Next Article in Journal
Overcoming Uncertainty in Novel Technologies: The Role of Venture Capital Syndication Networks in Artificial Intelligence (AI) Startup Investments in Korea and Japan
Previous Article in Journal
A Literature Review of the Digital Thread: Definition, Key Technologies, and Applications
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Review

The Importance of e-Recruitment within a Smart Government Framework

by
Gabriel Koman
*,
Dominika Toman
,
Radoslav Jankal
and
Patrik Boršoš
*
Department of Managerial Theories, Faculty of Management Science and Informatics, University of Žilina, Univerzitná 8215/1, 010 26 Zilina, Slovakia
*
Authors to whom correspondence should be addressed.
Systems 2024, 12(3), 71; https://doi.org/10.3390/systems12030071
Submission received: 26 January 2024 / Revised: 13 February 2024 / Accepted: 21 February 2024 / Published: 24 February 2024

Abstract

:
This literary review examines the current state of research in the field of e-recruitment within the framework of smart government and its implementation in the context of modern public services. We elucidate the concepts of “smart government” as a concept of efficient, technologically supported public administration, and “electronic recruitment” as a process utilizing digital tools in the search and acquisition of suitable candidates for job vacancies. The objective of this review is to provide a brief overview of the current state of smart government, e-HRM (electronic human resource management), and e-recruitment, and analyze their interconnection. The selection of relevant sources followed the PRISMA method. In the context of defining the key functional module of e-HRM, the Grounded Theory Method (GTM) was employed. The final part of the methodological approach involved designing a research problem for future research. Specifically, the review focuses on defining the key functional module of e-HRM and proposes an orientation for future research that should concentrate on the impacts of e-recruitment on the efficiency of human resources within public services. The results of this study can serve as a foundation for future research aimed at optimizing and utilizing e-recruitment in the specific field of smart government.

1. Introduction

Currently, technological progress is one of the most significant and fastest phenomena influencing various aspects of life. This dynamic technological development permeates different sectors and brings innovations that change the way people work and interact with the world. Technologies are increasingly being implemented not only within commercial organizational environments [1,2,3,4,5], but also beyond, e.g., in sports [6], transportation [7], education [8], tourism [9], and more. They also have a similar impact on the management of public institutions [10], gradually evolving toward more sophisticated and interactive governance models [11]. Based on this trend, a new type of governance is emerging, which experts refer to as open government [12]. The current trend of smart technologies considers the need to transform traditional methods of managing the public sector. In the current era of digitization and automation, it is essential to discuss the implementation of modern information systems and/or information technologies (IS/IT), including their application in the field of human resource management [13]. Advanced technologies such as artificial intelligence [14,15], big data [16], virtual reality [17], and blockchain [18,19] can significantly enhance the efficiency of these processes. This evolution may represent a significant step towards the modernization of public institutions [20], highlighting the need for adaptation to new challenges and responding to opportunities brought by the dynamics of the contemporary work environment [21].
In this context, e-recruitment plays a crucial role, and its significance is intertwined with the development of smart government. e-recruitment becomes a key pillar in the modernization efforts of public institutions. It enables these institutions to effectively compete and acquire qualified talents from the job market [22]. Via the use of technological innovations and information systems in the recruitment process, new possibilities emerge for faster, more accurate, and transparent placement of suitable candidates in public services [23].

1.1. Research Objectives

This research undertakes a comprehensive literature review, focusing on the significance of e-recruitment within the realm of smart governance in public institutions. Specifically, this study delves into the application of IS/IT in this context. The primary goal is to identify both conceptual and technological dimensions of e-recruitment.
Given the evolving nature of smart government, this study places emphasis on pinpointing the factors that render e-recruitment a crucial element in contemporary human resource management strategies. The central focus, representing the innovative aspect of the research, lies in providing a thorough understanding of the interplay between the recruitment process and IS/IT and their collective impact on the public sector. Additionally, a novel contribution involves the development of a graphical model solution designed to clearly illustrate individual aspects and their interconnections.

1.2. Purpose and Justification of the Research

The foundation for conducting this literature review is the existing imbalance in the literature, where the integration of IS/IT into e-recruitment processes has only been explored to a limited extent. Previous studies predominantly focus on various aspects of human resource management within the context of electronic human resource management (e-HRM). However, the potential and benefits that the implementation of IS/IT can bring into the field of e-recruitment have been insufficiently analyzed. That is why we focused on identifying key areas where it is possible to implement IS/IT within the employee recruitment process. So far, researchers have primarily focused on defining the concept of recruitment within e-HRM. However, there is a lack of research on the direct use of IS/IT within this recruitment process and the identification of the subsequent benefits of implementation. This represents the identified knowledge gap addressed by this study.
This article focuses on the creation of a theoretical knowledge base, which will be used in other research projects by the authors of this review, as well as by other world authors. A systematic theoretical analysis of existing research in this area will allow for a deeper understanding of both facets of the discussed topic—the significance of e-recruitment and its connection with IS/IT. This understanding can be utilized in the future when developing the concept of smart governance further.

2. Materials and Methods

Before conducting the analysis of theoretical foundations, parameters necessary for the effective identification of relevant sources had to be identified. The following parameters were chosen to focus on key concepts in the addressed issue and ensure that the research is closely connected to the subject of interest: (1) relevant databases, (2) keywords, and (3) topic categories.
Relevant Databases
To achieve an academic overview within the theoretical analysis of the selected issue, Web of Science and Scopus were chosen as the relevant scientific databases. These databases are considered reputable due to their extensive collection of scholarly materials, including scientific articles, conference proceedings, books, and reviews covering various research areas. Their use in the theoretical analysis contributed to securing reliable and relevant pieces of information.
Keywords
Based on the defined objective of this study, two main keywords were determined: “smart government” and “electronic human resources management.” Subsequently, modified terms for each keyword were also examined. An overview of all searched keywords is included in Table 1.
By using these keywords and their combinations (Table 1) in the selected databases, it was possible to identify a substantial number of publications related to the addressed issue. However, given the high number of publications discovered, it was necessary to narrow this set down. To achieve more precise results, additional search parameters were introduced.
Topic Categories
Another parameter involves the topic focus of publications. During the initial review of sources, it was possible to identify their focus on various scientific areas. However, during the detailed analysis of the obtained sources, it was necessary to primarily focus on those research areas directly related to the objective of this study. Following this procedure, the main scientific area defined was management.

2.1. Selection of Relevant Sources Based on the PRISMA Method

Despite incorporating several parameters into the source search, the number of obtained materials remained extensive. Therefore, it was necessary to systematically categorize these sources and evaluate their relevance based on predefined identifiers. For this purpose, the PRISMA (Preferred Reporting Items for Systematic Reviews) methodology was applied, representing a systematic approach to the identification, selection, assessment, and synthesis of various types of information sources, including books, case studies, scientific articles, and others [24]. This ensured a structured and objective analysis, allowing for the efficient processing and interpretation of a vast amount of information from various sources.
By using the selected scientific databases and journals, a total of 313 publications were identified. To effectively organize and manage this large collection of sources, the Zotero software tool 6.0.30 was employed, facilitating the straightforward removal of duplicates. After this refinement, a total of 64 sources were available (Figure 1).
Subsequently, a three-phase verification of sources was performed. Verification involved comparing publications with the topic and goal of this study based on three different identifiers. These included: (1) the title of the publication, (2) the abstract, and (3) the entire text of the publication. After including the first identifier, we retained 208 publications and removed 105 publications. After including the second identifier, we retained 124 publications. Thus, we removed 84 from the previous amount of 208. After including the third identifier, we kept 64 publications and removed 60 publications. After the successful completion of the three-phase verification, 64 online sources were identified.

2.2. General Use of Grounded Theory Method (GTM)

GTM is a qualitative research method primarily employed in social scientific disciplines to create theories and concepts based on acquired data. This method was developed in the 20th century by Glaser and Strauss [25,26]. GTM represents a research design where the researcher examines the behavior of subjects in connection with the main research objective [27]. GTM provides a verifiable and testable concept used to explain a specific phenomenon. It is an organized set of concepts and principles serving to rationally and clearly explain a particular phenomenon [28].
Several authors have already utilized this method in processing theoretical foundations, e.g., GTM was used to identify the “main concerns of job seekers and personnel agencies in electronic recruitment” [29]. Other authors employed GTM to “gather first-hand data on respondents’ experiences and perceptions regarding recruitment applications and discrimination based on artificial intelligence” [30]. In the processing of theoretical foundations, GTM was used for the conceptualization of e-recruitment [31]. Many other international authors use GTM in creating literature reviews and scientific articles [32,33,34,35].
In this article, the Grounded Theory Method (GTM) was employed to identify the key functional module within e-HRM. This method facilitated a systematic approach to comparing individual functional modules of e-HRM in connection with the primary research objective. This way, GTM provided a framework for gaining a deeper understanding and conceptualization of the functional modules in the field of e-HRM.

2.2.1. Criteria for Inclusion of Sources within a Specific Use of the GTM

In the second part of this article, the functional modules of e-HRM represent the subject for investigation. The object of study is their position and importance within personnel processes and the entire e-HRM system. The objective of this section is to identify the key functional module of e-HRM. To achieve this, it was necessary to identify sources that specifically describe the addressed issue, i.e., e-HRM. Table 2 provides an overview of these sources. Within the professional literature, only a few articles specifically address human resource management within public administration. To better document individual personnel processes, we have included various publications from the literature that focus on this issue within businesses. The key activities of specific personnel processes are the same or very similar.
The criterion for selecting the sources was that the authors directly describe the theoretical aspects of e-HRM systems in their publications. Many publications describe various functional modules from a practical or technical perspective, but they may not provide clear information about the importance of specific modules within e-HRM, or compare them with each other.

2.2.2. Procedure for the Identification of the Key Functional Module of e-HRM Using the GTM

GTM was employed to clearly define the key module of e-HRM. The specific procedure is illustrated in Figure 2. Within GTM, various levels of coding were utilized [26,35]:
  • Data collection—This initial phase involves gathering relevant information and materials related to e-HRM;
  • Open coding—This is performed to identify, (re)label, and/or create a set of concepts and perspectives based on excerpts from the publications. Open coding means that the researcher aims to conceptualize and formulate often hidden aspects of publications to address defined research questions;
  • Constant comparison—This integral component of GTM involves continually comparing data, codes, and emerging concepts throughout the analysis process. It facilitates the refinement and clarification of categories and relationships;
  • Axial coding—This involves identifying relationships between individual concepts from open coding. The result is the creation of basic categories for each concept;
  • Selective coding—Based on a thorough comparison, selective coding involves selecting one key category. All other categories either represent its subcategories or are significantly influenced by it. Selective coding occurs after achieving theoretical saturation.
Theoretical saturation denotes a state when the number and diversity of new concepts, categories, and relationships in the analyzed data can no longer be significantly expanded or improved via further exploration, study, or analysis [28,36]. Essentially, this means that researchers have reached the point where they no longer discover new ideas or new connections among the data points.
Finally, the construction of theory is conducted, representing the process of creating new theoretical frameworks, models, or explanatory structures. These serve to understand a specific phenomenon, issue, or area of study [26].
In the course of this study, the validation process was conducted through a comprehensive comparison with existing theories from other authors, specifically focusing on traditional human resources (HRM) and employee recruitment areas. These established theories were considered to be physical equivalents to the realms of e-HRM and e-recruitment, offering a broader framework for the assessment and validation of emerging concepts. Through this thorough analysis, similarities, differences, and potential innovative aspects within the spheres of e-HRM and e-recruitment were identified. This validation process plays a crucial role in determining whether the theoretical model accurately represents the investigated reality [37].

2.3. Proposal of the Research Problem for Longitudinal Research

To precisely define the research problem for current and future research, a foundational model has been developed. This model represents the basic concept that allows the formulation of research questions and hypotheses with accuracy and relevance. The model was created using the ArchiMate framework, which provides a systematic approach to modeling enterprise architectures. This tool is particularly suitable for creating complex models as it enables visualization and hierarchical structuring.
The derivation of the foundational model is based on a thorough literature review gathering existing knowledge and approaches in the field. This ensures that the initial model is anchored in recognized theoretical and practical contexts. The literature served as a fundamental element for identifying relevant factors, variables, and relationships impacting the defined research problem.
The resulting model offers a set of clearly defined variables and relationships, allowing for a precise analysis of the specific research problem. This way, a stable foundation has been established for further steps in the research process. The foundational model guides the formulation of specific research questions and hypotheses, enabling the systematic testing and development of the assumptions established.

3. Introduction to the Topic Smart Government Focusing on HR

The expansion of the internet in the 20th century had a significant impact on global commerce, giving rise to a new way of conducting business–electronic commerce [38]. This trend sparked increased interest among governments to reconsider the use of the internet, with a focus on its applications in public administration [39]. Their efforts aimed to enhance the delivery of services to citizens, increase the efficiency of the public sector, and strengthen government accountability.
As a result of the advancement of new technologies, governments are compelled to reassess their role in contemporary society [40]. They are elevating the concept of e-government to a higher level [41], recognizing the power of the data they possess and utilizing it to enhance the services provided. Governments seek to enable an integrated and seamless user experience in utilizing services, actively engage citizens in co-creating policies, and implement solutions for the benefit of the community. These steps aim at the transformation and adoption of smart government [42].
The everyday use of mobile applications and social networks significantly influences the interconnection of modern societies. Consequently, a new era of delivering public services to governments is emerging. Governments are integrating super-applications into their current portfolio of communication tools to provide services. In line with the modern concept of citizen-oriented services, emphasis is placed on meeting citizens’ needs. This is becoming a key element [43]. By combining modern technologies with government services, increased acceptance, and data-oriented services, governments have the potential to radically transform their role in contemporary societies [44].
Smart government is divided into various categories based on the stakeholders with whom governments communicate. These include [39]:
  • Government-to-Business (G2B)—for interactions with organizations;
  • Government-to-Citizen (G2C)—for interactions with citizens;
  • Government-to-Government (G2G)—for exchanges between governmental agencies;
  • Government-to-Employee (G2E)—for interactions with governmental employees.
One of the main areas of smart government is G2E, which represents the use of modern technologies to improve the relationship between employers and employees [45]. This part of smart government contributes the most to the efficient functioning of the government [39]. The primary component of G2E in the concept of smart government is the utilization of modern technologies to streamline human resources management, i.e., e-HRM.

3.1. Smart Government and Its Basic Characteristics

The Fourth Industrial Revolution brought the modern application of IS/IT not only into organizations but also into cities and governments. In connection with government institutions, the term “smart government” is being increasingly used, referring to the utilization of advanced technologies in public administration. These technologies may include blockchain, artificial intelligence, the Internet of Things (IoT), or cloud computing [46,47]. Al-Obaithani describes the term “smart” in the context of smart government as follows [48]:
  • Social—providing public services for citizens and enabling collaboration with the government via social media;
  • Mobile—using mobile technologies to provide information and services to citizens anytime and anywhere;
  • Analytics—utilizing big data and sensors to manage policies and tailor communication with the public;
  • Radical openness—transparency and citizen involvement in decision making, as well as enabling organizations to use data for new services;
  • Trust—assuring cyber security and protecting citizens’ privacy.
Smart government can be understood as a concept connecting various areas of public administration management with modern IS/IT. As some authors suggest, one of the most important initiatives for building a smart government framework is “smart working” [49,50,51]. Smart working is precisely connecting people with the entire concept of smart government. This is a system consisting of three main elements: (1) people, (2) technologies, and (3) organizations [52].
Authors dealing with this issue have identified 14 components of intelligence in government, including integration, innovation, citizen orientation, sustainability, creativity, efficiency, and others. This comprehensive framework helps avoid a simplified focus solely on technologies, providing recommendations for initiatives aimed at intelligent governance [53]. This piece of information shows that human resources with the necessary digital skills and knowledge can be a key element in the successful implementation of the concept of intelligent public administration in today’s digital age. These abilities should include not only technical skills but also the ability to quickly adapt to a rapidly changing technological environment. Similarly, it is essential for human resources to have the ability to think critically and creatively in solving complex problems arising during the implementation of intelligent public administration. For a narrow group of people who have access to confidential data within public administration, it is necessary for them to be transparent and accessible. The transparent aspect of information positively influences effective decision making [12,53]. The success of this concept may depend on investments in education [54] and the development of employees [55] to effectively harness the benefits and potential of modern technologies in public administration.

3.2. HR in the Concept of Smart Government

The importance of human resources (HR) in the concept of smart government is also emphasized by Guenduez et al., who defined that considering the growing importance of requalification and lifelong learning, it is necessary for public administration to reflect these trends in recruitment [56]. They also emphasize the resistance to change and a lack of required skills and know-how as identified obstacles to implementing intelligent public administration. In this context, e-recruitment represents an effective tool to help address these challenges related to recruitment and employment in public administration.
Recruitment in intelligent public administration should respond to new skills needed for these modern initiatives. The need to hire specialized professionals for highly specialized tasks, such as data management and cybersecurity, is emphasized as well. Additionally, it is expected that many job profiles will combine various categories of skills, including technological, methodical, and interpersonal ones. These results indicate that job profiles are becoming more hybrid and multi-rational in an effort to meet the requirements of intelligent public administration [56]. In defining smart government, the sources shown in Table 3 were used and chronologically arranged. The fourth column (the one on the right) was added, describing the use of the sources in the analysis of the theoretical foundations presented in this review. The column “article focus” contains keywords derived from the text of the articles. The titles of the articles are listed in the bibliography.

4. e-HRM and Its Characteristics

The current era is characterized by digital transformation, which significantly influences human resource management in organizations and government institutions [57]. The use of modern IS/IT in human resource management processes is referred to as e-HRM, which combines modern technologies, software applications, and personnel management [58,59]. This dynamic area brings new opportunities and challenges for organizations to effectively manage and develop human resources in the digital transformation environment.
After the introduction of informatization in human resources, various terms have emerged to describe the nature, role, and benefits of technologies in employee management. The most used terms are Human Resources Information System (HRIS) and e-HRM. Ruël et al. (2004) state that there is a fundamental difference between HRIS and e-HRM [45]. HRIS is primarily focused on providing information support for human resource management. Its users are mainly employees and managers of the personnel department. The objective of these systems is to improve managerial processes within the personnel department based on available information and simultaneously provide better services for the entire organization. On the other hand, e-HRM focuses on employees and management outside the personnel department. e-HRM services are usually accessible via the intranet, and every employee in the organization can use them. Thus, the main difference between HRIS and e-HRM lies in the transition from technological support for information management to the automation of personnel management services. HRIS can essentially be understood as a form of e-HRM, involving the use of conventional, web, and voice technologies to make significant progress in human resource management [60].
e-HRM, driven by IS/IT, manages intellectual capital in organizations [61]. It leverages technologies (social, mobile, analytical, cloud) for efficient employee service delivery, aligning with management trends such as decentralization through self-service apps, shared services, and outsourcing. Strategically, it utilizes big data, predictive analytics, and AI. e-HRM also considers unintended consequences like impacts on information security and privacy [62].
e-HRM has revolutionized the way organizations approach HR by utilizing technologies to streamline and optimize HR processes. These HR processes are referred to as functions or functional modules of e-HRM. Via the use of technologies, e-HRM functions can automate manual tasks, improve data accuracy, and enhance overall efficiency, allowing HR professionals to focus on strategic initiatives and talent development [62]. These functions may include e-recruitment, e-selection, e-testing, e-assessment, e-performance management, e-learning, e-training, e-attendance, e-benefit, e-compensation, and e-reporting. As implied by the names of these functional modules, each is focused on a specific HR process. The following section provides a detailed description of some of the most used functional modules of e-HRM in organizations.

4.1. Conceptual Framework of e-HRM

This framework provides a systematic approach to human resource management in the digital environment. Each of its four dimensions represents a key aspect that collectively forms an overall model for the effective utilization of e-HRM.
The first dimension comprises strategic approaches, specifically categorized into (1) bureaucratic, (2) market, and (3) clan approaches. The bureaucratic approach is applied in stable market environments [45] and emphasizes standardization and control, offering advantages in efficiency and cost savings but with limited adaptability [63]. The market approach is common in organizations responding to rapid changes [45], placing emphasis on competitiveness and results. This strategic approach is characterized by e-HRM supporting performance management and rewards [63]. The clan approach prevails in organizations focusing on quality and innovation [45]. It supports organizational culture, employee engagement, collaboration, communication, and knowledge sharing among employees, with an emphasis on building relationships and trust [63]. In the bureaucratic and market approaches, centralization dominates, while the clan approach often involves decentralization with high employee autonomy.
The objectives of e-HRM can be summarized in three main areas [45]: (1) improvement of the strategic orientation of human resource management, (2) cost reduction and increased efficiency, and (3) enhancement of personnel services for management and employees. These objectives are assigned to three levels of human resources management [61,64]:
  • Transformational level—involves aligning the organization’s strategy with human resource planning;
  • Operational level—emphasizes cost reduction and increased efficiency of work processes;
  • Relational level—focuses on improving personnel services via remote access, communication between departments, and connections with the organization’s internal and external environment [31,35].
The primary purpose of e-HRM (in connection with the objectives listed) is to focus on the organization’s strategy, increase the flexibility of employees, and streamline work processes, with a crucial emphasis on facilitating the employees’ work. From the analysis of theoretical foundations, additional objectives of e-HRM emerge, including providing comprehensive IS/IT with data about people, automating the transfer of employee information, and ensuring data security [65].
As mentioned above, there are three levels of e-HRM [45,60,62,65,66,67]. In some organizations, the emphasis in human resources management is placed on administration and recordkeeping (operational level), while others focus more on the application of operational tools for human resources management (transactional level). In another group, the emphasis is put on the strategic role of e-HRM (transformational level) [45]. The benefits of e-HRM can be summarized into four results groups [45]:
  • High engagement—This expresses motivation, understanding, and willingness to communicate with leadership regarding changes in the organizational environment and their impact on the internal organization. For the HR department, this means having the ability to act as a mediator of change;
  • High competencies—These highlight the employees’ ability to learn new tasks and roles, as circumstances require. Competence can also be perceived as the decentralization of certain personnel processes that do not need to be performed by HR personnel but by employees themselves (e.g., vacation or medical planning, selection of benefits, payroll control, and others) [65];
  • Cost efficiency—This concerns competitiveness, salary levels, and the rate of employee turnover, as well as the acceptability of costs resulting from various types of employee resistance, such as strikes. This outcome of e-HRM is captured by Kaur, pointing to a reduction in paperwork, increased data accuracy, and a decrease in redundant work while maintaining data quality. e-HRM also contributes to a more transparent system [65];
  • Higher congruence—This relates to the internal organization, the reward system, and the inputs, performance, and outputs of employees. These must be structured to align with the interests of all stakeholders. Congruence can also be perceived as alignment between the work of employees and the long-term direction of the organization.
Based on the characteristics listed, it is possible to create a conceptual model of e-HRM. The individual dimensions can be understood as four stages of e-HRM operation in the organization. The first stage represents approaches to strategy and policy within the organization. The second stage defines goals set within e-HRM. The third stage analyzes the various levels of e-HRM, and the last, fourth stage constitutes its results. The final stage concludes one cycle and simultaneously starts a new one [68].
e-HRM models also consider the influences of the internal and external environment, in addition to key areas. Internal influences encompass the organization’s ideology and socio-cultural influences, and are reflected in the divergence and convergence of e-HRM [69,70]:
  • Divergence—Refers to the distancing from a common point and considers the specific needs of all employees that expand the key areas of e-HRM. These standardization aspects influence the first and second stages of the e-HRM cycle;
  • Convergence—Represents the process of integrating different visions, philosophies, and missions into one system, enabling employees to find their own internal motivation. In the context of e-HRM, this means the system’s ability to adapt to the organization’s needs and integrate various functions and personnel processes.
External influences, including technological and institutional states, primarily affect the third and fourth stages of the e-HRM cycle. The technological state includes current technologies, their availability, and the level of utilization in the industry, where information technologies, automation, robotics, AI, and cloud services play a crucial role. Organizations that can flexibly respond to technological changes gain a competitive advantage. The institutional state encompasses legislation, regulations, tax policies, and cultural factors in the country, providing organizations with stable conditions for investment and creating an environment supporting growth and development [71].

4.2. Technological Structure of e-HRM

Introducing new technologies into organizations, including e-HRM systems, is a crucial step toward improving HR management and enhancing the organization’s overall efficiency. The technological architecture of e-HRM systems is one of the critical components of this process. When introducing new technologies into organizations, several factors must be considered [72]:
  • Technological factors—current IT architecture, digitization of HR data, and the management of technological projects;
  • Organizational factors—knowledge and skills of organizational components, organizational policies and procedures, project management, and financial resources;
  • Human factors—communication characteristics, employee demographics, attitudes of employees and management towards technological innovations (support and engagement), involvement of employees and management, skills of employees and management versus training needs, organizational culture and leadership, and psychological factors.
The technological architecture of e-HRM systems concerns the design and organization of technical components, infrastructure, and software elements that constitute these systems. The objective is to create an efficient, secure, and scalable system that improves and supports HR management in the organization. The technological architecture of e-HRM systems (Figure 3) generally includes core technologies, functional modules, support modules, and the presentation layer [73].
Within the model of the technological structure of e-HRM, four levels can be identified: basic technologies, functional modules, supporting modules, and the presentation layer [73]. Basic technologies include key components supporting the operation of e-HRM systems:
  • The operating system serves as the central core for the operation of all software and applications;
  • The database stores relevant data about employees and their HR management;
  • Modern technologies such as AI, big data, cloud computing, and VR expand the system’s capabilities and form the core of e-HRM.
Functional modules are responsible for various tasks and processes in HR management. Each module is designed to efficiently automate specific HR tasks. These may include e-recruitment, e-assessment, e-learning, e-performance management, and e-benefits. Supporting modules enhance the performance of the e-HRM system. Supporting modules include:
  • Case management that incorporates technological components such as chatbots and email spam filtering, improving support for employees and the HR department;
  • Business intelligence (BI) that helps analyze and interpret large amounts of data, generating information for reports, charts, and dashboards.
Finally, the presentation layer serves to present the outputs of the e-HRM system. With this, all layers shown in Figure 3 have been introduced. Many sources were utilized to define e-HRM, as well as its conceptual architecture and technological structure, which have been systematically incorporated into Table 4. The original last column (on the right) represents the utilization of the acquired information applied within this review. The column “article focus” contains keywords derived from the text of the articles. The titles of the articles are listed in the bibliography.

4.3. Functional Modules of e-HRM

The use of e-HRM provides the advantage of optimizing personnel processes and streamlining human resources management in organizations. From the perspective of e-HRM, the individual personnel processes are referred to as functions or functional modules. These effectively utilize technologies to automate manual tasks, improve data accuracy, and enhance overall efficiency. This ensures greater attention from managers towards strategy formulation and the long-term development of employees [62]. The following subsections describe selected, commonly used functional modules of e-HRM in organizations.

4.3.1. e-Assessment

Organizations are increasingly focusing on providing continuous feedback rather than following the traditional annual performance review cycle. The emphasis is on the future (employee development), rather than evaluating past performance. Various performance assessment tools are more frequently used, such as the multi-source, or the 360-degree performance assessment [62]. The use of such employee assessment methods with the support of IS/IT is referred to as e-assessment. Fontanillas et al. define e-assessment as any evaluative process utilizing IS/IT and/or IS to implement assessment activities and tasks [74]. This process involves recording responses and evaluating them from multiple perspectives. e-assessment can be seen as assessing candidates during employee recruitment and simultaneously as a performance management assessment for employees [75].
In the context of the recruitment process, e-assessment aims to generate a limited list of suitable candidates via online comparisons of applicants’ skills and abilities with the requirements of the job profile [76]. Diagnostic tools for suitability assessment, including electronic assessment procedures, can be classified based on their methodology [77]: attribute approach, simulation approach, and biographical approach (questionnaire survey, interview format).
The second application of e-assessment is within the job performance assessment, measuring the returns that the organization gains in exchange for the salary it pays. In this case, IS/IT supports e-assessment, streamlining the 360-degree performance evaluation process [78]. This method involves assessing an employee from the perspective of various stakeholders, such as colleagues, superiors, subordinates, customers, suppliers, and others.
In both situational perspectives, e-assessment is employed via a technologically enhanced assessment (TEA) system. TEA is a type of electronic assessment system that uses digital technologies to improve the assessment process. TEA systems can include various assessment methods, such as multiple-choice questions, short-answer questions, simulations, and interactive scenarios [79].

4.3.2. e-Learning

Based on the results of e-assessment, organizations often propose various educational activities and training for individual employees. This functional e-HRM module is called e-learning. It refers to electronic education, described as an innovative approach providing well-designed, individually oriented, interactive learning environments. Any employee can use it anywhere at any time. Open and flexible educational materials and various digital resources are utilized in this type of education [80]. Many organizations worldwide are creating educational platforms where employees organize and share content themselves. The main responsibility of these organizations is to guide their employees regarding necessary, valued, and rewarded skills and competencies. Their role also includes assisting in roleplaying, mentoring, coaching, providing opportunities for on-the-job learning, and supporting employee socialization. The objective of these organizations is to create a modern learning management system (LMS). While digital technologies can be useful tools in this area, they cannot replace the human approach necessary for employee education [62].
e-learning enables organizations to consistently provide training for all employees, update training content as needed, reduce travel costs to external training facilities, and offer on-demand training to employees anytime, anywhere. e-learning systems should be built based on cognitive learning theory and should incorporate the following principles [81]: multimedia; integration of graphics and text; modality; and personalization principles.
Some authors associate e-training with e-learning [82,83]. Nicholson describes e-training as acquiring skills and experiences, while e-learning is acquiring knowledge [84]. However, he acknowledges that in the knowledge era of the Fourth Industrial Revolution, these two functional modules can be viewed as one. Another module often associated with e-learning in the literature is e-development.

4.3.3. e-Attendance

Electronic attendance, or e-attendance, refers to the use of digital technologies to monitor and record the presence or absence of individuals, typically in educational or work environments. It replaces traditional manual methods, such as paper attendance sheets, with automated systems. These systems simplify the process and provide more accurate and efficient attendance management. By using electronic attendance not only to track presence and absence but also to monitor work on projects and plan time, it becomes an effective means of managing the performance of individuals and the entire organization [85]. Traditional paper-based attendance recording methods were prone to errors and manipulations, leading to inaccurate records. The implementation of modern technologies into these systems has introduced new e-attendance methods, such as RFID cards and chips [86], biometric fingerprint scans [87], facial recognition [88], and GPS location tracking [89].

4.3.4. e-Performance Management

Electronic Performance Management (e-PM) can be understood as the use of audiovisual computer systems to collect, store, analyze, and report performance data of individuals and/or groups [90]. The primary goal of utilizing technology in performance assessment is to enhance individual performances or organizational performance by providing employees with the necessary knowledge, techniques, methods, and supporting systems [91]. This functional module integrates with previous e-HRM modules, such as e-assessment, e-learning, e-attendance, and others. e-PM systems allow monitoring and comparing performance data at both individual and department levels. Emphasis is placed on criteria such as attendance, job performance, stakeholder satisfaction, and turnover. Department-level data can be used to identify human resources issues, uncover potential shortcomings in assessments, or highlight exceptional performance. The use of personnel analytics facilitates acquiring, documenting, and aggregating various performance data from different sources, enabling managers to utilize valuable information for monitoring and addressing employee performance issues [92]. e-PM is also associated with other functional modules, such as [62]
  • e-compensation—Electronic compensation enables managers to propose, manage, and report compensation policies more efficiently, using internet-based software tools [93]. Additionally, it aids in managing routine compensation management duties [94]. e-compensation tools facilitate the execution of bureaucratic responsibilities via real-time data and knowledge flow. Furthermore, electronic accounting can be beneficial in maintaining pay equity [93];
  • e-benefit—Electronic employee benefits involve the digitization and automation of various employee benefits offered by organizations. e-benefit platforms typically provide a centralized and user-friendly interface where employees can conveniently access, select, and manage their benefits. These benefits may include a wide range of offerings such as health insurance, retirement plans, paid time off, flexible spending accounts, wellness programs, employee assistance programs, and more [85];
  • e-reporting—Electronic reporting is the process of digitally collecting, submitting, and disseminating information, data, or reports via IS/IT. This method replaces traditional paper-based reporting systems and enables the rapid and efficient transfer of data and information between various stakeholders. In the organizational context, electronic reporting may involve a broad range of activities, including financial reporting, performance reporting, compliance reporting, environmental reporting, and others. It involves the use of electronic tools and platforms for compiling, analyzing, and presenting data in a structured and easily accessible format [85,95].

4.3.5. e-Recruitment

By utilizing technologies, e-HRM functions have the ability to automate manual tasks, improve data accuracy, and enhance overall efficiency (e-recruitment, e-selection, e-testing, e-assessment, e-performance management, e-learning, e-training, e-attendance, e-benefit, e-compensation, and e-reporting) [62]. e-recruitment has become a fundamental tool for many organizations. With the development of the internet and social media, the recruitment process has undergone a revolutionary change. e-recruitment can be defined as the electronic form of the employee recruitment process in organizations. The essence of this form of recruitment process involves the use of various digital technologies for sourcing, screening, and accepting job applicants. This method typically includes posting job vacancies on company websites, web career portals, as well as on various social media platforms or other websites. Additionally, the system is used as a tool for managing and monitoring the recruitment process and other related activities [72,96]. According to Abia and Brown, e-recruitment can be perceived in five concepts, as follows [31]:
  • Technology tool—a set of technologies supporting the management and execution of the recruitment process [97];
  • System—A set of independent but interconnected elements, where the main components are information, technologies, and organizations. The significance of these elements lies in the automated functions of the recruitment process [98];
  • Process—Activities of e-recruitment that are interconnected and contribute to achieving the objective of the employee recruitment process [99];
  • Service—A platform supporting the recruitment process. This perspective can be seen as follows:
    • Repository—A database of essential data that is linked to the recruitment process. This can include data on job positions, recruitment of employees, employers, as well as job applicants [100];
    • Medium—An intermediary of communication between the organization and job applicants [101];
    • Program—An algorithmic module of the recruitment process management system that utilizes various methods, techniques, computations, as well as logical interpretation and processing of data [102];
  • Proxy—Presentation of the organization’s image and culture [103].
e-recruitment may involve a variety of digital tools, such as software for aggregating job offers, applicant tracking systems, or online skills assessment. These tools can help streamline the recruitment process, reduce administrative work, and improve the quality of applicant selection [104].
In employee recruitment, technologies like AI are increasingly being used, especially in four general activity groups: sourcing, selection, assessment, and coordination. During the sourcing phase, organizations aim to identify potential applicants for specific job positions. Applying for a job involves filling out digital applications or electronically submitting applications and necessary documents. After submitting these applications, employers have the challenging task of evaluating applicants and determining who best fits the requirements of the job position. This stage may involve multiple rounds or methods of assessment to identify the best candidates who will receive job offers. AI can be used to coordinate with applicants throughout the entire process, contributing to the efficiency and accuracy of the selection process [105].
An analysis of theoretical foundations related to the functional modules of e-HRM was developed based on sources summarized in Table 5. In addition to the chronological arrangement of sources along with the titles of individual publications, the table also includes information on the use of specific information in relation to this review (fourth column). The column “article focus” contains keywords derived from the text of the articles. The titles of the articles are listed in the bibliography.

5. Research Gap

e-HRM is a holistic approach to human resources management, gaining prominence in the realm of smart government. Its crucial role involves leveraging innovative IS/IT applications to enhance efficiency across all HR functions, spanning recruitment, evaluation, and employee rewards. e-HRM offers an integrated framework that simplifies and supports personnel processes. It includes specialized modules designed to optimize HR activities, serving as a vital component for the successful integration of IS/IT in human resources management.
The current literature primarily focuses on explaining e-HRM and its key functional modules. However, it lacks a thorough examination of specific cases of using modern IS/IT within individual e-HRM modules, which represents the technological structure of e-HRM. The absence of this specific information clearly indicates the need for future research in this area. Future research should focus on identifying specific cases of using modern IS/IT in specific HR processes and analyze the impact of these technologies on their effectiveness. This gap in the literature hinders a full understanding of the potential use of modern technologies in e-HRM.
Each functional module of e-HRM has its own potential for using modern IS/IT. Therefore, it is necessary to analyze each of these functional modules separately and not as a whole within e-HRM. To propose the focus of future research, we conducted the identification of a specific key functional module of e-HRM using the GTM. The GTM proceeded in four basic steps: (1) open coding, (2) axial coding, (3) selective coding, and (4) summarizing results.
Based on open coding, we focused on specific parts of individual sources that define, describe, or illustrate various functional modules of e-HRM. Zotero software 6.0.30 was used for this part of the analysis, making the recording and summarization of specific data clear and systematic. This allowed for the creation of individual concepts. In this phase of GTM, twelve concepts focused on specific functional modules of e-HRM were identified (Figure 4).
The next step was axial coding, which compared individual concepts and looked for starting categories. In connection with individual concepts, two entities were defined: applicant and employee. While e-selection, e-testing, e-assessment, and e-recruitment can be linked to the applicant entity (who is not yet part of the organization), other functional modules are already associated with the employee entity (who is within the internal environment). For this reason, it is possible to divide functional modules of e-HRM into those that take place between:
  • The organization and the applicant—including e-recruitment (recruitment), e-selection (selection), e-testing (testing), and e-assessment (assessment);
  • The organization and the employee—including e-assessment (assessment), e-performance management (performance management), e-learning (education), e-training (training), e-attendance (attendance), e-benefit (benefits), e-compensation (compensation), and e-reporting (reporting).
After reaching theoretical saturation, i.e., when we no longer obtained new data from individual sources, selective coding followed. In this phase, individual concepts and categories were mutually compared.
To identify the key functional module of e-HRM, the relevant functional modules in both identified categories were compared. In the context of the “applicants” category, it was revealed that the key functional module is e-recruitment, as other functional modules serve to support the process of recruiting new employees. Regarding the “employees” category, there are two possible key functional modules—e-reporting and e-PM—as these modules are associated with the largest number of other functional modules. After a detailed examination of both modules, we agreed that e-reporting provides support for e-PM. Therefore, e-PM was identified as the key functional module within the “employees” category.
However, the objective of this analysis was to select only one key e-HRM module, so e-recruitment and e-PM were also compared. e-recruitment focuses on recruiting new employees via online platforms and digital tools. Its main objective is to attract and address potential candidates, acquiring qualified and capable employees for specific organizations. This module ensures that the organization has a sufficient and suitable number of candidates to fill job positions. On the other hand, e-PM deals with monitoring and evaluating the performance of employees. This module allows managers and supervisors to monitor and assess employee performance, identify strengths and areas for improvement, and provide feedback and rewards for good performance. e-PM aims to increase employee performance and contributes to achieving the goals of individual organizations. From a procedural perspective, e-recruitment is the first step, ensuring the arrival of suitable candidates into the internal environment of organizations. e-PM follows successful e-recruitment and focuses on evaluating and improving the performance of these employees. It can be concluded that e-PM is dependent on successful e-recruitment, as without quality and qualified employees, there would be nothing to evaluate and manage within e-PM. This means that, from a procedural perspective, e-recruitment is more important, and thus, this functional module was identified as pivotal. However, it is necessary to emphasize that a procedural approach to e-HRM was taken into consideration.
To ensure the credibility and reliability of the GTM result, it was necessary to verify whether e-recruitment could be considered the key functional module of e-HRM. Therefore, the following validations were performed. Currently, there is only a small number of publications on individual e-HRM modules, making it impossible to directly compare e-recruitment and e-PM. However, these functional modules can be compared based on their HR processes, which are employee recruitment (in relation to e-recruitment) and performance management (in relation to e-PM). Comparing these two HR processes in terms of significance is possible based on the human resources cycle (Figure 5), described by Armstrong (2007).
From Armstrong’s perspective, it is evident that employee recruitment is an essential process for managing work performance because having available employees whose performance can be managed is necessary.

5.1. Initial Model

The initial model illustrates the general connection between IS/IT and a specific functional module of e-HRM, which is e-recruitment (Figure 6). It consists of two parts, a process part, and a technological part. The process part (depicted in yellow) concerns defining the procedures, steps, and activities necessary to achieve a specific goal or outcome. In this case, it involves the employee recruitment process. The process part establishes the structure and plan of how individual process components will collaborate to achieve the main objective. The technological part (depicted in blue) focuses on technological tools, systems, and resources that will be used to support and streamline the processes defined in the process part. The individual subsystems thus encompass software applications, hardware devices, automation tools, and other technological solutions.

5.2. Definition of Research Questions and Hypotheses

Based on the developed initial model (Figure 6), research questions were defined:
  • Q1: What modern IS/IT can be utilized in e-recruitment in relation to employee recruitment in the public sector?
  • Q2: How do modern IS/IT contribute to increasing the efficiency of the e-recruitment process within the smart government framework?
  • Q3: What impact does the integration of e-recruitment have on the overall efficiency of personnel management in intelligent government?
Subsequently, three specific research hypotheses were formulated:
  • H1: There are modern IS/IT that can be used in e-recruitment in connection with employee recruitment in the public sector.
  • H2: If modern IS/IT are implemented in e-recruitment in connection with employee recruitment in the public sector, the efficiency of this process will increase.
  • H3: If modern IS/IT are used in e-recruitment in connection with employee recruitment in the public sector, it will have a positive impact on other e-HRM processes.
Future research will focus on evaluating the utilization of modern IS/IT in the field of e-recruitment within the public sector. The subjects under investigation will be specific to modern IS/IT, and the object of study will be the application of these technologies within e-recruitment. The main objective will be to analyze how these technological tools contribute to improving recruitment processes and personnel management in the context of smart government.
Under H1, existing IS/IT suitable for e-recruitment in the public sector will be analyzed. The research will examine how these tools can effectively support the recruitment process, from creating job offers to assessing candidates. Their compatibility with the needs of public institutions will also be scrutinized. To achieve this, case studies of specific IS/IT in e-recruitment will be investigated.
In continuation of H2, the research will focus on assessing specific benefits that modern IS/IT can bring to the e-recruitment process in the context of smart government. The analysis will explore how these technological tools influence the efficiency of the employee recruitment process in public administration. In this case, effectiveness will be expressed through four indicators:
  • Cost reduction—This will measure the efficiency of e-recruitment via financial aspects. The reduction in costs will involve analyzing the budget allocated for hiring new employees before and after the implementation of modern IS/IT in e-recruitment processes. The more efficient the system, the greater the expected reduction in costs associated with recruitment, such as advertising expenses, fees for personnel agencies, administrative costs, and others;
  • Employee motivation enhancement—This aspect will examine the extent to which modern IS/IT in e-recruitment contribute to increasing employee motivation. The analysis will assess whether new technological tools simplify and improve recruitment processes, potentially leading to positive effects on employee satisfaction and motivation. Successful e-recruitment solutions supporting work culture and increasing employee engagement will be evaluated as well;
  • Reduction in employee turnover—This indicator will track how effectively e-recruitment solutions decrease employee turnover. Cases will be analyzed where high-quality e-recruitment processes contribute to a better selection of candidates who are well-suited to the work environment and organizational culture. Reducing turnover can lead to a lower number of employees leaving the organization, enhancing workforce stability;
  • Reduction in overall recruitment process time—This will be measured by the time difference between announcing a job vacancy and filling it. Efficient e-recruitment solutions should expedite the candidate selection processes, providing the organization with quicker access to the necessary human resources. This indicator will provide insights into how modern IS/IT contribute to faster and more efficient filling of job vacancies.
In connection with H3, the overall impact of integrating e-recruitment on personnel management in smart public administration will be examined. The analysis will encompass the efficiency of other e-HRM processes, employee retention, and other related factors. The goal is to identify how integrated e-recruitment solutions influence the overall dynamics and performance of personnel management in smart governance.
Various research methods will be employed, including content analysis, case studies, surveys, and interviews with experts, to gather detailed and relevant information to address the specified hypotheses.

6. Discussion

In the current era, it is extremely important to discuss three key aspects that shape the development of organizations, governments, public administration, non-profit organizations, and others. These determinants are people, technologies, and funds [107], which collectively create dynamics and shape the direction of organizations. Regarding these aspects, an increasing number of authors emphasize the importance of the synergistic interaction between people and technologies [108,109,110]. This integrated approach applies not only to the topic of human development but also to specific sectors, such as e-recruitment [111,112,113,114].
However, the literature dedicated to this topic often exhibits a limited perspective, where authors mostly superficially map the fundamental aspects of electronic recruitment. This lack of in-depth exploration raises concerns, and researchers repeatedly highlight the need to pay greater attention to this subject [115,116,117]. If the objective is to analyze the challenges associated with e-recruitment, it is essential to understand how these aspects—people, technologies, and funds—mutually interact and influence the effectiveness of electronic recruitment processes.
Some authors even emphasize the need for research on e-recruitment in the context of smart government [118,119,120]. Smart government represents a new direction in the transformation of public services, placing emphasis on the use of modern technologies and analytical tools to improve the efficiency and quality of the public sector [121,122,123]. Analyzing e-recruitment in connection with smart government opens the door to the utilization of intelligent technologies such as artificial intelligence, big data analytics, and automated systems, which can significantly enhance the entire employee recruitment process. These innovations may include advanced algorithms for candidate selection, personalized interactions with job applicants, and effective talent management.
The benefits associated with smart government in e-recruitment extend beyond technological aspects. Modern approaches to public administration, integral to this concept, can contribute to transparency, participation, and better coordination in recruitment processes [124,125]. Introducing these elements can lead to the creation of a more agile and adaptable environment capable of effectively responding to the dynamics of the labor market.
Therefore, examining the connection between e-recruitment and smart government is not only an opportunity to optimize specific recruitment procedures but also a chance to transform how public administration approaches human resources management in pursuit of higher efficiency and innovative solutions.

7. Conclusions

Considering the growing importance of the digitization and modernization of public services within smart government, this literature review provided a theoretical overview of knowledge on e-recruitment. The analysis of the smart government concept, representing an efficient model of public administration utilizing technological innovations, and electronic recruitment, a process focused on digital identification and acquisition of suitable candidates, provide an important context for discussion in this area.
This study specifically focuses on defining the key functional module of e-HRM, which is a crucial element in implementing e-recruitment within the smart government framework. The analysis of this area highlights the need for in-depth exploration in future research, which should delve into the impact of e-recruitment on the efficiency of human resources in the public service sector. The results of this study can serve as a foundation for further research aimed at optimizing and successfully utilizing e-recruitment within the specific framework of smart government.
However, several limitations need to be considered within this study. The first limitation is the subjective selection of specific sources based on the PRISMA methodology, where different authors may apply varying approaches in selecting information sources. This fact could impact the overall objectivity and scope of the acquired information. The second limitation involves the individual selection of parameters for defining the key e-HRM module. Different authors may use different parameters in defining this module, leading to different results and interpretations. This subjectivity in parameter selection should be considered when comparing results with other research projects in this field.
Possible future directions in the research of e-recruitment within smart government and e-HRM open opportunities should be to build on existing knowledge and develop new research targets. One potential direction could involve conducting multiple studies focusing on specific institutions within public administration. This approach could provide a deeper understanding of the specific needs, challenges, and benefits of implementing e-recruitment in individual public administration institutions. Comparing these studies could then offer a more comprehensive view of the effectiveness and success of e-recruitment in various administrative environments.
Similarly, it would be fitting to direct research in business environments, where the implementation of e-recruitment in specific organizations could be analyzed. This approach could yield comparable data on the impact and benefits of e-recruitment within the business sector. Comparative studies between the public and private sectors could subsequently help identify and analyze potential differences and similarities in the effectiveness of this process between these two distinct environments. Such an approach could contribute to a broader understanding of the impact of e-recruitment on human resources in different organizational contexts.

Author Contributions

Conceptualization, G.K., D.T. and P.B.; methodology, P.B.; software, P.B.; validation, G.K. and R.J.; formal analysis, D.T. and P.B.; investigation, P.B.; resources, P.B.; data curation, P.B.; writing—original draft preparation, P.B.; writing—review and editing, D.T.; visualization, P.B.; supervision, G.K. and R.J.; project administration, P.B.; funding acquisition, G.K. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Data Availability Statement

The original contributions presented in the study are included in the article/supplementary material, further inquiries can be directed to the corresponding author/s.

Acknowledgments

This paper has been written with the support of the Grant System of the University of Žilina no. 1/2023 (17712) and decision making in the recruitment process was carried out with the support of artificial intelligence.

Conflicts of Interest

The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results.

References

  1. Kubina, M.; Lendel, V. Successful Application of Social CRM in the Company. Procedia Econ. Financ. 2015, 23, 1190–1194. [Google Scholar] [CrossRef]
  2. Mičiak, M. The Efficiency of Investment in Human Capital in IT Enterprises; Elsevier: Amsterdam, The Netherlands, 2019; Volume 40, pp. 1134–1140. [Google Scholar]
  3. Holubčík, M.; Soviar, J. Main Problems of Cooperation Management: Insights from Slovak Companies. Sustainability 2021, 13, 6736. [Google Scholar] [CrossRef]
  4. Vodák, J.; Soviar, J.; Lendel, V. Cooperation Management in Slovak Enterprises. Procedia-Soc. Behav. Sci. 2014, 109, 1147–1151. [Google Scholar] [CrossRef]
  5. Wang, C. Refined Intelligent Manufacturing Enterprise Human Management Based on IoT and Machine Learning Technology. Int. J. Adv. Manuf. Technol. 2024. [Google Scholar] [CrossRef]
  6. Varmus, M.; Kubina, M.; Mičiak, M.; Boško, P.; Greguška, I. More Sustainable Sports Organizations’ Operation as a Result of Fan Involvement into the Processes of Decision-Making and Community Building. Entrep. Sustain. Issues 2023, 11, 10–38. [Google Scholar] [CrossRef] [PubMed]
  7. Bubelíny, O.; Kubina, M.; Varmus, M. Railway Stations as Part of Mobility in the Smart City Concept. Transp. Res. Procedia 2021, 53, 274–281. [Google Scholar] [CrossRef]
  8. Segec, P.; Paluch, P.; Papan, J.; Kubina, M. The Integration of WebRTC and SIP: Way of Enhancing Real-Time, Interactive Multimedia Communication. In Proceedings of the 12th IEEE International Conference on Emerging Elearning Technologies and Applications (ICETA 2014), Stary Smokovec, Slovakia, 4–5 December 2014; IEEE: New York, NY, USA, 2014; pp. 437–442. [Google Scholar]
  9. Pollak, F.; Dorcak, P.; Markovic, P.; Soviar, J. Innovative Approaches to the Reputation Management in the Tourism Sector. In Proceedings of the Innovation and Transformation in a Digital World (IDIMT-2019); Doucek, P., Chroust, G., Oskrdal, V., Eds.; Trauner Verlag: Linz, Austria, 2019; Volume 48, pp. 285–292. [Google Scholar]
  10. Ukeje, N.; Gutierrez, J.; Petrova, K. Information Security and Privacy Challenges of Cloud Computing for Government Adoption: A Systematic Review. Int. J. Inf. Secur. 2024, 1–17. [Google Scholar] [CrossRef]
  11. Alqaryouti, O.; Siyam, N.; Abdel Monem, A.; Shaalan, K. Aspect-Based Sentiment Analysis Using Smart Government Review Data. Appl. Comput. Inform. 2020, 20, 142–161. [Google Scholar] [CrossRef]
  12. Milić, P.; Veljković, N.; Stoimenov, L. Using OpenGovB Transparency Indicator to Evaluate National Open Government Data. Sustainability 2022, 14, 1407. [Google Scholar] [CrossRef]
  13. Štaffenová, N.; Kucharčíková, A. Digitalization in the Human Capital Management. Systems 2023, 11, 337. [Google Scholar] [CrossRef]
  14. Votto, A.M.; Valecha, R.; Najafirad, P.; Rao, H.R. Artificial Intelligence in Tactical Human Resource Management: A Systematic Literature Review. Int. J. Inf. Manag. Data Insights 2021, 1, 100047. [Google Scholar] [CrossRef]
  15. Radonjić, A.; Duarte, H.; Pereira, N. Artificial Intelligence and HRM: HR Managers’ Perspective on Decisiveness and Challenges. Eur. Manag. J. 2022. [Google Scholar] [CrossRef]
  16. Al-Ahmadi, H.H. Utilization of Big Data Analysis in HRM? Challenges and Future Directions. Int. J. Comput. Sci. Netw. Secur. 2020, 20, 36–40. [Google Scholar] [CrossRef]
  17. Küpper, D.M.; Klein, K.; Völckner, F. Gamifying Employer Branding: An Integrating Framework and Research Propositions for a New HRM Approach in the Digitized Economy. Hum. Resour. Manag. Rev. 2021, 31, 100686. [Google Scholar] [CrossRef]
  18. Chen, Z. Revolutionising HRM Practice with Blockchain Technology: Unleashing Disruptive Paradigms of Work and Overcoming Management Challenges. Technol. Anal. Strateg. Manag. 2023. [Google Scholar] [CrossRef]
  19. Ioakimidis, M. The Promise of Blockchain for HRM: A Transaction Cost Theoretical Perspective. Manag. J. Contemp. Manag. Issues 2023, 28, 43–55. [Google Scholar] [CrossRef]
  20. Shashyna, M.; Gudz, P.; Pankova, A.; Benchak, O.; Nemyrovska, O. Modernization of Public Administration in Eastern Europe in the Context of Implementation of Digitalization. East.-Eur. J. Enterp. Technol. 2023, 4, 57–65. [Google Scholar]
  21. Bieńkowska, A.; Tworek, K. Job Performance Model Based on Employees’ Dynamic Capabilities (EDC). Sustainability 2020, 12, 2250. [Google Scholar] [CrossRef]
  22. Hashiyana, V.; Ujakpa, M.M.; Suresh, N.; Mukaya, K.T.; Mukupi, B. E-Recruitment System: A Case of Namibian Government. In Proceedings of the 2021 IST-Africa Conference (IST-Africa), South Africa, South Africa, 10–14 May 2021; pp. 1–8. [Google Scholar]
  23. Alsultanny, Y.A. Activate Climate of Change to Motivate Users Toward Using Innovative Public E-Services. Int. J. Electron. Gov. Res. IJEGR 2018, 14, 44–56. [Google Scholar] [CrossRef]
  24. Page, M.J.; McKenzie, J.E.; Bossuyt, P.M.; Boutron, I.; Hoffmann, T.C.; Mulrow, C.D.; Shamseer, L.; Tetzlaff, J.M.; Akl, E.A.; Brennan, S.E.; et al. The PRISMA 2020 Statement: An Updated Guideline for Reporting Systematic Reviews. BMJ 2021, 372, n71. [Google Scholar] [CrossRef]
  25. Glaser, B.G. The Future of Grounded Theory. Qual. Health Res. 1999, 9, 836–845. [Google Scholar] [CrossRef]
  26. Švaříček, R.; Šeďová, K. Kvalitativní Výzkum v Pedagogických Vědách; Portál: Praha, Czech Republic, 2014; ISBN 978-80-262-0644-6. [Google Scholar]
  27. Chametzky, B. Coding in Classic Grounded Theory: I’ve Done an Interview; Now What? Sociol. Mind 2016, 6, 163–172. [Google Scholar] [CrossRef]
  28. Hull, S. Doing Grounded Theory; University of Cape Town: Cape Town, South Africa, 2013. [Google Scholar] [CrossRef]
  29. Abia, M. Pursuing Fit: A Grounded Theory of E-Recruitment in Namibia—An Integrated Jobseeker and Agency Perspective; OpenUCT: Nairobi, Kenya, 2020. [Google Scholar]
  30. Chen, Z. Ethics and Discrimination in Artificial Intelligence-Enabled Recruitment Practices. Humanit. Soc. Sci. Commun. 2023, 10, 567. [Google Scholar] [CrossRef]
  31. Abia, M.; Brown, I. Conceptualizations of E-Recruitment: A Literature Review and Analysis. In Proceedings of the Responsible Design, Implementation and Use of Information and Communication Technology; Hattingh, M., Matthee, M., Smuts, H., Pappas, I., Dwivedi, Y.K., Mäntymäki, M., Eds.; Springer International Publishing: Cham, Switzerland, 2020; pp. 370–379. [Google Scholar]
  32. Allal-Chérif, O.; Yela Aránega, A.; Castaño Sánchez, R. Intelligent Recruitment: How to Identify, Select, and Retain Talents from around the World Using Artificial Intelligence. Technol. Forecast. Soc. Chang. 2021, 169, 120822. [Google Scholar] [CrossRef]
  33. Mikalef, P.; Gupta, M. Artificial Intelligence Capability: Conceptualization, Measurement Calibration, and Empirical Study on Its Impact on Organizational Creativity and Firm Performance. Inf. Manag. 2021, 58, 103434. [Google Scholar] [CrossRef]
  34. Trocin, C.; Hovland, I.V.; Mikalef, P.; Dremel, C. How Artificial Intelligence Affords Digital Innovation: A Cross-Case Analysis of Scandinavian Companies. Technol. Forecast. Soc. Chang. 2021, 173, 121081. [Google Scholar] [CrossRef]
  35. Wolfswinkel, J.F.; Furtmueller, E.; Wilderom, C.P.M. Using Grounded Theory as a Method for Rigorously Reviewing Literature. Eur. J. Inf. Syst. 2013, 22, 45–55. [Google Scholar] [CrossRef]
  36. Chen, T.; Zhang, C.; Yang, J.; Cong, G. Grounded Theory-Based User Needs Mining and Its Impact on APP Downloads: Exampled With WeChat APP. Front. Psychol. 2022, 13, 875310. [Google Scholar] [CrossRef]
  37. Adamy, E.K.; Zocche, D.A.D.A.; Vendruscolo, C.; Santos, J.L.G.D.; Almeida, M.D.A. Validation in Grounded Theory: Conversation Circles as a Methodological Strategy. Rev. Bras. Enferm. 2018, 71, 3121–3126. [Google Scholar] [CrossRef]
  38. Escursell, S.; Llorach-Massana, P.; Roncero, M.B. Sustainability in E-Commerce Packaging: A Review. J. Clean. Prod. 2021, 280, 124314. [Google Scholar] [CrossRef]
  39. Joseph, R.C.; Ezzedeen, S.R. E-Government and E-HRM in the Public Sector. In Encyclopedia of Human Resources Information Systems: Challenges in e-HRM; IGI Global: Hershey, PA, USA, 2009; pp. 272–277. ISBN 978-1-59904-883-3. [Google Scholar]
  40. Jiménez, C.E.; Solanas, A.; Falcone, F. E-Government Interoperability: Linking Open and Smart Government. Computer 2014, 47, 22–24. [Google Scholar] [CrossRef]
  41. Bernardo, M.d.R.M. Smart City Governance: From E-Government to Smart Governance. In Smart Cities and Smart Spaces: Concepts, Methodologies, Tools, and Applications; IGI Global: Hershey, PA, USA, 2019; pp. 196–232. ISBN 978-1-5225-7030-1. [Google Scholar]
  42. Harsh, A.; Ichalkaranje, N. Transforming E-Government to Smart Government: A South Australian Perspective. In Proceedings of the Intelligent Computing, Communication and Devices; Jain, L.C., Patnaik, S., Ichalkaranje, N., Eds.; Springer: New Delhi, India, 2015; pp. 9–16. [Google Scholar]
  43. Lemke, F.; Taveter, K.; Erlenheim, R.; Pappel, I.; Draheim, D.; Janssen, M. Stage Models for Moving from E-Government to Smart Government. In Proceedings of the Electronic Governance and Open Society: Challenges in Eurasia; Chugunov, A., Khodachek, I., Misnikov, Y., Trutnev, D., Eds.; Springer International Publishing: Cham, Switzerland, 2020; pp. 152–164. [Google Scholar]
  44. Glybovets, A.; Mohammad, A. E-government versus smart government: Jordan versus the united states. EUREKA Soc. Humanit. 2017, 3, 3–11. [Google Scholar] [CrossRef]
  45. Ruël, H.; Bondarouk, T.; Looise, J.K. E-HRM: Innovation or Irritation. An Explorative Empirical Study in Five Large Companies on Web-Based HRM. Manag. Rev. 2004, 15, 364–380. [Google Scholar] [CrossRef]
  46. Hujran, O.; Alarabiat, A.; Al-Adwan, A.S.; Al-Debei, M. Digitally Transforming Electronic Governments into Smart Governments: SMARTGOV, an Extended Maturity Model. Inf. Dev. 2021, 39, 811–834. [Google Scholar] [CrossRef]
  47. Kankanhalli, A.; Charalabidis, Y.; Mellouli, S. IoT and AI for Smart Government: A Research Agenda. Gov. Inf. Q. 2019, 36, 304–309. [Google Scholar] [CrossRef]
  48. Al-Obthani, F.; Ameen, A. Toward Proposing SMART-Government Maturity Model: Best Practices, International Standards, and Six-Sigma Approach; Lincoln University College: Petaling Jaya, Malaysia, 2017. [Google Scholar]
  49. Decastri, M.; Gagliarducci, F.; Previtali, P.; Scarozza, D. Understanding the Use of Smart Working in Public Administration: The Experience of the Presidency of the Council of Ministers. In Proceedings of the Exploring Digital Ecosystems; Lazazzara, A., Ricciardi, F., Za, S., Eds.; Springer International Publishing: Cham, Switzerland, 2020; pp. 343–363. [Google Scholar]
  50. Angelici, M.; Profeta, P. Smart Working: Work Flexibility Without Constraints. Manag. Sci. 2023. [Google Scholar] [CrossRef]
  51. Ilhami, R.; Marlovia, E.; Achmad, W. Smart Government Policy Implementation for Smart City Concept Realization. Int. J. Health Sci. 2022, 6, 8379–8389. [Google Scholar] [CrossRef]
  52. Martin, G.; Cerdin, J.L. Employer Branding and Career Theory: New Directions for Research; Sparrow, P., Scullion, H., Tarique, I., Eds.; Cambridge University Press: Cambridge, UK, 2014; pp. 151–176. ISBN 978-1-107-03210-1. [Google Scholar]
  53. Gil-Garcia, J.R.; Zhang, J.; Puron-Cid, G. Conceptualizing Smartness in Government: An Integrative and Multi-Dimensional View. Gov. Inf. Q. 2016, 33, 524–534. [Google Scholar] [CrossRef]
  54. Umair, M.; Cheema, M.A.; Cheema, O.; Li, H.; Lu, H. Impact of COVID-19 on IoT Adoption in Healthcare, Smart Homes, Smart Buildings, Smart Cities, Transportation and Industrial IoT. Sensors 2021, 21, 3838. [Google Scholar] [CrossRef] [PubMed]
  55. Andari, R.N.; Ella, S. Digital Talent Management Model for Smart Village in Indonesia. In Proceedings of the 2021 2nd International Conference on ICT for Rural Development (IC-ICTRuDev), Jogjakarta, Indonesia, 27–28 October 2021; pp. 1–6. [Google Scholar]
  56. Guenduez, A.A.; Singler, S.; Tomczak, T.; Schedler, K.; Oberli, M. Smart Government Success Factors. Jahrb. Schweiz. Verwalt. 2018, 9, 96–110. [Google Scholar] [CrossRef]
  57. Sima, V.; Gheorghe, I.G.; Subić, J.; Nancu, D. Influences of the Industry 4.0 Revolution on the Human Capital Development and Consumer Behavior: A Systematic Review. Sustainability 2020, 12, 4035. [Google Scholar] [CrossRef]
  58. Vrontis, D.; Christofi, M.; Pereira, V.; Tarba, S.; Makrides, A.; Trichina, E. Artificial Intelligence, Robotics, Advanced Technologies and Human Resource Management: A Systematic Review. Int. J. Hum. Resour. Manag. 2022, 33, 1237–1266. [Google Scholar] [CrossRef]
  59. Marler, J.H.; Fisher, S.L. An Evidence-Based Review of e-HRM and Strategic Human Resource Management. Hum. Resour. Manag. Rev. 2013, 23, 18–36. [Google Scholar] [CrossRef]
  60. Nenwani, P.J.; Raj, M. E-HRM Prospective in Present Scenario. Int. J. Adv. Res. Comput. Sci. Manag. Stud. 2013, 1, 422–428. [Google Scholar]
  61. Nivlouei, F.B. Electronic Human Resource Management System: The Main Element in Capacitating Globalization Paradigm. Int. J. Bus. Soc. Sci. 2014, 5, 147–159. [Google Scholar]
  62. Thite, M. E-HRM: Digital Approaches, Directions & Applications, 1st ed.; Routledge: London, UK; Taylor & Francis Group: New York, NY, USA, 2019; ISBN 978-1-351-69871-9. [Google Scholar]
  63. Mayrhofer, W. Between Market, Bureaucracy and Clan: Coordination and Control Mechanisms in the Cranfield Network on European Human Resource Management (Cranet-E). J. Manag. Psychol. 1998, 13, 241–258. [Google Scholar] [CrossRef]
  64. Strohmeier, S. Research in E-HRM: Review and Implications. Hum. Resour. Manag. Rev. 2007, 17, 19–37. [Google Scholar] [CrossRef]
  65. Kaur, P. E-HRM: A boon or bane. Anveshanam A Natl. J. Manag. 2013, 1, 35–38. [Google Scholar]
  66. Fındıklı, M.; Rofcanin, Y. The Concept of E-HRM, Its Evolution and Effects on Organizational Outcomes. In Technological Challenges and Management: Matching Human and Business Needs; CRC Press: Boca Raton, FL, USA, 2016; pp. 35–50. ISBN 978-0-429-09115-5. [Google Scholar]
  67. Hosseini, S.A.; Nematollahi, K. Electronic Human Resources Management and the Effectiveness of Human Resources Management. Eur. Online J. Nat. Soc. Sci. 2013, 2, 1812–1819. [Google Scholar]
  68. Martínez-López, F.J. Handbook of Strategic E-Business Management; Springer: Berlin/Heidelberg, Germany, 2014; ISBN 978-3-662-52479-4. [Google Scholar]
  69. Budhwar, P.S.; Varma, A.; Patel, C. Convergence-Divergence of HRM in the Asia-Pacific: Context-Specific Analysis and Future Research Agenda. Hum. Resour. Manag. Rev. 2016, 26, 311–326. [Google Scholar] [CrossRef]
  70. Kaufman, B.E. Globalization and Convergence–Divergence of HRM across Nations: New Measures, Explanatory Theory, and Non-Standard Predictions from Bringing in Economics. Hum. Resour. Manag. Rev. 2016, 26, 338–351. [Google Scholar] [CrossRef]
  71. Papadionysiou, E.; Myloni, B. Socio-Cultural Dimensions, Employee-Related Assumptions and HRM Practices-a Multivariate Model in a Cross-National Setting. Cogent Bus. Manag. 2023, 10, 2197157. [Google Scholar] [CrossRef]
  72. Rodríguez-Sánchez, J.-L.; Montero-Navarro, A.; Gallego-Losada, R. The Opportunity Presented by Technological Innovation to Attract Valuable Human Resources. Sustainability 2019, 11, 5785. [Google Scholar] [CrossRef]
  73. Foster, S. Making Sense of E-HRM: Technological Frames, Value Creation and Competitive Advantage; Dizertačná Práca, University of Hertfordshire: Hertfordshire, UK, 2009. [Google Scholar]
  74. Fontanillas, T.R.; Romero Carbonell, M.; Guitert Catasús, M. E-Assessment Process: Giving a Voice to Online Learners. Int. J. Educ. Technol. High. Educ. 2016, 13, 20. [Google Scholar] [CrossRef]
  75. Kroell, M. E-Assessment: A Suitable Alternative for Measuring Competences? In Proceedings of the Human-Computer Interaction, PT IV; Jacko, J.A., Ed.; Springer: Berlin/Heidelberg, Germany, 2009; Volume 5613, pp. 543–550. [Google Scholar]
  76. Buzzetto-More, N.A.; Alade, A.J. Best Practices in E-Assessment. J. Inf. Technol. Educ. Res. 2006, 5, 251–269. [Google Scholar] [CrossRef] [PubMed]
  77. Laumer, S.; von Stetten, A.; Eckhardt, A. E-Assessment. Bus. Inf. Syst. Eng. 2009, 1, 263–265. [Google Scholar] [CrossRef]
  78. Kanaslan, E.K.; Iyem, C. Is 360 Degree Feedback Appraisal an Effective Way of Performance Evaluation? Int. J. Acad. Res. Bus. Soc. Sci. 2016, 6, 172–182. [Google Scholar] [CrossRef] [PubMed]
  79. Khan, R.A.; Jawaid, M. Technology Enhanced Assessment (TEA) in COVID 19 Pandemic. Pak. J. Med. Sci. 2020, 36, S108–S110. [Google Scholar] [CrossRef]
  80. Khan, B. Managing E-Learning Strategies: Design, Delivery, Implementation and Evaluation; Information Science Publishing: New York, NY, USA, 2005; ISBN 978-1-59140-634-1. [Google Scholar]
  81. Derouin, R.E.; Fritzsche, B.A.; Salas, E. E-Learning in Organizations. J. Manag. 2005, 31, 920–940. [Google Scholar] [CrossRef]
  82. Tornero, R.; Torrente, J.; Moreno-Ger, P.; Manjón, B.F. E-Training DS: An Authoring Tool for Integrating Portable Computer Science Games in e-Learning. In Proceedings of the Advances in Web-Based Learnin—ICWL 2010; Luo, X., Spaniol, M., Wang, L., Li, Q., Nejdl, W., Zhang, W., Eds.; Springer: Berlin/Heidelberg, Germany, 2010; pp. 259–268. [Google Scholar]
  83. Nof, S.Y.; Ceroni, J.; Jeong, W.; Moghaddam, M. E-Learning and e-Training. In Revolutionizing Collaboration through e-Work, e-Business, and e-Service; Nof, S.Y., Ceroni, J., Jeong, W., Moghaddam, M., Eds.; Automation, Collaboration, & E-Services; Springer: Berlin/Heidelberg, Germany, 2015; pp. 357–390. ISBN 978-3-662-45777-1. [Google Scholar]
  84. Nicholson, P. E-Training or E-Learning? In Proceedings of the E-Training Practices for Professional Organizations; Nicholson, P., Ruohonen, M., Thompson, J.B., Multisilta, J., Eds.; Springer: Boston, MA, USA, 2005; pp. 19–27. [Google Scholar]
  85. Mika, F. E-Personalistika—Léta Dozrávání. Available online: https://hn.cz/c1-13360050-e-personalistika-leta-dozravani (accessed on 25 July 2023).
  86. Koppikar, U.; Hiremath, S.; Shiralkar, A.; Rajoor, A.; Baligar, V.P. IoT Based Smart Attendance Monitoring System Using RFID. In Proceedings of the 2019 1st International Conference on Advances in Information Technology (ICAIT), Chikmagalur, India, 25–27 July 2019; pp. 193–197. [Google Scholar]
  87. Sanath, K.; K, M.; Rajan, M.; Balamurugan, V.; Harikumar, M.E. RFID and Face Recognition Based Smart Attendance System. In Proceedings of the 2021 5th International Conference on Computing Methodologies and Communication (ICCMC), Erode, India, 8–10 April 2021; pp. 492–499. [Google Scholar]
  88. Wati, V.; Kusrini, K.; Al Fatta, H.; Kapoor, N. Security of Facial Biometric Authentication for Attendance System. Multimed. Tools Appl. 2021, 80, 23625–23646. [Google Scholar] [CrossRef]
  89. Nagothu, S.K.; Kumar, O.P.; Anitha, G. GPS Aided Autonomous Monitoring and Attendance System. Procedia Comput. Sci. 2016, 87, 99–104. [Google Scholar] [CrossRef]
  90. Reddington, M.; Graeme, M.; Heather, A. Technology, Outsourcing & Transforming HR; Routledge: Oxford, UK, 2008; ISBN 978-0-7506-8645-7. [Google Scholar]
  91. Benson, A.D.; Johnson, S.D.; Kuchinke, K.P. The Use of Technology in the Digital Workplace: A Framework for Human Resource Development. Adv. Dev. Hum. Resour. 2002, 4, 392–404. [Google Scholar] [CrossRef]
  92. Sharma, A.; Sharma, T. HR Analytics and Performance Appraisal System: A Conceptual Framework for Employee Performance Improvement. Manag. Res. Rev. 2017, 40, 684–697. [Google Scholar] [CrossRef]
  93. Dulebohn, J.H.; Marler, J.H. E-Compensation: The Potential to Transform Practice. In The Brave New World of e HR: Human Resource Mangement in the Digital Age; John Wiley & Sons, Inc.: San Francisco, CA, USA, 2005; p. 352. ISBN 978-0-7879-7338-4. [Google Scholar]
  94. Berger, L.; Berger, D. The Compensation Handbook, Sixth Edition: A State-of-the-Art Guide to Compensation Strategy and Design; McGraw Hill: New York, NY, USA, 2015; ISBN 978-0-07-183699-9. [Google Scholar]
  95. Hittmár, Š.; Lendel, V.; Kubina, M. Podnikové Informačné Systémy; EDIS—Vydavatel’stvo ŽU: Žilina, Slovakia, 2013; ISBN 978-80-554-0712-8. [Google Scholar]
  96. Fachrizal, M.R.; Radliya, N.R.; Manik, A. Development of E-Recruitment as a Decision Support System for Employee Recruitment. IOP Conf. Ser. Mater. Sci. Eng. 2019, 662, 022018. [Google Scholar] [CrossRef]
  97. Faliagka, E.; Tsakalidis, A.; Tzimas, G. An Integrated E-recruitment System for Automated Personality Mining and Applicant Ranking. Internet Res. 2012, 22, 551–568. [Google Scholar] [CrossRef]
  98. Chiwara, J.R.; Mjoli, T.Q.; Chinyamurindi, W.T. Factors That Influence the Use of the Internet for Job-Seeking Purposes amongst a Sample of Final-Year Students in the Eastern Cape Province of South Africa. SA J. Hum. Resour. Manag. 2017, 15, 1–9. [Google Scholar] [CrossRef]
  99. Llorens, J.J. A Model of Public Sector E-Recruitment Adoption in a Time of Hyper Technological Change. Rev. Public Pers. Adm. 2011, 31, 410–423. [Google Scholar] [CrossRef]
  100. Wang, B.; Guo, X. Online Recruitment Information as an Indicator to Appraise Enterprise Performance. Online Inf. Rev. 2012, 36, 903–918. [Google Scholar] [CrossRef]
  101. Bartram, D. Internet Recruitment and Selection: Kissing Frogs to Find Princes. Int. J. Sel. Assess. 2000, 8, 261–274. [Google Scholar] [CrossRef]
  102. Lee, I. An Architecture for a Next-Generation Holistic e-Recruiting System. Commun. ACM 2007, 50, 81–85. [Google Scholar] [CrossRef]
  103. Walker, H.J.; Feild, H.S.; Giles, W.F.; Bernerth, J.B.; Short, J.C. So What Do You Think of the Organization? A Contextual Priming Explanation for Recruitment Web Site Characteristics as Antecedents of Job Seekers’ Organizational Image Perceptions. Organ. Behav. Hum. Decis. Process. 2011, 114, 165–178. [Google Scholar] [CrossRef]
  104. Kulkarni, S.; Che, X. Intelligent Software Tools for Recruiting. J. Int. Technol. Inf. Manag. 2019, 28, 2–16. [Google Scholar] [CrossRef]
  105. Black, J.S.; van Esch, P. AI-Enabled Recruiting: What Is It and How Should a Manager Use It? Bus. Horiz. 2020, 63, 215–226. [Google Scholar] [CrossRef]
  106. Armstrong, M. Řízení Lidských Zdrojů: Nejnovější Trendy a Postupy; Grada: Praha, Czech Republic, 2007; ISBN 978-80-247-1407-3. [Google Scholar]
  107. Ferenc, P.; Varmus, M.; Vodák, J. Stakeholders in the Various Field and Relations between Them. Procedia Eng. 2017, 192, 166–170. [Google Scholar] [CrossRef]
  108. Holubcik, M.; Soviar, J.; Lendel, V. Sustainable Cooperation Management—Insights from a Selected Company*. Entrep. Sustain. ISSUES 2022, 10, 429–447. [Google Scholar] [CrossRef]
  109. Tschandl, P.; Rinner, C.; Apalla, Z.; Argenziano, G.; Codella, N.; Halpern, A.; Janda, M.; Lallas, A.; Longo, C.; Malvehy, J.; et al. Human–Computer Collaboration for Skin Cancer Recognition. Nat. Med. 2020, 26, 1229–1234. [Google Scholar] [CrossRef]
  110. Бeляeвa, И.Г. Dialog, Communication, Cooperation, and Collaboration: Facets of Human-Computer Interaction. Technol. Lang. Texнoлoгии B Инфocфepe 2021, 2, 181–197. [Google Scholar]
  111. Aljuaid, A. AI Based E-Recruitment System. Ph.D. Thesis, Brunel University, London, UK, 2021. Available online: http://bura.brunel.ac.uk/handle/2438/24663 (accessed on 25 July 2023).
  112. Freire, M.N.; de Castro, L.N. E-Recruitment Recommender Systems: A Systematic Review. Knowl. Inf. Syst. 2021, 63, 1–20. [Google Scholar] [CrossRef]
  113. Kučerov, D.; Tsybova, V. The Contribution of E-Recruitment Practices to e-Recruitment Outcomes in Russian Companies. Meas. Bus. Excell. 2021, 26, 366–377. [Google Scholar] [CrossRef]
  114. Rahman, M.; Aydin, E.; Haffar, M.; Nwagbara, U. The Role of Social Media in E-Recruitment Process: Empirical Evidence from Developing Countries in Social Network Theory. J. Enterp. Inf. Manag. 2020, 35, 1697–1718. [Google Scholar] [CrossRef]
  115. Hosain, S.; Manzurul Arefin, A.H.M.; Hossin, M.A. E-Recruitment: A Social Media Perspective. Asian J. Econ. Bus. Account. 2020, 16, 51–62. [Google Scholar] [CrossRef]
  116. Alamro, S.; Dogan, H.; Cetinkaya, D.; Jiang, N.; Phalp, K. Conceptualising and Modelling E-Recruitment Process for Enterprises through a Problem Oriented Approach. Information 2018, 9, 269. [Google Scholar] [CrossRef]
  117. Brahmana, R.K.; Brahmana, R. What Factors Drive Job Seekers Attitude in Using E-Recruitment? South East Asian J. Manag. 2013, 7, 39–50. [Google Scholar] [CrossRef]
  118. Selden, S.; Orenstein, J. Government E-Recruiting Web Sites: The Influence of e-Recruitment Content and Usability on Recruiting and Hiring Outcomes in US State Governments. Int. J. Sel. Assess. 2011, 19, 31–40. [Google Scholar] [CrossRef]
  119. Musaa, N.; Junaini, S.N.; Bujang, Y.R. Improving Usability of E-Recruitment Website: A Preliminary Study on Sarawak Government Website; Association for Information Systems: Atlanta, GA, USA, 2006. [Google Scholar]
  120. Kim, S.; O’Connor, J.G. Assessing Electronic Recruitment Implementation in State Governments: Issues and Challenges. Public Pers. Manag. 2009, 38, 47–66. [Google Scholar] [CrossRef]
  121. Almuraqab, N.A.S.; Jasimuddin, S.M.; Mansoor, W. An Empirical Study of Perception of the End-User on the Acceptance of Smart Government Service in the UAE. J. Glob. Inf. Manag. JGIM 2021, 29, 1–29. [Google Scholar] [CrossRef]
  122. Löfgren, K.; Webster, C.W.R. The Value of Big Data in Government: The Case of ‘Smart Cities’. Big Data Soc. 2020, 7, 2053951720912775. [Google Scholar] [CrossRef]
  123. Shaban, A.I.; Farhan, M.A.; Ahmed, S.R. Building a Smart System for Preservation of Government Records in Digital Form. In Proceedings of the 2022 International Congress on Human-Computer Interaction, Optimization and Robotic Applications (HORA), Ankara, Turkey, 9–11 June 2022; pp. 1–6. [Google Scholar]
  124. Kim, S.; Andersen, K.N.; Lee, J. Platform Government in the Era of Smart Technology. Public Adm. Rev. 2022, 82, 362–368. [Google Scholar] [CrossRef]
  125. Wu, W.; Wu, Y.J.; Wang, H. Perceived City Smartness Level and Technical Information Transparency: The Acceptance Intention of Health Information Technology during a Lockdown. Comput. Hum. Behav. 2021, 122, 106840. [Google Scholar] [CrossRef]
Figure 1. Processing model of secondary sources according to the PRISMA methodology. Source: own elaboration.
Figure 1. Processing model of secondary sources according to the PRISMA methodology. Source: own elaboration.
Systems 12 00071 g001
Figure 2. GTM scheme. Source: own elaboration.
Figure 2. GTM scheme. Source: own elaboration.
Systems 12 00071 g002
Figure 3. Model of e-HRM technological structure. Source: created according to [73].
Figure 3. Model of e-HRM technological structure. Source: created according to [73].
Systems 12 00071 g003
Figure 4. Concepts focused on individual functional modules of e-HRM. Source: own elaboration.
Figure 4. Concepts focused on individual functional modules of e-HRM. Source: own elaboration.
Systems 12 00071 g004
Figure 5. Human resources cycle. Source: created according to [106].
Figure 5. Human resources cycle. Source: created according to [106].
Systems 12 00071 g005
Figure 6. Initial model of the IS/IT and e-recruitment connection. Source: created according to [106].
Figure 6. Initial model of the IS/IT and e-recruitment connection. Source: created according to [106].
Systems 12 00071 g006
Table 1. Overview of keywords and their modifications.
Table 1. Overview of keywords and their modifications.
Main KeywordsSearched Keyword Modifications
smart governmente-government
electronic human resources managemente-HRM
digital HR management
technology-enabled HRM
Source: own elaboration.
Table 2. Overview of sources used during the indicative analysis.
Table 2. Overview of sources used during the indicative analysis.
AuthorYearTitleFocus within e-HRM
Huub Ruël; Tanya Bondarouk; Jan Kees Looise2004e-HRM: Innovation or Irritation. An Explorative Empirical Study in Five Large Companies on Web-based HRMinnovation, empirical study
Stefan Strohmeier2007Research in e-HRM: Review and Implicationsimplications
Steve Foster2009Making Sense of e-HRM: Technological Frames, Value Creation and Competitive Advantagetechnological frames, value, competitive advantage
Emma Parry; Shaun Tyson2011Desired goals and actual outcomes of e-HRM: e-HRM goals and outcomesgoals and outcomes
Janet H. Marler; Sandra L. Fisher2013An evidence-based review of e-HRM and strategic human resource managementstrategic human resource management
Parveen Kaur2013e-HRM: A BOON OR BANEadvantages, disadvantages
Pinkiben J. Nenwani; M. Raj2013e-HRM Prospective in Present Scenariocurrent use, benefits
Seyyed Abdorasoul Hosseini; Khalil Nematollahi2013Electronic Human Resources Management and the Effectiveness of Human Resources Managementeffectiveness
Fahimeh Babaei Nivlouei2014Electronic Human Resource Management System: The Main Element in Capacitating Globalization Paradigmglobalization
H.J.M. Ruël; Tanya Bondarouk2014e-HRM Research and Practice: Facing the Challenges Aheadchallenges, future
Mine Fındıklı; Ebru Bayarcelik2015Exploring the Outcomes of Electronic Human Resource Management (e-HRM)?outcomes
Mine Fındıklı; Yasin Rofcanin2016The concept of e-HRM, its evolution and effects on organizational outcomesevolution, effects
Mohan Thite2019e-HRM: digital approaches, directions and applicationsdirections, applications
Hale Alan2023A Systematic Bibliometric Analysis on the Current Digital Human Resources Management Studies and Directions for Future Researchdirections for future research
Source: own elaboration.
Table 3. Overview of resources focused on smart government.
Table 3. Overview of resources focused on smart government.
AuthorYearArticle FocusUtilization in Literature Review
Martin, G.2014employer branding, talent management, career managementimpact of HR on the success of smart government
Gil-Garcia, J.R.2016smart government, smartness, smart cityidentification of HR as the key component of smart government
Al-Obthani, F. et al.2017smart government, maturity, qualityexplanation of the SMART acronym in the context of smart government
Guenduez, A.A.2018smart government, IS/IT, digitalizationimportance of HR, and specifically recruitment, in smart government
Kankanhalli, A. et al.2019smart government, modern technologies, technological innovationstechnological support for smart government
Decastri, M.2020smart government, smart work, HRlinking smart government to smart work
Umair, M., et al.2021smart homes, smart cities, IoTimportance of investments in the context of smart government
Andari, R. N. and Ella, S.2021smart village, HR, employee developmentimportance of employee development in the context of smart government
Hujran, O. et al.2021smart government, digital transformation, intelligent governmenttechnological support for smart government
Ilhami, R., et al.2022smart government, smart city,
e-government
definition of smart government
Angelici, M. and Profeta, P.2023smart work, work–life balancedefinition of smart work
Source: own elaboration.
Table 4. Overview of sources focused on e-HRM.
Table 4. Overview of sources focused on e-HRM.
AuthorYearArticle FocusUtilization in Literature Review
Mayrhofer, W.1998HRM, market approach, bureaucratic approach, clan approachdefining strategic e-HRM approaches
Ruël, H. et al.2004e-HRM, connecting IS/IT and HRMdefining e-HRM
Strohmeier, S.2007e-HRM, HRM approaches, HRM objectivesdefining e-HRM objectives
Foster, S.2009e-HRM, modern trends in e-HRMdefinition of the e-HRM technology structure model
Nenwani, P.J. and Raj, M.2013impact of IS/IT on HRM, technological innovations, application of e-HRMcomparison of HRIS and e-HRM
Kaur, P.2013technological innovation, digitalization, HRIS, IS/ITdefining the objectives and benefits of e-HRM
Marler, J.H. and Fisher, S.L.2013e-HRM, strategic HRM, evidence-Based Managementthe importance of using technological innovation in e-HRM
Hosseini, S.A. and Nematollahi, K.2013HRM, e-HRM, e-HRM componentsdefining the levels of e-HRM
Martínez-López, F.J.2014e-business, e-HRM, trendsdefining the stages of e-HRM
Nivlouei, F.B.2014e-HRM, globalizationthe importance of e-HRM in organizations
Budhwar, P.S. et al.2016HRM, convergence, divergenceexplanation of the concepts of convergence and divergence in relation to e-HRM
Kaufman, B.E.2016HRM, convergence, divergenceexplanation of the concepts of convergence and divergence in relation to e-HRM
Fındıklı, M. and Rofcanin, Y.2016HRM, e-HRM, technological innovation, IS/ITdefining the levels of e-HRM
Thite, M.2019e-HRM, technological innovationthe impact of IS/IT on e-HRM
Rodríguez-Sánchez, J.-L. et al.2019HRM, technological innovations, e-recruitmentdescription of the technological structure of e-HRM
Sima, V. et al.2020Industry 4.0, human capital, digital transformationthe impact of digitization on e-HRM
Vrontis, D. et al.2022automation, e-HRM, technological innovationthe importance of using technological innovation in e-HRM
Papadionysiou, E. and Myloni, B.2023HRM, socio-cultural dimensionsExplanation of the technological and institutional requirements for e-HRM
Source: own elaboration.
Table 5. Overview of sources focused on functional modules e-HRM.
Table 5. Overview of sources focused on functional modules e-HRM.
AuthorYearArticle FocusUtilization in Literature Review
Bartram, D.2000e-recruitment, the impact of technology on recruitmentdefining e-recruitment as a medium
Benson, A.D., et al.2002HRM, technological innovationdefining e-performance management
Mika, F.2003e-HRM, e-recruitment, e-learning, e-benefits, e-assessment, e-attendancedefining e-attendance,
defining e-benefits
Dulebohn, J.H. and Marler, J.H.2005HRM, e-HRM, IS/IT, HRISdefining e-compensation
Khan, B.2005e-learning, e-HRMdefining e-learning
Derouin, R.E., et al.2005e-learningidentification of e-learning principles
Nicholson, P.2005e-training, cognitive and social aspects of learningdefining e-training
Buzzetto-More, N.A. and Alade, A.J.2006e-assessment, e-learning, assessment data managementdefining e-assessment in connection with e-recruitment
Lee, I.2007e-recruitment, IS/IT, technological innovationdefining e-recruitment as a program
Reddington, M., et al.2008IS/IT, HRM, e-performance managementdefining e-performance management
Kroell, M2009e-assessment, self-organizationdistribution of perceptions of e-assessment
Laumer, S. et al.2009e-assessment, e-recruitment, e-businessdefining e-assessment in connection with e-recruitment
Tornero, R., et al.2010e-training, e-learning, gamificationconnecting e-learning and e-training
Walker, H.J., et al.2011organizational image, recruitment, web sitesdefining e-recruitment as a proxy
Llorens, J.J.2011e-recruitment, technological innovationdefining e-recruitment as a process
Wang, B. and Guo, X.2012e-recruitment, NLP, AI, e-HRMdefining e-recruitment as a repository
Faliagka, E., et al.2012e-recruitment, automatizationdefining e-recruitment as a technological tool
Hittmár, Š. et al.2013HRM, HRIS, HRdefining e-reporting
Berger, L.; Berger, D.2015compensation in HR, HRM, IS/ITdefining e-compensation
Nof, S.Y., et al.2015automation in education, IS/IT, e-training, e-learningconnecting e-learning and e-training
Kanaslan, E.K. and Iyem, C.2016360-degree feedback, e-assessmentdefining e-assessment in connection with e-performance management
Romeu Fontanillas, T. et al.2016industry 4.0, HRM, e-HRM functional modulesdefining e-assessment
Nagothu, S.K., et al.2016GPS, GPRS, employee monitoring, attendancean example of a trend in e-attendance
Chiwara, J.R., et al.2017technological innovation, e-recruitmentdefining e-recruitment as a system
Sharma, A. and Sharma, T.2017HR Analytics, employee performancedefining e-performance management
Thite, M.2019e-HRM, technological innovationimpact of IS/IT on e-HRM, definition of e-HRM functional modules
Koppikar, U., et al.2019RFID, IoT, technological innovation, trendsan example of a trend in e-attendance
Fachrizal, M.R. et al.2019e-recruitment, profile matching, HRMdefining e-recruitment
Rodríguez-Sánchez, J.-L., et al.2019HRM, technological innovation, e-recruitmentdefining e-recruitment
Kulkarni, S. and Che, X.2019e-recruitment, technological innovationapplication of e-recruitment
Khan, R.A. and Jawaid, M2020online learning, assessment methods, e-assessmentdefining TEA systems
Abia, M. and Brown, I.2020e-recruitment, conceptualization, Grounded Theory Methodidentification of five e-recruitment concepts
Black, J.S. and van Esch, P.2020AI-enabled recruiting, AI, e-recruitment, HRMbenefits of e-recruitment
Sanath, K., et al.2021RFID, face recognition, technological innovationan example of a trend in e-attendance
Wati, V., et al.2021face recognition, biometrics, attendance recordsan example of a trend in e-attendance
Source: own elaboration.
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Koman, G.; Toman, D.; Jankal, R.; Boršoš, P. The Importance of e-Recruitment within a Smart Government Framework. Systems 2024, 12, 71. https://doi.org/10.3390/systems12030071

AMA Style

Koman G, Toman D, Jankal R, Boršoš P. The Importance of e-Recruitment within a Smart Government Framework. Systems. 2024; 12(3):71. https://doi.org/10.3390/systems12030071

Chicago/Turabian Style

Koman, Gabriel, Dominika Toman, Radoslav Jankal, and Patrik Boršoš. 2024. "The Importance of e-Recruitment within a Smart Government Framework" Systems 12, no. 3: 71. https://doi.org/10.3390/systems12030071

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop