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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.

Due to government policies, accreditation demands, competition, digital India reforms and National Education Policy (NEP) 2020, the need for electronic human resource management (e-HRM) has increased considerably in the Indian higher education (HE) sector, but the literature has revealed that the adoption of e-HRM practices in Indian HE institutions (HEIs) is still in its embryonic stage; therefore, the purpose of the current qualitative study is to explore the challenges and facilitators of e-HRM adoption in the Indian HE sector through interpretative phenomenological analysis (IPA).

The present study incorporates IPA, to capture the personal lived experiences of the HR executives employed in the Indian HEIs. Using purposive sampling, semi-structured interviews were conducted with the HR executives employed in Indian universities and institutions to know the perspectives on the adoption of e-HRM practices in Indian HEIs.

The study identified two superordinate themes, namely, challenges and facilitators of e-HRM adoption in the Indian HE sector. The superordinate theme “challenges” comprises eight sub-themes. Further, the theme “facilitators” consists of six subthemes.

The study has implications for the stakeholders of the HE sector, i.e. HR practitioners, top executives of the HE sector, government and HE regulators and other stakeholders of the HE sector.

This study has given deep insights into the challenges and facilitators in the adoption of e-HRM practices in the Indian HE sector, and to the best of the authors’ knowledge, no study till date has filled this knowledge gap through qualitative exploration using IPA.

Smart HR 4.0 is a new concept characterized by adopting innovative technologies of Industry 4.0 (I4.0) in the HR domain. This study attempts to identify the key factors of Smart HR 4.0 to foster organizational innovation ambidexterity.

Based on review of literature and survey from expert opinions by using the Delphi method, 12 factors were found most suitable for this study. Further, the fuzzy-TISM technique was used to establish contextual relationships and develop a hierarchical model on the identified factors. Subsequently, the MICMAC analysis was applied to classify these factors according to their driving and dependence power.

This study framed a conceptual hierarchical model of Smart HR 4.0 and established contextual relationships among identified factors. Result shows that smart organic structure, industry–institute interface, IT-enabled system and ambidextrous leadership are important factors as they have the highest driving power. Further, knowledge management, learning culture and psychological empowerment are the linkage factors having both driving as well as dependency power in the whole system.

This study can guide the managers in smoothly implementing these practices to manage their human capital amidst digital disruption, ensuring innovation competitiveness of the firm. The structural hierarchical framework of Smart HR 4.0 may serve as a blueprint for HR professionals and business leaders to attain organizational innovation ambidexterity in the current wave of digital disruptions (Industry 4.0).

This study provides a holistic model of smart HR 4.0 integrating innovation ambidexterity in I4.0.

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.

This study was designed to contribute to the extant literature by discovering the perceptions of restaurant employees and managers toward equal opportunities in restaurant labor and working in a diversity-rich restaurant work environment.

A qualitative research approach was utilized. Through in-depth interviews, data were collected purposefully from restaurant workers in different positions (e.g. managers, servers, chefs and cooks) in the USA.

As a result of content analysis, different perspectives emerged on equal employment opportunity and diversity in restaurant labor. While some employees and managers believe that restaurant labor has equal employment opportunities, others think there is a lack of equal employment opportunity and partial equal employment opportunity in the industry. Most participants perceive working in a diversity-rich restaurant work environment as beneficial (an opportunity to learn about different cultures and an opportunity to learn different experiences and approaches).

To the best of our knowledge, this is the first paper to explore employees' and managers' perceptions of equal employment opportunity and diversity in the hospitality labor context, specifically restaurant labor. Therefore, the research findings will create value for scholars to understand the view on equal employment opportunity and diversity in restaurant labor. Further, it will assist practitioners in designing their labor structure regarding equal employment opportunity and diversity management for the future.

This study aims to provide an extensive review of the employer brand literature by capturing research trends and proposing a research agenda.

A bibliometric analysis was conducted to study 232 peer-reviewed articles indexed on Scopus from 2004 to 2021. Content analysis is added where appropriate to further explore empirical studies and influential papers.

Based on bibliometric analysis, this study provides data about the volume, growth trajectory, geographic distribution, main authors, three main themes and future research avenues for each of these themes. Content analysis sheds light on research subjects, types of data, methods and most influential papers.

This paper is among the first to conduct a bibliometric analysis along with content analysis focusing on employer brand. An extensive research agenda derived from the studied literature is also provided for interested scholars.

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.

The study sought to examine the mediating effect of employee environmental commitment (EEC) in the relationships between green human resource management practices (Green HRMPs) and environmental sustainability (ES) and employee turnover intentions (ETI).

Using a cross-sectional survey approach, data was sourced from 296 respondents from five manufacturing firms listed on the Ghana Stock Exchange. Data was analysed using descriptive and inferential statistics with the help of Statistical Package for Social Sciences (SPSS) and SmartPLS.

Results showed that EEC had a partial mediation effect on the relationship between Green HRMPs and ES at the organisational level but fully mediated the relationship between Green HRMPs and ETI at the individual level.

It is evident from the findings that Green HRMPs improve ES and employee stability. Therefore, practitioners and educational institutions should consider integrating environmental concerns into their functional processes and operations. In addition, governments as policymakers should formulate and strengthen the enforcement of already-existing environmental management and sustainability policies that promote the integration of green practices and initiatives in both private and public entities.

Little is known about Green HRM and its effect on organisational and individual-level outcomes, especially in Sub-Saharan Africa. This study presents empirical evidence from an emerging economy.

Considering the significance of the human resource management (HRM) and corporate social responsibility (CSR) relationship, the aim of this research is twofold: first is to measure the cultural differences between HRM, CSR and sustainable performance relationship (study 1) and second is to identify the how HRM instigates CSR and sustainable performance (study 2) in the hospitality industry of UK and Pakistan.

A mixed-method approach was used to collect the qualitative and quantitative data from upscale hotels. In Study 1, a multi-respondent and time-lagged strategy was employed to collect the data from 162 Pakistani and 290 UK upscale hotels. In Study 2, in-depth semi-structured interviews were conducted to understand the HRM–CSR–performance nexus.

The results of Study 1 highlight the significant cultural differences in the relationships of HRM–CSR–performance, while Study 2 explains that ethical culture, shared objectives, transparency, training and development, and economic incentives are the factors that push the employees to take part in CSR-related activities and attaining higher sustainable performance.

This study addresses the debate on the difference between cross-cultural studies related to implementing Western theories in shaping, developing and implementing business strategies, including CSR, HRM and sustainable performance in an Asian context.

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.