Unlock the black box of remote e-working effectiveness and e-HRM practices effect on organizational commitment

Abstract

Organizations realizes that, after COVID-19, remote e-working will be the new working arrangement for a sizable portion of their workforce. In light of this, this study attempted to unlock the black box of remote e-working effectiveness and e-HRM practices by theoretically and empirically establishing the path by which they may deliver value to the business. Accordingly, the study investigates the effects of remote e-working and e-HRM practices on organizational commitment via the mediation of job satisfaction. The data used for this research were collected from 273 participants from 25 commercial banks in Jordan using self-administrated electronic questionnaire. The PLS-SEM method was used to analyze the data. The results supported the study hypotheses revealing that e-HRM practices positively affect remote e-working effectiveness by enabling a real-time information based communication, interactive work environment, e-training, and e-performance appraisal. The findings show that since it gives employees more control over how much time they devote to work and family life, remote e-working improves employee focus levels while they are working from home. Their satisfaction is therefore increased. Furthermore, Job satisfaction is significant predictors of whether remote work enhances organizational commitment. A satisfied e-worker will feel more emotionally connected to the organization and more obligated remain in the organization. Our research provides evidence that remote e-working effectiveness and e-HRM practices have an effect on organizational commitment and this relationship becomes stronger when it mediated by Job satisfaction. Conclusion, limitations, and future research directions are included.

Keywords:

• e-HRM practices
• remote e-working
• remote e-working effectiveness
• job satisfaction
• organizational commitment

Public interest statement

After COVID-19, remote e-working will be the new arrangement of work for a sizable portion of their workforce. This could be an entirely remote or hybrid form. Due to these new possibilities, this study attempted to unlock the “black box” of remote e-working effectiveness and e-HRM practices by identifying theoretically and empirically the path through which remote e-working effectiveness and e-HRM practices may deliver value to the organization .

Organizations should generally embrace and manage remote e-working with the understanding that certain prerequisites can ensure that the benefits of remote e-working exceed the drawbacks. e-HRM practices and the effectiveness of remote e-working are important keys in the consecution of organizational commitment. When e-HRM practices are developed or improved, they should take into consideration remote e-working effectiveness. Our findings have provided practitioners with more information about the factors that may be prioritized to increase employee commitment to remote e-working.

1. Introduction

The COVID-19 pandemic has changed the characteristics of the work environment across many fields (Donnelly & Johns, 2021; Hamouche & Chabani, 2021). The desire to work more efficiently and safely, combined with advancements in information and communication technologies (ICT), has fueled the fast expansion of remote e-working (Adekoya et al., 2022). Indeed, remote e-working is now the new reality, and this practice will continue beyond the epidemic (Dayaram & Burgess, 2021; Vyas, 2022; Williamson et al., 2020). Consequently, businesses are increasingly embracing electronic human resources management systems (e-HRM) not only to improve their human resources management (HRM) function but also to influence the performance and behavior of employees by developing an interactive, self-service, real-time, and information-based remote working environment to guarantee the continuity of their work operations (Basu et al., 2022).

In essence, e-HRM has evolved into a pivotal tool for companies to continuously support remote e-working activities and make sure they contribute successfully to the achievement of organizational goals (Farhan et al., 2021). In the same vein, E-HRM offers ongoing evaluation of human resources (HR) to make sure they successfully and efficiently accomplish company goals (Alshibly, 2014; Stone et al., 2015). In the remote e-working environment, employees may struggle with a lack of clarity on the desired performance outcomes and responsibilities they need to oversee. If they have no prior experience with remote e-working or have very little knowledge of it, this arguably increases the importance of the technology used to communicate with the workplace, including e-HRM practices. Nevertheless, extant research reveals a dearth of studies investigating the link between e-HRM practices and remote e-working effectiveness.

Although greater attention has been given to studying the broad advantages and disadvantages of remote e-working for businesses and employees, there remains controversy about whether it is advantageous (Sharma et al., 2022; Taser et al., 2022). The effectiveness of remote e-working with regard to work-related outcomes like job satisfaction and organizational commitment is, however, little documented (B. Wang et al., 2021). Therefore, businesses cannot rely on conclusive proof that remote e-working is beneficial just yet.

Organizational commitment is one of the key indicators or benchmarks that confirm if remote e-working and e-HRM practices can foster emotional connections between employees’ and businesses’ goals (Singh & Onahring, 2019). In particular, the employee obtains remote e-working and e-HRM practices and develops commitment to the organization in a relationship of reciprocal exchange (Meyer et al., 2002), leading to organizationally relevant behaviors (Hoq, 2021) and the intention to stay (Devananda & Onahring, 2019). According to a number of studies (e.g., Haar & Brougham, 2022; Siregar, 2022), increased commitment has a positive impact on a variety of outcomes, including work performance and organizational citizenship behaviors. Therefore, organizational commitment is regarded as a key organizational outcome and a major notion in the canon of HRM research (Aydoğan & Arslan, 2020).

Accordingly, by theoretically establishing and empirically evaluating the path through which remote e-working effectiveness and e-HRM practices may benefit the organization, this study aimed to open the “black box” of remote e-working effectiveness and e-HRM practices. It suggests organizations should adopt and manage remote e-working with the idea that there are certain prerequisites that can ensure that the benefits of remote e-working exceed its drawbacks. e-HRM practices and remote e-working effectiveness are critical factors in developing organizational commitment. When e-HRM practices are developed or improved, organizations should take into consideration remote e-working effectiveness and their employees’ organizational commitment to remote e-working and prioritize it accordingly.

2. Literature review and hypotheses development

2.1. Remote e-working effectiveness

Firms are becoming more reliant on remote e-working, particularly after the wake of the COVID-19 epidemic (Adekoya et al., 2022). Even yet, there are many terms and vocabulary items used to describe essentially the same concept as what we call remote e-working. Terms like “working from home,” “remote working,” “virtual working,” “e-work,” “agile working,” “smart working,” “home office,” and “teleworking” are widely used in the literature to denote distributed modes of working outside the office (Grant et al., 2019). This study focuses on any type of work arrangement that involves using an electronic connection or medium and involves three dimensions: work location that might be anywhere (outside of the typical office), time distribution, and usage of ICT. Therefore, we define remote e-working as the substitution of work that is located in a specific physical location where the worker must travel to the workplace rather than the work traveling to the worker (Smith et al., 2018). Additionally, we used the term “e-workers” to refer to employees who access work mostly through ICTs while working outside of typical office settings (Charalampous et al., 2019).

The concept of remote e-working was first introduced in the 1970s, but it did not gain popularity as quickly as was expected (Adekoya et al., 2022). At first, organizations viewed remote e-working as an optional practice that could be used to reduce employees’ workloads by allowing them to work for a set period of time away from their usual workplace. Consequently, organizations were able to lower the cost of maintaining their physical infrastructure (Davidescu et al., 2021).

Despite expectations that ICT advancements would lead more organizations to use these arrangements, the adoption of remote e-working did not proceed as expected prior to COVID-19 (Torten et al., 2016). Therefore, earlier remote e-working studies have focused on investigating the advantages and disadvantages of remote e-working for both businesses and individuals. These studies have shown that remote e-working has a number of advantages, including job autonomy; increased job flexibility, increased productivity, decreased travel costs, improved office space, decreased intentions of turnover, and increased employee engagement, according to research by Beňo (2021) and W. Wang et al. (2020). However, there have also been documented negative effects, including poor well-being due to work overload, social isolation, time management, limited knowledge sharing, and employers’ loss of control over workflow (Baakeel, 2021; Popovici & Popovici, 2020).

Indeed, one of the most remarkable developments brought about by COVID-19, according to Dayaram and Burgess (2021), is the transition of many employees into remote e-working arrangements across all professions, even when this was not previously possible. During the COVID-19 epidemic, remote e-working has been made mandatory and the standard working arrangement for most companies in order to preserve both the health of employees and business continuity (Chang et al., 2021). Due to the travel restrictions and social segregation imposed by COVID-19, firms had to overnight relocate employees’ work from offices to their homes, necessitating remote e-working for all parties. Hence, the employees had to decide if they were qualified for and motivated to perform this type of work, adapt to new working conditions and environments, and utilize new technologies for the first time (Chen, 2021; Williamson et al., 2020).

The effectiveness of remote e-working has not been sufficiently studied in previous research because remote workers cannot be tracked in the same manner as office workers (Adekoya et al., 2022; Afrianty et al., 2022). The aspects that contribute to the effectiveness of remote e-working must thus be thoroughly investigated and identified.

According to Grant (2021), firms should evaluate the performance of remote e-working in order to explain cost savings, capture productivity increases, and maintain employee well-being. Grant et al. (2019) suggest that firms should evaluate the effectiveness of remote e-working in order to explain cost savings, capture productivity increases, and maintain employee well-being. Consequently, when studying remote e-working effectiveness, an evaluation based on job effectiveness and work-life balance is required.

Job effectiveness is the appraisal of the results of an employee’s job performance (Gashi et al., 2022), often measured by how closely operations outcomes match the planned goal (Borman, 1991), and is linked with increased productivity in various roles in which a worker engages (Hanaysha, 2016). Grant et al. (2019) relate job effectiveness in remote e-working to a certain set of skills and competences required to ensure e-workers are committed to achieving their job goals and devoted to high quality and quantity of output while fulfilling performance targets. They suggest that consideration must be given to both the positive and negative effects that technology will have on e-workers. The ability to self-manage one’s work, which includes but is not limited to setting appropriate goals and making sure that goals are reached, is one area in which e-workers in particular need to have or acquire certain skills and competences that match with remote e-working practices (Grant et al., 2013).

Work-life balance is described as a favorable perception of the integration of different aspects of one’s life, including family and work, and minimizing the conflict between different responsibilities (Jang & Zippay, 2011). Work-life balance includes an effective balancing of work and non-work activities and keeping the tension between a person’s responsibilities to their family and their professional commitments to a minimum (Sirgy & Lee, 2018). Keeping a work-life balance is considered to fulfill expectations related to the roles that an individual performs in both their professional and non-professional lives (Haar & Brougham, 2022).

The main advantages of remote e-working are specified as the ability to handle tasks more effectively and prevent role conflicts more easily because of the increased flexibility of the home environment (Vyas, 2022). Working remotely is useful for many employees since it makes it easier for them to access their jobs while still taking care of their personal or family responsibilities. Grant et al. (2019) assert that remote e-working can lessen conflict in the workplace and enhance work-life balance. On the other hand, organizations see remote e-working as a way to provide flexibility and consider the wellbeing of their employees (Beňo, 2021).

2.2. E-HRM practices and remote working effectiveness

E-HRM is defined as web-based information systems and applications that support collective participants in joint HRM activities (Strohmeier & Kabst, 2014). It serves as both a tool for conducting HRM operations and a means of bringing geographically separated groups of players together (Mauro & Borges-Andrade, 2020). Through web-based channels, e-HRM supports HRM operations and meets an organization’s human resource needs (Ruël et al., 2007).

Njoku et al. (2019) assert that e-HRM has three levels: Operational e-HRM includes administrative duties like payroll and employee personal data and information; relational e-HRM relates to business processes that support HRM, like hiring, training, and performance management; and transformational e-HRM relates to strategic HR activities like knowledge management and strategic reorientation. Consequently, in comparison to conventional HRM methods, e-HRM may aid in streamlining transactional HRM operations, accelerating HR procedures, enhancing communication, reducing HR staff, and more accurately capturing, developing, and disseminating knowledge (Njoku et al., 2019).

Managers, staff members, and HR specialists may access and extract the data and information needed for managing the organization’s HR using the platform provided by the e-HRM (Bondarouk et al., 2017). With the help of e-HRM, managers can easily gather crucial data and information, carry out analyses, make decisions, and communicate with coworkers. Employer handbooks, safety protocols, and emergency evacuations are just a few examples of the HR-related data, information, and records that e-HRM enables firms to handle electronically (Johnson et al., 2016). Employees are empowered through e-HRM to take ownership of a significant portion of information, which fosters a feeling of accountability and therefore enhances the quality of HR services (Alshibly, 2014). Additionally, the adoption of e-HRM and ongoing HR technology innovation have allowed HR practitioners to focus on value-added services for workers and company success, which has decreased the likelihood of judgment mistakes (Azizi et al., 2021).

The COVID-19 pandemic has highlighted the necessity of reforming HRM practices (Janadari, 2020). Training and assisting employees in their adaptation to the digital technology environment have been important functions of HRM during the digital transformation. The crisis has required employees to have the technological skills to be productive remotely (Hamouche & Chabani, 2021). Similarly, HRM’s function was to act as a change agent, continually coordinating and constructing the dynamics between employees and management to guarantee that operations were running smoothly (Azizi et al., 2021). Additionally, HR professionals channel their energies into improving skills and empowering employee transformation to adapt to changing workplace practices, to be flexible, and take advantage of innovative new technologies. The latter is achieved with different sub-functions of e-HRM, such as e-communication, e-training, e-learning, e-recruiting, and e-performance appraisal (Nayak et al., 2022).

Employees in the remote e-working environment frequently need to transition to a new method of work and train themselves on new or different technical tools. In the context of e-HRM, e-training is one of the essential processes that a company may use to enhance the skills and capabilities of its workforce (Charalampous et al., 2020). Employee training promotes skill renewal, which enhances employee satisfaction, commitment to the business, and organizational performance. (Rysavy & Michalak, 2020). Physical presence at the workplace is not necessary, and the work location might be anywhere. This arguably increases the importance of the technology used to communicate with the workplace, including the e-HRM. Academics and practitioners alike consider e-HRM practices a valuable resource. Nonetheless, researchers have not yet investigated the relationship between e-HRM practices and remote e-working effectiveness. Based on the preceding discussion, the following hypotheses is suggested:

H₁: e-HRM practices positively affect remote e-working effectiveness.

2.3. Remote e-working job satisfaction

Job satisfaction is described as a favorable or enjoyable emotional state that emerges from an individual’s appreciation of his or her own job or experience (Locke, 1976). According to Landy (1999), it relates to a person’s positive and emotional attitude toward their work, the advantages they get, and the social, organizational, and physical components of their working environment.

Job satisfaction is a measure of how successfully an employee’s expectations are met, as well as a person’s general attitude towards their job (Aziri, 2011). Employees benefit from job satisfaction since it is connected to desired work behaviors and attitudes. Employees who are happy and satisfied with their employment outperform those who aren’t (Katebi et al., 2022).

Job satisfaction is one of the job behaviors that develops as a result of work experiences (Oluwatayo & Adetoro, 2020). Employees, according to Giri and Pavan Kumar (2010), will be devoted to their companies and satisfied with their occupations if they are happy with the nature of the work itself. Therefore, the most often cited benefit of remote e-working is increased job satisfaction (Battisti et al., 2022).

Researchers have argued that remote e-working gives employees more control over their interactions with others, lowers costs associated with working, reduces stress because managers and coworkers are less likely to interrupt, and allows them to better meet non-work-related family responsibilities (Ingusci et al., 2022; Taser et al., 2022). This reduces the likelihood of work-family conflict, which in turn increases job satisfaction (Irawanto et al., 2021). The number of days a person works remotely is positively correlated with their job satisfaction, according to research by Niebuhr et al. (2022). According to Zammitti et al. (2022), remote e-working has an impact on job satisfaction because it allows employees to tailor their work schedules to better accommodate their personal demands and family obligations.

In a study on remote e-working during the pandemic, Moens et al. (2022) discovered that nearly two-thirds of participants reported higher levels of work-life balance and job satisfaction. According to Felstead and Henseke (2017), despite the negatives of increased workloads and fewer prospects for advancement, e-workers reported higher levels of job satisfaction. Nonetheless, other studies have also claimed that e-workers are less satisfied with their jobs since it leads to fewer social interactions with supervisors and coworkers and increases feelings of loneliness (Donati et al., 2021). Additionally, inter-role conflicts, hidden overtime, combining private and work lives, or an inappropriate working environment at home, a lack of professional support, and a barrier to career progression all have a detrimental influence on job satisfaction (Charalampous et al., 2019). Working from home increases some expenses while also introducing new ones for the employee. As the costs of space and utilities are shifted from employers to employees when employees work from home, as well as the home office setup (technology, accountability, expenditures, and maintenance), this has sparked debate about whether organizations must support employees working from home in the medium- to long-term (Yang et al., 2021).

Because both positive and negative effects have been observed, the existing research on the impact of remote e-working on job satisfaction is still unclear. This study therefore suggests the following:

H₂: Remote e-working effectiveness positively affects job satisfaction.

E-HRM acts as a channel of communication between a firm and its employees; it gives employees the ability to independently follow HRM regulations through web-based channels (Ruël et al., 2007). One goal of e-HRM is to manage and improve working relationships by giving employees more control over their work environments.

Businesses are increasingly investing in e-HRM systems to create positive employment relationships by fostering confidence in institutional practices, policies, procedures, and systems (Iqbal et al., 2019). Work autonomy is made possible by e-HRM, which also supports employees’ well-being by giving them the freedom to work remotely (Azizi et al., 2021). As a result, it has a variety of positive effects on boosting employee satisfaction through remote e-working. An e-HRM system, for example, can provide employees with sufficient information on incentive distribution and how it relates to performance assessment. It also provides information on the desired behaviors, which are linked to employee consequences (Nurlina et al., 2020). As a result, we developed the following hypothesis:

H₃: e-HRM practices positively affect job satisfaction.

2.4. Organizational commitment

Organizational commitment is the term indicating one’s involvement with the company for which they work, and it is strongly tied to how well employees behave and perform (W. Wang et al., 2020). In HRM research, an attachment to or identification with the organization is the most common definition of commitment (Meyer et al., 2002). Such an attachment has a substantial correlation with employee behavior and performance (Hanaysha, 2016). In light of this, Allen and Meyer (1990) described it as the sentiment that an employee has to stay with the company. Gill-Simmen et al. (2018) defined it as the degree of a person’s identification with and involvement in a certain organization. Meyer et al. (2002) characterized organizational commitment as a person’s alignment with the values and objectives of the organization, their desire to carry out tasks, and their demonstration of efforts on behalf of the organization. As organizational commitment grows, so does organizational learning and success (Khajuria & Khan, 2022).

Meyer and Allen’s (1991) three-component model of affective, continuance, and normative commitment is often used in organizational commitment research. According to the model, affective commitment is an employee’s emotional attachment to a company. Employees who have higher degrees of affective commitment to their employers wish to stay with them because of the desire they feel to work there. The employees’ willingness to continue in the company in light of the costs involved in quitting the company is referred to as their “continuance commitment.” Because quitting the company would be expensive, employees who exhibit a high level of continuing commitment tend to stay (Galanaki, 2019). Finally, normative commitment is defined as the “obligation to remain in the company” (Mercurio, 2015, p. 396), which means that individuals who demonstrate great normative commitment believe they have a duty to work for their employer (Khajuria & Khan, 2022).

According to HRM literature, there are several reasons why managers should support organizational commitment. Both high staff productivity and the risk of undesired employee turnover are influenced by organizational commitment (Mercurio, 2015). By increasing organizational commitment, businesses can improve workforce stability and reduce worker churn (Galanaki, 2019).According to Lamba and Choudhary (2013), devoted employees perform better because they feel better emotionally and physically, and they disseminate their devotion by creating a more positive working environment for their colleagues.

In terms of satisfaction, previous studies show a positive relationship between job satisfaction and organizational commitment (Markovits et al., 2010). Organizational commitment can be seen as an extension of job satisfaction, as it deals with an employee’s favorable attitude toward the company rather than her own work, organizational commitment can be seen as an extension of job satisfaction. The total impact size between work satisfaction and organizational commitment is statistically significant, according to a meta-analysis of 7.218 research papers done by Çınar et al. (2022) Job satisfaction has more capacity to favorably affect organizational commitment. With regard to remote e-working, it’s critical to comprehend how COVID-19ʹs widespread shift to remote e-working and the growing popularity of hybrid work practices in businesses may impact the connection between job satisfaction and organizational commitment. We thus proposed the following hypotheses:

H₄: Job satisfaction positively affects organizational commitment.

2.5. The mediating role of job satisfaction

The relationship between e-HRM practices, remote e-work effectiveness, and organizational commitment is not clear and has not been assessed yet. Studies that examined how organizational commitment might be influenced by work design and flexible working arrangements generally revealed a positive relationship between these variables (Ahamad et al., 2022; Choo et al., 2016). In the context of remote working, organizational commitment can be seen as an emotional response to a positive appraisal of the flexible working arrangements. According to a Gallup International Association (2020), employees who work remotely for 60% to 80% of the time are more likely to be engaged, dedicated, and inspired at work. Employees who are engaged remotely are those who, even in a distant situation, demonstrate a high level of personal dedication to their employer’s goals, principles, and values (Gallup International Association, 2020).

There is a relationship between remote e-working and organizational commitment, and it has been shown that these practices have the ability to lower turnover intentions (Choi, 2019). These conclusions are supported by a review of the literature by Vleeshouwers et al. (2022), who also found that flexible working arrangements had a positive effect on organizational commitment. During the COVID-19 outbreak, the work flexibility offered by remote e-working arrangements may have enhanced workers’ perceptions of organizational support for managing the interface between their professional and personal lives (Franken et al., 2021).

Organizational commitment is defined in the HRM literature as an employee’s response to HR practices (Aydoğan & Arslan, 2020). In particular, HRM practices are likely to create work conditions and an environment where employees become strongly committed to the business and try their best to achieve the organization’s goals, while lowering absenteeism and turnover rates (Devananda & Onahring, 2019). E-HRM practices can provide a unique and effective method for carrying out HRM processes with greater accuracy and efficiency, thereby increasing labor productivity (Hoq, 2021; Siregar, 2022). Furthermore, e-HRM offers a variety of services, such as employee self-service and information exchange (Parry & Tyson, 2011); the availability of e-communication improves information exchange and gives timely information. Similarly, the adoption of e-HRM may improve the service offered to employees by allowing them remote access to HR databases, which helps them make decisions and improves information sharing (Jawaad et al., 2019).

According to the previous discussion, remote e-work effectiveness and e-HRM practices appear to have a major impact on organizational commitment. However, a number of authors have asserted that job satisfaction is particularly important for comprehending the impact of numerous other factors on organizational commitment (Haar & Brougham, 2022). According to causal models of organizational commitment, job satisfaction may operate as a mediator for the impact of numerous antecedents on commitment (Aruldoss et al., 2020; Haar & Brougham, 2022; Jawaad et al., 2019). The current study will investigate the extent to which job satisfaction may mediate the causal relationships between organizational commitment and e-HRM practices and remote e-work effectiveness variables. Hence, the following is hypothesized:

H₅: Job satisfaction mediates the relationship between remote e-work effectiveness and organizational commitment.

H₆: Job satisfaction mediates the relationship between e-HRM practices and organizational commitment.

3. Methodology

3.1. Sample and procedures

The data used for this research were collected from participants from 25 commercial banks in Jordan using a self-administrated electronic questionnaire and the connivance-sampling method. Specifically, Google forms and a snowball sampling method were used to collect 384 responses from employees who practiced remote e-working during and after the COVID-19 pandemic. The link to the electronic questionnaire was delivered to e-workers via social media or email, and they were then asked to share it with any coworkers or other e-workers they knew in order to boost the sample size.

The respondents were asked whether they had engaged in remote e-working over the previous five months. Participants who have never worked remotely were not included in the survey. Those who chose not to answer any of the questions or gave the same answer to all of the scale questions were also excluded. Consequently, the final data set yielded 273 legitimate responses for further examination. Of the 273 respondents who completed the online questionnaire, 173 (63.3%) were males and 100 (36.7%) were females, and 92.4% had completed college education or above. With respect to work experience, 62 % had more than 10 years’ experience.

3.2. Measures

A survey instrument using previously validated measures borrowed from previously published and validated scales was developed to measure the study model and hypotheses (Hair et al., 2021). The questionnaire was developed in English and then translated into Arabic by the authors; any amendment required to fit the instruments to the specific context of the Jordanian banking sector was appropriately performed, and all questions were stated positively. An expert panel of three experts who were fluent in both Arabic and English then checked the survey instruments. The experts examined the measurement items for similar content, ensuring that they were clear, consistent with the proposed dimensions, easy to complete, and appropriate for the remote e-working context.

Based on the feedback received, any measurement item that would cause confusion or was deemed potentially difficult to understand was deleted. Furthermore, prior to hypothesis testing, we conduct a PLS-SEM analysis to evaluate the measurement model, including individual item reliability, internal consistency, and discriminant validity of the measures. At the start, any construct items that did not meet the minimum acceptable level of average variance extracted (AVE) or composite reliability were deleted (Sarstedt et al., 2021). The items were removed from the construct until it met the minimum acceptable level of AVE and composite reliability (Hair et al., 2021). In particular, the five-item scale used to measure e-HRM practices (e-HRMP) was adapted from (Farhan et al., 2021; Iqbal et al., 2019). To measure the remote e-work effectiveness construct (RWOE), a four-item scale was adapted from instruments developed by Grant et al. (2019). The job satisfaction (SATISF) construct was assessed using a four-item scale adapted from the job satisfaction scales developed by Brayfield and Crockett (1955) and Diener et al. (1985). A four-item measure adapted from Allen and Meyer (1990) and Jaros (2007) commitment scales measures organizational commitment (OCOMIT). To determine the respondent’s degree of agreement and disagreement with a particular statement, each of these items was scored using a 5-point Likert scale ranging from “strongly disagree” (1 point) to “strongly agree” (5 points). Measurement items are presented in Table 1

Table 1. Measurement items

Construct	Survey items	Source
e-HRM practices (e-HRMP)	E-HRMP_1: During remote e-working, E-HRM has enabled me to obtain relevant information on a wide range of issues important to my work. E-HRMP_2: During remote e -working, E-HRM has helped me communicate with my colleague more effectively. E-HRMP_3: During remote e-working, our organization utilized e-HRM for online training and learning. E-HRMP_4: During remote e-working, our organization utilized e-HRM to effectively handle official grievances and complaints. E-HRMP_5: e-HRM is being utilized for performance evaluation in our organization during remote e-working.	Iqbal et al., 2019 and Farhan et al. (2021)
Remote e-work effectiveness (RWOE)	RWOE _1: I can concentrate better on my work tasks while I work remotely. RWOE _2: My ability to work remotely has enhanced my overall job productivity. RWOE _3: When I work remotely, I have a good work-life balance. RWOE _4: Remote e-working makes me more productive in meeting my major objectives and deliverables.	Grant et al. (2019)
Job satisfaction (SATISF)	SATISF _1: I feel fairly satisfied with my present job. SATISF _2: The conditions under which I do my work are excellent. SATISF _3: I am satisfied with the type of work I do. SATISF _4: I find real enjoyment in my work.	Brayfield and Crockett (1955); Diener et al. (1985)
Organizational commitment (OCOMIT)	OCOMIT_1: I would be very happy to spend the rest of my career with this organization. OCOMIT_2: I really feel as if this organization’s problems are my own. OCOMIT_3: I am loyal to this organization because I have invested a lot in it, emotionally, socially, and economically. OCOMIT_4: My organization deserves my loyalty because of its treatment of me.	Allen and Meyer (1990) Jaros (2007)

4. Analysis and results

The partial least squares structural equation modeling (PLS-SEM) method was used for the statistical analysis (Ringle et al., 2015). We initially examined the measurement model to investigate the validity and reliability of each of the constructs. The structural model was then evaluated to assess the hypothesized relationships between the constructs as recommended by Sarstedt et al. (2021) and Hair et al. (2021). Finally, because Preacher and Hayes (2008) technique is the most exact way of examining mediating effects and is more suitable for use with PLS-SEM (Hair et al., 2021), we conducted mediation analysis using this method.

4.1. Measurement model testing: reliability and validity

The measuring model’s internal consistency reliability, convergent validity (Table 1), and discriminant validity (Table 2) were all evaluated.

Table 2. Individual Items factor loadings, reliability, VIF, and convergent validity

Latent variable	Indicators	VIF	Convergent validity		Internal consistency reliability
			Factor Loading	AVE	Cronbach’s Alpha	CR	rho_A
		≤ 5	> 0.70	> 0.50	0.70–0.90	> 0.70	> 0.70
e-HRMP	e-HRMP_1	2.646	0.783	0.611	0.845	0.887	0.863
	e-HRMP_2	2.911	0.770
	e-HRMP_3	2.503	0.775
	e-HRMP_4	2.457	0.845
	e-HRMP_5	2.076	0.732
RWOE	RWOE _1	4.529	0.884	0.658	0.835	0.884	0.851
	RWOE _2	4.301	0.813
	RWOE _3	3.475	0.845
	RWOE_4	1.163	0.700
SATISF	SATISF _1	2.114	0.835	0.675	0.839	0.892	0.844
	SATISF _2	1.989	0.802
	SATISF _3	2.071	0.861
	SATISF _4	1.669	0.786
OCOMIT	OCOMIT_1	3.908	0.911	0.721	0.868	0.911	0.882
	OCOMIT _2	2.643	0.832
	OCOMIT _3	1.457	0.731
	OCOMIT _4	3.145	0.910

Internal consistency Cronbach’s alpha (0.70–0.90), rho A coefficient reliability (> 0, 7) and composite reliability (CR) (> 0, 7) were used to assess construct reliability (Hair et al., 2021). The results in Table 2 reveal that all of the constructs are internally consistent and reliable. Individual item loadings and average variance extracted (AVE) with a cut-off criterion value of 0.50 or above were used to assess convergent validity (Sarstedt et al., 2021). Table 1 shows that the AVE values for all constructions are greater than 0.50. As a result, this gives evidence for the measures’ convergent validity.

The discriminant validity is assessed using the Fornell and Larcker (1981) criterion and the heterotrait-monotrait (HTMT) correlation ratio (Henseler et al., 2015). The square root of the AVE, as indicated in Table 3, exceeded the correlations between all pairs of components (Fornell & Larcker, 1981).

Table 3. Fornell-Larcker Criterion Discriminant Validity

Latent variable	OCOMIT	e-HRM Practices	RWOE	SATISF
OCOMIT	0.849
e-HRMP	0.367	0.782
RWOE	0.736	0.302	0.811
SATISF	0.781	0.428	0.711	0.821

Note(s): The data on the diagonal (in italic) is the square root of AVE of the construct while the other values are the correlations with other constructs. *P < 0.001

Table 4 demonstrates that the HTMT ratios between constructs are less than 0.85 and the upper bounds of the HTMT confidence interval (UB95) are less than one (Sarstedt et al., 2021), indicating discriminant validity. In summary, the aforementioned analysis shows that the research constructs’ reliability and validity are established and that the measurement model is appropriate for structural analysis.

Table 4. Discriminant Validity Using the HTMT Ratio

	SATISF	OCOMIT	RWOE	e-HRMP
SATISF
OCOMIT	0.814 (UB95: 0.833)
RWOE	0.842(UB95: 0.809)	0.786(UB95: 0.834)
e-HRMP	0.488(UB95: 0.577)	0.407(UB95: 0.498)	0.275(UB95: 0.371)

Note: UB95: represents the upper bounds of the 95% confidence interval

4.2. Structural model assessment

PLS-SEM was also used in this study to identify structural relationships between different constructs and their effects and to test hypotheses for this study. The variance inflation factor (VIF) values of each set of predictor constructs in the structural model are first checked for collinearity problems. If the VIF values are greater than five, it means that there are problems with collinearity between the predictor variables (Hair et al., 2021). As shown in Table 2, the values of the VIF range from 1.163 to 4.529 in Table 1, indicating that the structural model is free of collinearity issues.

The path coefficient estimates of the structural model were then examined. The main standards used were the coefficient of determination (R²) for predictive accuracy, the strength of the relationship (path coefficient (β), the (f²) effect size, and the cross-validated redundancy index (Stone-Geisser’s Q²) for the predictive relevance of the model.

The explanatory power of the model is assessed by the coefficient of determination (R²), which calculates the variance in each of the endogenous constructs explained by the explanatory variables (Hair et al., 2021). Sarstedt et al. (2021) state that the R² value ranges from zero (0) to one (1), with a higher R² indicating a higher level of predictive accuracy. R² values range between 0.75, 0.50, and 0.25, which indicate substantial, moderate, and weak values, respectively. As shown in Table 5, The R² values of e-HRMP and RWOE were reported (0.091), which is considered weak but still satisfactory. Meanwhile, the R² values of e-HRMP, RWOE, and SATISF were reported (0.636), which is considered moderate, and the R² values of SATISF and OCOMIT were reported (0.776), which is considered substantial.

Table 5. Hypothesis testing summary

							Bias CI
Hypothesis	β	t-value	p -value	ƒ^2	R^2	Q^2	2.5%	97.5%	Support
H1: e-HRMP—> RWOE	0.302	6.363	0.000	0.101	0.091	0.034	0.199	0.384	Yes
H2: RWOE -> SATISF	0.705	7.422	0.000	0.243	0.635	0.419	0.667	0.741	Yes
H3: e-HRMP -> SATISF	0.215	7.151	0.000	0.115			0.153	0.27	Yes
H4: SATISF -> OCOMIT	0.881	8.070	0.000	0.466	0.776	0.543	0.858	0.898	Yes

The second evaluation is path coefficients (β) values, β vary in values from −1 to +1 and are used to assess relationships between constructs, β values are considered to be the weakest for coefficients that are closest to zero (Hair et al., 2021). The results in the table showed the most essential β of SATISF on OCOMIT (0.881), followed by the β of RWOE on SATISF (0.705), then the β of e-HRMP on RWOE (0.302), and the lowest in the β of e-HRMP on SATISF (0.215).

Using ƒ² effect sizes, the third criterion is the size of the prediction between the predictor factors and the dependent variable. A change in the R² values following the removal of a specific variable from the model is evaluated using the ƒ² effect sizes (Hair et al., 2021). ; asserts that ƒ² effect size values of ≥ 0.02 indicate that there is no effect; the ƒ² values higher than 0.02, 0.15, and 0.35 depict small, medium, and large ƒ² effect sizes. as shown in Table 5 the ƒ² effect values for this study fall within the acceptable range. The lowest ƒ² value was of e-HRMP → RWOE (ƒ² = 0.101) and e-HRMP → SATISF (ƒ² = 0.115) which correspond to medium effect size, the effect sizes ƒ² of RWOE → SATISF is large (ƒ² = 0.363), likewise, it is obvious that SATISF (ƒ² = 0.466) has a large influence in producing the R² for OCOMIT.

The model’s predictive relevance (Q²) is calculated in order to determine the model’s predictive accuracy, which is the fourth requirement. The Q² measures the accuracy of the path model’s predictions of the initially observed data (Hair et al., 2021, p. 183). Hair et al. (2021) added that Q² values greater than zero reflect the model’s predictive relevance; if not, it may not be possible to draw that conclusion. The Q² statistics in this study were calculated using the blinding method with an omission distance of seven (Hair et al., 2021). The results revealed that the Q² values for OCOMIT (Q² = 0.543), SATISF (Q² = 0.419), and RWOE (Q² = 0.034) were greater than zero. Therefore, these Q² values establish the strong predictive relevance of the model.

The last step in structural model assessment is testing the hypothesized relationships between the constructs by determining the significance of the path coefficients using a bootstrapping approach with 5,000 subsamples as recommended (Hair et al., 2021). Through the bootstrapping technique, the significance of path coefficients is determined. If the empirical t-values are greater than the critical values for the t distribution, the coefficient is deemed significant at a given probability of error. This study used critical values for one-tailed tests: 1.65 (significance level = 5%; Hair et al., 2021).

The path coefficients given in Table 5 show that all t-values in the model’s relationships between the constructs are greater than 1.65, all p-values are lower than 0.05, and the confidence interval between the results, when bias is corrected, is between 5% and 95%, which does not include zero. The findings reveal that e-HRMP (β = 0.302, t = 6.363, p = .000) has a positive and significant impact on RWOE. Similarly, RWOE (β = 0.705, t = 7.422, p = .000) and e-HRMP (β = 0.215, t = 7.151, p = .000) have significant effects on SATISF. Furthermore, SATISF (= 0.881, t = 8.070, p = .000) has a statistically significant positive effect on OCOMIT. Hence, the findings lend support to our H1–H4 hypothesis.

4.3. Job satisfaction mediation analysis

Using the Sarstedt et al. (2021) recommended approach to assess mediation effects on PLS-SEM, we investigated the SATISF association with both RWOE and e-HRMP; Table 5 shows that SATISF is both positively and significantly associated with both RWOE and e-HRMP. Then, we used Preacher and Hayes (2008) methods to explore the mediating influence of job satisfaction. According to these authors, the mediating effect requires that the indirect effect be significant and that the confidence interval not contain zero. Table 6 shows that the specific indirect effects of both RWOE and e-HRMP are significant; their confidence intervals do not contain zero. The specific indirect effects of RWOE and e-HRMP are p > 0.05. Thus, SATISF mediates relationships between RWOE, e-HRMP, and OCOMIT. Thus, the H5 and H6 hypotheses are supported.

Table 6. Specific indirect effects

	Sample Mean (M)	Standard Deviation	T	P	Confidence Intervals
					2.5%	97.5%
RWOE -> SATISF -> OCOMIT	0.622	0.018	33.997	0.000	0.587	0.654
e-HRMP -> SATISF -> OCOMIT	0.189	0.028	6.779	0.000	0.131	0.238

Bootstrapping based on n = 5.000 subsamples.*p ≤ 0.05

Figure 1 shows structural path coefficients and the results of structural model evaluation are given in Table 3.

Figure 1. Structural model with path coefficients.

5. Discussion and implications

The present study responds to recent calls to infer the impact of e-HRM practices and remote e-working effectiveness on organizational commitment (Janadari, 2020; Vyas, 2022), as well as expand remote e-working research (Adekoya et al., 2022; Battisti et al., 2022; Popovici & Popovici, 2020). Notably, the study analyzed the effect of e-HRM practices and remote e-working effectiveness on organizational commitment as mediated by job satisfaction.

As expected, the study results reveal that e-HRM practices are a significant predictor of the effectiveness of remote e-working, meaning that e-HRM practices promote employee perceptions of greater overall job productivity, improved work-life balance, and better adjusting work activities to match personal demands and family-related commitments, as well as improvements in their capacity to do their job efficiently. On the other hand, E-HRM practices improve remote e-working effectiveness by providing real-time information-based communication, an interactive work environment, e-training, and e-performance appraisal.

In addition, our results support the idea that e-HRM practices contributed to the enhancement of remote workers’ perceptions of work-life balance (Santhanam et al., 2021). It specifically adds to the literature that effective e-HRM practices aid in the integration of various aspects of one’s life, such as family and work, as well as minimizing tension between a person’s responsibilities to their family and professional commitments. Remote workers’ job productivity and work-life balance are influenced by the extent to which e-HRM practices enable them to obtain a wide range of information relevant to their work, maintain effective communication with colleagues, effectively handle their official grievances and complaints, better utilize online training and learning, and utilize e-HRM for performance evaluation. As a result, firms may increase the effectiveness of remote e-working by using high-quality e-HRM practices.

According to the findings of the present study, e-HRM practices positively and strongly affect job satisfaction in the context of remote e-working, which is consistent with previous studies in conventional HRM and the limited number of previous studies that have examined similar relationships (e.g., Iqbal et al., 2019; Nurlina et al., 2020). In a variety of ways, e-HRM practices may improve employee satisfaction with remote e-working. Employees, for example, can obtain adequate information from an e-HRM system regarding a wide range of work-related issues that are linked to employee consequences (Nurlina et al., 2020). Our study findings also indicate that e-HRM practices positively increased the employee’s satisfaction with work conditions, the type of job they do, and their sense of enjoyment. The findings also revealed that e-HRM practices might help those employees who have low job satisfaction by facilitating effective communication between them and their colleagues and effectively handling their grievances and complaints.

Consistent with previous research (e.g., Zöllner & Sulíková, 2021), our study confirms that the effectiveness of remote e-working positively and strongly affects job satisfaction. The findings show that since remote e-working gives employees more control over how much time they devote to work and family life, remote e-working improves employee focus levels while they are working from home. Their satisfaction is therefore increased. The results show that remote working improves employee focus levels while they are working remotely due to the ability to schedule time for both work and family life. Additionally, we found that remote e-working enables businesses to be flexible while also addressing their workers’ well-being, including work-life balance, all while lowering business costs and increasing job satisfaction.

Furthermore, we found that job satisfaction is a significant predictor of whether remote work enhances organizational commitment. As predicted, satisfied remote workers did report high levels of organizational commitment. The results indicate that when remote e-working is part of a suitable work arrangement, it generates a feeling of satisfaction and enhances employees’ organizational commitment. Employees will feel more emotionally connected to the organization and more obligated to remain in the organization as a result. This suggests that the company’s consistency in maintaining and improving job satisfaction is the key to raising organizational commitment among its employees.

Job satisfaction has been found to be particularly important for understanding the effects of various antecedents on organizational commitment (Haar & Brougham, 2022; Jawaad et al., 2019). Yet, the mediating effect of job satisfaction on the relationships between remote e-working effectiveness and e-HRM practices on organizational commitment has not been examined before. Our findings show that remote e-working effectiveness and e-HRM practices have a positive and significant impact on organizational commitment, and that this relationship is strengthened when it is mediated by job satisfaction. This study, therefore, contributes to the growing remote e-working and e-HRM literature by establishing and explaining the relationship between these constructs.

In the remote e-working environment, digital technologies help release work from a fixed location. It can now be completed electronically from a broad range of physically and temporally dispersed locations (Donnelly & Johns, 2021). It often means employees switching to a different style of working. It implies that employees must expand their knowledge as well as learn new or different technological tools in order to succeed in their current environment. e-HRM promotes innovation in training methods and content, helps employees improve their competences and skills, reduces psychological stress, and facilitates virtual communication. Consequently, it boosts employee satisfaction. Furthermore, e-HRM strengthens employees’ bonds with the firm and establishes a strong organizational commitment.

Consistent with this study’s proposed hypothesis, we found that remote e-working effectiveness’s effect on organizational commitment is mediated by job satisfaction. Prior studies have suggested that remote e-working has benefits and drawbacks for organizational commitment (Charalampous et al., 2019). The study’s findings imply that by implementing effective remote e-working practices, the benefits of remote e-working will outweigh the downsides as long as organizational commitment is not jeopardized. As a result, businesses must mitigate the negative effects of remote e-working while boosting the benefits of remote e-working for their employees. Because remote e-working entails the use of ICT, managers must provide employees with tools that not only increase job productivity but also aid in the enhancement of work-life balance when e-working remotely. Furthermore, in order to reduce the potential negative aspects of remote e-working, employee satisfaction must be taken into account. There are several ways to accomplish this, such as by trying to instill a sense of obligation in e-workers by maximizing the benefits employees will receive from remote e-working.

This research contributes to the theory by providing a structure for understanding the effect of e-HRM practices and remote e-working effectiveness on organizational commitment. Thus, our study advances the theoretical development in the area of e-HRM practices and remote e-working effectiveness, serving as a basis for future research in these fields.

6. Conclusions

Organizations recognize that after COVID-19, remote e-working will be the new arrangement of work for a sizable portion of their workforce. This could be an entirely remote or hybrid form. Due to these new possibilities, this study attempted to unlock the “black box” of remote e-working effectiveness and e-HRM practices by identifying theoretically and empirically the path through which remote e-working effectiveness and e-HRM practices may deliver value to the organization via the mediation of job satisfaction.

Organizations should generally embrace and manage remote e-working with the understanding that certain prerequisites can ensure that the benefits of remote e-working exceed the drawbacks. e-HRM practices and the effectiveness of remote e-working are important keys in the consecution of organizational commitment. When e-HRM practices are developed or improved, they should take into consideration remote e-working effectiveness. Our findings have provided practitioners with more information about the factors that may be prioritized to increase the success of remote e-working, e-HRM practices, and employee commitment to remote e-working.

7. Limitations and future research avenues

Despite this study’s obvious theoretical and practical implications, it is important to state some limitations that emerged in this research, which suggest avenues for future research.

Similar to any other research, our study has some limitations that must be considered when interpreting its results. These constraints present opportunities for future researchers seeking to understand the relationship between the effectiveness of remote e-working, e-HRM practices, and organizational commitment. This study was done in the context of banks in Jordan and a specific type of remote worker working at home, which therefore reflected the perspectives of a specific category of employees in a specific sector whose nature of work is unique to that sector and does not reflect the views of employees in other sectors. Thus, a certain level of caution may be required in generalizing the study results to different contexts. Further research is needed to validate the model proposed and tested in this study in other industry sectors such as insurance, telecommunications, and other services. A cross–cultural study could also be conducted to identify differences in conceptualizations of the effectiveness of remote e-working, e-HRM practices, and organizational commitments due to cultural effects. It is also interesting to consider the role of work experience. Future studies may adopt a more systematic sampling approach in order to investigate whether those who have never worked in “real” banking will get committed in the same way as those who have already worked. This study is limited in that it employed a convenience-sampling method to collect data. A random sample would have improved the results’ generalizability.

Another limitation was the measures used to collect the data because there are a limited number of validated and reliable scales for organizational commitment in a remote e-work context. To the best of researchers’ knowledge, there are no measures tailored towards assessing the organizational commitment of remote e-workers, and the available measurements of organizational commitment were developed for employees working in conventional work settings. It is possible that these instruments exclude variables that would enable organizations to detect and manage any issues raised by remote e-working, enabling organizations to develop an organizational commitment. Future research may valuably validate and develop organizational commitment instrument in the context of remote e-working.

Previous research found that it is important to evaluate and classify employees based on individual characteristics for implementing best e-HRM practices (Zhou et al., 2022). This is because the employee’s characteristics influence the perceptions of and reactions to an organization’s e-HRM. Hence, the same e-HRM practice can be interpreted in different or even contrary ways, and it is individuals’ perceptions of this system that are most relevant to individual-level attitudinal and behavioral outcomes (Alshibly, 2014). In the case of our study, this would not be possible because it seems to be slightly outside the scope of this study. We believe it is important that future studies take into consideration, with a more specific research design and a more representative sample, classifying employees based on their individual characteristics for the purposes of implementing best e-HRM practices.

In fact, organizational commitment and job satisfaction have garnered a lot of attention in workplace studies. This is because it is well acknowledged that these variables can be key predictors of organizational effectiveness. For that reason, many antecedents of job satisfaction and organizational commitment have been suggested in the earlier studies, including the work environment, organizational culture, and leadership. Many antecedents of job satisfaction and organizational commitment have been suggested in earlier studies (Sousa-Uva et al., 2021). For example, Sousa-Uva et al. (2021) found that the work environment and organizational culture play a crucial role in affecting teleworker satisfaction. Sinclair et al. (2021) found transformational leadership to be an effective tool for managing and motivating the remote employee. However, the influence of e-HRM practices, remote e-work effectiveness, and their subsequent effects on employee satisfaction and organizational commitment were not explored. As a result, this research concentrated only on these factors. However, for future research, other variables, such as organizational culture, work environment, organizational culture, e-HRM quality, different types of leadership, and empowerment, could be considered mediators in the relationship between the effectiveness of remote e-working, e-HRM practices, and organizational commitment. In addition, the study can be further enhanced by including moderating variables such as age, gender, and so on, to gain a thorough understanding and exploration of the other influential factors. Additionally, future research may examine a broader set of businesses and industries. Finally, it is also recommended to reexamine the same model on a longitudinal basis, as attitudes and behaviors may change over time in a remote e-working context.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

The authors received no direct funding for this research.

Notes on contributors

Haitham H. Alshibly

Haitham H. Alshibly is Professor of Management Information Systems at Al Balqa Applied University, Jordan. He received his BSc and MBA from the University of Jordan and his PhD in information systems from the University of Newcastle, Australia. He is the vice president of quality assurance and center affairs at the moment. Professor Alshibly has been actively pursuing research related to customer empowerment, e-commerce, s-commerce, e-government, e-marketing, and decision support systems, as well as EDMS evaluation and adoption. He has published over 100 papers in the form of books, book chapters, journal articles, and conference papers, among others.

Khalid N. Alzubi

Khalid N. Alzubi is an associate professor of management information systems at Al Balqa Applied University, Jordan. He received his BSc from the University of Jordan and his PhD in management information systems from Sheffield Hallam University, UK. Dr. Alzubi is the Dean of Students Affairs at the moment. He has contributed more than 20 research publications presented in international and national journals.