their methods to suit the specific research question and context and can use both qualitative and quantitative data. This philosophy helps to mitigate different types of subjective challenges as per the research requirements and helps to conduct a proper research methodology for collecting accurate data based on the selected topic where it helps to compare multiple types of recruitment techniques as per the research requirements.
Several types of research approaches are present that work as a part of the research methodology. In that case, “deductive research approach” has been used and works as a comprehensive research strategy in order to analyse, collect, and data comparison. This selected research approach is a method of scientific investigation that involves developing a hypothesis or theory and then testing it through empirical observations and data analysis (Young et al. 2020). In addition, this approach allows researchers to start with a clear and well-defined “research question”, “hypothesis, or theory” which helps to focus the research process and ensure that the research is relevant and meaningful. It has been based on the different types of systematic and objective processes that are widely used in data collection and analysis that is also necessary for reducing the potential bias along with the subjectivity of this entire research work. It maintains the entire reliability that provides an accurate along with transparent method in order to conduct the research work. This research approaches has been selected for multiple aspects such as “cost-efficiency” and it has been used in order to test the hypothesis in research design. It also provides a clear direction among other research approaches and helps to get an accurate data based on the selected research topic. It also contributes in theory building within a selected field that is necessary for identifying the particular theoretical concept along with principles that have been based on the data evidence. It improves the quality of the research work and helps to build an accurate theoretical concert for completing the research work.
There are several types of data analysis techniques are present where “qualitative data analysis techniques” has been used for collecting data about the chosen topic. This data analysis works as one of the most important critical aspects that helps to generate accurate conclusion rates for the research work. In addition, Finding patterns, themes, and categories that arise from the data and interpreting them in light of the research question and body of literature is the main objective of data analysis in qualitative research (Raskind et al. 2019). This data analysis is important for identifying the data patterns and it can also handle an enough range of data as per the research requirements. It helps to analyse the technical aspects that have been used for the recruitment and hiring process. On the other hand, these data analysis techniques help to develop interview sessions by sampling multiple questionnaires. Also, it has been used to transcribe and code the data that is collected through interviews or focus groups. This involves breaking the data down into smaller units, such as words or phrases, and categorizing them into themes or codes. This analysis technique has been selected as it helps to interpret data by applying observation, interviews, and many others where questions have been created based on the details of job recruitment techniques. It maintains flexibility based on the context of the research topic and also helps to gather effective data for this research work.
In this data collection method, mixed method has been used such as “primary data collection” and “secondary data collection” for this research work. In the case of this method, several general pieces of information have been collected by applying multiple “scholarly journals”, “online articles”, “books”, “websites” and many others. The primary research has been conducted based on the “interviews” where answers have been interpreted in order to get an accurate conclusion and complete the entire research work within time (Dawadi et al. 2021). In that case, this mixed method has been selected as it helps to control the data quality that has been collected during research work. The proper enhancement of the mixed method has been used in order to fit specific research questions that provide more detailed information along with relevant information for maintaining research flexibility. On the other hand, it helps to save project time as the data has been already collected based on the multiple existing research work. It also saves project expenses rather than the other data collection method and also provides more detailed information for generating an accurate thematic analysis for the result.
This research work has been conducted by maintaining confidentiality and privacy. It is crucial to make sure that every participant is willing to engage in the study and that they are all aware of its aim. Before deciding to participate, participants should be given access to all pertinent information and should have a chance to ask questions. Ethical considerations have been taken into account throughout the research process for the current topic. All participants have given informed consent before to the start of the study, and they have been made aware of their ability to withdraw from it at any moment without incurring any fees (Möllmann et al. 2021).
| Suggesting recommendation | ||||||||||
| Project closure |
Figure 3.9.1: Implementation of project timeline
As per the work, this chapter helps has been focused on the data collection that helps to fulfil the project aim and objectives. It helps to build an accurate systematic approach for generating accurate conclusion rates. In that case, this research methodology ensures ethical consideration and also helps to protect their data. Overall, a well-designed research methodology is essential for conducting rigorous and relevant research that contributes to the advancement of knowledge and understanding in a particular field. Several pieces of information have been addressed in this chapter where the details about the research onion, research philosophy along with the details research analysis have been clearly discussed in this part. This part also helps to maintain the research gap and provides a possible solution for conducting an accurate thematic analysis. It also helps to develop new theories along with the models for mitigating the gap of the entire research.
“Artificial intelligence” has become an important part of overall recruitment along with the selection process. This process helps to perform several types of automated tasks that are necessary in order to improve the efficiency and accuracy of the entire process. On the other hand, the proper applications of AI algorithms help to easily scan multiple resumes and identify relevant information including “education”, “work experience”, “skills” and many others (Vardarlier & Zafer, 2020). This can save recruiters a significant amount of time and allow them to focus on more strategic tasks. Also, the proper enhancement of AI is able to match multiple job recruitments according to candidates’ qualifications along with their experiences. AI can be used to evaluate data from previous hiring procedures to spot trends and forecast which candidates will perform well in a given position. As a result, there is a lower chance of employing the incorrect person and firms can make better selections. It also helps in a video in a video interview where this AI helps to recognize candidates’ expressions, voice tone, along with their body language that plays an important role in order to conduct a proper interview session as per the organization’s requirements.
This chapter will help to enhance a proper thematic analysis where multiple gaps will be addressed. Also, a general overview of this topic will be discussed in order to complete the entire project work within the proper time (Pan et al. 2022). This thematic analysis plays an important role in getting an accurate result that has been based on the chosen topic. It helps to fill multiple gaps that are already identified in the literature gap. In that case, the effects along with the recruitment process of AI will be covered in this chapter. Also, the key benefits along with the challenges of artificial intelligence in the recruitment process will be covered. The process will be clearly addressed where AI is used in order to reduce multiple human errors in the recruitment process.
4.2.1 Theme 1: Effects of AI in the recruitment process
In this recent times, maximum businesses and other organizations are using Ai technology for their hiring process as it has several positive effects that are necessary for business growth. In that case, the proper enhancement of AI techniques helps in several automating and repetitive tasks including “resume screening”, “scheduled interview”, “responding to candidate’s queries” and many others that save the recruiter’s time and helps to increase the efficiency level of every business organization (Ore & Sposato, 2022). On the other hand, it has been widely used in order to reduce the costs that are associated with the hiring and recruitment process. It helps to reduce the specific need for human intervention in the recruitment process. The proper enhancement of AI algorithms helps in data analysis faster than the other techniques by identifying the proper data trends along with data patterns. It is necessary for the organization’s recruiters in order to make different informed decisions and also helps to identify the most suitable candidates that have based on the candidate’s qualifications. In addition, an impressive part of the AI is “AI-powered chatbots” that provide an impressive and quick response for candidates in order to solve their multiple queries. Also, it helps to enhance their job experiences while the recruitment process is going on. It works really well for an online interviews and monitoring employee’s performance levels as per the organization’s requirements. It helps in activity tracking where the activities of remote workers, including the amount of time spent on tasks and the applications utilized, can be monitored by AI-powered solutions. Managers can use this to track productivity and spot areas where staff might need more assistance or training.
It helps to evaluate the overall performance matrices where AI is capable of analyzing information on employee performance, including the quantity and calibre of performed jobs as well as the time it took to complete each activity. In that case, managers can use this to spot patterns and trends in performance and decide how best to allocate resources. It plays an important role in order to analyze multiple comments from supervisors along with their coworkers to pinpoint employees’ strengths and weaknesses (Kot et al. 2021). It also has been widely used in order to improve employee performance levels and also able to identify key opportunities for improving professional development skills. On the other hand, AI can use data from past performance to predict future performance and identify potential areas of improvement or risk. This can help managers in order to take proactive steps to address issues before they become a problem. AI-powered coaching solutions can give remote workers individualized coaching and feedback to help them perform better. Even while working from home, this can help employees feel encouraged and motivated. Overall, AI can provide valuable insights into the performance of remote employees, allowing managers to monitor productivity, identify areas for improvement, and provide support and coaching where necessary.
In addition to that, AI-powered solutions can monitor the actions of remote workers by gathering information about their computer usage, such as the “time spent on various applications”, “the quantity of keystrokes”, and “the amount of idle time”. This information can be utilized to “track productivity”, and “spot inefficiencies”, and offers perceptions on how staff members are allocating their time. AI is capable of analyzing information on employee performance, including the quantity and caliber of work accomplished as well as the time required to complete each task. By comparing the performance of various individuals and identifying performance patterns and trends, this data may be utilized to allocate resources sensibly. AI is capable of analyzing feedback from supervisors and coworkers, including survey responses, performance appraisals, and comments on the task itself. This information can be utilized to pinpoint an employee’s performance’s strong and weak points, offer perceptions of how others see them, and pinpoint areas where they can improve.
4.2.2 Theme 2: Process of AI for influencing job candidates and hiring process
AI has the ability to greatly impact the hiring and applicant processes by streamlining and improving many areas of the procedure. It can be used to analyze previous job postings and determine the best language, structure, and distribution channels for luring top candidates, screen resumes and applications for essential skills and qualifications, match candidates with job requirements and company culture, streamline interview scheduling, evaluate candidates using a variety of methods, and use predictive analytics to improve hiring decisions. In addition, AI can help recruiters save time and improve the efficiency of the hiring process by automating time-consuming tasks, providing data-driven insights, and reducing the risk of bias. However, it is important to use AI ethically and transparently and to ensure that human decision-making is still involved at key stages of the process to avoid bias and ensure a fair and equitable hiring process (Van Esch & Black, 2019). It also helps in interview scheduling where chatbots and automated scheduling tools help in order to streamline the interview scheduling process and reduce delays and errors. This can help candidates move through the hiring process more quickly and smoothly. In order to find patterns and elements that are indicative of success in the role, AI can analyze data on previous hiring and performance. By using this information, recruiting decisions may be made better and there is less chance of choosing employees who will perform poorly or leave the business prematurely.
AI can help streamline and optimize the hiring process, from job posting to candidate assessment, by providing data-driven insights and automating time-consuming tasks. However, it is important to use AI ethically and transparently and to ensure that human decision-making is still involved at key stages of the process to avoid bias and ensure a fair and equitable hiring process. The scheduling of interviews can be substantially improved by AI-powered chatbots and automated scheduling systems, which also help candidates progress through the hiring process more swiftly and smoothly. Chatbots can interact with candidates through text or voice-based interfaces to answer questions, provide information about the job or the company, and schedule interviews. They can also be programmed to ask screening questions to identify the best candidates for the job and to follow up with candidates after the interview to gather feedback or schedule additional interviews.
In that case, the automated scheduling tools help to analyze the overall availability of candidates along with interviewers and also provide an accurate timeslot in order to perform multiple tasks as per the user requirements. This can lessen and reduce scheduling issues and the amount of time and effort needed to organize interviews. Reminders and confirmations can be sent to candidates through email or text message as well, which will lessen the likelihood that they will forget or be late for their interviews. AI-powered chatbots and scheduling systems can help both candidates and hiring managers by streamlining the scheduling process for interviews. This frees up recruiters and hiring managers to concentrate on higher-value duties like candidate vetting and candidate selection (Johnson et al. 2020). In general, automated scheduling systems and chatbots powered by AI can assist simplify and streamline the interview scheduling process, making the hiring process more effective and advantageous for both candidates and recruiters. Yet, it can be useful to examine the overall resumes combined with the specific job description to find the pertinent terms and phrases. Also, it makes it easier to swiftly weed out resumes that are unsuitable for the job and makes sure that the best prospects are selected for further evaluation. AI may examine job titles and past employment to find relevant experience needed for a position. This can include identifying the types of companies and industries the candidate has worked in, as well as specific roles and responsibilities that match the requirements of the job.
In addition to that, a candidate’s education and credentials can also be evaluated by AI to see if they satisfy the basic requirements for the position. The degree of education gained, the applicability of the degree or certification to the position, and the accreditation of the educational institution can all be evaluated in this process. AI can also be used to identify discrepancies or errors in resumes and applications, such as inconsistent work history or inaccurate job titles. This can save recruiters time and help to ensure that top candidates are not overlooked due to errors or discrepancies (Van den Broek et al. 2021). Overall, AI-powered resume screening can help recruiters and hiring managers quickly and efficiently identify top candidates for a job, while also ensuring that the screening process is consistent and unbiased. However, it is important to use AI ethically and transparently and to ensure that human decision-making is still involved at key stages of the process to avoid bias and ensure a fair and equitable hiring process.
4.2.3 Theme 3: Identification of key benefits along with challenges of AI in the hiring process
Several key benefits along with challenges are present in the evaluation of AI technology that needs to be focused on during the hiring process. The benefits along with the challenges are discussed in the below session,
Automating time-consuming procedures like resume screening and interview scheduling can be done with the use of AI-powered recruiting solutions. By utilizing AI, recruiters can save time and concentrate on tasks that have a higher economic return, including developing relationships with applicants or improving the candidate experience. Automated procedures can aid in minimizing errors and enhancing consistency. On the other hand, By automating parts of the hiring process, such as scheduling interviews, AI-powered recruiting tools can offer faster response times and better communication with candidates (Nawaz & Gomes, 2019). This can lead to a more positive overall experience for candidates and help to build a positive employer brand. The top candidates for a position can be found using AI’s analysis of resumes and other candidate data. A candidate’s probable performance in a role can also be predicted by AI using predictive analytics based on the candidate’s prior experience and skills. Artificial intelligence (AI)-based recruiting technology can aid businesses in making better hiring decisions by minimizing bias and locating the best candidates. Automating key hiring processes phases, such as those involved with advertising, candidate sourcing, and hiring manager time, can help businesses cut expenditures on hiring. Businesses can utilize AI-powered recruiting tools to improve employee retention in addition to saving money on administrative tasks like data input and resume screening.
AI systems have the potential to reinforce prejudice and discrimination. For instance, an AI system may be trained with old data that reflects hiring prejudices, resulting in biased recommendations. This can be particularly troublesome if the AI system is used to select candidates for interviews or hiring, as biased recommendations might support inequality and restrict diversity in the workplace. AI algorithms can be complicated, making it challenging to comprehend how judgments are reached. Due to this lack of openness, bias or inaccuracies may be more difficult to identify and address. For instance, it might not be obvious why one candidate was chosen over others if an AI system suggests a candidate for an interview, making it challenging to judge the recommendation’s fairness (Hmoud & Laszlo, 2019). AI systems might not be able to comprehend intricate situations, such as cultural differences or unique experiences, which can result in bad conclusions. For instance, an AI system might be unable to understand that a candidate’s expertise from non-traditional employment might be relevant to the present position, resulting in a recommendation that omits otherwise suitable people.
4.2.4 Theme 4: Enhancement of AI for reducing human errors
Several ways are present in order to reduce human errors where AI works in an impressive way that helps in hiring and recruitment process. To detect faults more accurately and make wiser decisions, AI algorithms can be upgraded. To increase accuracy, this may entail utilizing more sophisticated machine learning techniques or adding more data sources. AI can also be used for predictive maintenance in industries such as manufacturing or transportation, where it can identify potential equipment failures before they occur. This can help companies avoid costly downtime and repairs. AI can also aid in minimizing errors brought on by human prejudice or exhaustion. Artificial intelligence can assist in removing errors that may be brought on by human emotions or prejudices by employing algorithms that are built to make decisions based on data and logic (Mujtaba & Mahapatra, 2019). In that case, it provides real-time feedback for users and also helps users in order to enhance errors and it helps to mitigate multiple errors. On the other hand, it has been programmed in order to autocorrect certain errors without any human intervention. The accuracy and mistake rate of AI systems can be improved over time by designing them to continuously learn and adapt. This may entail using fresh data sources or customer feedback to improve their algorithms. On the other hand, it provides an attractive user interface design that is also necessary for creating the recruitment process easier than the other technology.
By identifying and fixing faults automatically, automatic error correction is a characteristic of AI systems that can help to decrease human errors. In circumstances where mistakes can have serious repercussions, like in data processing or medical diagnosis, this can be especially helpful. Algorithms created to spot patterns and flaws are used by AI systems. When a mistake is found, the system has two options: either it will automatically fix the problem or it will flag it for a human operator to look over. Automatic error correction can be used to swiftly and effectively fix problems in massive data sets when processing data. An AI system may, for instance, be used to find and fix mistakes in a database of client data, such as misspelled names or wrong addresses.
In conclusion, using AI in numerous processes can greatly reduce human mistakes. One method for using AI to eliminate errors without human interaction is automatic error correction. Errors can be found and fixed quickly and effectively, improving overall accuracy and efficiency, by programming AI systems to do so in real-time. But it’s vital to remember that artificial intelligence (AI) systems may still need human monitoring to assure accuracy and avert unintended consequences (Houser, 2019). Overall, AI can contribute significantly to lowering human error rates and increasing process efficiency by combining automatic error correction and other improvements. In that case, the ability of automatic error correction to save time and lighten the workload of human operators is one of its key benefits. It is simple to make mistakes or ignore errors while working with enormous amounts of data, which might have detrimental effects. AI can help ensure that data is accurate and consistent by automating the error-correction process, lowering the likelihood of errors, and enhancing the data’s quality. In addition to that, automatic error correction can increase data processing efficiency in addition to eliminating errors. The requirement for human operators to spend time manually checking and correcting the data is eliminated when errors are recognized and repaired automatically (Peres et al. 2020). This may shorten processing times and lower overall data management expenses.
It is vital to note that even while automatic error correction can be a useful tool, it is crucial to make sure the AI system is properly created and trained in order to prevent the introduction of fresh faults or biases. In other circumstances, human involvement might still be required to guarantee the data’s accuracy and guard against potential mistakes. Consequently, before implementing automatic error correction in a specific setting, it is crucial to carefully evaluate the use cases and technology constraints.
The recruitment and selection process has been considerably changed by technology, which has made it quicker, more effective, and more efficient. In today’s environment, where organizations are seeking ways to streamline their operations, cut expenses, and improve the quality of their personnel, the use of technology in recruiting and selection has become essential. With the use of technology, conventional methods of recruitment and selection have given way to more contemporary ones. The number of candidates that a corporation could reach using the conventional approach of recruiting and selection was constrained. Technology has made it feasible to find applicants faster and from a larger pool of candidates. Businesses have been able to automate a variety of processes, including applicant sourcing, screening, assessment, and onboarding, thanks to the use of technology in recruiting and selection (Fabian et al. 2023).
The hiring process can be streamlined to save time and money while increasing the quality of employees thanks to technology like applicant tracking systems, job boards, video interviews, and AI-based solutions. It’s crucial to remember that technology shouldn’t take the place of the human touch in hiring and choosing employees. The process should still involve human recruiters because they can provide a personal touch, build rapport with prospects, and evaluate soft talents that are inaccessible to technology. The recruitment and selection process has undergone a transformation thanks to technology, which has made it quicker, more effective, and more efficient. To choose the best people for their organization, organizations must create a balance between technology and the human touch (Hafidz et al. 2023).
This chapter will be covered some future recommendations after doing the analysis to help future research works and how the arisen research questions have met the outcomes significantly. However, the aim of this research remarkably gained and the objectives have helped to obtain the research questions almost accurately and successfully.
Any firm must have effective recruitment and selection procedures, and technology has greatly enhanced these procedures. Nonetheless, there are certain tips that businesses can take into account in order to further improve the recruitment and selection process. Several recommendations can be demonstrated like below:
This objective is fully met in this specific research. “Artificial Intelligence” or AI can facilitate the following recruitment and also hiring procedures by automation of particular tasks like resume screening and also candidate matching. It can save overall time and also specific resources while enhancing the overall accuracy of the selection of the particular candidate. The respective tools that are AI-powered can also offer several sorts of insights into the respective candidate behavior along with the specific preferences, assisting organizations in making the following data-driven decisions during the hiring procedure.
This particular objective is also fully met. The effective realization of the respective advantages and also the respective challenges of the AI for the choosing of the specific candidates are represented here. The advantages of AI for the selection of the candidate involve enhanced accuracy, efficiency, and also cost-effectiveness. The respective AI-powered tools can also assist in reducing bias and enhancing diversity in the following hiring procedure. This is crucial for striking a balance between utilising AI for augmenting human decision-making and also making sure fairness and also transparency in the procedure of selection.
This objective is also met completely. The effective explanation of the particular development along with the recruitment procedure of the AI that assists in decreasing human error is represented effectively. The advancement of AI for specific recruitment includes collecting data and also utilising specific algorithms of machine learning for training models that can automate tasks along with decreasing overall human error. However, this is crucial for making sure that the particular AI models are implemented and also trained utilising unbiased data and also that they are regularly modified for adapting to changing the overall requirements.
The respective objective is fully met. The effective thematic analysis for the visualisation of an effective conclusion rate is also represented.
For visualizing an effective conclusion rate, this is crucial for carefully analyzing the specific data, recognising the themes, and also utilisation of effective visualization tools like graphs for representing the overall findings. The particular analysis is conducted systematically, utilising an effective and also transparent methodology for making sure the overall reliability and also overall accuracy of the particular outcomes.
The utilisation of technology in recruitment and also the selection has conducted important advancements, but there is scope for additional development in this particular area. Future research can concentrate on the inclusion of dissimilar technologies for generating a more effective and comprehensive recruitment procedure. The combination of the respective AI-based tools with the following virtual interviews and also data analytics can offer a more precise and also thorough assessment of potential along with the abilities of the specific candidates (Mak and Pichika, 2019).
Future research may also focus on creating more sophisticated AI models that can recognise not only technical talents but also soft skills like leadership, teamwork, and communication. This might result in more successful and diverse team structures that foster creativity and success.
Future studies should also examine the potential dangers and moral dilemmas related to the use of technology in hiring and choosing candidates. For instance, the use of impartial data and ethical principles should be used to carefully assess and eliminate bias in algorithms and the potential for discriminatory effects.
Human interaction plays an important part in the hiring process and shouldn’t be undervalued. Despite the fact that technology can automate and speed up some operations, it is still crucial to keep a human touch and offer a favourable applicant experience. Future studies might look into how to balance the advantages of technology with the value of interpersonal communication and empathy during the hiring process.
In addition to that, it is important to look into the role of social media in hiring along with selecting candidates. Social media networks offer particular data about specific candidates, but it is crucial to utilise this data ethically and make sure that data protection and privacy rules are upheld ( Eccles and Qualter, 2021).
Overall, instantaneous evaluation and also advancement of the following selection and also recruitment procedures can be highlighted. The utilisation of the following data analytics as well as the specific feedback from candidates and also particular employees can offer valuable insights into the significance of the following recruitment procedure and also assist in recognising the particular areas for advancement.
More chances for organisations to enhance their hiring and selection procedures will probably arise as technology develops. In order to retain their competitiveness in the labour market and recruit top talent, it is critical for organisations to keep up with the most recent developments and trends (Carbonell et al. 2020).
In conclusion, there is still much space for improvement even though the use of technology in recruiting and selection has already produced major benefits. Future studies ought to concentrate on combining various technologies, creating more sophisticated AI models, resolving ethical issues, preserving human connection, using social media in an ethical manner, and continuously assessing and refining the hiring procedure. Organizations may do this to attract top personnel, enhance their employer brand, and promote success and creativity.
The recruitment and selection process has been considerably improved by the use of technology. By putting the aforementioned suggestions into practice, organizations can further improve the recruitment and selection process. Organizations can attract top talent, lower turnover rates, and improve their employer brand by utilizing data analytics, implementing a diverse and inclusive recruitment strategy, conducting video interviews, using AI-based tools for candidate screening, offering a positive candidate experience, utilizing social media for recruitment, and continuously evaluating and improving the recruitment and selection process (Tsymbaliuk et al. 2023). The chapter has discovered the importance of technology in the recruitment process.
The usage of chatbots is one way that technology can be further incorporated into the recruitment and selection process. Chatbots can be used to respond to candidate questions, present details about the company, and even carry out preliminary candidate screening. Recruiters may be able to focus on more high-level duties as a result of the time they will save.
The usage of gamification in the hiring process is another area that is expanding. Gamification can be used to develop fun and interactive tests that gauge a candidate’s aptitude and character. This can not only increase the candidate’s enjoyment and engagement in the process but also give a more accurate evaluation of their skills. Moreover, the inclusion of the respective blockchain technology can improve the transparency along with the security of the recruitment procedure. It can assist prevent the fraud as well as enhance the overall integrity of the following procedure.
It has been noticed that technology is rapidly growing in terms of the selection process in organizations and the growth is quite significant over time. However, still, some fields can be improved to get effective outcomes of future works on this topic. The use of AI can play a significant role in terms of the improvement of technology securely and data analysis is playing an important role to find more efficient employees for recruitment. The rapid growth of virtual interviews is making the whole recruitment process easier and time-saving. The previous studies have introduced several technologies which are helping in this recruitment process. Several factors have been discovered that are included in virtual selection processes. Moreover, the proper AI models should be developed to get an accurate result on the abilities of the employees.
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Question1: What is your age?
25-35 69 (63.9%)
35-45 14 (13%)
45-55 9 (8.3%)
Others 16 (14.8%)
Question 2: What is your Gender?
Male 62 (57.4%)
Female 46 (42.6%)
Question 3: Which is the best recruitment process according to you?
Traditional recruitment 24 (22.2%) process
Online recruitment process 42 (38.9%)
Both 42 (38.9%)
Question 4: Do you agree on how AI is utilised to streamline the recruiting and recruitment processes?
Strongly Agree 28 (25.9%)
Agree 60 (55.6%)
Strongly disagree 9 (8.3%)
Disagree 11 (10.2%)
Question 5:AI is developed and used to assist the hiring process to minimize human error.
Strongly Agree 32 (29.6%)
Agree 56 (51.9%)
Strongly disagree 7 (6.5%)
Disagree 13 (12%)
Question 6: Do you agree that the artificial intelligence technology used for recruiting and selecting candidates complies with privacy and data protection laws?
Strongly Agree 34 (31.5%)
Agree 52 (48.1%)
Strongly disagree 9 (8.3%)
Disagree 13 (12%)
Question 7: Do you agree that AI technology can help reduce bias in the hiring process?
Strongly Agree 38 (35.2%)
Agree 47 (43.5%)
Strongly disagree 14 (13%)
Disagree 9 (8.3%)
Question 8: Should there be a mix/balance between using AI technology and human interaction during recruitment?
Strongly Agree 26 (24.1%)
Agree 54 (50%)
Strongly disagree 14 (13%)
Disagree 14 (13%)
Question 9: Adopting AI technology has improved the effectiveness of hiring and selecting procedures.
Strongly Agree 24 (22.2%)
Agree 59 (54.6%)
Strongly disagree 10 (9.3%)
Disagree 15 (13.9%)
Question 10: The staff should be effectively trained to use AI technology for recruiting and recruitment process.
Strongly Agree 33 (30.6%)
Agree 50 (46.3%)
Strongly disagree 9 (8.3%)
Disagree 16 (14.8%)
Question 11:AI technology should be applied to the employment and recruitment process to draw a varied pool of candidates.
Strongly Agree 19 (17.6%)
Agree 62 (57.4%)
Strongly disagree 11 (10.2%)
Disagree 16 (14.8%)
Question 12: E-recruitment is mandatory to survive in the competitive market.
Strongly Agree 28 (26.2%)
Agree 53 (49.5%)
Strongly disagree 9 (8.4%)
Disagree 17 (15.9%)
Question 13: The E-recruitment process allows software like Applicant Tracking System (ATS) to measure the recruitment and selection process with minimal errors.
Strongly Agree 31 (28.7%)
Agree 56 (51.9%)
Strongly disagree 3 (2.8%)
Disagree 18 (16.7%)
Question 14: To apply inclusion and diversity in the company, e-recruitment is crucial as it opens to a wider audience.
Strongly Agree 28 (25.9%)
Agree 66 (61.1%)
Strongly disagree 3 (2.8%)
Disagree 11 (10.2%)
0_THE_ROLE_OF_TECHNOLOGY_IN_RECRUITMENT_AND_SELECTION
Sureji Mohamed (M030LON) Page 1 21 Mar 2023
Meeting Diary
Evan John