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Abstract

In an integrated world, knowledge-based economies require high-quality labor, which has always been challenging to cultivate, use, satisfy, and have a long-term competitive advantage. This article aims to identify areas of scientific research into high-quality workers in the labor market and to conduct data analysis. Using the Web of Science database from 1991 to 2023, the research outlined emerging trends in high-quality human resource management in the labor market through bibliometric analysis and text-mining approaches. This research also recommends developing research papers and exploring various aspects of high-quality human resource management in the labor market.

Plain language summary

Purpose: In an increasingly interconnected global context, this article endeavors to investigate the evolving landscape of high-quality labor within knowledge-based economies. We aim to identify areas of scientific research in this domain and employ bibliometric analysis and text-mining techniques to extract insights from the Web of Science database, spanning 1991 to 2023. Methods: Utilizing data encompassing the period from 1994 to February 2023, our research amassed a substantial corpus of 1,560 articles. We examined emerging trends, identifying 14,870 citations, and assessed regional influence, notably the United States. We categorized publications by domains, emphasizing the intersection of education research with economics. Our analysis extended to the delineation of five primary color clusters, each representing a pivotal facet of governance within high-quality human resource management. Conclusions: Our research signifies a robust interest in high-quality human resources, with a peak in publications during 2019. The United States has been a prominent contributor to this body of work. Management, business, and economics emerged as dominant publishing domains, closely associated with educational research. Our analysis reveals pressing challenges and opportunities related to high-quality human resource management, factors influencing governance, the role of knowledge management in digital transformation, strategies for attracting and retaining top-tier employees, and the impact of self-efficacy on their performance. These findings underscore the contemporary relevance of high-quality human resource management in addressing gender equality, labor mobility, brain drain, and attraction. Implications: The study illuminates the necessity of addressing multifaceted challenges within high-quality human resource management. Organizations must navigate issues of gender equality, labor mobility, and talent attraction while adapting to technological advancements and enhancing knowledge management. The research fosters global collaboration, provides insights into current management trends, and extends the scope of research content. Limitations: While our study offers a comprehensive analysis, it is constrained by the availability of data within the Web of Science database and does not encompass the entirety of existing literature. Additionally, our findings are reliant on the quality and completeness of the database’s indexing and citation records.

Keywords

high-quality labor force highly qualified resources human resource management highly-skilled workforce

Introduction

A high-quality labor force is vital to a country’s development (Barkun et al., 2020). A resource-poor nation can still proliferate and develop sustainability if it adopts the right economic paths, competent leadership, management teams of competent intellectuals, and a skilled labor force (Cubas et al., 2016). If countries do not prioritize worker training and skill development, they will lack interest in investing in human resources and compete with nations offering low-cost human resources. The economy will fall into three circular traps: poverty, unskilled unemployment, and underemployment. In addition, as economies become more knowledge-based, there is an increase in demand for high-quality or highly-skilled human resources, as these resources provide a sustainable and potential competitive advantage. Skills (Moroko & Uncles, 2008).

On the other hand, human resources are experiencing a “golden population” structure, yet high-quality human resources always lack quantity, are limited in quality, and are structurally inadequate (Tien etal., 2021). Thus, human resource management faces difficulties in attracting and maintaining highly qualified, active people and a high-quality workforce that must be maintained long-term to secure a sustainable competitive advantage for the company (Schuler & MacMillan, 1984; Wilkinson et al., 2001; Wright & McMahan, 1992; Wright et al., 1994). It demonstrates that, regardless of the country-specific strategy at the macro level or the distinctions between enterprises at the micro level, economic actors often concur that they are identical. There is a need for skilled workers (Barkun et al., 2020).

Previous research has primarily focused on investigating specific categories, such as the theory of high-quality human resources (Body, 2005; Ha, N. T. T., & Van Huan, T., 2022; Wright & McMahan, 1992), measuring the productivity of high-quality employees (Tokarčíková, 2013), effectively operating the high-quality labor market in the innovation economy (Aybek & Fozilov, 2021), achieving a high-quality educational process (Drobyshev et al., 2019), and managing and retaining highly qualified employees (Marx, 1995; Mukmin, 2021). Besides, Prior research has employed diverse methodologies to develop “high-quality human resources” theories. However, a dearth of recent scholarly literature offers a comprehensive summary and statistical analysis of prior works concerning “high-quality human resource management in the labor market.” Furthermore, a diverse range of methodologies were employed. However, bibliometric analysis was scarcely utilized by individuals concerning this subject matter. This research presents a statistical analysis of the primary concerns surrounding the topic of high-quality human resource management in the labor market. The findings are based on a review of 1,560 scientific publications published from 1994 to 2023. This study aims to provide readers with an overview of the current knowledge of high-quality human resource management in the labor market. Simultaneously, this research will suggest avenues for the advancement of scholarly articles and facets of the subject matter of superior human resource management within the workforce.

Literature Review

Nowadays, there are numerous notions of high-quality human resources, particularly in the context of globalization and international integration, when the economy is predominately knowledge-based and human resources, especially high-quality human resources, play an increasingly crucial role (Uoc et al., 2022). Human resources with the potential to become a sustained competitive advantage must be highly qualified and highly motivated (Wright & McMahan, 1992). High-quality human resources have a high level of education and technical experience, as well as excellent labor skills and the capacity to adapt rapidly to rapid changes in production technology. “Capacity to use trained knowledge and abilities creatively to the manufacturing process to achieve high productivity, quality, and efficiency”.

High-quality human resources are considered a subset of human resources; they are the culmination of the most defining characteristics of human resources: they are an employee with a healthy body, education, and technology. High productivity usually results from high expertise, good labor skills, creative capacity, and the ability to apply the trained knowledge and skills (Body, 2005). Modern growth theories also indicate that an economy that aspires to grow swiftly and at a high rate must be supported by at least three fundamental pillars: the acceptance of new technologies, the development of modern infrastructure, and the development of modern infrastructure. The most crucial driver of sustainable economic growth is people, particularly high-quality human resources, that is, individuals who are invested in development, have talents, knowledge, skills, experience, and the capacity to be “capital—human capital, human capital” (Cubas et al., 2016). The research found that the above concepts all refer to high-quality labor resources defined by good skills, high professional qualifications, and the ability to apply knowledge and adapt quickly and creatively. Thereby bringing high performance and sustainable competitive advantage to the organization and contributing to society. Because of the significant influence of quality human resources, many authors have studied this topic in different aspects and methods, including the author’s research. Tokarčíková, (2013) concludes in her study on assessing the productivity of high-quality employees that, if correctly interpreted and implemented, the measures will aid in increasing employment on the labor market and bolstering the benefits of high-quality workers to the firm.

Complementing the theory of employment of high-quality labor resources is a study that explicitly proposes problems and solutions for training human resources with university degrees Aybek and Fozilov (2021). In this paper, the author examines the problems of the efficient functioning of the labor market in the innovation economy. The proportion of skilled workers in the labor market is increasing under the influence of digitization, globalization, and the growing and innovative economy. This study analyzes the scientific and methodological issues related to the establishment, management, and expansion of companies and enterprises specializing in producing new and innovative products and services, demanding educational institutions to train qualified personnel to meet the methods and techniques they put into production. The development and modernization of the education system in line with the business market’s requirements will significantly impact the sustainable development of business entities, contributing to economic growth. In addition, the country’s modern and innovative business environment provides a solid basis for job growth, especially for young people to tackle essential tasks such as getting jobs that match their qualifications.

It is only feasible to achieve a high-quality educational process when a team of teachers collaborates effectively, supports new educational approaches, and employs quality management systems and models. These components are geared toward accomplishing a single objective: training a highly skilled, in-demand professional (Drobyshev et al., 2019). The key to successfully retaining highly qualified employees, according to Marx (1995), is to create an environment that encourages them to stay by motivating them from within. This environment is created when management expresses confidence in employees’ potential and demonstrates that they have opportunities for advancement and career development within the organization. Mukmin’s study demonstrates that organizational culture, a style of leadership that changes and divides work directly or indirectly through dynamic competency and competitive advantage, has a favorable effect on energy management—personnel force. In contrast, employee performance management affects job satisfaction, performance, and commitment to job security, and efforts to cultivate high-quality personnel must include numerous elements.

Research Methodology

Data Collection

The research used the Web of Science database related to high-quality human resources. The Web of Science was chosen because this database is considered one of the most prestigious and largest databases today, with a vast number of scientific journals, conferences, and author information. Web of Science stands out for its extensive coverage of scholarly literature spanning diverse academic disciplines, a crucial attribute given the multidisciplinary nature of research. Furthermore, the database’s rigorous indexing procedures and comprehensive citation analysis have established it as a widely trusted resource for conducting bibliometric and text-mining analyses. In selecting Web of Science, the research was motivated by its well-earned reputation for curating high-quality, peer-reviewed content, a hallmark that assured the data’s reliability and robustness. This meticulous choice resonates with a steadfast commitment to upholding the highest standards of rigor and credibility in arch pursuits, reflecting dedication to making meaningful contributions.

To identify publications related to the topic, a search is performed through the following syntax: TOPIC (“highly qualified” or “highly skilled” or “talented”) AND TOPIC (“workforce” or “employee”) *S"), period time from 1994 to February 2023. After going through the search process, the results obtained 1,560 articles.

Research Methodology

Keyword Co-occurrence Analysis

The bibliometric analysis employs statistical analysis to characterize the distribution pattern of research publications with a particular subject and period (Yang et al., 2012). Co-occurrence keyword analysis identifies relationships between keywords co-occurring in document titles, keyword lists, and abstracts using five primary bibliometric techniques (Zupic & Čater, 2015). A co-occurrence keyword analysis is a method for measuring the co-occurrence of keywords (Callon et al., 1991) that enables the visualization of the publication’s essential content (Leung et al., 2017; Vallaster et al., 2019). The researchers employed this methodology to determine the association between research themes and new research trends.

Using the VOSviewer software created by the Leiden University Research Center for Science and Technology allowed the construction of keyword networks and the analysis of phrases (Van Eck & Waltman, 2010). All keywords are regarded as units of analysis in co-occurrence keyword analysis, backed by a comprehensive counting procedure. This study also limited the analysis, including at least seven (7) instances of a term. Hence, out of 5,524 keywords in 1,560 articles, only 226 match the criterion, and after filtering for duplicate and inappropriate keywords, only 183 are presented. Each term is examined by software that calculates its linkages, total link strength, and co-occurrence with other keywords. According to Guo et al. (2019), the strength of a connection is proportional to the sum of the quoted parameters between a keyword and word other keys. In addition, the number of occurrences of a keyword represents the number of articles in which it appears. The keywords are organized into color groups. The prominence of the circles and text in each cluster shows their co-occurrence with other keywords.

In contrast, the space between the keywords and their related connections indicates their relevance and importance in the conjunction of keywords. Co-occurring keywords are typically clustered closer together (Van Eck & Waltman, 2014). Link strength was the measurement utilized by VOSviewer (Van Eck & Waltman, 2007; Van Eck et al., 2006). To apply the link strength, the significance of S_ij between elements i and j is determined as follows:

S_{ij} = C_{ij} / W_{i} W_{j}

where C_ij denotes the number of co-occurrences of elements i and j; W_i represents the total number of occurrences of element i; W_j represents the total number of occurrences of the element j.

Data Mining

In this study, the research found that the collection and extraction of information from the database for VOSviewer-based review articles were limited in scope. Consequently, text mining was performed to extract keywords from the samples and present an overview. Text mining (also known as text data mining or text database knowledge discovery) is the technique of extracting useful and nontrivial information from text documents (Ertek et al., 2018). Text mining encompasses the disciplines of feature extraction, text classification, clustering, trend analysis, association mining, and visualization, among others. However, only the most pertinent data, that is, the most commonly heard terms, were reported in the research. With RapidMiner version 10.1.001, text clustering is supported. RapidMiner is the most widely used open-source data mining program in the world, and it heavily supports text mining and other data mining techniques used in tandem with text mining (Hofmann et al., 2016).

The following are the stages of implementation that the research carried out for text mining. But first need to check and make sure the necessary extension packages are installed, including Text Processing, Web Mining, and Operator Toolbox.

Stage 1: Prepare

First, find and load data from a source or data warehouse. The research applied the Read Excel operator to load data into the database. Nominal to Text operator is selected to convert all nominal properties to string properties. In the properties section of this operator, the group sets some parameters as follows first, at the attribute filter type select subset, this option allows multiple attributes to be selected through a list. Second, attributes open a new window with two lists which use Abstract and Article Title.

Stage 2: Text Processing

For text processing, another function that the research has adopted, is Process Document from Data Natural Language Processing (NLP) steps are performed as Tokenize, Transform Cases, Filter Stopword, Filter Tokens (by Length), Generate n-Grams

In “Process Document from Data,” the document is converted to a vector model by selecting to generate a TF-idf parameter vector (Term Frequency-Inverse Document Frequency). TF-idf is frequently used to determine the similarity ratio between the query vector and the document vector used for training. This gives the relevant term a higher weight and the unimportant term a lower weight. Its vector value is between 0 and 1. 0 indicates that the term has no relevance to the materials being researched, whereas 1 indicates that the term is significant. TF-idf (Equation 3) is the product of two statistics, term frequency (Equation 1) and inverse document frequency (Equation 2), expressed as follows:

T {F_{(t,}}_{d)} = \frac{f (t, d)}{max {f (w, d) : w \in d}}

(1)

id f_{(t, D)} = \log \frac{N}{| max {f (w, d) : w \in d} |}

(2)

TF - id f_{(t, d, D)} = t f_{(t, d)} x id f_{(t, D)}

(3)

There are numerous methods for determining the precise values of both statistics. The frequency term tf_(t,d) is calculated by dividing the number of occurrences of the term t in document d by the number of occurrences of the most often cited word (w) in the same document (Equation 1). idf is a measurement of a word’s occurrence in all documents. The logarithmic fraction of documents containing a particular word is calculated by dividing the total number of documents by the number of documents containing the term and then taking the logarithm of this proportion (Equation 2). N represents the number of papers in which the phrase t appears. The TF-idf is then computed (Equation 3) (İkiz & Ozaolu, 2015).

The WordList to data operation is then applied, which generates the data set from the word list. Before reporting, operators can be used to filter word lists. The group then does the Sort operation, which sorts the dataset in ascending or descending order.

Results

The Growth of the Number of Publications

The changes in the number of publications published per year from 1991 to January 2023 are shown in Figure 1. There is a gradual increase in the number of publications published in the Web database. of Science, it is understandable that there are more and more scientists interested in this topic. In, the highest number of publications was published in 2019 (N = 159).

Figure 1.

The growth of the number of publications.

From 1991 to 2023, the number of publications increased unevenly. From 1991 to 2006, the number of publications increased but remained below 20 copies. Because, at this stage, the quality of human resources is still relatively new and unattractive. Most of the companies and enterprises at this time, with small and medium-scale operators in the traditional way, do not need high-quality human resources but only focus on human resources with physical and labor factors. Manual movements, professional techniques, and knowledge have yet to be paid attention to.

From 2006 to 2023, the number of publications increased more than from 1991 to 2006, with more than 140 copies per year. High-quality human resources have the knowledge and abilities to execute complicated occupations, adapt quickly to new technologies, and appropriately apply their knowledge and skills in the workplace. On the other hand, this period has been characterized by the transfer of 4.0 technology to meet innovation in science and technology and the development of high-quality human resources for long-term growth. Thus, there has been an increase in the number of publications on high-quality human resources.

Evolution of the Number of Citations

The growth of the number of citations is described in Figure 2. From 1994 to 2023, there were 14,870 citations related to “human resources,”“high-quality human resources,” and “highly qualified human resources.” The increase in citations generally confirms the growing interest in these subjects. However, the number rises throughout various periods. From 1994 to 2004, the number of citations grew by approximately 100. From 2004 to 2023, the number of citations increased from approximately 100 to over 2,400 (an increase of approximately 24 times). It demonstrates that high-quality human resources are of great interest at this point. The research provides ample evidence, arguments, and persuasion through numerous citations.

Figure 2.

The growth in the number of citations.

Most Influential Countries

The data indicates that the United States has the highest number of publications, with 368 publications accounting for 23.59% of the total (refer to Figure 3). Germany ranks second with 115 publications, representing 7,372% of the total. The United Kingdom follows closely with 110 publications, representing 7,051%. A significant discrepancy exists between the foremost nation and the subsequent nation, with a margin of 253 publications, equivalent to 16,218%. Conversely, the variance between the second-ranked and the remaining countries is relatively insignificant. This observation underscores the dominant influence of the United States in the field of study.

Figure 3.

Visual map of the number of publications by country.

This trend can be ascribed to the percentage of the skilled and knowledgeable workforce in the United States. According to the definition of the professional workforce by the U.S. Bureau of Labor Statistics (BLS), individuals employed in management, professional, and associated occupations are included in this category. According to the Bureau of Labor Statistics (BLS), the United States employed over 88 million professionals in 2020, which accounted for 59.8% of the total labor force. Despite the challenge of defining professional and technical labor forces, the data suggests that professionals play an increasingly crucial role in the United States economy. The increase in the number of professionals in recent decades has generated a keen interest in assessing their performance and the unique challenges they face in their respective work environments. Professionals generally possess unique professional identities, extensive education, and training and receive higher-than-average wages despite the wide range of professional occupations available (Barrows, 2021).

Popular Research Fields

According to Figure 4, management is the field most commonly associated with the concept of high-quality human resources in the labor market, with 386 publications. Other fields that have a significant number of publications on this topic include business (209 publications), economics (202 publications), and educational research (199 publications). It demonstrates a keen interest in the practical and research aspects of obtaining top-notch human resources. The fields of management, business, and economics encompass a wide range of topics, and the diversity of human resources necessitates a thorough search and screening process to identify high-quality candidates.

Figure 4.

Popular research areas.

The important domains that have received relatively less attention about the concept of high-quality human resources are applied psychology (43 publications), occupational and environmental health (44 publications), and the corporate finance industry (48 publications). These occupations are highly specialized and require professionally trained individuals who have undergone formal training. The selection process for human resources is stringent, focusing on high-quality candidates. However, there is a need for more qualified workers in these fields.

Analysis of Keyword Co-Occurrence

The results of keyword co-occurrence are illustrated in Figure 5 as the following clusters.

Figure 5.

Results of keyword co-occurrences.

Red Cluster: Challenges and Opportunities in High-Quality Human Resource Management

This cluster comprises a total of 49 keywords, with 12 of them being critical keywords. These keywords include inequality, discrimination, gender, migration, immigration, higher education, mobility, brain drain, information technology, innovation, and competition. Within this cluster, it has been observed that there exist research articles on the prevalence of inequity and bias within organizational settings, with a particular focus on gender-based discrimination. The representation of women on corporate boards in developed nations, such as the United Kingdom, France, and Germany, is relatively low. Additionally, while the percentage of women in leadership positions within the UK public sector is noteworthy, there is still room for improvement. According to the Equality and Human Rights Commission in 2011, the average height in the UK is higher, with a difference of approximately 25%. Research indicates that companies that invest in women and integrate gender-diverse teams tend to experience higher levels of creativity and revenue growth than their competitors. This has been supported by studies conducted by Pearl-Martinez and Stephens (2016), Woolley et al. (2010), and Greg et al. (2011). According to Woolley et al. (2010), enhanced gender parity within groups is linked to more effective and comprehensive results in the process of decision-making.

The findings pertain to migrant workers who relocate to a new location for academic and professional advancement while gaining knowledge about mobility, including ability and availability. The mobility of human resources, particularly in the era of globalization, pertains to the willingness to relocate from one industry or location to another. Subsequently, various studies conducted within the cluster have indicated a phenomenon known as "brain drain," wherein an increasing number of individuals possessing technical expertise or skills relocate to foreign countries for employment opportunities. Individuals may seek employment opportunities abroad for various reasons, such as conflicts, limited prospects, political instability, or health hazards in their home country. The phenomenon of brain drain is commonly viewed as an economic burden, as migrants frequently bring with them a valuable portion of their education and training that has been subsidized by the government of the host country (Iravani, 2011).

Furthermore, the grouping above of colors implies that technology plays a vital role in corporate competition when it substantially impacts the competitive advantage or industry structure, as stated by Porter (1985). Integrating technological innovation in all value activities can significantly affect cost and differentiation from competitors by establishing linkages between activities. Technology can be leveraged for various aspects of resource management, including recruitment communications, candidate management, employee evaluation, feedback, and solution development, to ensure high-quality outcomes. According to Sivathanu and Pillai’s (2020) data analysis, organizational governance issues need to be addressed. An effectively managed human resource of high caliber can serve as a critical competitive advantage for an organization concerning its competitors.

Green Cluster: Factors Affecting the Management of High-Quality Human Resources

This cluster comprises 37 words and centers on the factors that impact high-quality human resource management. It also highlights six primary keywords, namely work-life balance, job satisfaction, employee turnover, transformational leadership, organizational justice, and intention to leave, which are crucial in retaining talented individuals. This cluster comprises scholarly articles exploring the advantages of effective human resource management. The findings suggest that transformational leadership can positively and directly impact management. Mukmin (2021) states that effective personnel capacity management is crucial for organizational success. Additionally, Mey et al. (2021) suggest that managers should align their leadership behavior with a transformational leadership style. There exist multiple perspectives on the characteristics of transformational leadership, including the capacity to anticipate, equip, communicate, and innovate to impact a collective based on a specific context positively. To achieve clear and measurable goals, it is important to have well-defined values and beliefs (Anderson, 1998). It includes envisioning the future, recognizing oneself as a change agent, being willing to take risks, trusting others, making decisions based on a value system rather than self-interest, continuously improving one’s skills and knowledge throughout life, and having the ability to navigate complex, ambiguous, and uncertain situations (Luthans, 2002; Nanus, 1992). Furthermore, it is widely believed that issues of organizational justice are associated with superior human resource management, as per the principle of “reciprocity” from social exchange theory and the notion that individuals place a premium on equitable treatment. According to Cropanzano and Mitchell (2005), individuals who possess exceptional abilities and receive economic and socioemotional advantages from an organization may feel a sense of responsibility, leading them to exert more effort, perform better, and enhance their level of commitment. The current high-quality literature on human resource management identifies two sub-concepts of organizational justice, namely justice in distribution and procedure, as stated by Kwon and Jang (2022). Distributive equity allocates benefits such as promotions, salaries, professional growth opportunities, and job security. It is evaluated based on the balance between the benefits provided and the contributions made by the organization’s estimated workforce, as cited in the works of Gelens et al. (2013) and Slan-Jerusalim and Hausdorf (2007). Procedural justice is the second type of organizational justice, which pertains to the allocation procedure utilized by an organization to ensure the validity of talent management and individual compensation (Kwon & Jang, 2022). Furthermore, within this cluster, some articles focus on strategies for retaining high-quality employees. Talent retention is essential for all organizations, as it plays a crucial role in achieving organizational success and efficiency (Khandelwal & Shekhawat, 2018). Organizations can implement strategies and practices to retain high-quality shift employees by improving their work-life balance. Flexible work arrangements can help maintain employees’ interest in their work without causing undue pressure or stress (Khandelwal & Shekhawat, 2018). In addition, it is noteworthy that job satisfaction is a significant factor in mitigating employee turnover, as per the research conducted by Khandelwal and Shekhawat (2018). Moreover, the crucial elements for maintaining a workforce of exceptional caliber include implementing optimal salary policies, providing opportunities for capacity-building that equip employees with necessary skills, offering training and development programs, fostering motivation through effective management, ensuring satisfaction with organizational decisions, providing retirement benefits, conducting employee evaluations, establishing trust, cultivating positive personal relationships between employees and management, offering rational compensation and benefits, and ultimately, ensuring that the nature of the work is conducive to employee satisfaction (Hanif & Yunfei, 2013).

Blue Cluster: Knowledge Management Combined With Digital Transformation

The blue cluster consists of 35 words, with eight prominent keywords: knowledge management, career development, professional development, globalization, intelligent artificial, digital transformation, managers, and mentoring. In this cluster, one can link employees’ career development and advancement to the organization’s digitalization, knowledge management, and the support and mentoring of grassroots managers. One proposed concept of knowledge management is “related to the exploitation and development of an organization’s knowledge assets to advance the organization’s goals” (Rowley, 2000). To ensure that employees with the most suitable skills are used effectively, several researchers (Collings & Mellahi, 2009; Huselid et al., 2005) concentrated on important talent positions that might influence a firm’s competitive advantage. A sound knowledge management strategy will combine a key position with a key employee, helping them develop their careers and leverage their capabilities and experience through controlling and solving organizational problems, which in turn leads to high organizational commitment (Kristof, 1996). In addition, the primary objective of enterprise knowledge management is to make knowledge accessible and reusable inside the enterprise (O’Leary, 1998). For others to gain and acquire information, it must flow freely and be passed systematically between people (Cheese et al., 2007). Enterprise knowledge management comprises the formal management of knowledge resources to enable knowledge access and reuse, often through modern information technology (O’Leary, 1998). Thanks to artificial intelligence and digitalization, organizations are increasingly finding and developing new ways to receive, store, control, access, and filter knowledge more quickly and efficiently while avoiding biases in decision-making.

In addition, this cluster also shows that direct managers have the most direct contact with employees and, therefore, have the most significant impact and influence on employees’ knowledge acquisition. Managers must demonstrate open-minded behavior, systems thinking, creativity, confidence, and empathy to build an organization based on knowledge sharing. Organizations must ensure that their line managers are accountable for employee acquisition, performance measurement, and development (Cheese et al., 2007).

Yellow Cluster: Attracting and Retaining High-Quality Employees

This cluster has 34 words, in which eight prominent keywords are human resource management, employee retention, employer branding, attractive organizational news, person-organization fit, competitive advantage, corporate social responsibility, and social media. This cluster mainly talks about human resource management in attracting and keeping employees.

These are articles about employee engagement through company branding. Employer branding creates a distinct and distinctive employer identity, a corporate idea that differentiates a company from its competitors (Backhaus & Tikoo, 2004). Employees’ perceptions of an organization’s attractiveness can be altered through internal and external employer branding efforts (Kalinska-Kula & Staniec, 2021). By establishing a strong employer brand, a company can readily attract the attention of prospective employees, particularly first-time job searchers (Srivastava & Bhatnagar, 2010). Social media can be crucial in the recruitment process regarding potential employees’ corporate branding (Sivertzen et al., 2013).

Moreover, external corporate social responsibility actions significantly impact a company’s reputation rating, which appears to be a crucial factor in attracting bright personnel (Story et al., 2016). “The best employees are attracted to corporate social responsibility, and an appreciation of CSR is connected with valued characteristics such as empathy, care for others, and integrity” (Berger & Danninger 2007). Because prospective employees need more information about working circumstances, they use it to fill the void (Turban et al., 2009). It examines the connections between corporate social responsibility and competitive advantage (Verčič & Ćorić, 2018).

Other articles in this cluster also raise the issue of retaining high-quality employees. It is mentioned that employer branding helps high-quality employees build trust in leadership and develop stronger relationships (Eger et al., 2018). Even though the higher the fit between people and the organization, the smaller the employee’s departure from the organization. The organization should provide accurate and timely information to increase the fit between people and the organization. Enough for candidates so that they reduce the surprise when they join the organization (Wei, 2015). In addition, corporate social responsibility initiatives are perceived as being able to make a positive impact on employee satisfaction and retention by meeting the ERG (survival, relationship, and growth) needs of employees (Lee & Chen, 2018).

Purple Cluster: Self-Efficacy Affects the Performance of High-Quality Employees

The purple cluster includes 28 keywords, with seven prominent words: self-efficacy, job performance, motivation, training, leadership, mediating role, and organizational culture. Self-efficacy involves belief in one’s ability to organize and carry out the actions necessary to achieve specific accomplishments (Bandura & Locke, 2003). Research shows that individuals’“self-efficacy” can be an essential indicator of “talent” and “potential” (Rhodes, 2012). Individuals with high self-esteem will devote all their efforts to achieving goals; failure will make them try harder (Lee & Bobko, 1994). Damanik et al. (2020) found that self-efficacy has a considerable impact on motivation (both internally and externally motivated) and a favorable impact on motivation regarding job performance and inventiveness at work (Cherian & Jacob, 2013; Damanik et al., 2020; Ghosh et al., 2021). These individuals will contribute to the organization’s development of high-quality human resources and are more involved. When it comes to training, individuals with high confidence in their talents are more likely to acquire the material, have reasonable expectations about it, and apply what they have learned to their work. Work (Quinones, 1995). (Quinones, 1995). Similarly, competency confidence mediates an organization’s leadership culture and how employees translate what they have learned into work, contributing to overall performance (Simosi, 2012).

Results of Data Mining From Text Mining

Using the n-grams technique, distinct attributes have been assigned to individual words and identifying the most frequently appearing terms. Furthermore, the frequency of these properties across the entire database and within documents was demonstrated in Table 1. The research utilized the frequency of occurrences in the literature as a baseline for interpreting the results of this investigation.

Table 1.

List of 20 Most Appearing Words After Running Text Mining.

Word	Print documents	Total
Highly	1,006	1,312
Employees	933	2,053
Workforce	709	1,080
Study	679	1,288
Skilled	660	998
Research	628	1,263
Talented	621	827
Highly-skilled	587	700
Development	543	1,123
Paper	521	820
Work	504	1,205
Results	495	664
Data	476	664
Based	467	688
Management	466	1,293
Qualified	434	565
Analysis	415	566
Education	414	1,099
Highly qualified	388	442
Findings	379	554

Table 1 presents the outcomes of the 20 most commonly appearing words derived from the title and abstract as the input. The term “highly” is the most frequently occurring word in the titles and abstracts of publications, appearing 1,006 times. It is followed by “employees” and “workforce” with 933 and 709 occurrences, respectively. Utilizing these keywords makes it possible to locate relevant studies on high-quality human resources. Additionally, it is noteworthy that terms such as “highly skilled,”“education,” and “highly qualified” exhibit a considerable frequency of occurrence. The primary focus areas on superior human resources are administration, education, and training. Education is a means of enhancing one’s knowledge and advancing one’s career development.

Conclusions

The research findings have determined a significant interest in high-quality human resources and related keywords. Specifically, there have been 1,560 publications on this topic, with the highest number of publications occurring in 2019. These publications have received a total of 14,870 citations. The United States has the highest level of influence, with 368 publications.

Management, business, and economics are widely recognized as the most popular areas of publishing. Additionally, the field of educational research is closely associated with economics. The sectors above represent the primary industries in each respective nation. While abundant human resources exist, the focus lies in cultivating high-caliber personnel. This research endeavor’s practical management of such individuals is a crucial objective.

Moreover, the study delves into five primary color clusters, representing five critical facets of governance. The red cluster has highlighted the challenges and opportunities associated with high-quality human resource management. The Green cluster has identified certain factors that impact high-quality governance. The blue cluster has indicated the significance of knowledge management in conjunction with digital transformation. The Yellow cluster has demonstrated the importance of attracting and retaining high-quality employees. Lastly, the purple cluster has described how self-efficacy can influence the performance of high-quality employees. Based on the analysis of color clusters, it is evident that the key areas that require attention in contemporary high-quality human resource management are gender equality, labor mobility, brain drain, and attraction. The organization aims to maintain a skilled workforce, stay up-to-date with technological advancements such as artificial intelligence and digitalization, and enhance its knowledge management capabilities.

This research has broadened the scope of research content, expanded the range of keywords, and gathered ample data sources up to 2023. The article’s current and relevant information source provides valuable insights into contemporary management changes and trends. Prior research has primarily focused on defining and distinguishing the notion of “high-quality human resources” from related concepts such as “talent” and “talent management.” Our research analyses the primary concerns surrounding “high-quality human resource management in the labor market” and delves further into the topic of high-quality human resource management. Thus far, the research confirms that the subject of “high-quality human resources” has garnered significant attention in both practical and academic spheres.

Implication

High-quality labor is a fundamental pillar underpinning economic competitiveness, catalyzing growth and innovation within knowledge-based economies. The cultivation of such labor necessitates a relentless focus on practical education and skills development. However, it is essential to recognize that the presence of high-quality workers can profoundly influence labor market dynamics, with potential repercussions on wages and the perpetuation of income disparities. Robust research and data analysis are invaluable tools, offering critical insights that empower policymakers, businesses, and educators to craft and implement effective strategies and policies. Policymakers, in particular, are poised to harness research-driven recommendations to inform human resource management and education policies, while businesses are well-situated to tailor their strategies for a competitive edge. Fostering global collaboration is pivotal in the realm of research, often spotlighting the intricate interplay between high-quality labor and innovation, underscoring the imperative of sustainability strategies, and exerting influence over societal values and individual perspectives concerning career and educational choices.

Moreover, the study conducted here has meticulously analyzed the data, reaffirming previously established principles on high-quality “human resources.” It underscores the paramount importance of top-tier human resources within an organization. To engage in effective human resource management practices, managers must consistently prioritize their employees’ well-being in work-life balance, job satisfaction, equity, and alignment between employee and organizational goals. Notably, fostering self-confidence, not only among employees meeting high-quality human resources criteria but across the workforce, is imperative. The bedrock of a robust employer-employee relationship hinges on the employee’s perceived competence, fueling their performance and ultimately culminating in heightened organizational productivity.

Limitations and Directions for Further Research

The research observed a pre-existing constraint. The research utilizes solely two platforms for processing a vast data source. This constraint restricts the capacity to conduct cross-platform result comparisons, impeding enhanced analysis potential. Hence, the complete potential of the data may need to be actualized, an overview of contemporary big data analytics tools. The study mitigates potential bias by utilizing data from the Web of Science. This constraint can be remedied and enhanced in subsequent research; however, it does not impact the credibility of the results. Theoretically, this could facilitate research and theory formulation, providing a more precise and integrated definition of “high-quality workforce” and management. This labor source requires special treatment. Subsequently, it is incorporated into the curricula to enhance management theories and bolster managerial effectiveness in contemporary times.

The article’s management techniques can assist managers in effectively managing high-quality human resources. The study can expand through a new research project focusing on specific aspects of the global labor market. An exhaustive examination of the United States’ influence on the publishing industry and the ample pool of skilled labor in the job market has the potential to yield valuable insights. The research paper enabled researchers to leverage big data in their investigations, enhancing their understanding of management principles. The research posits that big data will find utility in various domains such as education, research, and other related fields.

Footnotes

Appendix

Label	Links	Total link strength	Occurrences	Label	Links	Total link strength	Occurrences	Label	Links	Total link strength	Occurrences
Red cluster
Performance	149	521	118	Efficiency	32	41	12	unemployment	38	48	16
Innovation	77	178	60	Experience	30	34	12	competition	20	24	13
Gender	92	184	44	Perspective	39	51	12	inequality	37	48	13
Migration	57	109	38	Policy	31	38	12	labor market	24	29	13
Employment	65	99	34	Brain drain	13	18	11	workers	37	48	13
Human capital	62	101	33	Incentives	22	28	11	compensation	35	45	12
Productivity	65	123	32	Discrimination	27	33	10	earnings	25	30	12
Higher education	47	59	27	Immigration	27	36	10	creative class	12	16	8
Diversity	54	85	24	Scientists	24	29	10	life	35	38	8
Labor	43	64	23	Universities	24	28	10	ownership	28	33	8
Mobility	47	76	23	Age	28	39	9	participation	29	35	8
Challenges	53	72	21	Income	19	23	9	employers	23	27	7
Entrepreneurship	33	51	20	Investment	21	23	9	inclusion	24	31	7
Growth	42	67	19	R&D	30	42	9	foreigner	17	22	7
Industry	43	60	19	Size	19	28	9	wages	21	24	7
Experiences	52	78	18	United States	21	23	9
Technology	46	61	18	Strategies	48	60	17
Green cluster
Talent management	113	324	115	Talent retention	46	62	13	Support	49	69	17
Commitment	89	236	53	Work-life balance	44	56	12	Turnover intention	49	97	17
Model	107	212	49	Affective commitment	35	60	10	Career	38	56	15
Job-satisfaction	93	235	42	Perceived organizational support	42	64	10	Employee turnover	41	54	14
Job satisfaction	82	182	41	Trust	40	57	10	Transformational leadership	42	58	14
Turnover	78	168	36	Psychological contract	38	47	9	India	32	38	13
Organizational commitment	78	170	35	Stress	30	39	9	Normative commitment	23	35	7
Satisfaction	75	149	33	World	23	29	9	Organizational justice	29	40	7
Retention	76	139	32	Employee performance	28	33	8	Organizational performance	19	20	7
Outcomes	70	112	23	Intentions	29	47	8	Relevance	21	30	7
Attitude attitude	63	106	22	Moderating role	35	45	8	Social-exchange	35	43	7
Consequences	63	102	19	Turnover intentions	36	51	8	Job	55	86	19
								Voluntary turnover	31	38	8
Blue cluster
Education	79	142	82	Time	37	48	14	Employability	32	40	16
Impact	132	348	80	Digitalization	24	33	13	Science	27	41	15
Knowledge	77	132	42	Communication	24	28	11	Career development	64	59	14
Workforce	66	99	41	Future	28	34	11	Globalization	25	28	14
Skills	73	107	32	School	18	26	11	Qualitative research	30	34	14
Training	54	72	31	Teachers	16	22	11	Success	47	65	14
Women	72	119	29	Artificial intelligence	10	14	10	Professional development	15	15	8
Students	41	57	27	Managers	35	43	10	Knowledge workers	25	26	7
Quality	47	56	20	Collaboration	29	36	9	Lifelong learning	4	5	7
Knowledge management	39	49	19	Digital transformation	8	11	9	Machine learning	4	7	7
Faculty	35	61	17	Mentoring	27	32	9	Trends	20	21	7
Care	17	23	16	Nurses	24	32	8
Yellow cluster
Management	132	303	82	Reputation	27	44	11	Firm performance	45	60	14
Human resource management	62	98	34	Service	35	44	11	Competencies	21	25	13
Talent	76	122	34	Identification	37	46	10	Framework	36	51	13
Employee retention	52	95	26	Organizational attractiveness	31	48	10	Sustainability	24	30	12
Employer branding	49	91	25	Corporate social responsibility	23	32	9	Development	21	28	11
Recruitment	58	91	24	Employer brand	22	26	9	Flexibility	22	23	8
Identity	49	73	20	Image	33	49	9	Decision-making	23	24	7
Employee engagement	45	76	19	Selection	38	45	9	People	33	40	7
Information	42	53	17	Social media	23	28	9	Person-organization fit	27	36	7
Systems	46	69	17	Attractiveness	37	49	8	SME	22	24	7
Competitive advantage	41	56	16	Business	32	36	8	Culture	42	56	15
								Employee	12	16	8
Purple cluster
Work	130	339	79	Design	32	39	12	Workplace	52	76	16
Employees	94	187	47	Mediating role	49	69	12	Industry 4.0	25	31	13
Leadership	84	161	39	Organizational culture	41	55	12	Resources	46	58	13
Behavior	77	148	33	Personality	36	52	11	Burnout	36	53	12
Motivation	70	117	33	Emotional intelligence	25	35	10	Creativity	30	44	12
Perceptions	74	115	28	Context	29	35	9	Autonomy	23	25	7
Organizations	62	94	24	Self-efficacy	38	51	9	Demands	27	39	7
Engagement	60	78	16	Training and development	24	28	9	Job-performance	28	37	7
Work engagement	44	79	16	Validity	25	36	8	Learning	19	20	7
								Validation	39	46	7

Author’s Note

This research was conducted while (Phung Phi Tran) was at (Faculty of Business Administration, Ton Duc Thang University, Ho Chi Minh City, Vietnam.). She is now at (Faculty of Sport Science, Ton Duc Thang University, Ho Chi Minh City, Vietnam).

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

ORCID iD

Phung Phi Tran

Data Availability Statement

The data for this study are available from the Web of Science database at Web of Science. Access may require a subscription. Specific datasets generated during the study can be requested from the corresponding author.

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High-Quality Human Resources in the Labor Market: A First Assessment of Potential and Obstacles

Abstract

Plain language summary

Keywords

Introduction

Literature Review

Research Methodology

Data Collection

Research Methodology

Keyword Co-occurrence Analysis

Data Mining

Stage 1: Prepare

Stage 2: Text Processing

Results

The Growth of the Number of Publications

Evolution of the Number of Citations

Most Influential Countries

Popular Research Fields

Analysis of Keyword Co-Occurrence

Red Cluster: Challenges and Opportunities in High-Quality Human Resource Management

Green Cluster: Factors Affecting the Management of High-Quality Human Resources

Blue Cluster: Knowledge Management Combined With Digital Transformation

Yellow Cluster: Attracting and Retaining High-Quality Employees

Purple Cluster: Self-Efficacy Affects the Performance of High-Quality Employees

Results of Data Mining From Text Mining

Conclusions

Implication

Limitations and Directions for Further Research

Footnotes

Appendix

Author’s Note

Declaration of Conflicting Interests

Funding

ORCID iD

Data Availability Statement

References