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Article

Assessing the Role of HRM and HRD in Enhancing Sustainable Job Performance and Innovative Work Behaviors through Digital Transformation in ICT Companies

by
Yuanyuan Lou
1,
Ahreum Hong
2,* and
Yannan Li
2
1
The Graduate School of Ewha Womans University, Ewha Womans University, 52 Seodaemun-gu, Seoul 03760, Republic of Korea
2
Graduate School of Technology Management, Kyung Hee University, Yongin 17104, Republic of Korea
*
Author to whom correspondence should be addressed.
Sustainability 2024, 16(12), 5162; https://doi.org/10.3390/su16125162
Submission received: 9 May 2024 / Revised: 12 June 2024 / Accepted: 13 June 2024 / Published: 17 June 2024
(This article belongs to the Special Issue Digital Transformation and Innovation for a Sustainable Future)
Browse Figure
Versions Notes

Abstract

:
In the era of Industry 4.0, digital transformation has become a cornerstone for modern organizations, fundamentally altering how businesses operate and compete. This study delves into the impact of digital transformation on human resource management (HRM), human resource development (HRD), and employees’ innovative work behaviors and job performance in a rapidly evolving business environment. In conducting a survey among 391 employees from information and communication technology (ICT) companies in China, structural equation modeling was employed to analyze the data. The findings reveal a correlation between digital transformation and innovative work behaviors and job performance, with HRM and HRD playing partial mediating roles. Digital transformation not only optimizes work processes and enhances productivity but also fosters the innovation of business models and processes. Moreover, the research indicates the critical importance of implementing efficient digital systems and processes in promoting an organizational culture of innovation and enhancing employees’ innovative capabilities. Thus, digital transformation is seen as a pivotal strategic tool, altering not just the modus operandi of organizations but also influencing employee behavior and performance.

1. Introduction

“Industry 4.0” refers to the Fourth Industrial Revolution and is used to describe the transformation and innovation of industries due to digital transformation [1]. To actively respond to changes in the digital environment, not only ICT (information communication telecommunication) companies, but also manufacturing, service, and financial industries, digital transformation (DT), which is a variety of strategic changes in work methods, is being promoted [2]. Digital transformation is the use of new digital technologies such as social media, mobile technology, analytics, or embedded devices to enable major business improvements including enhanced customer experiences, streamlined operations, or new business models [3]. Digital transformation (DT) is becoming an increasingly strategic focus for building competitive and sustainable economic advantages in many countries [4,5]. There is an increasing body of literature on digital transformation [6,7] and various literature reviews have been written to better understand the breadth, consequences, and implications of the digital transformation literature [8,9,10]. Digital transformation is a concept first announced by Professor Erik Stolterman of Sweden in 2004, it was defined as “using continuously evolving digital technology to infiltrate people’s lives and enrich them” [11]. At the company level, it can be seen as transforming business areas by applying digital technology to improve business models [12]. In the case of digital transformation, the introduction of digital technology a little further from the concept of digitalization brings about continuous changes in everyday life, society, and economy [13,14]. Digital transformation is a management strategy that fundamentally changes a company’s strategy, organization, process, business model, culture, communication, system, etc., in response to various changes brought to companies by digital technology and innovation called “All things Digital” [15].
Digital transformation is currently at the heart of a fundamental change in the operation of the modern economy [16]. This can be confirmed once again through the contents below. The digital transformation concept refers to the networking of all company actors across the levels of the value chain, based on advanced technological developments [17]. Digital transformation is a process that aims to improve physical characteristics by achieving major changes in physical characteristics through a combination of information, computing, communication, and technology [18]. In general, digital transformation is defined as “the use of new digital technologies to make major business improvements. can” [3]. Digital technologies affect how industrial companies approach customers and how they strengthen the workforce within them (those who design products, sell products, or design products in stores). All of this is being transformed by digital technologies [19]. Digitization means “the act or process of digitization; the conversion of analog data into digital form” [20]. On the other hand, the term digitization refers to the conversion of business functions and business models into digital form [21,22,23]. Digitization is also used to integrate digital technologies into various areas of business [24].
A sample study of North American SMEs reports that adopting digital transformation can improve innovative work behavior [25]. Studying the impact of digital transformation on the financial performance of the services sector, specifically, the authors used social networks and training on digital tools to capture metrics of digital transformation and found that factors improve firm performance [26]. Another study studied the impact of digital transformation strategies on job performance models and stakeholder satisfaction in the automotive industry. The authors suggest that digital transformation brings greater revenue, productivity, and competitiveness [27].
The adoption of new technologies and the digitization of organizational processes compel the rapid evolution of HR management practices, necessitating the development and adoption of new HR capabilities, novel forms of employment, and agile HR processes [28,29]. Such fast technological change and development possibly require the organization and employees to accept they must competently and continuously reevaluate procedures and practices to develop a new form of work organization to introduce as expected [30,31]. The recent literature has emphasized the critical role of human resource management (HRM) and human resource development (HRD) in sustainability, advocating for integrating social, economic, and environmental goals into HR practices and policies [32]. Nevertheless, researchers have criticized the shortsightedness in incorporating these practices into profitable, sustainable businesses and the tendency to analyze sustainability primarily from an environmental perspective, neglecting the HR perspective [33,34,35].
This study explores the mediating role of human resource management (HRM) and human resource development (HRD) in the interaction between digital transformation, sustainable work performance, and innovative work behavior. This study will provide a scientific basis for enterprise managers to implement digital transformation strategies, help formulate more comprehensive and effective human resource policies, better motivate employees, and improve organizational performance and innovation capabilities. In addition, the research results will provide valuable references for future academic research and the combination of digital transformation and human resource practices.
In the subsequent sections of this study, we begin with a comprehensive literature review of each research variable. Following this, we provide a detailed description of our data collection and analysis methods. We employ structural equation modeling to test our hypotheses rigorously. Lastly, we discuss our findings’ theoretical and practical implications, offering a thorough evaluation of the study’s significance from both academic and practical perspectives.

2. Theoretical Background and Hypothesis

2.1. DT and HRM and HRD

Human resource management (HRM) practices, including recruitment, training, performance appraisal, compensation, and employee development, play a pivotal role in shaping the performance and productivity of employees within academic institutions [36,37]. These practices are designed to equip employees with the necessary skills and knowledge to contribute to achieving organizational goals [38]. Bondarouk and Brewster (2016) highlight the challenge of taking a different, contextual perspective, broader consideration of stakeholders, and a longer-term view of digital transformation outcomes when conceiving HRM. “Good HRM”, he argues, “is made up of policies and actions that work for the survival and success of the company over the long term, not just generating short-term returns for shareholders [39]”.
HRD, which includes HR training, career and performance management, and organizational development [40], often incorporate technological changes such as e-learning [41,42]. Through digital technologies, processes, products, business models and human behavior can be modified to design business activities more efficiently and effectively [43]. Betchoo (2016) conducted a survey at two public institutions, a university, and a post office, and announced that digital transformation had a positive effect on human resource development, talent management, and performance management [44]. Digital transformation of human resource management refers to the technological process of converting manual human resource information into digital form. This is the process of harnessing digital potential to realize strategy and operationalize human resource management goals [45]. The introduction of new technologies and the digitization of organizational processes require rapid evolution of human resource management practices, requiring the development and adoption of new personnel competencies, employment patterns, and flexible personnel processes [28,29]. Bell et al. (2006) pointed out that digital transformation has had an additional impact on the role of human resources, their capabilities, and competencies [46]. Additionally, Larkin (2017) argues that the changes that digital technologies will bring to human resources will be pervasive and omnidirectional in all companies. As a result, the impact of digitization on digital transformation is meaningful in facilitating day-to-day administrative tasks [47]. Digitization refers to the way people use IT, and it means that IT is doing the work that people used to do in the past. Digital technologies are increasingly having an impact on the work lives of employees, and human resource management is expected to be affected in a variety of ways [48].
H1. 
Digital transformation will have a positive (+) impact on human resources.
H1-1. 
Digital transformation will have a positive (+) impact on human resource management.
H1-2. 
Digital transformation will have a positive impact on human resource development.

2.2. Relationship between HRM, HRD, and IBW

Innovation has long been an important topic in the business strategy literature. Scholars who have conducted research on innovation have suggested various definitions of innovation [49]. Innovative work behavior is individual behavior that leads to useful new work roles, processes, products, or procedures. Furthermore, innovative work behavior can be viewed as an employee’s “willingness” to develop innovation [50]. Karimi et al. (2023) and Khairunnisa et al. (2023) defined innovative work behavior as employee actions to create, recognize, or implement novel ideas, processes, products, or procedures within their respective roles, groups, or organizations [51,52]. Workers’ employability includes work sustainability, qualifications, and future-oriented perspectives [53]. Additionally, employees should assimilate occupational expertise and apply it to new areas of work, which enhances both their career potential and future innovative work behaviors [54]. Since the introduction of new and useful perspectives is not usually executed in a linear relationship, innovative work behavior translates into an acceptable multi-step process involving idea generation, coalition building, and implementation [55]. Employees at all levels of the organization can help the organization achieve success through their innovative work behavior (IWB). Innovative work behavior is an additional role of the individual, aimed at active and proactive behavior and generating, disseminating, and implementing new ideas in the workplace [56]. Typically, innovative business behavior is a complex process involving multi-step processes. Scholars point out that innovative work behavior is a multi-step process involving individual, group, and organizational relationships [57].
ICT companies, especially, showed that innovation is very important for organizational success, and a critical factor is human resource management, which should support organizational strategies that encourage innovative work behavior [58]. Based on the results of the Tran (2020) study, it was concluded that there was a positive impact and significant relationship between human resource management (autonomy, compensation, training, and development) of IWB [59]. There are studies showing a positive relationship between human resource management and corporate innovation [60]. It shows that human resource management in the digital age favors the development of innovative behaviors in employees [61]. Waheed et al. (2019) empirically analyzed the mediating effect of organizational innovation and the moderating effect of innovative climate between new human resource management (NHRM) practice and innovation performance in Pakistani IT companies. As a result, the new human resource management (NHRM) practice of Pakistani IT companies had a significant impact on innovation performance, and organizational innovation showed a mediating effect [62]. According to Aris et al. (2019), human resource development has a significant effect on the improvement of innovative work behavior, and as a result of each component, education and human resource development have a significant effect on innovative work behavior [63].
H2. 
HRM and HRD will have a positive (+) effect on innovative work behavior.
H2-1. 
Human resource management will have a positive (+) effect on innovative work behavior.
H2-2. 
Human resource development will have a positive effect on innovative work behavior.

2.3. Relationship between HRM, HRD, and Job Performance

Organizations are deploying AI agents to manage information, coordinate team processes, and perform simple tasks, thereby enhancing service efficiency and work processes while also improving the use of innovative tools and overall worker performance [64,65]. Job performance refers to the degree to which an organization member’s work has been completed. Unlike productivity, which has a negative meaning, job performance is a broad concept that refers to the overall work achievement of organization members, including productivity, goal achievement degree, flexibility, and adaptability [66]. Citing the study of Viswesvaran (1993), he empirically identified several components of job performance and stated that the components of job performance comprehensively represent the domain of job performance. It consists of productivity, quality, leadership, communication competence, administrative competence, effort, interpersonal competence, job knowledge, acceptance and compliance with authority, and overall job performance. Therefore, it contains important elements to describe and evaluate job performance in various aspects [67].
Human resource management focuses on corporate performance and emphasizes the role of human resource management as a solution to business problems [68]. Previous studies have highlighted that sustainable HRM practices positively impact employees’ job performance by improving their motivation, attitudes, and behaviors, which in turn enhances both organizational and individual job performance [69]. According to Tabiu and Nura (2013), Usmanu Danfodiyo University, Sokoto’s human resource management practice has a significant impact on job performance [70]. Five of the six human resource management practices and activities (recruitment, training, engagement, retention, and intention to leave) all had a significant impact on employee performance, the only exception being compensation, as seen in Thailand, in a qualitative study [58]. Human resource quality and human resource development practices play a positive role in improving employee performance and organizational efficiency [71]. Keltu, T. T. (2024) emphasized in the study that HRD is crucial for enhancing job performance and organizational effectiveness by equipping employees with specific skills, knowledge, abilities, and competencies [72].
H3. 
HRM and HRD will have a positive (+) effect on job performance.
H3-1. 
Human resource management will have a positive (+) effect on job performance.
H3-2. 
Human resource development will have a positive (+) effect on job performance.

2.4. DT, IWB, and Job Performance

Digital technologies are expanding in terms of business management, changing the overall management process. They are rewriting the rules of customers, competition, data, innovation, and value [73]. Responding to change requires a holistic integration effort, not a piecemeal approach, and requires a holistic digital transformation process within the enterprise [74]. Joseph K. Nwankpa and Yaman Roumani (2016) studied the effect of digital transformation on innovative business behavior and corporate performance as a parameter. In addition, it was found that digital transformation had a positive effect on innovative work behavior and a positive relationship was drawn with corporate performance [49]. According to Mubarak (2019), factors in digital transformation include the Internet of Things (IoT), Big Data, Virtual Physical Systems (CPS), and interoperability. In this study, it was verified that big data, CPS, and interoperability have a positive effect on the performance improvement of SMEs [75]. According to Singh et al. (2021), digital transformation has a positive (+) effect on corporate performance, and strategic alignment as a parameter has the greatest impact on corporate performance [76]. Also, according to Aboobaker and KA (2020), digital learning orientation has a positive (+) effect on innovative work behavior, and readiness for change shows a mediating effect in this relationship [77].
H4. 
Digital transformation will have a positive (+) impact on innovative work behavior.
H5. 
Digital transformation will have a positive (+) impact on job performance.

2.5. Mediating Effect of HRM and HRD

Digital innovation programs led by governments worldwide have changed HRM, with digital HRM approaches playing a growing role and holding the key to shaping HR strategy and the organization. [78]. There are scholars who have studied human resource management practice as a parameter [79,80]. A study was published on the mediating effect of human resource management practice between independent variables (i.e., leadership and quality culture (QC)) and successful implementation of TQM (total quality management), as a dependent variable of corporate performance, and the results of mediating statistics were published. Human resources (HR) is the perfect intermediary between the independent variable (i.e., leadership) and successful TQM implementation for corporate performance [79]. According to Deng et al. (2023), coordination and communication through digital technology have a positive effect on job performance, and decision-making and knowledge sharing show a mediating effect in this relationship. Coordination through digital technology has a significant effect on decision-making and knowledge sharing, but communication through digital technology has no significant effect on decision-making [81]. According to Khatib and Alshawabkeh (2022), a survey was conducted on mid- to high-level managers of Palestinian cellular telecommunications companies (Jawwal Company, Ooredoo Company) and found that digital transformation has a positive (+) effect on strategic advantage and digital human resources. Management was seen to have a mediating effect in this relationship [82]. Li (2022) secured 223 valid responses from 500 companies and presented an analysis result that digital transformation has a positive effect on economic performance. It also showed a U-shaped relationship with environmental performance [83]. Nicolas-Agustin et al. (2022) empirically analyzed the mediating effect of human resource management practice and innovative business behavior between strategic alignment and digital transformation. As a result, the strategic strategy had a significant influence on digital transformation and showed a mediating effect between human resource management practice and innovative work behavior [61].
H6. 
HRM and HRD will have a mediating effect on the relationship between digital transformation and innovative work behaviors.
H6-1. 
HRM will have a mediating effect on the relationship between digital transformation and innovative work behaviors.
H6-2. 
HRD will have a mediating effect on the relationship between digital transformation and innovative work behaviors.
H7. 
HRM and HRD will have a mediating effect on the relationship between digital transformation and job performance.
H7-1. 
HRM will have a mediating effect on the relationship between digital transformation and job performance.
H7-2. 
HRD will have a mediating effect on the relationship between digital transformation.
The study’s framework, as illustrated in Figure 1, investigates the relationships among various constructs within the context of China. This framework encompasses both direct and mediating effects. Specifically, it examines the direct impact of digital transformation (DT) on human resource management (HRM) and human resource development (HRD), and subsequently, the effects of HRM and HRD on innovative work behavior (IWB) and job performance (JP). Additionally, the framework explores the direct influence of DT on IWB and JP.

3. Methods

3.1. Measurement of Variables

  • Independent Variable—Digital transformation
Digital transformation was measured with a modified version of the questionnaire originally developed by Verhoef et al. (2021) [4]. For this study, six items were used, each measured on a five-point Likert scale.
  • Mediating variables—HRM and HRD
Human resource management (HRM) and human resource development (HRD) were operationalized for measurement. HRM was measured based on the framework provided by Tsaur and Lin (2004) [84], covering aspects such as employment and selection, education and development, rewards and benefits, and performance management. Six items from this framework were adapted to align with the research objectives and context and were measured on a five-point Likert scale. For measuring HRD, a tool developed by Bae and Lawler (2000) [85] was adapted to suit the specific research context. This measurement included seven items that focused on systematic education and training programs, as well as career development planning for employees, with each item rated on a five-point Likert scale.
  • Dependent variables—IWB and JP
The dependent variables in the research model were innovative work behavior (IWB) and job performance. IWB was measured using a scale developed by Scott and Bruce (1994) [55], supplemented with six items from Kleysen and Street (2001) [86] to better fit the research context. Job performance was assessed using a measurement tool developed by Fiedler (1993) [87], which included seven items tailored to the specific research purpose and context and measured on a five-point Likert scale.
The measurement items and sources of all variables are shown in Table 1.

3.2. Sample and Data Collection

China’s digital transformation is emerging as a future new growth engine for the Chinese economy due to the COVID-19 pandemic and is an important topic in global competition in the era of the Fourth Industrial Revolution. According to the World Digital Competitiveness Ranking announced annually by the International Graduate School of Management Development (IMD), China’s digital overall ranking in 2018 was 30th, but it ranked 17th in 2022. The sample of this study utilized the results of a survey conducted from 21 March 2023 to 1 April 2023, targeting Chinese ICT company employees. The survey sample was randomly selected based on voluntary participation and was conducted in parallel with the online survey. The survey participants were employees from ICT companies located in Guangdong (Guangzhou), Shenzhen, Yunnan (Kunming), and Shanghai, China. A total of 400 samples were collected, but questions with a standard deviation of 0.3 or less were judged to be inappropriate due to the nature of this survey, which asks for a link between the degree of understanding and personal disposition, so these were classified as insincere responses and excluded. A total of 391 questions were used [88].
The demographic characteristics of the respondents are shown in Table 2. As for the gender distribution, males and females accounted for 50.6% and 49.4%, respectively, and by age, 45.5% in their 30s, 38.9% in their 20s, 13% in their 40s, and 2.6% in their 50s or older. As for the distribution by education level, 48.4% are college graduates, 27.6% are junior college graduates, 13.3% are high school graduates, and 10.7% are graduate school graduates and above, and the distribution by years of service is 1–2 years 12.0%, 3–4 years 16.6%, 5–6 years 9.5%, 6.4% for 7 to 9 years and 55.5% for 9 years or more. The distribution by company size was 14.3% for 1–100 employees, 18.9% for 101–300 employees, 20.2% for 301–600 employees, 27.9% for 601–900 employees, and 18.7% for 900 or more employees. Finally, the distribution by department was the highest at 40.9% for production, 22.0% for sales/service, 12.0% for administration/human resources, 15.6% for research and development, and 9.5% for others.

4. Results

In the study, SPSS 26 and AMOS 24 were used. Using data analysis, the next steps were as follows. First, the sample demographic characteristic analysis for frequency and ratio was derived. Second, a measure of tool reliability check using Cronbach’s α coefficient for the use of dot product consistency analysis was used, and the variable discrimination and convergence feasibility verification for factor analysis proceeded. Third, the variable between relevance check for correlation analysis was executed. Fourth, hypotheses verification AMOS 24 for the use of route analysis was performed. Finally, research into the model followed the theory by Baron and Kenny (1986) [89] analyzing the procedure according to medium effect verification executed.

4.1. Measurement Reliability and Validity Assessment

We conducted an exploratory factor analysis (EFA) using SPSS 26.0 to determine the reliability and validity of the measurement. Table 3 summarizes the findings from the exploratory factor analysis. Reliability is a measure of whether the result values appear consistently when the same concept is repeatedly measured. Reliability analysis uses the Cronbach α coefficient when determining whether a measurement tool has internal consistency. In general, if Cronbach’s alpha coefficient value is 0.6 or more, variables are evaluated as having internal consistency, and the Cronbach’s alpha coefficient of latent variables of all items in this study is 0.8 or more, which means that digital transformation is 0.885, human resource management practice is 0.870, human resource development is 0.934, job performance is 0.904, and innovative work behavior is 0.912, all of which were verified to have high internal consistency. The reliability and validity analysis results, as presented in Table 4, robustly confirm that each variable demonstrates high reliability. The higher factor loading values and Cronbach’s α values, indicative of our measurement tool’s high internal consistency and reliability, further strengthen the trust in this study.

4.2. Reliability, Validity Analysis, and Correlation Analysis

We present the basic descriptive statistics and correlations of the measures in Table 4 The correlation coefficients are Pearson’s correlation coefficients, which are used in correlation analysis, and are all over 0.7, indicating that the possibility of multicollinearity is low. Looking at the correlation between major variables, digital transformation, and human resource management (r = 0.378, p ≤ 0.01), job performance (r = 0.460, p ≤ 0.01), and innovative work behavior (r = 0.491, p ≤ 0.01) and human resource development (r = 0.341, p ≤ 0.01) all showed a positive correlation.
The empirical correlation between the dependent and independent variables, which closely aligns with the research constructs proposed in the paper’s theoretical background, strongly validates our main argument. The constructs of digital transformation, human resource management (HRM), human resource development (HRD), innovative work behavior (IWB), and job performance (JP) are all significantly correlated, supporting our research’s main argument.

4.3. Hypothesis Testing

The results of hypothesis testing are presented in Table 5. The fit of the structural model is CMIN/DF = 1.611 < 2, p < 0.001, comparative fit index [CFI] = 0.974, Tucker–Lewis’s index [TLI] = 0.972, incremental fit index [IFI] = 0.947, root mean square error of approximation [RMSEA] = 0.303, confirming that the model is at a satisfactory level. Hypothesis 1-1 is “digital transformation will have a positive (+) effect on human resource management”. The analysis results show that digital transformation has a statistically significant positive (+) effect on human resource management as a path coefficient of 0.466 (p < 0.001). Therefore, Hypothesis 1-1 was accepted. Hypothesis 1-2 is “digital transformation will have a positive (+) effect on human resource development”. Looking at the analysis results, digital transformation has a path coefficient of 0.502 (p < 0.001) on human resource development. It appears to have a statistically significant positive (+) effect, so Hypothesis 1-2 was adopted. Hypothesis 2-1 is “Human resource management will have a positive (+) effect on innovative work behavior”. The analysis results showed that human resource management had a statistically significant positive (+) effect on innovative work behavior with a path coefficient of 0.121 (p < 0.05). Therefore, Hypothesis 2-1 was adopted. Hypothesis 2-2 is “Human Resource Development will have a positive (+) effect on innovative work behavior”. Looking at the analysis results, HRD has a path coefficient for innovative work behavior and was found to have a statistically significant positive (+) effect at 0.126 (p < 0.01). Therefore, Hypothesis 2-2 was adopted. Hypothesis 3-1 is “Human resource management has a positive (+)”. Looking at the analysis results, it was found that human resource management had a statistically significant positive (+) effect on job performance with a path coefficient of 0.281 (p < 0.001). Therefore, Hypothesis 3-1 was accepted. Hypothesis 3-2 is “Human resource development will have a positive (+) effect on job performance”. Looking at the analysis results, human resource development has a statistically significant effect on job performance with a path coefficient of 0.228 (p < 0.001). It was found to have a significantly positive (+) effect, so Hypothesis 3-2 was adopted: Hypothesis 4 is “digital transformation will have a positive (+) effect on innovative work behavior”. The analysis results showed that digital transformation had a statistically significant positive (+) effect on innovative work behavior with a path coefficient of 0.464 (p < 0.001). Therefore, Hypothesis 4 was accepted Hypothesis 5 is “digital transformation will have a positive (+) effect on job performance”. Looking at the analysis results, digital transformation has a statistically significant effect on job performance with a path coefficient of 0.303 (p < 0.001). It was found to have a positive (+) effect, so Hypothesis 5 was accepted.
To verify the mediating effect of HRM and HRD in the relationship between DT and IWB and job performance, a research model was developed. analyzed, the significance of the mediating effect was confirmed using the bootstrapping method. According to the analysis results presented in Table 4, DT has a significant effect on IWB and job performance through HRM and HRD. (DT → HRM → IWB β = 0.078, p < 0.01; D T → HRM → JP β = 0.165, p < 0.01; DT → HRD → IWB β = 0.074, p < 0.01; D T → HRD → JP β = 0.139, p < 0.01). And direct effects of DT and I WB, D T and job performance were significant (DT → HRM → IWB β = 0.487, p < 0.01; D T → HRM → JP β = 0.373, p < 0.01; D T → HRD → IWB β = 0.493, p < 0.01; D T → HRD → JP β = 0.400, p < 0.01). Therefore, Hypotheses 6-1, 6-2, 7-1, and 7-2 were all confirmed as partial mediation, and all hypotheses were accepted.

5. Discussion

This study focuses on digital transformation and human resource management, human resource development, and innovative business behavior. The purpose of the study was to empirically identify the relationship between job performance. The results of this study, which conducted empirical analysis, can be summarized into three points as follows.
First, it was verified that digital transformation has a positive effect on HRM and HRD. According to Kumar’s (2016) research results, digital transformation has a positive impact on human resource factors and concludes that it will play an influential role in the workplace [44]. Regarding human resource management in the digital age, Palmer et al. (2016) argue that human resource management is becoming more diverse and human-oriented, allowing young employees to be more immersed in work and designing diverse and challenging tasks responsibly [90]. Technological advances in the global workplace are having a profound impact on the role of human resource development professionals. In the past, in human resource development, technology was primarily an educational medium used to support training [91]. According to a study by Nahayo and Rutikanga (2020), it is arguable to say that digital transformation is one of the main and pure factors that positively impact human resource development in the current digital age [74]. Digital transformation raised questions about the traditional methods of human resource management and human resource development in organizations, and prior studies analyzing the correlation between digital transformation and human resource management have been actively conducted. It was confirmed that studies on human resource management and its impact on human resource development are lacking.
Second, it was verified that HRM and HRD have a positive effect on IWB and job performance, respectively. This is like the conclusion that there is a positive impact and significant relationship between innovative work behaviors in human resource management, such as autonomy, compensation, training, and development, based on the results of the Tran et al. (2020) study [59]. There are studies showing a positive relationship between human resource management and corporate innovation [92]. It shows that human resource management in the digital age favors the development of innovative behaviors in employees [93]. Human resource management and human resource development can strengthen the company’s overall innovation capacity while fostering an innovative culture within the organization through the competence and enthusiasm of employees and facilitating the acceptance and implementation of innovative ideas. Human resource development refers to the process of improving the competencies and skills of employees. You can help your employees develop their ability to discover and materialize innovative ideas. Appropriate human resource management and human resource development can promote innovative work behaviors, improve job performance, and induce organizational innovation. This can help companies strengthen their competitiveness and achieve sustainable growth.
Third, prior studies on innovative work behavior and job performance have been actively conducted, but among them, human resource management has become an independent variable in the relationship between digital transformation and human resources, innovative work behavior and job performance, and influences innovative work behavior and job performance. Unlike previous studies on the mediating effect of digital transformation, this study is especially meaningful in that it identified a significant mediating effect between human resource management and human resource development. Wang et al. (2020) empirically analyzed the mediating effect of cognitive conflict between digital transformation strategy and performance [94]. As a result, digital transformation had a significant impact on short-term and long-term financial performance, and cognitive conflict showed a mediating effect. As a result of Rajah and Aris’ (2018) study on the impact of entrepreneurial competency on innovative work behavior, entrepreneurial competency showed a significant positive relationship with innovative work behavior [95]. In addition, in the relationship between entrepreneurial competency and innovative work behavior, human resource development confirmed a partial mediating effect. The mediating effects of two variables, digital transformation, human resource management, and human resource development, were tested, and the characteristic feature is that both variables have only partial mediating effects. Therefore, research that identifies in detail the relationship between innovative work behavior, job performance, human resources, and digital transformation should be conducted more thoroughly.
From the above results, digital transformation has a direct impact on innovative work behavior and job performance and an indirect impact through human resource management and human resource development. Therefore, to improve innovative work behavior and the job performance of employees, digital transformation should be fully utilized, and the impact of human resource management and human resource development should be exerted. ICT companies should put more effort into forming a corporate culture in which the impact of human resource management and human resource development can be fully expressed.

6. Conclusions

This study underscores the critical role of academic research in offering valuable insights and theoretical frameworks for scholars, researchers, and practitioners aiming to navigate the complexities of organizational digital transformation. Our findings offer not just theoretical insights but also actionable strategies and guidelines for effectively implementing digital transformation initiatives within organizations.
A key takeaway from our research is the pivotal importance of human resource management (HRM) and human resource development (HRD) in facilitating digital transformation. We propose that organizations should not only recognize the significance of HRM and HRD but also strategically utilize their sub-elements to drive effective digital transformation. This involves developing and implementing personnel policies and strategies that are aligned with digital objectives and can foster a digitally competent workforce. In the current business landscape, where digital transformation is increasingly becoming a necessity rather than a choice, our study provides several implications for corporate leaders and managers. Primarily, it emphasizes the need for adequate resources and support for HRM and HRD initiatives as essential components of digital transformation strategies. This encompasses establishing workforce development and management programs specifically designed to enhance digital competencies and promote innovative work behaviors within the organization.
Furthermore, our research advocates for a strategic approach to HRM and HRD in digital transformation, emphasizing the importance of setting clear goals and directions for enhancing digital capabilities and cultivating innovative business practices. This strategic approach requires reevaluating existing HRM and HRD practices to ensure alignment with the organization’s digital transformation goals. The study indicates that corporate policy performance can significantly improve by supporting digital transformation through targeted HRM and HRD interventions. Organizations can enhance their competitiveness and overall performance by focusing on strengthening digital capabilities and fostering innovative work behavior. Hence, the findings of this research provide a foundation for corporate leaders and managers to consider HRM and HRD as integral to their digital transformation strategies and leverage these areas to bolster corporate policy performance.
Our research also confirmed the mediating role of human resource management and human resource development between digital transformation and employee job performance and work innovation behavior. Such results can help companies identify and respond to challenges and opportunities that may be encountered in implementing digital transformation, such as understanding how to use digital tools for employee training and development, how to improve performance evaluation systems through data analysis, and how to create a work environment that supports an innovative culture.
In addition, understanding the specific impact of digital transformation on employee job performance and innovative work behavior can help companies better adapt and adjust their strategies in a rapidly changing market, ensure that technological progress and human resource management complement each other, and achieve long-term sustainable development. Through these practical applications, this study will help companies stay ahead in the digital age and drive business success.

Research Limitations and Future Directions

This study provides theoretical and practical implications based on the results mentioned above but has the following limitations. First, this study tried to conduct research by collecting data on ICT companies, but sufficient data were not collected for other industries, so in-depth studies such as differences between industries were not sufficiently conducted. In future studies, more in-depth research should be conducted by securing sufficient data based on the limitations of this study, and furthermore, it is considered necessary to conduct more accurate research by overcoming problems or limitations such as research on differences between industries. Second, this study was limited to a cross-sectional survey that collected data based on a specific period. However, it is important to analyze the dynamic changes in the research subject because social science is characterized by continuous change due to various environments. To this end, accurate research, including trends and changes in development, must be conducted, and for this, it is necessary to conduct research over a certain period.

Author Contributions

Conceptualization, Y.L. (Yuanyuan Lou) and A.H.; Methodology, Y.L. (Yannan Li); Software, A.H.; Formal analysis, Y.L. (Yannan Li); Investigation, A.H.; Resources, Y.L. (Yuanyuan Lou); Data curation, Y.L. (Yannan Li); Writing—original draft, Y.L. (Yuanyuan Lou) and Y.L. (Yannan Li); Writing—review & editing, A.H. All authors have read and agreed to the published version of the manuscript.

Funding

This work received no external funding.

Institutional Review Board Statement

The study did not require institutional ethical approval as it involved a survey administered as part of a training program, ensured anonymity of responses, and provided participants with the option to decline participation.

Informed Consent Statement

Informed consent was obtained from all subjects involved in the study.

Data Availability Statement

Data are unavailable due to privacy or ethical restrictions.

Conflicts of Interest

The authors declare no conflicts of interest.

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Sustainability 16 05162 g001
Figure 1. Research model.
Figure 1. Research model.
Sustainability 16 05162 g001
Table 1. Questionnaire constructs, variables for each construct, and sources.
Table 1. Questionnaire constructs, variables for each construct, and sources.
ConstructsMeasurement Items
Digital transformation (DT)
Verhoef et al. (2021) [4]		Our company uses digital marketing strategies to provide multi-channel sales services (online stores, mobile applications, social media, etc.).
Our company uses a digital supply chain management system to handle daily operations (order processing, inventory management, logistics tracking, etc.).
Our company uses digital technology to increase sales or improve customer experience.
Our company uses digital technology to improve customer satisfaction and loyalty.
Our company uses digital technology to process internal company reports.
Our company uses various digital communication channels between employees and customers.
Human resource management (HRM)
Tsaur and Lin (2004)
[84]		Our company while employing new person often uses employment test (foreign language tests, personality tests, knowledge tests, etc.).
During the company employment process, the company explains both the positive and the negative aspects of the job.
In order to work better, our company will provide relevant training or lectures for employees.
The workers learn the performance evaluation results with an official notification.
Our company takes job-related criteria for promotions and appointments.
Our company has good compensation and benefits.
Human resource development (HRD)
Bae and Lawler (2000)
[85]		Our company systematically provides educational and training programs that employees can participate in.
Our company invests significantly in the education and training of its employees.
Our company offers a variety of training programs and opportunities related to business to as many employees as possible.
The education and training provided by our company for formal employees is more than that of other companies in the same industry.
Our company has established a long-term and systematic career planning for staff members.
Our company provides various information required for the career planning of staff members.
Our company offers career counseling activities for all employees in the company.
Innovative work behavior (IWB)
Scott and Bruce (1994) [55]
Kleysen and Street (2001) [86]		I will try new methods or ideas at work.
I will investigate and obtain the resources needed to implement ideas.
In order to implement new ideas, I will make appropriate plans and schedules.
I will continue to take on new challenges and try new things.
I can actively adapt to changes in the environment.
In order to improve the level of service, I will actively strive to master new technologies.
Job performance
(JP)
Fiedler (1993)
[87]		I act independently or without specific instruction.
I diagnose well situations and conditions.
I possess knowledge and information with respect to position requirements.
I can meet the needs of different customers.
I often concentrate on accuracy and timelines of my work.
I achieve high volume of assigned work accomplished.
I am willing to take on additional responsibilities (including overtime) to achieve work goals.
Table 2. Demographic characteristics of respondents.
Table 2. Demographic characteristics of respondents.
Categories(N)(%)
GenderMale19850.6
Female19349.4
Age20s15238.9
30s17845.5
40s5113.0
50+102.6
EducationHigh school graduate5213.3
College graduate10827.6
College graduate18948.4
Graduate award4210.7
Years of service1–2 years4712.0
3–4 years6516.6
5–6 years379.5
7–9 years256.4
9+ years21755.5
Company size1–100 people5614.3
101 to 300 people7418.9
301–600 people7920.2
601 to 90010927.9
Over 9007318.7
DepartmentSales/service8622.0
Production16040.9
Administration/human resources4712.0
Research and development6115.6
Others379.5
Sum 391100.0
Table 3. Results of exploratory factor analysis.
Table 3. Results of exploratory factor analysis.
Varimax Rotation Loadings (n = 391)Cronbach’s α
Factor 1
(HRD)		Factor 2
(JP)		Factor 3
(IWB)		Factor 4
(DT)		Factor 5
(HRM)
HRD-50.8190.1780.1020.060.1340.934
HRD-20.8140.2010.0870.040.109
HRD-60.8130.0740.1290.1530.148
HRD-40.8060.1970.0430.0910.140
HRD-30.8040.1780.1440.1330.122
HRD-70.8030.1540.1050.1590.152
HRD-10.7860.1440.1260.1210.100
JP-50.1780.7490.1750.1650.1480.904
JP-20.0820.7320.1740.1520.181
JP-40.1690.7220.2170.1260.239
JP-30.1760.7160.2010.1510.180
JP-10.2130.7130.2080.2250.087
JP-70.1930.6910.2130.0940.205
JP-60.2500.6910.2110.1350.114
IWB-30.1370.1930.8050.1480.0390.912
IWB-20.0630.2430.7840.1640.091
IWB-50.1390.2080.7720.1970.133
IWB-60.0960.1810.7700.1880.172
IWB-10.1750.2160.7610.1600.098
IWB-40.0980.2010.7290.2380.085
DT-10.1110.0910.1190.7740.1590.885
DT-20.0990.1320.1290.7580.090
DT-30.1190.1590.2050.7530.073
DT-50.1580.1550.2400.7330.135
DT-60.1190.2140.2140.7270.030
DT-40.0800.1390.1430.7200.255
HRM-40.0580.1510.0440.0960.7570.870
HRM-50.0940.240.0310.1950.749
HRM-20.1190.2040.1330.0650.737
HRM-30.1660.1050.1700.0790.721
HRM-60.1970.1520.1060.0530.720
HRM-10.1750.0810.0680.2280.720
Note: n = 391, DT: digital transformation, HRM: human resource management, HRD: human resource development, IWB: innovative work behavior, JP: job performance.
Table 4. Mean, standard deviations, and correlations.
Table 4. Mean, standard deviations, and correlations.
MeanSDDTHRMJPIWBHRD
DT3.9470.8341
HRM3.7290.8530.378 **1
JP3.8670.8170.460 **0.471 **1
IWB4.0650.8270.491 **0.333 **0.553 **1
HRD3.6310.9680.341 **0.380 **0.471 **0.344 **1
Note: N = 391, ** p ≤ 0.01, DT: digital transformation, HRM: human resource management, HRD: human resource development, IWB: innovative work behavior, JP: job performance.
Table 5. Hypothesis testing.
Table 5. Hypothesis testing.
HypothesisβCRp
H1-1DT → HRM0.4667.320***
H1-2DT → HRD0.5026.961***
H2-1HRM → IWB0.1212.2270.026
H2-2HRD → IWB0.1263.0520.002
H3-1HRM → JP0.2815.345***
H3-2HRD → JP0.2285.772***
H4DT → IWB0.4646.976***
H5DT → JP0.3035.177***
Test of mediation of HRM and HRD on the relationship between DT and WIP and JP: Bootstrap results
HypothesisIndirect effectsDirect effectsTotal_effects
H6-1D T → HRM → IWB0.078 **0.487 **0.566 **
H6-2 D T → HRM → JP0.165 **0.373 **0.538 **
H7-1D T → HRD → IWB0.074 **0.493 **0.567 **
H7-2D T → HRD → JP0.139 **0.400 **0.539 **
Note: N = 391, ** p ≤ 0.01, *** p < 0.001. DT: digital transformation, HRM: human resource management, HRD: human resource development, IWB: innovative work behavior, JP: job performance.
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Lou, Y.; Hong, A.; Li, Y. Assessing the Role of HRM and HRD in Enhancing Sustainable Job Performance and Innovative Work Behaviors through Digital Transformation in ICT Companies. Sustainability 2024, 16, 5162. https://doi.org/10.3390/su16125162

AMA Style

Lou Y, Hong A, Li Y. Assessing the Role of HRM and HRD in Enhancing Sustainable Job Performance and Innovative Work Behaviors through Digital Transformation in ICT Companies. Sustainability. 2024; 16(12):5162. https://doi.org/10.3390/su16125162

Chicago/Turabian Style

Lou, Yuanyuan, Ahreum Hong, and Yannan Li. 2024. "Assessing the Role of HRM and HRD in Enhancing Sustainable Job Performance and Innovative Work Behaviors through Digital Transformation in ICT Companies" Sustainability 16, no. 12: 5162. https://doi.org/10.3390/su16125162

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