1. Introduction
The subtle nature of humans has maintained a resistive approach toward change since the beginning of early civilizations. The concept of work was centered around activities such as farming, construction, and resource mobilization, which provided compensation for necessities such as food, shelter, clothing, and more. Kings, lords, and authorities of old often compelled their subjects to perform these necessary tasks through force. This was also evident in the construction of the Pyramids of Giza in Egypt, one of the ancient world’s most magnificent structures, built at the cost of countless lives lost to grueling labor conditions. As humanity progressed with advancements in education, infrastructure, lifestyle, social systems, and governance, the values associated with work were also shaped more decently and healthily. The abolition of slavery, the introduction of labor laws, and the United Nations’ Sustainable Development Goals (SDGs) are the most significant contributions to ensuring the safe and sustainable management of the human workforce. Similarly, technological advancements have driven traditional workplace scenarios towards digital, virtual, and collaborative modes. To drive productive outcomes and stay competitive with industry players, organizations invest significant resources in innovation management, process improvement, and employee training and development to facilitate digital transformation [
1].
Technological transformation is captivating organizational operations, causing them to transition from the conventional way of doing business to a digital and sustainable one. Such transmuting of the business operations to digital modes manifests in computerized machinery for the employees’ activities and customers’ services. However, to reap the benefits of digital transformation on a long-term basis through engaging human capital is quite different from installing the digital system and tangible resources [
2]. In the traditional business model, workforce engagement at conventional workplaces was influenced by factors such as job satisfaction, rewards and recognition, bonuses, promotions, supervisor support, training and development, and more. However, the impacts of volatile scenarios of rapid technological integration on the nature of skill management and the workplace have indicated the need for contemplating and grasping the factors involving technology management for engaging the workforce. With the increasing role of information technology in organizations, the traditional factors of workforce engagement may not be as effective, given the changing nature of the workplace, type of organizational activities, interaction among business units, organizational culture, and connectedness [
3]. The approach to human labor has undergone a profound transformation, evolving from coercion to voluntary involvement. The modern workplace recognizes and considers employees’ cognitive and situational factors, departing from the harsh realities of the past and embracing a more compassionate and innovative approach. By pondering such an analogy, implementing digital systems for work has less to do with the type of installed machinery and more to do with employees’ level of productivity and engagement through a collaborative work approach [
2].
In this scenario, an organization’s human capital is crucial, as a report by Gartner [
4] indicated that 83% of organizations failed to achieve their goals regarding digital transformation due to a lack of employee involvement in technology-driven business processes. A Microsoft study uncovered a prevalent sentiment among employees, with 61% confessing that implementing technology at their organization stirs up anxiety. Additionally, nearly half of all staff members, 49%, expressed fear regarding the ramifications of digital transformation in the workplace. Consequently, their motivation levels during work tasks decreased, leading to lower productivity and decreased commitment from employees in the organization [
5]. Therefore, the challenge of engaging employees in a digitally-enabled workspace needs to be investigated by elucidating the cognitive and circumstantial determinants of the workforce [
2].
The integration of Industry 4.0 (IR4.0) and the impact of the COVID-19 pandemic have compelled a move towards a more digital and virtual environment across various spheres of life, including business, governance, and education [
1,
6,
7,
8,
9]. Within education, remote learning via online classes and virtual sessions is becoming increasingly popular, yet the critical role played by non-academic staff in maintaining the longevity of organizations cannot be overstated [
10]. Their responsibilities in managing and facilitating behind-the-scenes organizational tasks contribute significantly to the change in management process and organizational growth. To enhance an organization’s efficiency, it is crucial to consider the non-academic staff’s perception of their work environment, motivation, benefits, and ways to foster their engagement in the workplace [
11]. By considering the part employees play in digital transformation, the involvement of non-academic staff in the education sector also plays a crucial role in successfully integrating digital technologies in the workplace. The contribution of non-academic staff to academic ranking and institutional reputation may be limited [
12]. However, the involvement of a motivated workforce is a strong indicator of organizational growth and development, and the implication of an engaged workforce strongly confers the signals of organizational development. The engagement of non-academic staff is assessed through evaluations of motivation, working conditions, benefits, career development and growth opportunities [
13], knowledge management, training, and leadership roles [
14]. The validation of social exchange theory (SET) for understanding the engagement factors of non-academic staff has also manifested in organizational development [
15].
Within the context of a sustainable organization, numerous factors impact employee engagement. For example, work with supporting knowledge sharing is always beneficial for the organization, leading to engagement and a surge in employee motivation [
16]. The Deloitte 2016 Millennial survey reported that 75% of millennials discoursed that they would prefer to do office tasks frequently from home or other places where they feel more creative and innovative [
17], which portrays the significance impact of employee mobility on employee engagement. As digital transfusion in businesses requires up-to-date skills and business processes for the workforce, there is high demand for essential training and development programs [
18]. These manage the employees during organizational changes and ensures their keen interest in being skilled in keeping stride with modern workplace requirements [
19]. At the same pace as engaging workforces in digitally enabled workplace settings, psychological empowerment enables the workforce to perform their work more productively and innovatively. As Aldabbas et al. [
20] explored, the individual’s job roles and their internal motivation, coupled with a sense of control in performing organizational tasks through constructive involvement, tend to orchestrate positive relations with engagement at the workplace. Correspondingly, using SET in examining different factors for employee engagement, previous studies pinpointed how such factors predict employee attitude and intention towards digitally enabled organizations [
21]. For instance, SET argues that dealing with psychological work associations is parallel to interpersonal relations, which mainly incorporate the individual- and organizational-level interactions of employees in the modern workplace [
21]. Knowledge sharing is also prefaced on SET to explain individual behavior [
22]. SET also provides a deeper insight into training and development, with employee mobility used to elucidate employee behavior at the workplace [
23].
Since digital transformation is rapidly reshaping the majority of sectors [
24], a sense of urgency regarding employee connectedness has become crucial for the current organizational change [
25]. However, there are certain aspects that previous studies could not address, such as the collective contemplation of flexible working conditions, disseminating skillful information among peers, empowering the employees with a sense of control in digitally enabled business activities, and managing the talent through new skills, learning, and development. Previous research on non-academic staff has been lacking in its examination of the factors affecting employee engagement in digital transformation [
12,
14,
15,
26]. This is a pressing issue, as important questions remain unanswered: what are the key drivers of employee engagement that support digital transformation for non-academic staff, and how does their perception of their job role and work environment impact their engagement in this process? By considering these elements and aspects of employee behavior, the authors believe that valuable insights can be gained to help stakeholders develop strategies for engagement and retention in digital transformation. Moreover, assessing employee engagement (EE) in the digital transformation era on a departmental basis is important in ensuring the success of these initiatives. Previous studies have also neglected to examine the impact of digital transformation on different departments within an organization [
10,
11,
12,
13,
14,
15,
26]. By gaining a deeper understanding of these effects, decision makers can adopt a targeted approach to overcoming the challenges they encounter. Initially, this will allow for a better understanding of departmental differences, including their unique cultures, work processes, and resources, which can impact their ability to adopt and implement digital transformation initiatives. By evaluating EE on a departmental level, universities can identify which departments are leading the way and which may need additional support. Furthermore, having these data also enables the more effective allocation of resources. If a department is struggling with low EE levels in the face of digital transformation, additional resources can be directed towards overcoming obstacles and ensuring success. Finally, evidence-based decision making is key in navigating the complex challenges of the digital era. By studying the impact of digital transformation on a departmental basis and gathering data and insights on EE levels, universities can make informed decisions that support their employees and drive positive outcomes. For such purpose, multigroup analysis (MGA) [
27] and importance-performance map analysis (IPMA) [
28] would yield resourceful inferences that have yet to be explored.
By accumulating the topical engagement factors under the same umbrella, this study proposed the conceptual framework of employee engagement on digitally enabled educational institutional platforms through knowledge sharing, psychological empowerment, employee mobility, and training and development towards the prediction of non-academic employees’ engagement. With a fresh perspective, this study sheds light on the often neglected aspect of employee engagement that could help to understand the workforce perspective in digital transformation. The significance of this hypothesized model inclined towards a better understanding of the modern and sustainable way of work and labor connection. The study will present the backgrounds of engagement at the workplace as an innovative contribution, and this novel addition to the sustainable perspective of employee engagement will manifest in pathways for organizational decision makers. The research contemplated the empirical survey to grasp the inferences of the proposed relationships between variables. The PLS-SEM, MGA, and IPMA were implied to exhibit the results of quantitative analysis from surveyed data.
3. Methodology
This study employed a quantitative research design, adopting a positivist paradigm and a deductive approach. The research strategy involved conducting a survey with a cross-sectional approach [
56]. The positivist paradigm seeks to establish causality between variables. The hypotheses were developed using the social exchange theory (SET), which was approached through the deductive method. A survey-based, cross-sectional research design was utilized to gather data. The study data were collected from the non-academic employees of the different educational institutes in Klang Valley using online survey forms. During uncertain times, such as the ongoing pandemic of COVID-19, reaching the targeted participants from the wider population can become challenging. In such scenarios, non-probability sampling methods such as convenience sampling can be ideal [
57]. To ensure safety and accessibility, convenience sampling was utilized, which is a cost-efficient, uncomplicated, and swift way to gather information [
58]. Due to the pandemic restrictions, in-person data collection was impossible, so an online survey was used instead. The survey was sent to working non-academic staff members from various departments at higher education institutes through various contacts. The data gathering took place from January to September 2021. As per the guideline of Kline [
59], the goal was to collect at least 200 responses to ensure that the sample size was large enough to draw meaningful conclusions from the collected data. The survey ensured the anonymity and confidentiality of all participants. In the end, 205 responses were received.
The questionnaire consisted of two sections. The first section focused on each respondent’s personal information, including demographic information such as gender, age, race, educational background, length of service, job level, and department. The second section consisted of 39 statements on a five-point Likert scale (i.e., strongly disagree = 1, strongly agree = 5). Seven items for KS and six for EM were adapted from Juan et al. [
41] and i4cp [
60], respectively. For measuring TD, one item, including skill enhancement, was adopted from Edgar and Geare [
61], while four items were related to professional growth and personal growth, adopted from Siddiqui and Noor-us-Sahar’s [
62] research. PE was measured using Spreitzer’s [
52] scale, including 12 items. Finally, EE was determined by adopting nine items from Utrecht Work Engagement Scale [
63]. All items are listed in
Appendix A.
For the data analysis, multiple techniques were utilized through SmartPLS v3, including partial least squares structural equation modeling (PLS-SEM), multigroup analysis (MGA), and importance-performance analysis (IPMA). PLS-SEM is a statistical approach to modelling complex relationships between latent variables and their indicators. It is beneficial for use in research in fields with small sample sizes and when the relationships between variables are not well understood. This study used PLS-SEM to examine the relationships between the model variables based on 39 statements on the Likert scale [
64]. MGA was performed to compare the results of multiple groups, such as different department subgroups. This technique allows for the examination of group-specific relationships and differences in the results between groups. MGA was justified in this study to provide a more nuanced understanding of the results and to determine if there were any significant differences between subgroups [
27]. IPMA is a tool used to evaluate various factors or variables’ relative importance and performance. In this study, IPMA was used to identify the most important factors that contributed to the survey results and to assess the relative performance of these factors in different groups. This analysis provided insights into the results’ key drivers and helped prioritize areas for improvement [
65,
66]. The study also employed the common method bias (CMB) correction to ensure that the results were not influenced by the data collection method and that the findings were made more robust [
28]. Moreover, the PLS-Predict technique was also implied to make predictions about the results based on the findings of the PLS-SEM analysis [
67].
5. Discussion and Implications
The purpose of this research was to shed light on the impact of significant elements, such as knowledge sharing (KS), employee mobility (EM), training and development (TD), and psychological empowerment (PE), on cultivating employee engagement (EE) within the context of workplace transformation driven by modern technologies. Following the analysis of survey responses from 205 non-academic professionals working in the Malaysian higher education sector, our results were based on PLS-SEM analysis, used to test the hypotheses and validate the theoretical model; multigroup analysis (MGA), used to compare the level of significance of model variable on the basis of departments; and importance-performance map analysis (IPMA), used to assess the overall model position, as well as that of the individual departments. Before PLS-SEM analysis, data were assessed for biasness using the CMB technique. After conducting the PLS-SEM analysis, the model was validated for its prediction relevance through the blindfolding process. Later on, to assess the strength of the model prediction power, the PLS-predict technique was also applied and validated.
PLS-SEM results indicated that KS, EM, TD, and PE were jointly constructed to explain the 76% change in EE. More specifically, each hypothesis, i.e., H1 (KS → EE), H2 (EM → EE), H3 (TD → EE), and H4 (PE → EE), was supported with a significance level of <0.05. These findings confirm and support prior research conclusions regarding the proposed structural relationship in our model [
27,
28,
33,
39,
40,
60]. On the other hand, among the four hypotheses, H1 and H2 are robustly supported by the regression path of KS (26%) and EM (48%) towards EE; thus, KS and EM seem to be more influential factors in increasing EE. This shows that organizations should find ways for the employee mobility factor to strengthen EE effectively.
Our analyses reconfirmed prior views that TD and PE positively change employee engagement in the same direction [
34,
40,
43,
61]. According to ICTC [
49], TD accelerates “21st-century learning environments” to reduce the tech skills gap, resulting in higher-skilled employees, in which the difficulty of engaging workforces for the modern workplace can be irresistible. As today’s organizations are facing several changes through digital transformation, psychologically empowered workers are much more crucial in triggering those changes [
81,
82,
83]. Consistently, we found that TD and PE enhance EE in these days of modern organizations. These findings may benefit higher education institutions by promoting a positive organizational culture and improving employee engagement. This, in turn, can lead to increased operational efficiency in digital transformation and provide a competitive advantage. However, TD and PE have comparatively less impact among the modelled variables towards EE. Reliance on these two variables, while ignoring two key variables (i.e., KS and EM), may not robustly achieve the desired engagement levels among staff in a technology-driven working environment.
By developing their information technology strategies, several firms—for example, higher education institutions—are well prepared to shift to the digital workplace, known by a new term: “born-digital” organizations [
84]. KS and EM are key trends [
25,
30,
33]. Likewise, technological innovations develop the knowledge and actions of employees in an organization in a practical setting [
85]. This is why innovative socio-technical systems, and new norms and behaviors are assessed in an organization with technological transformation [
40]. Therefore, KS among the employees stimulates them to learn and perform together at the organization [
86], resulting in sustainable EE [
27,
28,
65].
To assess the robustness of crafting EE predictors, the MGA and IPMA were tested for each department. Understanding the role of the model in each department within a university is crucial for comprehending differences, providing targeted support, effectively allocating resources, and making informed decisions. It helps identify leading departments, support struggling ones, allocate resources, and make evidence-based decisions for digital transformation initiatives. In this sense, the MGA result explains inferences about departments, as the KS role has more influence on EE in the admission department than the IT department. This means that the practice of knowledge sharing was found to have a more significant impact on enhancing employee engagement levels in the admission department compared to the IT department in universities. This suggests that the admission department may benefit more from implementing effective knowledge-sharing initiatives and practices than the IT department. Moreover, the role of employee mobility (EM) in engaging employees in the finance and HR departments is significantly varied. This could be due to differences in departmental goals, work processes, job responsibilities, and employee motivation, among other factors. In the finance and marketing departments, increased employee mobility may increase exposure to new ideas, diverse perspectives, and opportunities, leading to higher engagement. To justify this result, further research could be conducted to understand the underlying reasons for this impact difference and identify best practices for managing employee mobility in each department to enhance engagement levels.
By expanding the sturdiness of analysis, the IPMA results for all departments explained that EM lies in Q2 (with higher importance and lower performance), suggesting that all stakeholders should pay attention to this factor.
Table 6 shows that the IT and HR departments need to pay more attention to improving employee mobility practices, towards engaging the employees. There are various ways to increase employee mobility in IT and HR departments, including flexible work arrangements, job rotation programs, cross-functional collaboration, training and development opportunities, and employee recognition and rewards. Offering flexible work arrangements such as working from home or flexible hours can reduce commuting time and increase employee mobility. Implementing job rotation programs allows employees to gain new experiences and skills, leading to growth opportunities. Encouraging cross-functional collaboration and providing training and development programs can broaden employees’ skills and knowledge. Recognizing and rewarding employees for their contributions can also increase employee engagement and motivation. These measures can help improve employee mobility and drive engagement in the IT and HR departments. While knowledge sharing for the admission, marketing, and finance departments lie in the Q2 quadrant, revealing their lower level of performance with higher importance, ultimately calls for focus and ponderance. Enhancing knowledge sharing in the marketing, admission, and finance departments can be achieved through several strategies; for example, creating a collaborative work environment, where team members work together in shared spaces, is one way to increase cross-functional collaboration. Implementing mentorship programs can offer employees opportunities to learn from experienced colleagues. A knowledge management system can help to store, organize, and share information and best practices. Encouraging employees to share their knowledge through presentations, workshops, or other forms of training and development can help spread information throughout the departments. Incentives, such as bonuses or recognition programs, can be offered to employees who share their knowledge. Open communication channels, such as suggestion boxes or regular meetings, facilitate the sharing of information and ideas. Finally, cross-departmental projects can bring employees from different departments together, promoting knowledge sharing across the organization.
Relatedly, as digital transformation is rapidly reshaping most business firms [
24], a sense of urgency regarding employee connectedness has become crucial for the current organizational change [
87]. Therefore, current employers are keenly aware of interpreting those factors that may influence EE in the digital workplace, such as cognitive-based encouragement, transferring knowledge, agile workforces, and training and development [
27,
31,
36,
88]. Although higher education institutions have been found to be more flexible in adopting KS and EM practices compared to other sectors [
27,
66,
89], the digital workplace is not limited to a single sector and is becoming increasingly prevalent across all industries. In this context, “technological innovation” involves better reflecting advancements in other professionals, such as academicians, corporate trainers, IT professionals, and clerical and administrative staff. The impact of COVID-19 has also urged many organizations towards digital workplace trends, in which KS and EM may be dynamically embraced as the new normal. Working from home and the sharing of knowledge occur genuinely due to this pandemic, which brings individuals, team members, and opinions together. The findings of our research are also consistent with these views. We thus recommend that not only higher education institutions but also other sectors bear KS and EM in mind more specifically for making sustainable EE goals. Indeed, HR managers, business leaders, and academics may benefit from these research findings for better understanding and to substantiate the perceived impacts of KS and EM on EE in the digital workplace.
Social exchange theory (SET) is a sociological perspective that views social behavior as the outcome of a reciprocal exchange process between individuals. According to Chernyak-Hai and Rabenu [
21], SET provides valuable insight into the exchange relationship between employees and companies in today’s digital workplaces. Our findings in this study confirm the validity of SET in promoting employee engagement. Organizations can create a positive and reciprocal relationship by adopting practices such as implementing a knowledge sharing platform, embracing remote work culture, providing training and development opportunities, and promoting psychological empowerment among employees. Employees who perceive that their companies are concerned about their wellbeing and growth become more engaged in and dedicated to their work. The mutual action between the company and employees fosters a work environment where both parties benefit. This, in turn, leads to increased employee satisfaction, motivation, and overall productivity. Therefore, organizations need to understand the significance of SET and adopt practices that promote a positive exchange relationship between employees and their company [
17,
22,
23,
67].
From an academic viewpoint, this study is among the first attempts to illustrate the relationship between certain factors (i.e., KS, EM, TD, and PE) and EE in the digital workplace context. Earlier research on the impact of these factors on employees’ positive behavioral outcomes was conducted with limited scope, particularly in a non-digital workspace scenarios [
27,
31,
33,
40,
65]. Thus, the findings of this study undoubtedly represent a novel contribution to the existing academic literature to reshape EE in sustainability. In addition, our study has potency in aiding understanding of “Sustainable Development Goal 9 (SDG-9)”, i.e., reliable, workable and resilient infrastructures, including human resources and innovation management [
90].