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Various scholars suggest that there is a lack of research on the recruitment in small and medium-sized enterprises (SMEs) and also a scarcity of theoretical basis for the recruitment procedures used by these companies. As the vast majority of studies concentrate on larger organizations, they may not accurately reflect the challenges faced by smaller-sized entities to profoundly and accurately comprehend their recruitment procedures. In addition, the use of technology in recruitment has grown in importance in today’s quickly evolving business environment, particularly in light of the COVID-19 pandemic footprint. This study aims to examine the recruitment procedures used by SMEs and how they have been compelled to adjust to different extents to these technological improvements by the effects of the aforementioned epidemic.

With the aim to investigate the current recruitment practices in SMEs and the extent to which digital technologies are embraced by these companies within human resources (HR) procedures, this research relied on interviews with SMEs representatives. The qualitative methods used provided access to relevant data and insights, as they allowed close interactions with top managers and CEOs of ten companies from various sectors. Thus, the research results draw a vivid and reliable image of the procedures and practices used by small and medium-sized companies to attract, select and retain their staff.

This study’s findings are of increased interest to HR professionals, recruiters and managers in SMEs, who aim to attract and retain the best talent and optimize their recruitment strategies in a rapidly changing business environment, enabled by technological advancements. Effective HR recruitment procedures adapted to the specific needs of small and medium-sized companies can lead to several benefits for the organization, including improved employee selection, reduced turnover and increased organizational productivity.

Although the interviews examined here encompass recruitment techniques from SMEs in a variety of industries, the results’ generalizability is limited by the sample size and geography. Furthermore, the findings’ dependability is dependent on the accuracy of the data provided by the respondents.

This investigation confirms some of the theoretical underpinnings which point to the lack of formalized structures and procedures in the recruitment process in SMEs, which enjoy more flexibility in managing HR processes. In addition, the results reinforce the arguments indicating an adjustment between HR strategies or policies and organizational goals in smaller enterprises which adapt faster to changes in the market. Moreover, it becomes apparent that there is a relationship between the quality of job descriptions and the successful fit in attracting the right candidates for the open positions. Furthermore, digital technologies offer opportunities for expanding the recruiters’ reach to a wider audience and also support the selection stage, thus increasing the chances of finding suitable staff. As the need to shift from traditional recruitment to e-recruitment in SMEs has been highlighted in the literature, the qualitative research revealed that this need was driven on the one hand by the COVID-19 pandemic when these companies successfully adapted and implemented new online methods of recruiting, but also by the lack of skilled labor, leading to the expansion of recruitment to other parts of the country or even to other countries.

With regard to the proportion of men and women used in small and medium-sized companies, there is a clear need to involve and train more women in the predominantly male-dominated industrial and IT sectors. From this point of view, companies tend to devote more interest to integrating communities of women in these industries, as well as in key management positions. Another point of interest that the study highlights is the fact that SMEs have started to get creative with the benefits package they propose to candidates and focus on remote work, hybrid office–home working, or seasonal work to offer future employees a better work–life balance.

The added value of this investigation is filling the gaps in the current literature concerning recruitment procedures currently used by SMEs, the challenges they face and the solutions they advanced to solve them. Furthermore, SMEs often drive innovation and competition in the market and play a crucial role in the supply chain of larger companies, providing them with the goods and services they need to operate and supporting the availability and reliability of products from larger companies. They are often the driving force behind revitalizing local economies and creating new employment opportunities. Consequently, the underlying significance of this study is rooted in the need to modernize and simultaneously improve HR recruitment procedures through the integration of technology and a focus on innovation.

Staffing is one of the most influential human resource (HR) activities and is the primary method of hiring and retaining human resources. Among staffing’s several activities, recruitment and selection are one of the most crucial activities. It is possible to rehire former firm employees using the talent management strategy known as “boomerang recruitment”. The boomerang recruitment trend has tremendously grown because many employees who believe they are qualified for the position now wish to return to their old employers. According to data, boomerang employees can be 50% less expensive than conventional ways of hiring. The purpose of this study is to identify the generic critical factors that play a role in the boomerang hiring process based on the literature review. Next, the objective is to determine the relative weight of each of these factors, rank the candidates, and develop a decision-making model for boomerang recruitment.

This paper focuses on the grey-based multicriteria decision-making (MCDM) methodology for recruiting some of the best candidates out of a few who worked for the organization earlier. The grey theory yields adequate findings despite sparse data or significant factor variability. Like MCDM, the grey methods also incorporate experts' opinions for evaluation. Furthermore, sensitivity analysis is also done to show the robustness of the suggested methodology.

Seven (7) recruitment criteria for boomerang employees were identified and validated based on the opinions of industry experts. Using these recruitment criteria, three candidates emerged as the top three and created a pool out of six. In addition, this study finds that Criteria 1 (C1), the employee's past performance, is the most significant predictor among all other criteria in boomerang hiring.

Since the weights and ratings of attributes and alternatives in MCDM methods are primarily based on expert opinion, a significant difference in expert opinions (caused by differences in their knowledge and qualifications) may impact the values of the grey possibility degree. However, enough attention was taken while selecting the experts for this study regarding their expertise and subject experience.

The proposed method provides the groundwork for HR management. Managers confronted with recruiting employees who want to rejoin may use this model. According to experts, each attribute is not only generic but also crucial. In addition, because these factors apply to all sectors, they are industry-neutral.

To the best of the authors’ knowledge, this is the first study to apply a grey-based MCDM methodology to the boomerang recruitment model. This study also uses an example to explain the computational intricacies associated with such methods. The proposed system may be reproduced for boomerang recruiting in any sector because the framework is universal and replicable. Furthermore, the framework is expandable to include new criteria for different work.

Our proposed machine learning model contributes to improving the quality of Hire by providing a more nuanced and comprehensive analysis of candidate attributes. Instead of focusing solely on obvious factors, such as qualifications and experience, our model also considers various dimensions of fit, including person-job fit and person-organization fit. By integrating these dimensions of fit into the model, we can better predict a candidate’s potential contribution to the organization, hence enhancing the Quality of Hire.

Within the scope of the investigation, the competencies of the personnel working in the IT department of one in the largest state banks of the country were used. The entire data collection includes information on 1,850 individual employees as well as 13 different characteristics. For analysis, Python’s “keras” and “seaborn” modules were used. The Gower coefficient was used to determine the distance between different records.

The K-NN method resulted in the formation of five clusters, represented as a scatter plot. The axis illustrates the cohesion that exists between things (employees) that are similar to one another and the separateness that exists between things that have their own individual identities. This shows that the clustering process is effective in improving both the degree of similarity within each cluster and the degree of dissimilarity between clusters.

Employee competencies were evaluated within the scope of the investigation. Additionally, other criteria requested from the employee were not included in the application.

This study will be beneficial for academics, professionals, and researchers in their attempts to overcome the ongoing obstacles and challenges related to the securing the proper talent for an organization. In addition to creating a mechanism to use big data in the form of structured and unstructured data from multiple sources and deriving insights using ML algorithms, it contributes to the debates on the quality of hire in an entire organization. This is done in addition to developing a mechanism for using big data in the form of structured and unstructured data from multiple sources.

The purpose of this study is to explore the association between select human resource management practices and employee performance in academic libraries in India.

The current study uses the quantitative method of research. Partial least squares-structural equation modelling (PLS-SEM) was used to analyse the results. The current study uses a cross-sectional approach by using a convenient sampling method. The sample size of the study was 163, which was adequate for conducting PLS-SEM analysis.

The study found a significant positive correlation between human resource management practices and employee performance in academic libraries. This suggests that the implementation of effective human resource management practices has a beneficial impact on various aspects of employee performance.

The study’s cross-sectional design may limit the ability to establish causality or determine the direction of the relationship between human resource management practices and employee performance. The study may have limitations regarding the sample size and its representativeness. If the sample is small or limited to specific academic libraries in India, it may not be possible to generalise the findings to a broader population of academic libraries in the country or to libraries in other regions or countries.

The study has practical implications for academic libraries in India. By recognising the significant correlation between human resource management practices and employee performance, libraries can prioritise the implementation of effective human resource management strategies. This includes aligning human resources practices with organisational goals, focusing on employee development and engagement and adopting best practices in recruitment, training and performance management.

This study can have broader social implications by promoting a supportive and productive work culture that positively impacts the academic library community.

The paper focuses on a quite important and largely unexplored area of human resource management within the academic libraries sector.

From managerial perspective, the authors investigate the boundary and effective conditions of recruitment practices (e.g. job advertising and manager recruiting behavior) on recruitment outcomes that include employer image and organizational commitment in the context of recruitment practices. Drawing on signaling theory, the authors argue that using recruitment practices is generally more effective for creating employer image and organizational commitment.

The authors received a final sample of 213 from the employees of beverage industry. In doing so, statistical softwares SPSS (v.23) for data screening and SmartPLS (v.3.3.3) were used for hypothesis testing.

Using survey-based study, the study finds (1) that recruitment practices including job advertising and managers' recruiting behavior can be superior to developing employer image that positively can value the organizational commitment (2) The study identifies a significant role of employer image that is mediating between recruitment practices and post recruitment outcome (e.g. organization commitment).

The outcomes of the study provide valuable directions for human resource (HR) managers in national and multinational public organizations. The article offers recruitment strategies/practices to enhance employer image and organizational commitment.

The novelty of the study is the unique research framework, as the current paper is among the pioneers to empirically analyze the effect of recruitment practices on post-recruitment outcome testing the mediating relationship of employer image between job advertising organizational commitment and between managing recruiting behavior and organizational commitment.

This article provides an overview of lessons we can learn from human resource (HR) policies and practices related to neurodiversity.

We conducted a practice-based review using information obtained from organizations’ websites, summarized the information and reflected on how scholars can continue to advance this area of research based on what is happening in practice.

The review provided a selective overview of programs and practices per HR cluster: selection and recruitment; onboarding, integration and retention; job design; flexible work options and working remotely; training; employee resource groups (ESGs) and support. The review provides a description of practices and policies implemented within organizations that focus on neurodiversity among employees.

Our review showed that organizations have a multitude of HR practices and policies in place to include neurodivergent individuals in their workforces, though many of these have not been empirically investigated. Sharing this knowledge is important so that research insights and practice can reciprocally influence one another.

The purpose of this study is to explore the perspectives of Generation Z college students regarding the job selection process, as well as the impact of digital technology on their career choices and job search endeavors.

Using the grounded theory methodology, the study used in-depth interviews with 15 participants to investigate the research inquiries.

The study identified six emerging themes related to the career aspirations of Generation Z students. The authors generated a job selection process model of Generation Z based on participants’ accounts of their recent job search experience. The model portrays the decision-making process performed by Generation Z job seekers while determining their career path.

To enhance comprehension of the job selection process among Generation Z individuals, future studies should incorporate a broader range of participants encompassing diverse cultural, social and economic backgrounds. Scholars have the potential to examine the relationships between Generation Z job seekers’ job selection, job performance and job satisfaction through a quantitative approach.

The six themes pertaining to optimal jobs for Generation Z can assist HR professionals in enhancing their understanding of the emerging pool of young and talented individuals. The utilization of the four-stage job selection process model may serve as a valuable tool for college career service professionals in the enhancement of tailored training programs.

This empirical study examines Generation Z job seekers’ attitudes toward their future profession, their perceptions of ideal occupations and the influence of technology on their search, preparation and selection processes for future careers.

The purpose of our study was two-fold: (1) to examine the effect of perceived value derived from perceived benefits and sacrifices in the adoption of artificial intelligence (AI) in talent acquisition and (2) to investigate the moderating role of human resource (HR) readiness in the association between perceived value and AI adoption intention.

A structured questionnaire was administered to 198 talent acquisition executives and HR professionals of Indian IT companies based on a purposive sampling technique. Partial least squares structural equation modeling (PLS-SEM) was used on the Smart PLS 2.0 platform to analyse the data and test the model.

Results revealed that perceived benefits and sacrifices significantly predict perceived value which significantly affects the HR professional’s AI adoption intention. The study further found that HR readiness moderates the link between perceived value and the intention of HR professionals to adopt AI in the talent acquisition process in the Indian IT industry.

IT companies are advised to continuously monitor and evaluate the performance of AI tools to ensure that they are meeting the recruitment process needs to leverage AI’s benefits in talent acquisition. This study seeks to provide the impetus for a planned AI adoption in talent acquisition.

This research provides ample evidence for the existing technology adoption theories. It explored the predictors of adoption by validating the value-based adoption model in the Indian context. It provides valuable insights into the practice of acquiring talents in the IT sector using artificial intelligence.

Drawing on the contemporary literature and the theory of employer attractiveness, the authors aimed to examine key antecedents and consequences of employer attractiveness by proposing functional hypotheses and relationships between some endogenous variables.

Using the quota-cum-purposive sampling method, the unit of analysis selected for this study was millennials aged 18–35 years and working in the hospitality, travel, tourism and leisure (HTTL) sectors for the last two years. A total of 218 responses were collected in three months (June–August 2022). The data were analysed using partial least squares structural equation modelling (PLS-SEM).

For young employees, company recruitment behaviour, company image and source credibility are significantly and directly related to company attractiveness. The relationship between company image and employee word of mouth (WOM) was significantly positive. Company recruitment behaviour was found to significantly influence employee commitment. Company attractiveness was found to be directly related to young employees' WOM about the company and commitment to it.

The study establishes the significance of company attractiveness because a company's success largely depends on the company's ability to attract and retain a talented and skilled workforce. Moreover, the present study provides much-needed insights to policymakers and regulators that can help the policymakers define and implement favourable policies to promote and protect the country's job market and offer directions to youth employment.

This paper critically evaluates potential barriers to employment opportunities for ethnic minority (EM) individuals in Scottish Local Authorities – both in terms of access to job and development opportunities. It provides a fundamental discussion of concepts around race and ethnicity, and the levels of social injustice, with an explicit focus on institutional racialisation, discrimination and segregation. The paper explores organisational approaches towards recruitment, including positive action and workforce development.

This paper adopts a subjectivist (ontology) and interpretivist (epistemology) stance, based on a small-scale, in-depth investigation. The data have been gathered through semi-structured interviews with equality diversity and inclusion (EDI) officers in four Scottish Local Authorities, utilising thematic analysis.

The finding suggests that participating local authorities have a long way to go to ensure the elimination of barriers to employment for EM people. This is largely based on concerns around limitations in the application of positive action and elimination of disadvantages in recruitment and access to career and development opportunities?

The paper aims to contribute by exploring the availability of employment opportunities for EMs through the eyes of EDI Officers in four local authorities. Their thorough understanding, over- and insight into potential equality issues from an employment perspective are invaluable, focussing on more tangible organisational issues and approaches.