The interrelations between micro-level CSR,Job engagement and organizational engagement during the COVID-19 pandemic: A PLSpredict model assessment

Abstract

BACKGROUND:

Amid the mounting COVID-19 situation, we take up the opportunity to examine micro-level CSR practices as an internal strategic approach for employees’ engagement to assist organizational resiliency. Past research had documented the Matthew effects of engaged employees and the fatal threat of disengaged employees. However, little is known to the precise outcome of job engagement and organizational engagement.

OBJECTIVE:

This study endeavors to offer comprehensive findings on job engagement and organizational engagement through the antecedent of micro-level CSR practices. Additionally, job engagement was modelled as the mediator between micro-level CSR practices and organizational engagement. Stakeholder Theory, Social Exchange Theory and Engagement Theory guided the development of the hypotheses.

METHODS:

Quantitative judgmental sampling technique was employed to reach out to the targeted respondents. A total of 336 responses was collected for statistical analysis facilitated by partial least squares structural equation modeling (PLS-SEM) approach.

RESULTS:

The study revealed that employees’ involvement and working environment are positively influencing job engagement and organizational engagement while the others micro-level CSR practices demonstrated mixed results. Also, job engagement was found to mediate the relationships between the four dimensions of micro-level CSR practices (i.e., employees’ involvement, employees’ empowerment, work-life balance and working environment) and organizational engagement.

CONCLUSIONS:

Micro-level CSR practices positively affecting job engagement and organizational engagement with different degree of influences. Organizations could consider implementing micro-level CSR practices for enhanced job engagement and organizational engagement to ease the challenging moment during uncertainty.

Keywords

Micro-Level CSR job engagement organizational engagement PLSpredict mediating role

Mei Peng Low is an Assistant Professor in Faculty of Accountancy and Management, Universiti Tunku Abdul Rahman (UTAR). She holds a PhD in Organizational Behavior. Her core research interests lie in employee-centered social responsibility, organizational behaviour, and digital transformation. Her work on employee-centered CSR has been published in several the reputable journals (e.g., Business Ethics, Environmental Responsibility Journal; Social Responsibility Journal; Quality and Quantity). Apart from that, she is the reviewer for a few High Impact Journals. She has worked with numerous government agencies for research grant and consultancy as such Institut Masa Depan Malaysia (MASA) and Malaysian Technology Development Corporation Sdn Bhd (MTDC).

Dr. Mumtaz is an Associate Professor of Human Resource Management at the NUST Business School (NBS), Islamabad, Pakistan. He holds a Ph.D. in Management, MBA in Human Resource Management, and MS in Human Resource Development. Mumtaz has published in several international refereed journals (ABS, SCOPUS and ISI Web of Science Indexed) and presented at several conferences in locally and abroad. One of his articles was selected as an Outstanding Paper in the 2018 Emerald Literati Awards. Currently, he is the Managing Editor of the Journal of Applied Structural Equation Modeling and the Guest Editor of several international journals, including the International Journal of Manpower, Electronic Journal of Applied Statistical Analysis, The Bottom Line, Journal of Internet Commerce, and Journal of Marketing Analytics. He also serves as a reviewer for several international journals and member of organizing committees for several conferences of repute.

1 Introduction

COVID-19 has been an unprecedented catastrophe to all industries and individuals worldwide. Since mid-March 2020, many parts of the world went into lockdown, while others implemented a restricted movement order [1]. Non-essential businesses were mandated to cease operations, which led to widescale business disruptions that have scarred the economy [2]. Despite the administration of the vaccine, COVID-19 cases continue to spike; as of September 2022, the virus has taken 6.54 million lives [3]. The hike in cases is caused by the COVID-19 virus mutation while the vaccination research fails to keep up with the speed of mutation. This signifies that the battle against this pandemic may prevail for some time. Organizations’ responses to the profoundly disrupted business activities and the national economic situation are urgently called for with revitalization strategies [4]. The evidence of the desirable outcomes of micro-level CSR practices in past studies (e.g., Low & Spong [21], Jamali et al. [10], Mory et al. [11]) motivated this study to investigate its impact as a frugal fix during a crisis context.

From the strategic management perspective, corporate social responsibility (CSR) has a protagonist role to play by offering a conservative revival. Matten and Moon [5] explained that today’s corporations are vehicles for change which transform CSR with an emphasis on sustainability. While many past CSR initiatives have been linked to external stakeholders at the firm-level based on social, environmental, and financial performance indicators [6], which is called macro-level CSR, it is time to extend CSR efforts to more pertinent stakeholders –employees [7], i.e., micro-level CSR practices. Micro-level CSR refers to activities devoted to enhance employees’ physiological and psychological welfare. When the internal resource of the organization is in top-notch condition, it would then translate into the driving force of the organization’s success and resiliency. Many researchers (e.g., Piao, & Managi [8], Yasmeen, Yasmeen, & Zahra, [9]) have consistently claimed the importance of employees’ well-being in any organization’s achievement. The implementation of micro-level CSR also comes with manifold benefits such as discharging the role of a responsible employer.

Therewith, this study is set to answer the core research question of whether micro-level CSR practice would produce a more engaged workforce in times of crisis. Specifically, what is the influence of micro-level CSR practices on job engagement and organizational engagement; and would job engagement mediates the relationship between micro-level CSR and organizational engagement? We believe that micro-level CSR practices offer dual benefits to employees and organizations during the pandemic. This study aspires to accomplish three objectives. The first objective is to examine the distinct effects of the five dimensions of micro-level CSR (employee empowerment, employee involvement, employment stability, working environment, and work-life balance) on job engagement, while the second objective examines the influence of these dimensions on organizational engagement. The third objective investigates the mediating effect of job engagement on the connection between micro-level CSR practices and organizational engagement.

In addressing these three research objectives, this study bridges the existing research gaps in four ways. First, it highlights the importance of micro-level CSR, which concerns the welfare of the employees. Micro-level CSR practices are deemed timely and appropriate at this juncture because they are a form of internal strategic management without external assistance, which is scarce during a global crisis. In fact, Low and Siegel [7] expounded on the emergence of micro-level CSR as a new frontier of CSR research with an upward trend in employee-centered CSR research recently. Low and Spong [21] testified the positive outcomes of micro-level CSR on employee engagement while Jones et al. [12] also asserted the need and the importance of multilevel insights. However, most CSR research has predominantly focused on macro-level CSR activities (e.g., Ye et al. [13]), which involve a vast group of external stakeholders at the firm-level. Our study seeks to showcase the importance of micro-level CSR practices in contributing to organizational success through the employee-centered approach.

Second, this study investigates the execution of micro-level CSR practices for business resilience in an unprecedented pandemic situation. In the fight against COVID-19, many organizations have been ordered to close and/or adopt a new set of standard operating procedures (SOP). The pandemic has caused many unique phenomena to surface, be it individuals or organizations [85]. The predicaments that organizations encounter in this context uniquely differ from the conventional environment of perennial competition, which has been the common theme of employee-centered CSR research. For example, Golob and Podnar [14] studied the role of internal CSR for cooperating marketing purposes, Goergen et al. [15] investigated internal CSR for firm propensity, Donia et al. [16] examined how employee-centered CSR initiatives attract the millennials, and Merriman et al. [17] investigated the incentives of micro-level CSR for organizational sustainability. These studies were conducted during the typical business cycle when micro-level CSR practices were considered to outdo rivals in reputation, talent attraction, and sustainability. Unlike these studies, our work investigates micro-level CSR practices in an unprecedented context. In parallel, Conley and Johnson [18] highlighted that the past is the future for the period of COVID-19 research in the social sciences. In this regard, we supplement the existing literature by enriching our understanding of micro-level CSR practices during the pandemic through insightful findings.

Third, this study considers employee engagement comprises of two distinguishable categories: job engagement and organizational engagement. Based on our recent engagement literature review, we observed that researchers have often studied the concept of employee engagement as a single construct (e.g., Saks et al. [89], Bapat & Upadhyay, [19], Gupta, [20], Low & Spong, [21]) without differentiating job engagement from organizational engagement. Job engagement or work engagement refers to a state of dedication, vigor and absorption at work in the context of high job demands [21]. On the other hand, organizational engagement connotes employees’ complete involvement of themselves with the organization, as governed by organizational objectives and values [23]. Therefore, by examining job engagement and organizational engagement distinctively, this study stands out from previous studies and complements the existing literature with more informative findings.

The fourth contribution arises from its utilization of the latest social science statistical approach in explanation and prediction assessment. Traditionally, social science research draws on the explanatory approach by testing and quantifying the causal relationships for generalization from a sample to the population of interest [24]. The current study advances the dichotomy of the explanation and prediction method by offering causal relationship explanations as well as out-of-sample predictions. The predictive element in social science is indeed gaining a foothold to assess a hypothesized model’s predictive ability apart from its explanatory power. This study performs vigorous statistical testing to derive more robust findings.

Current study portrays the nexus of micro-level CSR practices with job and organizational engagement in the pandemic milieu by reviewing the Stakeholder Theory, the Social Exchange Theory (SET), and the Engagement Theory. The remainder of this paper is structured in the following manner. The theoretical background and hypotheses development are presented after the introduction section. This is followed by the research method, data analysis, and results, before proceeding to the discussion and conclusion section. The paper concludes with the study’s limitations and directions for future research.

2 Theoretical background and hypotheses development

2.1 Stakeholder theory, social exchange theory and engagement theory

Three underpinning theories guide the development of this study. Firstly, the Stakeholder Theory [25] offers a deviation from the customary understanding of business as a vehicle to maximize owners’ returns, as it advocates generating value and interest to diverse stakeholders [26]. This theory highlights the importance of building and maintaining sustainable stakeholder relationships for firm performance. In this vein, micro-level CSR practices reflect the essence of the Stakeholder Theory to build and uphold sustainable relationships with highly pertinent stakeholders –employees.

Next, referring to the Social Exchange Theory (SET), the implementation of micro-level CSR practices is rewarded with the Matthew effect of positive employee outcomes. According to Zhang et al. [27], social life often involves a progression of consecutive dealings between two or more parties through a reciprocity process. The reciprocity process results in one party’s tendency to repay the good or bad deeds of the other party, depending on the relationship and trust level [28]. Based on an integrated understanding of the Stakeholder Theory and the SET, when employees receive good deeds through micro-level CSR practices in times of disaster, they would repay their organizations with encouraging attitudes and behaviours.

Hejjas et al. [29] ascertained the role of Stakeholder Theory in providing a valuable foundation to study employee disengagement. The Engagement Theory [30] elucidates disengagement as the lack of commitment and attachment towards the execution of work, while engagement is described as the employees’ motivation and commitment towards their role performance [31, 32]. Therefore, employee engagement is a core priority for every organization, especially during uncertainty.

Taken together, the three aforementioned theories collectively purvey an integrative theoretical foundation for this study. Aguinis et al. [33] articulated that for effective positive outcomes, organizations are recommended to select a CSR strategy that is embedded into the organization’s core competencies. It should be integrated into a firm’s strategy, routines, and operations. Henceforth, the notion of micro-level CSR which aims to create and maintain sustainable employee relationships indicates the execution of internal strategic management as a firm’s strategy. The anticipation of employees’ positive outcomes is advanced by the SET and the Engagement Theory. Specifically, Aguinis et al. [33] explained that a behavioural CSR approach, such as micro-level CSR, benefits both employees and organizations in a mutual exchange process. Moyo [32] pointed out that employee disengagement has heightened during the pandemic, raising the significant need for health and safety to achieve employee engagement. This backdrop motivates the study of micro-level CSR practices for employee engagement in times of crisis.

2.2 Micro-level CSR practices, job engagement and organizational engagement

A team of micro-level CSR pioneer researchers (e.g., Al-bdour et al. [34], Turker, [35]) explained that CSR activities discharged by organizations to their employees cover the areas of safety, health, wellbeing, work-family relationships, training and development, and equal opportunities. Ergo, micro-level CSR refers to the psychological and physiological aspects of employees. In Mory et al. [11]’s work, seven dimensions are used to gauge the psychological and physiological aspects of employees. There are employment stability, employee involvement, empowerment, working environment, skill development, workforce diversity, and work-life balance; while in Al-bdour et al. [34]’s research, human rights, health and safety, work-life balance, workplace diversity training, and education were the measures for employees’ welfare. After a careful examination of these two works, we decided to consolidate the overlaps and adopt the more current and complete measurement to address our current research context of the vitality of micro-level CSR in relation to employee engagement in times of crisis. With this, employee empowerment, employee involvement, employment stability, working environment, and work-life balance are incorporated in current study to comprehend its impacts on employee engagement during the COVID-19 crisis.

Nonetheless, the link between CSR perceptions and work engagement is not to be taken as universal. Rupp et al. [36] explicated the potential of individual and contextual factors to act as meaningful boundary conditions for employee engagement. Additionally, Glavas and Agunis [37] provided the nexus of sense making in the significance of micro-level CSR practices; thus, it is worth making the important distinction between job engagement and organizational engagement.

Engagement at work was originally conceptualized by Kahn [30] as harnessing the organizational members to their work roles, hence, it is also known as employee engagement. It refers to the extent to which an employee believes in the mission, purpose and values of the organization and displays that commitment through their actions as an employee and their attitude towards the employer. Engaged employees express themselves physically, cognitively and emotionally during the performance of their roles, which is termed as job engagement [86]. Therewith, there are three degrees of employee engagement, i.e., actively engaged, not engaged and actively disengaged. Commonly, the research uncovered that employees fall into the middle level specifically, not engaged. HR personnel and managers’ opinion that engagement challenge has to do with how the employee feels about the work experience and how he/she is treated in the organization. It is something the employee has to offer; it cannot be explicitly stated in the employment contract. Also, engagement is distinctive on its own and different from satisfaction, and motivation. The original widely used term of employee engagement embraces two attempts of organizations which are to motivate the employees and focus on their commitment to achieving the organizational objectives. These two attempts branched out to job/ work engagement and organizational engagement.

Employee engagement started to gain attention in the late 2000 s after Gallup pointed out the alarming financial losses borne by the US economy (approximately US$450 billion to US$550 billion) due to the declined productivity of disengaged employees. Following this report, employee engagement studies proliferated (e.g., Balliester & Elsheikhi, [38]; Ismail et al. [39]). Gallup’s report also indicated that higher employee engagement is directly related to a greater level of productivity, while Al-Mehrzi and Singh [40] linked it with economic growth and profitability. Subsequently, the positive chain effects of engagement are drivers of innovation and competitive advantage [41]. With the intensified focus on employee engagement levels in business, it is crucial to make distinctions between the different types of employee engagement. Saks and Gruman [23] stated that employee engagement is not a unidimensional concept but a multidimensional notion. Schaufeli and Salanova [42] enlightened that employee engagement covers the relationship between an employee and his/her occupation, work, and organization. This connotation leads to the classification of job/work engagement and organizational engagement. Organizations need to differentiate employees’ engagement with their job from their engagement with their organization. It is possible for employees to be highly engaged in their jobs but feel disconnected from the overall organization or vice versa. Therefore, only by examining job engagement and organizational engagement distinctly can organizations craft appropriate strategies to address the different requirements of both engagement types.

2.3 Employee empowerment

Employee empowerment involves employees taking independent actions or decisions in their assigned tasks. It refers to the extent to which the employee is given the opportunity to determine his/her operating context in a self-actualizing way. The adoption of Work from Home (WFH) practices during the COVID-19 pandemic has made the element of employee empowerment more relevant and crucial. Tripathi et al. [43] revealed how psychologically empowered employees to develop a robust consideration of their roles due to perceived organizational support. Employee empowerment will progress into creativity and engagement [44]. Parallel with this discussion, the following direct hypotheses are posited:

H1a: Employee empowerment positively influences job engagement.

H1b: Employee empowerment positively influences organizational engagement.

2.4 Employee involvement

Employee involvement refers to the practice of having employees participate in critical operations and management meetings. Carmeli et al. [45] asserted that employee involvement is part of the normative foundation of moral decision-making grounded in the theory of social responsibility. Macey et al. [46] claimed that employee involvement and work engagement are vital to drive organizational success. This assertion is substantial in a crisis context because employee involvement sends a message to the employees that they are valued and trusted [46]. Applied to the understanding of SET, employee involvement necessitates trust between both parties and enhances their reciprocity with positive outcomes. Therefore, the following two direct relationships are put forth:

H2a: Employee involvement positively influences job engagement.

H2b: Employee involvement positively influences organizational engagement.

2.5 Employment stability

Employment stability reflects the extent to which organizations provide and secure stable jobs for their employees. In the past, employment stability was analyzed by Lin and Wei [48] in the early CSR context because of aggressive global competition. At present, the battle with COVID-19 has posed a severe economic threat to many businesses. Adopting the Stakeholder Theory’s lens, business organizations have the most fundamental responsibility to their employees, who should be prioritized by granting a secure job. The SET further highlights the occurrence of an obligatory transactional exchange from employees to the organization when this form of organizational support is given. Based on this rationale, two direct hypotheses are proposed:

H3a: Employment stability positively influences job engagement.

H3b: Employment stability positively influences organizational engagement.

2.6 Working environment

The working environment carries equal weight in the consideration of micro-level CSR practices. The working environment refers to the issues of health and safety in the workplace. In certain industries and organizations, it is explicitly written in company policies to demonstrate organizational sensitivity towards employees’ safety [91]. In line with the core concept of micro-level CSR, a safe and conducive working environment reflects the physiological well-being of employees. Taking the current pandemic into account, the working environment is extremely important for employees to feel safe before they could engage in their work. Consequently, the following hypotheses are developed:

H4a: The working environment positively influences job engagement.

H4b: The working environment positively influences organizational engagement.

2.7 Work-life balance

To cultivate mindfulness for mental health, striking a balance between work-related matters and personal life matters is important as one does not infringe on the other; this is called work-life balance (WLB) [48]. According to Bekir [50], WLB in several countries has severely deteriorated due to the pandemic. The implementation of WFH practices to minimize COVID-19 infection has indeed blurred the line between work life and personal life. Many employees have endured the stress of fulfilling multiple roles’ demands, ranging from high workload requirements to ad-hoc family care arrangements. Such situations cause a deterioration in WLB and detrimentally affect the mental health of employees [51]. These negative consequences do not halt at the individual level but transfer to the work context and organizational level. With this, the following hypotheses are formulated:

H5a: Work-life balance positively influences job engagement.

H5b: Work-life balance positively influences organizational engagement.

2.8 Job engagement, organizational engagement and the mediating role of job engagement

Job engagement is described as the relationship of an employee with his/her work. In this context, the core focus is on the employee’s job and roles within the organization. Positive job engagement denotes that the employee perceives meaningfulness in his/her job that extends beyond his/her remuneration package. Job-engaged employees associate their value with the role tied to their own self-perception. When they believe that their job is important and valuable in the organization, they tend to work the extra mile and perform progressively in their job. Commonly, job engagement is interchangeable with work engagement. For this study’s purpose, job engagement is used, to clearly differentiate it from organizational engagement.

Meanwhile, organizational engagement casts a wider scope by going beyond the individual level to encompass employees’ emotional commitment of their complete selves to their organization and its goals [23]. Therefore, organizational engagement is affected by organizational factors such as organizational objectives and values. When organizational engagement is achieved, it benefits organizations substantially as everyone is committed to the firms’ common goals and motivated to work towards them [89]. Henceforth, job engagement reflects self-perception while organizational engagement covers a broader focus. Based on this understanding, we hypothesize that a job-engaged employee will display positive organizational engagement by diligently meeting organizational goals as postulated in H6:

H6: Job engagement positively influences organizational engagement.

Considering the self-originating nature of job engagement, the challenges faced by organizations during this pandemic have more profoundly impacted organizational engagement. Many business organizations are adopting WFH practices during the pandemic, which has landed employees in a vulnerable isolation state. Social distancing and isolation phenomena run the risk of employees perceiving their roles as singular instead of inter-complementary when a job is to be done. Likewise, ensuring organizational engagement at every level has always been a challenge for business organizations. In this regard, we attempt to study the mediating role of job engagement in bridging the relationship between micro-level CSR practices and organizational engagement. Hypotheses H7 to H11 predict a positive mediating effect of job engagement between the five micro-level CSR practices and organizational engagement, as follows:

H7: Job engagement mediates the relationship between employee empowerment and organizational engagement.

H8: Job engagement mediates the relationship between employee involvement and organizational engagement.

H9: Job engagement mediates the relationship between employment stability and organizational engagement.

H10: Job engagement mediates the relationship between wok-life balance and organizational engagement.

H11: Job engagement mediates the relationship between working environment and organizational engagement.

Fig. 2

Measurement model assessment.

The above literature review has underscored the importance of micro-level CSR practices and their interrelations with employee engagement. The hypotheses formulated are further illustrated in Fig. 1: Research Framework. According to Alhozi et al. [86], employee empowerment promotes job engagement by augmenting an organization’s ability to materialize its strategic approach to gain comparative advantage and this positive outcome is cascaded to the organizational level as organization engagement [87]. Thereby, H1a and H1b are developed. Employee involvement is another pertinent element of organizational effectiveness. Dade et al. [88] empirically testified the significant relationship between employee involvement and employee engagement which positively link to organizational effectiveness. With this, H2a and H2b are formulated. In 2015, United Nations envisions to achieve full and productive employment and decent work for all through United Nations Sustainable Development Goal (UNSDG) 8, i.e., Decent Work and Economic Growth. The grand vision has inspired much research to examine the context of decent work. Drawing from The International Labour Organization (ILO), decent work is defined as productive work for individuals in conditions of freedom, equity, security, and human dignity. In essence, work is considered decent when: it pays a fair income; guarantees a secure form of employment and safe working conditions. The definition and work conditions are closely related to the description of micro-level CSR practices [7 , 90]. Henceforth, H3 to H5 are formed accordingly to investigate its influence on job engagement. Subsequently, Saks et al. [89] highlighted the need to further explore employee engagement as current literature demonstrated a deficiency in distinguishing between job engagement and organization engagement. H6 to H11 are the indirect relationships that aim to address this absence of enriching findings on job engagement and organization engagement.

Fig. 1

Research framework.

3 Research methods

3.1 Sampling and data collection

The World Health Organization (WHO) announced that there were over 118,000 COVID-19 cases reported in more than 110 countries as of March 11th, 2020 [84]. No country has escaped from this pandemic and like most countries, the Malaysian government took various precautions to prevent the virus outbreak.

Beginning March 18th, 2020, a series of national quarantines and cordon sanitaire measures were implemented by the Malaysian government. Five phases of the MCO were mandated from March 18th to August 31st, 2020. Data collection began in March 2020 and lasted for three months up to June 2020. We extended our questionnaires to employees who were employed and working throughout that period. Data was collected from eligible candidates throughout Peninsular Malaysia, which is justified as the region contributes 78.6% of the overall Malaysia labor force, as per the Department of Statistics Malaysia.

The judgmental sampling technique was employed wherein researchers exercise their professional judgment in identifying the targeted respondents. This technique enables researchers to reach out to the targeted population and increases the relevance of the sample, given that individuals who do not meet the criteria would not be included. To be eligible to participate in this study, respondents had to be working and attached to an organization but not be self-employed.

3.2 Instrument

The measures used in this study were adapted from current literature with minor revision to better suit the research context. The measures of the five micro-level CSR practices dimensions were adopted from Mory et al. [11] while the measure of job engagement was derived from Schaufeli et al.’s [42] five-item scale. All the measures adopted are reflective measures whereby the indicators are consequences of the constructs. A 7-point Likert scale with “1” indicating strongly disagree and “7” indicating strongly agree was used for all the measures. The measures of this study are presented in the Appendix.

3.3 Power analysis

G*Power program was utilized to calculate the required sample size for statistical significance. With our research model comes with six predictors, a minimum of 107 observations are required to attain an effect size of 0.15 at 95% power level [52]. Memon et al. [53] informed that there is no one-size-fits-all solution to address the sample size, yet they recommended a sample size of 160–300 is most appropriate for multivariate statistical analysis techniques such as PLS-SEM. With this in mind, we had sent out 800 questionnaires and successfully collected 336 completed responses, yielding a response rate of 42.0%. According to Holbrook et al. [96], a response rate that ranges from 5% to 54% is only marginally less accurate than those that reported a higher response rate. They further explained that while the response rate is informative, it is insufficient to determine the validity of the results. Reporting about the recruitment and furnishing more detailed information about how representative those who agree to participate in comparison with those who do not agree based on the population characteristics is a better risk assessment. Henceforth, the current study’s response rate of 42.0% falls into the indicative acceptable level.

3.4 Non-response bias

In conducting a quantitative questionnaire survey, it is not uncommon to have non-response bias. Non-response bias occurs when there is a significant variance between those who responded and those who did not. Therefore, it presents a threat to the findings. Armstrong and Overton [97] offered some approaches to estimate the non-response bias, such as comparison with the know values in the population, subjective estimate, and extrapolation method. For the current study, the subjective estimate was implemented for three core reasons: first, it is a widely recommended basis to cope with the non-response bias; second, Brown [98] claimed that it is a useful approach; and third, Schwirian and Blaine [99] tested and confirmed its’ validity. Subjective estimates state that people who are more interested in the subject of a questionnaire often respond more readily and thereby providing the necessary information for researchers to understand the subject matter. With judgmental sampling technique adopted and the consideration of non-responses bias along with the response rate of 42.0%, we are confident that the detrimental effect of non-response bias is not a concern in this study.

3.5 Common method bias

Common method bias (CMB) is a serious methodological phenomenon caused by common variation induced by the measurement method adopted [54]. Data that suffered from CMB potentially lead to artificial inflation of relationships that hinder the measures’ reliability and validity. MacKenzie and Podsakoff [55] proposed statistical and procedural remedies to alleviate the issues of CMB. Current study adopted both procedural and statistical strategies to mitigate CMB issue. Jordan and Troth [56]’s suggestion of procedural remedy was employed. A copy of the detailed research information coversheet was given to all the respondents in order to increase the probability of response accuracy. Also, pilot-test was performed, and comments gathered were incorporated. For the statistical approaches, Harman’s single factor and full collinearity variance inflated factor (AFVIF) approach were executed. Harman’s single factor test results informed that 23.76% of the variance was explained by a single factor which indicates that less than a majority of the variances were explained. Also, the value of 2.208 was obtained for AFVIF which is below the threshold of 3.3 [57]. All in all, CMB did not substantially influence the results of the study as evidenced by the procedural and statistical approaches.

3.6 Analytical technique

There are two commonly used Structural Equation Modeling (SEM) to analyze complex inter-relationships between observed and latent variables, namely Covariance based Structural Equation Modeling (CB-SEM) and Partial Least Squares based Structural Equation Modeling (PLS-SEM) [92]. CB-SEM is based on covariance which is also known as factor-based SEM approximates latent variables by common factors, while PLS-SEM is based on variance, called composite-based SEM [93]. Even though factor-based SEM remains prevalent in practice, recent research in psychometrics calls the central principles of the common factor model into question. Rigdon et al. [94] highlighted that common factor proxies cannot be assumed to carry greater significance than composite proxies regarding the existence or nature of conceptual variables. They further expounded that the indeterminacy of common factors creates a band of (metrological) uncertainty in the relationship between the factor inside the model and any variable outside the model including the conceptual variable that the factor seeks to represent [94].

Current study decides on Partial Least Squares Structural Equation Modeling (PLS-SEM) to proceed with the statistical analysis for two core reasons. Firstly, PLS-SEM permits researchers to evaluate complex models [58], which it matches our current research model that comes with many indicators, constructs and structural paths. Secondly, PLS-SEM is a causal predictive approach advancing on regression-based technique in social sciences areas to estimate path relationship with manifest variables [59, 60]. Most recently, Sarstedt and Dank [61] claimed that a model with a certain degree of explanatory power potentially led to immensely different levels of predictive power and contrarywise despite of having identical and different contexts. As the proposed research framework is destined as a frugal fix for organizations during this turbulent time, predictability power is our core priority. These two appealing merits of PLS-SEM justified its’ usage in the current study.

4 Data analysis and results

4.1 Respondents’ demographic profile

An outline of the total 336 respondents’ demographic profiles is provided in Table 1. The majority of the respondents are females (54.46%) with most of them in the age group of 25 to 30 years old (38.99%), followed by the age group of 18 to 24 year old (32.44%). The married respondents represent many of the responses with 58.63% while the single respondents contributed 38.39% of the responses. It was interesting to find out that a large group of respondents have been working with the existing company for 5 to 10 years. Respondents who are working in the service sector dominated the samples (66.67%), followed by the manufacturing sector (18.45%) and the construction sector (4.17%).

Table 1
Respondents’ demographic profile

Variable Description Frequency Percentage (%)

Gender Male 153 45.54%

Female 183 54.46%

Age Group 18– 24 years old 109 32.44%

25– 30 years old 131 38.99%

31– 40 years 24 7.14%

41– 50 years 27 8.04%

51– 60 years 40 11.90%

61 years or above 5 1.49%

Marital status Single 129 38.39%

Married 197 58.63%

Others 10 2.98%

Year of service Less than 5 years 63 18.75%

Between 5– 10 years 185 55.06%

More than 10 years 88 26.19%

Sector Manufacturing 62 18.45%

Services 224 66.67%

Agricultural 9 2.68%

Construction 14 4.17%

Retail 12 3.57%

Logistic 5 1.49%

Others 10 2.98%

Total 336 100.00%

Variable	Description	Frequency	Percentage (%)
Gender	Male	153	45.54%
	Female	183	54.46%
Age Group	18– 24 years old	109	32.44%
	25– 30 years old	131	38.99%
	31– 40 years	24	7.14%
	41– 50 years	27	8.04%
	51– 60 years	40	11.90%
	61 years or above	5	1.49%
Marital status	Single	129	38.39%
	Married	197	58.63%
	Others	10	2.98%
Year of service	Less than 5 years	63	18.75%
	Between 5– 10 years	185	55.06%
	More than 10 years	88	26.19%
Sector	Manufacturing	62	18.45%
	Services	224	66.67%
	Agricultural	9	2.68%
	Construction	14	4.17%
	Retail	12	3.57%
	Logistic	5	1.49%
	Others	10	2.98%
	Total	336	100.00%

4.2 Internal consistency reliability

Following Hair et al. [63]’s recommendation, the first step in evaluating PLS-SEM begins with the measurement model assessment. This assessment consists of the evaluation of internal consistency reliability, convergent validity, and discriminant validity. Internal consistency reliability measures the degree to which the items reflect the latent constructs. It is measured through composite reliability (CR). According to Sarstedt et al. [60], a CR values above 0.70 is considered acceptable. The values of CR for the current study fall in the range of 0.921 to 0.965 which is higher than the recommended threshold of 0.70. The values of Cronbach alpha and rho_A were examined and both values were above the required threshold values. The results in Table 2 signify that internal consistency reliability is achieved.

Table 2
Measurement model assessment

Construct Item Loading rho_A Composite Reliability Average Variance Extracted (AVE)

Employee Empowerment EeEm1 0.882 0.911 0.937 0.789

EeEm2 0.895

EeEm3 0.883

EeEm4 0.893

Employee Involvement EI1 0.838 0.956 0.961 0.733

EI2 0.861

EI3 0.792

EI4 0.860

EI5 0.869

EI6 0.909

EI7 0.884

EI8 0.830

EI9 0.856

Employment Stability ES1 0.880 0.899 0.921 0.701

ES2 0.825

ES3 0.774

ES4 0.876

ES5 0.827

Job Engagement JobEn1 0.837 0.919 0.935 0.741

JobEn2 0.837

JobEn3 0.889

JobEn4 0.864

JobEn5 0.876

Organization Engagement OrgEn1 0.897 0.957 0.965 0.822

OrgEn2 0.914

OrgEn3 0.917

OrgEn4 0.917

OrgEn5 0.874

OrgEn6 0.921

Working Environment* WE2 0.926 0.915 0.946 0.854

WE3 0.922

WE4 0.924

Work Life Balance WLB1 0.871 0.897 0.923 0.751

WLB2 0.911

WLB3 0.826

WLB4 0.855

Construct	Item	Loading	rho_A	Composite Reliability	Average Variance Extracted (AVE)
Employee Empowerment	EeEm1	0.882	0.911	0.937	0.789
	EeEm2	0.895
	EeEm3	0.883
	EeEm4	0.893
Employee Involvement	EI1	0.838	0.956	0.961	0.733
	EI2	0.861
	EI3	0.792
	EI4	0.860
	EI5	0.869
	EI6	0.909
	EI7	0.884
	EI8	0.830
	EI9	0.856
Employment Stability	ES1	0.880	0.899	0.921	0.701
	ES2	0.825
	ES3	0.774
	ES4	0.876
	ES5	0.827
Job Engagement	JobEn1	0.837	0.919	0.935	0.741
	JobEn2	0.837
	JobEn3	0.889
	JobEn4	0.864
	JobEn5	0.876
Organization Engagement	OrgEn1	0.897	0.957	0.965	0.822
	OrgEn2	0.914
	OrgEn3	0.917
	OrgEn4	0.917
	OrgEn5	0.874
	OrgEn6	0.921
Working Environment*	WE2	0.926	0.915	0.946	0.854
	WE3	0.922
	WE4	0.924
Work Life Balance	WLB1	0.871	0.897	0.923	0.751
	WLB2	0.911
	WLB3	0.826
	WLB4	0.855

^*WE1 was removed due to low factor loading.

4.3 Convergent validity

Convergent validity examines the extent to which the distinct indicators reflect a construct converging in comparison to indicators measuring other constructs [62]. Hair et al. [63] informed that convergent validity is evaluated based on the factor loadings and average variance extracted (AVE). Hair et al. [63] provided a rule of thumb for the factor loading and AVE respectively. A factor loading value equal to and greater than 0.7 is acceptable while an AVE of 0.5 or higher is considered satisfactory. Most of the items’ loadings are greater than the threshold value of 0.7 except WE1, while the AVE is higher than 0.5.

4.4 Discriminant validity

Discriminant validity is then examined to ensure that each latent variable is differentiated from other constructs in the model [63]. Often, it is referred to as the degree to which the indicators are distinct from others across constructs. According to Hair et al. [62], heterotrait-monotrait (HTMT) criterion is recommended to perform the discriminant validity testing. This is in line with Henseler et al. [64]’s suggestion of HTMT ratio of correlation criterion for discriminant validity evaluation. Henseler et al. [64] further explicated that the establishment of discriminant validity is ascertained when the HTMT statistics do not exceed 0.85 or 0.90. Table 3 shows that none of the HTMT values are above 0.90 [64, 65]. Furthermore, all the values of the confidence interval in Table 3 do not display a value of 1 in between, indicating that discriminant validity has been established [64, 65].

Table 3
Discriminant Validity using HTMT approach

Construct 1 2 3 4 5 6 7

1. Employee Empowerment

2. Employee Involvement 0.569 (0.459, 0.653)

3. Employment Stability 0.573 (0.470, 0.664) 0.586 (0.6487, 0.668)

4. Job Engagement 0.668 (0.580, 0.740) 0.534 (0.404, 0.642) 0.426 (0.283, 0.535)

5. Organization Engagement 0.638 (0.548, 0.713) 0.726 (0.658, 0.794) 0.595 (0.500, 0.671) 0.716 (0.615, 0.792)

6. Work-Life Balance 0.506 (0.428, 0.588) 0.697 (0.637, 0.752) 0.513 (0.411, 0.598) 0.346 (0.236, 0.446) 0.569 (0.482, 0.660)

7. Working Environment 0.626 (0.549, 0.710) 0.643 (0.562, 0.712) 0.648 (0.538, 0.736) 0.527 (0.411, 0.634) 0.653 (0.581, 0.728) 0.682 (0.619, 0.744)

Construct	1	2	3	4	5	6	7
1. Employee Empowerment
2. Employee Involvement	0.569 (0.459, 0.653)
3. Employment Stability	0.573 (0.470, 0.664)	0.586 (0.6487, 0.668)
4. Job Engagement	0.668 (0.580, 0.740)	0.534 (0.404, 0.642)	0.426 (0.283, 0.535)
5. Organization Engagement	0.638 (0.548, 0.713)	0.726 (0.658, 0.794)	0.595 (0.500, 0.671)	0.716 (0.615, 0.792)
6. Work-Life Balance	0.506 (0.428, 0.588)	0.697 (0.637, 0.752)	0.513 (0.411, 0.598)	0.346 (0.236, 0.446)	0.569 (0.482, 0.660)
7. Working Environment	0.626 (0.549, 0.710)	0.643 (0.562, 0.712)	0.648 (0.538, 0.736)	0.527 (0.411, 0.634)	0.653 (0.581, 0.728)	0.682 (0.619, 0.744)

Note: A complete bootstrapping procedure was conducted and the values in the bracket indicate the lower and upper confidence interval bias-corrected (CIBC).

4.5 Structural model assessment

Upon completion of measurement model assessment, we proceed with the structural model evaluation which involves the hypotheses testing. The structural model assessment entails the examination of path coefficients, coefficients of determinations (R²), the effect size (f²) and predictive relevance (Q²) [62]. R² alludes the overall predictive accuracy of the research model [62]. Cohen [65] provided a guide of R² values, with 0.26 indicating large while 0.13 and 0.02 represent medium and small respectively. The results are available in Table 4. The R² for Job engagement was recorded as 44.4%, which indicates that 44.4% of the variance in Job engagement can be explained by the independent variables. Meanwhile, Organizational engagement achieved a R² of 66.3% indicating 66.3% of its variance are explained by the five dimensions of micro-level CSR practices and job engagement.

Table 4
Structural model assessment (direct hypotheses testing)

Direct Relationship 95% BCa CI

Std Beta Std Error t-value LL UL R² Adjusted R² VIF f ² Q²

H1a: Employee Empowerment 0.444 0.436 0.318

->Job Engagement 0.451 0.071 6.338 0.344 0.569 1.694 0.216 (M)

H2a: Employee Involvement

->Job Engagement 0.274 0.082 3.329 0.146 0.407 2.145 0.063 (S)

H3a: Employment Stability

->Job Engagement – 0.014 0.058 0.232 – 0.113 0.08 1.748 0.000

H4a: WLB

->Job Engagement 0.171 0.067 2.561 0.287 0.066 2.013 0.026 (S)

H5a: Working Environment

->Job Engagement 0.181 0.067 2.724 0.063 0.279 2.242 0.027 (S)

H1b: Employee Empowerment 0.663 0.588 0.474

->Organizational Engagement 0.052 0.058 0.888 – 0.045 0.14 1.694 0.068 (S)

H2b: Employee Involvement

->Organizational Engagement 0.313 0.07 4.499 0.195 0.43 2.145 0.193 (M)

H3b: Employment Stability

->Organizational Engagement 0.126 0.047 2.693 0.041 0.195 1.748 0.020 (S)

H4b: WLB

->Organizational Engagement 0.064 0.049 1.305 – 0.014 0.145 2.013 0.000

H5b: Working Environment

->Organizational Engagement 0.101 0.06 1.695 0.004 0.200 2.242 0.030 (S)

H6: Job Engagement

->Org Engagement 0.367 0.062 5.908 0.259 0.467

Direct Relationship				95% BCa CI
H1a: Employee Empowerment						0.444	0.436			0.318
->Job Engagement	0.451	0.071	6.338	0.344	0.569			1.694	0.216 (M)
H2a: Employee Involvement
->Job Engagement	0.274	0.082	3.329	0.146	0.407			2.145	0.063 (S)
H3a: Employment Stability
->Job Engagement	– 0.014	0.058	0.232	– 0.113	0.08			1.748	0.000
H4a: WLB
->Job Engagement	0.171	0.067	2.561	0.287	0.066			2.013	0.026 (S)
H5a: Working Environment
->Job Engagement	0.181	0.067	2.724	0.063	0.279			2.242	0.027 (S)
H1b: Employee Empowerment						0.663	0.588			0.474
->Organizational Engagement	0.052	0.058	0.888	– 0.045	0.14			1.694	0.068 (S)
H2b: Employee Involvement
->Organizational Engagement	0.313	0.07	4.499	0.195	0.43			2.145	0.193 (M)
H3b: Employment Stability
->Organizational Engagement	0.126	0.047	2.693	0.041	0.195			1.748	0.020 (S)
H4b: WLB
->Organizational Engagement	0.064	0.049	1.305	– 0.014	0.145			2.013	0.000
H5b: Working Environment
->Organizational Engagement	0.101	0.06	1.695	0.004	0.200			2.242	0.030 (S)
H6: Job Engagement
->Org Engagement	0.367	0.062	5.908	0.259	0.467

Notes: p < 0.005, VIF (Variance Inflation Factor); LL (Lower Level), UL (Upper Level), Effect size (f²):<0.02 (Small), 0.15 (Medium), 0.35 (Large).

For the effect size, Employee empowerment has a medium effect on Job engagement (f² = 0.216), while Employee involvement (f² = 0.063), Work life balance (f² = 0.026) and Working environment (f² = 0.027) have small effect size on Job engagement. Interestingly, Employment stability has no effect on Job engagement. Slightly different effect size was observed on Organizational engagement. For example, Employee involvement has a medium effect on Organizational engagement (f² = 0.193), while Employee empowerment (f² = 0.068), Employment stability (f² = 0.020) and Working environment (f² = 0.030) have small effect size on Organizational engagement but Work life balance displays no effect.

In terms of the naïve predictive relevance, it was assessed using Stone-Geisser Q² [67], all the predictive values are higher than 0, informing the model possesses predictive relevance [68].

According to Diamantopoulos and Siguaw [69], researchers shall address the collinearity issue through variance inflated factor (VIF) before assessing the structural model. They suggested that VIF values below 3.3 for each of the constructs signifies that collinearity is not a threat. Table 4 outlines the collinearity test results with all the VIF values lower than 3.3. With this, it concluded the collinearity is not a threat in the model.

4.6 Results of direct hypotheses testing (direct effect)

Next, the bootstrapping procedure using 5,000 resampling was performed to generate the t-values in measuring the statistical significance of the path coefficients. Table 5 illustrates the path co-efficient assessment results informing that there are 8 direct relationships found to be significant. There are H1a, H2a, H2b, H3b, H4a, H5a, H5b and H6. This shows that Employee empowerment is positive affecting Job engagement (β= 0.451, t = 6.338 > 1.645) in H1a. Employee involvement is positively affecting Job engagement and Organizational engagement (β= 0.274, t = 3.329 > 1.645; β= 0.313, t = 4.499 > 1.645) in H2a and H2b. Interestingly, Employment stability only positively affecting Organizational engagement (β= 0.126, t = 2.693 > 1.645) as hypothesized in H3b but not in Job engagement. While Work-life balance is positively affecting Job engagement (β= 0.171, t = 2.561 > 1.645) as hypothesized in H4a but not in Organizational engagement. As for Working environment, it is positively affecting Job Engagement and Organizational Engagement (β= 0.181, t = 2.724 > 1.645; β= 0.101, t = 1.695 > 1.645) in H5a and H5b. Lastly, Job Engagement is found to be positively influencing Organizational Engagement (β= 0.367, t = 5.908 > 1.645) in H6. In short, out of the five dimensions of micro-level CSR practices, only two dimensions, namely Employee involvement and Working environment having significant positive effects on both Job engagement and Organizational engagement. Job engagement displayed significant positive influence on Organizational engagement.

Table 5
Structural model assessment (Indirect Hypotheses Testing)

Indirect Relationship 97% BCa CI Decision VAF % Type of Mediation

Std Beta Std Error t-value* LL UL

H7: Employee Empowerment ->Job Engagement->Org Engagement 0.166 0.035 4.719 0.111 0.230 Supported 76.09 Partial mediation

H8: Employee Involvement ->Job Engagement ->Org Engagement 0.100 0.037 2.728 0.049 0.178 Supported 24.32 Partial mediation

H9: Employment Stability ->Job Engagement ->Org Engagement –0.005 0.022 0.227 –0.042 0.031 No Supported

H10: WLB ->Job Engagement ->Org Engagement –0.063 0.027 2.296 –0.114 –0.022 Supported 49.51 Partial mediation

H11: Working Environment ->Job Engagement ->Org Engagement 0.067 0.028 2.340 0.021 0.110 Supported 39.68 Partial mediation

Indirect Relationship				97% BCa CI	Decision	VAF %	Type of Mediation
H7: Employee Empowerment ->Job Engagement->Org Engagement	0.166	0.035	4.719	0.111	0.230	Supported	76.09	Partial mediation
H8: Employee Involvement ->Job Engagement ->Org Engagement	0.100	0.037	2.728	0.049	0.178	Supported	24.32	Partial mediation
H9: Employment Stability ->Job Engagement ->Org Engagement	–0.005	0.022	0.227	–0.042	0.031	No Supported
H10: WLB ->Job Engagement ->Org Engagement	–0.063	0.027	2.296	–0.114	–0.022	Supported	49.51	Partial mediation
H11: Working Environment ->Job Engagement ->Org Engagement	0.067	0.028	2.340	0.021	0.110	Supported	39.68	Partial mediation

Notes: ^*two-tailed test, VAF (Variance Accounted For).

4.7 Results of indirect hypotheses testing (indirect effect)

Thereafter, we employed Sarstedt et al. [58] and Preacher and Hayes [70]’s approach in testing the five mediation hypotheses (H7, H8. H9, H10, and H11). We specified the indirect effect of the five dimensions of micro-level CSR practices on Organizational engagement via Job engagement. Again, bootstrapping procedure was conducted to test these mediation hypotheses by generating Biased Corrected and accelerated Confidence Interval (BCa CI). Preacher and Hayes (2008)’s approach for mediation analysis was utilized, whereby 0 signifies no mediation. Table 5 shows that there are four dimensions of micro-level CSR practices (i.e., Employee empowerment, Employee involvement, Working environment and Work-life balance) have positive significant indirect effects on Organizational engagement. This was ascertained through BCa CI with a lower level at 2.5% and an upper level at 97.5% in H7 [LL = 0.111, UL = 0.230], H8 [LL = 0.049, UL = 0.178], H10 [LL = –0.114, UL = –0.022], and H11 [LL = 0.021, UL = 0.110], do not straddle a zero value in between. Hence, H7, H8, H10 and H11 are supported indicating the presence of indirect. A comparable result is established through the variance accounted for (VAF) index [) to decide the size of the indirect effect. We obtained VAF values of larger than 20% and less than 80% for H7, H8, H10 and H11. With VAF values between 20% to 80%, typical partial mediations are observed for H7, H8, H10 and H11 [62].

However, when the Job engagement was introduced, Employment stability is no longer showing significance influence on Organizational engagement in H9. The result was confirmed through BCA CI with a lower level at 2.5% and an upper level at 97.5% with 95% [LL = –0.042, UL = 0.031] which there is a zero value straddles in between. This concludes of H9 is not supported.

4.8 PLSpredicts

Following Shmueli et al. [71]’s recent research, PLS-SEM is regarded as a causal-predictive application. In essence, PLS predict works on the concepts of segregating training and holdout samples with the aim to estimate model parameters and evaluate model’s predictive power. With the symmetrical nature of the prediction error of the existing data, root mean squared error (RMSE) and mean absolute error (MAE) were used. Table 6 shows that PLS-SEM<LM for majority of the indicators in the PLS analysis. This is demonstrated in the lower RMSE and MAE values in comparison to the naïve LM benchmark. Besides, the Q² values for the indicators of PLS model performed better when compared to those generated for LM model (Q² > 0). Hence, the results indicate that current research model has a medium predictive power to represent reality.

Table 6
PLS predict assessment

PLS-SEM LM PLS-LM

RMSE MAE Q²_ predict RMSE MAE Q²_ predict RMSE MAE Q²_ predict

JobEn3 1.188 0.876 0.289 1.157 0.881 0.325 0.031 –0.005 –0.036

JobEn5 1.045 0.824 0.399 1.042 0.804 0.403 0.003 0.020 –0.004

JobEn4 1.138 0.891 0.333 1.085 0.843 0.393 0.053 0.048 –0.060

JobEn2 1.219 0.935 0.209 1.235 0.955 0.188 –0.016 –0.02 0.021

JobEn1 1.099 0.870 0.289 1.120 0.881 0.262 –0.021 –0.011 0.027

OrgEn6 1.060 0.756 0.492 1.071 0.794 0.481 –0.011 –0.038 0.011

OrgEn5 1.074 0.810 0.430 1.042 0.788 0.464 0.032 0.022 –0.034

OrgEn4 1.160 0.864 0.408 1.101 0.842 0.466 0.059 0.022 –0.058

OrgEn1 0.986 0.695 0.482 0.999 0.719 0.469 –0.013 –0.024 0.0130

OrgEn3 1.019 0.743 0.485 0.995 0.739 0.509 0.024 0.004 –0.024

OrgEn2 0.973 0.713 0.499 1.002 0.743 0.469 –0.029 –0.03 0.030

	PLS-SEM	LM	PLS-LM
JobEn3	1.188	0.876	0.289	1.157	0.881	0.325	0.031	–0.005	–0.036
JobEn5	1.045	0.824	0.399	1.042	0.804	0.403	0.003	0.020	–0.004
JobEn4	1.138	0.891	0.333	1.085	0.843	0.393	0.053	0.048	–0.060
JobEn2	1.219	0.935	0.209	1.235	0.955	0.188	–0.016	–0.02	0.021
JobEn1	1.099	0.870	0.289	1.120	0.881	0.262	–0.021	–0.011	0.027
OrgEn6	1.060	0.756	0.492	1.071	0.794	0.481	–0.011	–0.038	0.011
OrgEn5	1.074	0.810	0.430	1.042	0.788	0.464	0.032	0.022	–0.034
OrgEn4	1.160	0.864	0.408	1.101	0.842	0.466	0.059	0.022	–0.058
OrgEn1	0.986	0.695	0.482	0.999	0.719	0.469	–0.013	–0.024	0.0130
OrgEn3	1.019	0.743	0.485	0.995	0.739	0.509	0.024	0.004	–0.024
OrgEn2	0.973	0.713	0.499	1.002	0.743	0.469	–0.029	–0.03	0.030

5 Discussion

The protectionist lockdown and social distancing measures introduced during the worldwide pandemic have affected many levels of business, from the global arena to regions, industries, and organizations. When organizations are compelled to adhere to the lockdown order, adverse effects are felt not only in terms of business vitality but also in the form of disengaged employees. From past research, we observe that employee disengagement is the key antagonist of an organization as it threatens productivity, performance, and sustainability. The current study thus sought to deep dive into the utilization of micro-level CSR as a dual solution for both organizations and employees.

Based on current empirical research, it is interesting to note that the different dimensions of micro-level CSR display diverse influences on employees’ job and organizational engagement. The findings produce three distinguishable implications from theoretical, practical, and methodological perspectives.

5.1 Theoretical implication

Our first theoretical contribution concerns the applicability of the Stakeholder Theory and the SET to micro-level CSR practices. While prior CSR research (e.g., Miller et al. [72]) has predominantly focused on external stakeholders for firm performance, our study signifies the benefits of focusing on internal stakeholders for firm survival and resilience during crises. With reference to the fundamental concepts of the Stakeholder Theory [25], the generation of value is the core driver of any firm, and this value is to be shared by a group of stakeholders as well as all actors in the society. The Stakeholder Theory further delineates the responsibility of organizations to their stakeholders. In the pandemic situation, it bodes well for organizations to discharge their responsibility to their employees, by implementing micro-level CSR practices. Our findings further reinforce the importance of the Stakeholder Theory in the interconnectivity between business and society. When organizations play their role pertinently through micro-level CSR, such as by ensuring employment stability, they cushion employees’ psychological stress. This is significant as Nordt et al. [73] reported the spike in suicide cases following the rise in the unemployment rate. Hence, it is also part of the governance process of corporate managers and organizations to consider the interest of employees in this critical context. The absence of micro-level CSR practices could potentially result in more severe social issues (e.g., rising suicidal cases and psychological distress) and unfavorable consequences for society. Our research findings provide empirical evidence on the outcome of micro-level CSR practices, i.e., engaged employees, which is much desired in times of crisis. The Stakeholder Theory works hand-in-hand with the SET by expanding the benefits of an engaged workforce from the organizational boundary to societal wellbeing. Using the principles of the Stakeholder Theory, the findings also extend the general perception of CSR to become more relevant to internal stakeholders and showcase the positive effects of micro-level CSR practices on organizations and society.

Our second theoretical implication lies in the detailed reciprocity mechanism of micro-level CSR and its consequences for organizations and employees. We utilized the SET concept and proposed micro-level CSR to create and uphold employees’ engagement in turbulent times. Yet, by examining employee engagement as a single concept, the implications derived would have been limited. As such, we carefully studied the mechanism of micro-level CSR through employees’ job engagement and organizational engagement. The results support the reciprocity approach of the SET. Specifically, when micro-level CSR practices (e.g., employee involvement, employee empowerment, working environment, and work-life balance) are implemented, employees’ job engagement is enhanced. However, for organizational engagement, micro-level CSR practices appear to take a slightly different path. That is, employee empowerment does not influence organizational engagement, while employee involvement, employment stability, working environment, and work-life balance positively affect organizational engagement. With this, we highlight the second theoretical contribution concerning the Engagement Theory as the reciprocity mechanism underlying micro-level CSR practices. Our findings expand on Kahn’s [30] engagement theory, which states that the precursors of job engagement and organizational engagement are not uniform but deviated. For instance, it is interesting to uncover that employment stability does not lead to job engagement but does lead to organizational engagement. Without such in-depth understanding and differentiation of these two types of engagement, organizations and managers may get an ‘A’ for effort yet fail to achieve intended results.

The third theoretical implication emphasizes the applicability of employee-centered CSR research in the unprecedented pandemic context. Despite employee-centered CSR research gaining a foothold (e.g., Low & Spong, [21], Jamali et al. [10]) in the late 2000 s, most studies were mainly conducted in the competitive business landscape. In contrast, the current study was carried out during a disastrous global pandemic. The empirical findings inform us that the execution of micro-level CSR practices does not lead to divergent impacts from the conventional business competitive setting. In fact, the inclusion of micro-level CSR practices is welcome as an internal enabler to weather through the external challenges. Inherently, micro-level CSR is a favorable strategy to be considered in various contexts.

5.2 Managerial implication

Many human resource (HR) personnel and managers understand and realize the dampening effects of disengaged employees. However, Clark [74] observed that employees’ engagement levels are consistently low despite the best efforts of organizations. Our study offers some rational explanations for this phenomenon. We believe the HR personnel and managers would be greatly benefited from these findings. We adopted a multifaceted approach by separating employee engagement into job and organizational engagement in order to fully address motivation and engagement in the workplace. Drawing from Saks’s [23] conceptualization, job engagement refers to the extent of which an individual pays attention to the performance of his/her role and is absorbed in his/her work. Meanwhile, organizational engagement denotes an individual’s psychological role in an organization by doing his/her best. Organizational engagement is the emotional commitment employees have to their organizations, which is affected by factors such as organizational objectives, values, and beliefs [23]. When everyone involved is equally committed to the organization’s shared goals and productivity, businesses can reap significant advantages. This understanding guides our deduction that job engagement incorporates an individual’s enthusiasm towards his/her job [42] while organizational engagement delivers the shared values of the organization to employees.

Despite our findings showing a positive relationship between job engagement and organizational engagement, it is organizational engagement that predicts more positive outcomes like organizational commitment, job satisfaction, and organizational citizenship behaviors. For organizations and industries that require a cohesive workforce to stay afloat during the pandemic challenge, we would therefore recommend an emphasis on organizational engagement. Our results show that employee involvement, employment stability, and working environment are the micro-level CSR practices that nurture organizational engagement. The amalgamation of micro-level CSR and organizational engagement instils the organization’s shared values among employees by providing a motivational environment to work in [75]. Additionally, organizationally engaged employees are prepared and willing to devote their time and effort to complete their tasks to achieve organizational goals. This is much needed during an unprecedented and challenging crisis.

Job engagement delivers a different level of outcomes compared to organizational engagement. Since it represents individuals’ enthusiasm towards their job, it improves employees’ ability and performance, and in turn, foster their creativity. Based on our empirical findings, if organizations wish to bring employees’ job engagement to a higher level, micro-level CSR practices under cognitive and physical categories (e.g., employee empowerment, employee involvement, working environment, and work-life balance) would serve this purpose.

Our study highlights the importance for organizations to draw a distinction between the different types of engagement to facilitate targeted, evidence-based interventions that meet their desired outcomes more effectively. This study also offers practical implications to organizations and HR practitioners to vary the use of micro-level CSR practices to achieve the intended engagement outcome. The absence of a clear and distinct understanding in this regard would put most efforts in vain. Nevertheless, micro-level CSR is recommended on a large scale as it does produce an overall Matthew effect on organizations during a crisis.

5.3 Methodological implication

This study adopted PLS-SEM owing to its appealing assumptions in the social sciences. Recent developments in PLS-SEM suggest that prediction-driven explanations are unconventional in the social sciences [71, 76]. Hence, framing managerial recommendations as prescriptive statements somewhat diminishes value and credibility. Kaplan [76] concurred that if researchers are unable to successfully predict the empirical outcome of a certain explanation, they will not have solid ground to accept the explanation presented in the managerial implication. Hence, the literature indicates a credential recommendation based on predication in evaluating theoretical falsifiability [83]. The predictive scenario posited herein is substantiated with the assessment of out-of-sample predictive power in PLSpredict analysis. Our predictive assessment results reveal that the proposed research model possessed medium predictive power in symbolizing reality. We confirm the achievement of our initial research objective to examine the influence of micro-level CSR on job engagement and organizational engagement during a crisis period.

6 Conclusion

With hopes of offering a frugal fix for struggling organizations, this study examined the influence of micro-level CSR practices on the dual dimensions of employee engagement during the unprecedented pandemic. The Stakeholder Theory, SET, and Engagement Theory underpinned the research framework. Overall, the findings evidence micro-level CSR practices’ significant positive on job engagement and organizational engagement, albeit to varying degrees across the dimensions of micro-level CSR. The results add value to the existing literature, which has shown that different antecedents lead to different forms of engagement. Along this vein, the findings offer an explanation for the failure of organizations to achieve employee engagement despite substantial efforts. When job engagement and organizational engagement are studied distinctly, organizations can strategize the appropriate tactics based on targeted goals. Nevertheless, employee engagement requires both these elements to thrive. With strong job engagement, employees will appreciate the value of their work and progress towards successful organizational engagement on a wider scale. By implementing micro-level CSR to attain higher organizational engagement, organizations will be able to weather through this turbulent environment without sourcing for external assistance. Jung et al. [78] explained that substantial research has indicated that higher employee engagement results in lower turnover intention, making engagement the most influential psychological predictor of employee retention.

7 Limitations and direction for future research

Although this research offers several insights, there are a few limitations that should be considered. First, the samples were collected using the non-probability judgment sampling technique. Therefore, the findings suffer from poor generalizability. Additionally, the size of the respondents’ organizations was not controlled for in the current research. Firm size may influence employee engagement and thereby affect firm performance [79]

The second limitation concerns the use of the cross-sectional approach, which may limit us from drawing final conclusions. Though we have put forth a convincing theoretical discussion, future research should adopt a longitudinal approach to further ascertain the impact of micro-level CSR practices on job and organizational engagement. Next, data was collected during the early MCO phases in 2020. In 2021, the country moved on to other phases of fighting the COVID-19 pandemic through the National Recovery Plan. Therefore, the findings may not be current.

Despite these limitations, our study opens avenues for future research. Future researchers could address the concern of generalizability and representation arising from the non-probability sampling method. For instance, Cheah et al. [80] and Low et al. [81] suggested the use of weighted PLS (WPLS) to achieve better average population estimates when a set of appropriate weights is possible. Also, the generalized structured component analysis (GSCA) approach is recommended for future research, if it is a composite-based SEM [95]. Meanwhile, future researchers might consider other antecedents of employee engagement in the context of the volatile, uncertain, complex, and ambiguous (VUCA) environment, such as leadership, employees’ subjective age, work meaningfulness, the job resource model, and other organizational variables. Likewise, upcoming research could explore more organizational outcomes of micro-level CSR, such as organizational resilience, performance, creativity, and innovativeness (e.g., Aldabbas et al. [82]) and perform a comparison of during and post-crisis. Alternatively, the execution of micro-level CSR could be further examined in future research by linking it with the United Nations Sustainable Development Goals.

Footnotes

Acknowledgments

This research was self-funded.

Author contributions

CONCEPTION: Mei Peng Low.

METHODOLOGY: Mei Peng Low.

DATA COLLECTION: Mei Peng Low.

INTERPRETATION OR ANALYSIS OF DATA: Mei Peng Low.

PREPARATION OF THE MANUSCRIPT: Mei Peng Low.

REVISION FOR IMPORTANT INTELLECTUAL CONTENT: Mumtaz Ali Memon.

SUPERVISION: Mumtaz Ali Memon.

The Appendix is available in the electronic version of this article: .

References

Ketels

, Clinch

. Acting now while preparing for tomorrow: Competitiveness upgrading under the shadow of COVID-19. 2020. (Doctoral dissertation).

Meyer

, Prescott

, Sheng

. The impact of the COVID-19 pandemic on business expectations, International Journal of Forecasting, Working Paper, Federal Reserve Bank of Atlanta. 2020.

WHO Coronavirus (COVID-19) Dashboard; 2022. Available from: https://covid19.who.int/ Accessed 5 May 2022.

Singh

, Chamola

, Kumar

, Verma

, Makkar

. Explaining the revival strategies of Indian MSMEs to mitigate the effects of COVID-19 outbreak. Bench-marking: An International Journal. 2022;ahead of print. DOI: 10.1108/BIJ-08-2021-0497

Matten

, Moon

. Reflections on the 2018 decade award: The meaning and dynamics of corporate social responsibility, The Academy of Management Review. 2020;45(1):7–28. DOI: 10.5465/amr.2019.0348

Aguinis

, Glavas

. What we know and don’t know about corporate social responsibility, Journal of Management. 2012;38(4):932–68.

Low

, Siegel

. A bibliometric analysis of employee-centred corporate social responsibility research in the 2000s, Social Responsibility Journal. 2020;16(5):691–717. DOI: 10.1108/SRJ-09-2018-0243

Piao

, Managi

. Evaluation of employee occupational stress by estimating the loss of human capital in Japan, BMC Public health. 2022;22:411. DOI: 10.1186/s12889-022-12751-7

Yasmeen

, Yasmeen

, Zahra

. Impact of psychological capital, perceived organizational support and perceived supervisor support on employee psychological well-being, Journal of Business Management Studies-JBMS. 2022;1(2):18–34.

10.

Jamali

, Samara

, Zollo

, Ciappei

. Is internal CSR really less impactful in individualist and masculine Cultures? A multilevel approach, Management Decision. 2012;58(2):362–75. DOI: 10.1108/MD-11-2018-1260

11.

Mory

, Wirtz

, Göttel

. Corporate social responsibility: The organizational view, Journal of Management & Governance. 2017;21(1):145–79.

12.

Jones

, Willness

, Glavas

. When corporate social responsibility (CSR) meets organizational psychology: New frontiers in micro-CSR research, and fulfilling a quid pro quo through multilevel insights, Frontiers in Psychology. 2017;8(520). DOI: 10.3389/fpsyg.2017.00520

13.

, Wang

, Lu

. Opening the “black box” between corporate social responsibility and financial performance: From a critical review on moderators and mediators to an integrated framework, Journal of Cleaner Production. 2021;127919.

14.

Golob

, Podnar

. Corporate marketing and the role of internal CSR in employees’ life satisfaction: Exploring the relationship between work and non-work domains, Journal of Business Research. 2021;131:664–72.

15.

Goergen

, Chahine

, Wood

, Brewster

. The relationship between public listing, context, multi-nationality and internal CSR, Journal of Corporate Finance. 2019;57:122–41.

16.

Donia

, Ronen

, Sirsly

CAT

, Bonaccio

. CSR by any other name? The differential impact of substantive and symbolic CSR attributions on employee outcomes, Journal of Business Ethics. 2019;157(2):503–23. DOI: 10.1007/s10551-017-3673-5

17.

Merriman

, Sen

, Felo

, Litzky

. Employees and sustainability: The role of incentives, Journal of Managerial Psychology. 2016;3(4):820–36. DOI: 10.1108/JMP-09-2014-0285

18.

Conley

, Johnson

. Opinion: Past is future for the era of COVID-19 research in the social sciences, Proceedings of the National Academy of Sciences. 2021;118(13):1–4. DOI: 10.1073/pnas.2104155118

19.

Bapat

, Upadhyay

. Implications of CSR initiatives on employee engagement, Social Responsibility Journal. 2021;17(2):149–63. DOI: 10.1108/SRJ-05-2018-0120

20.

Gupta

. Corporate social responsibility, employee–company identification, and organizational commitment: Mediation by employee engagement, Current Psychology. 2017;36(1):101–9.

21.

Low

, Spong

. Predicting employee engagement with micro-level corporate social responsibility (CSR) practices in the public accounting firms. Social Responsibility Journal. 2021.

22.

Bakker

, Demerouti

. Towards a model of work engagement, Career development international. 2008;13(3):209–23.

23.

Saks

, Gruman

. What do we really know about employee engagement?Human resource development quarterly. 2014;25(2):155–82. DOI: 10.1002/hrdq.21187

24.

Shmueli

, Ray

, Estrada

JMV

, Chatla

. The elephant in the room: Predictive performance of PLS models, Journal of Business Research. 2016;69(10):4552–64. DOI: 10.1108/EJM-02-2019-0189

25.

Freeman

. A stakeholder theory of the modern corporation, Perspectives in Business Ethics Sie. 2001;3(144):38–48.

26.

Freeman

, Dmytriyev

, Phillips

. Stakeholder theory and the resource-based view of the firm, Journal of Management. 2021;47(7):1757–70.

27.

Zhang

, Lou

, Guan

. How and when perceived leader narcissism impacts employee voice behavior: A social exchange perspective, Journal of Management & Organization. 2022;28(1):77–98.

28.

Blau

. Exchange and power in social life. JohnWiley & Sons, Inc. 1964.

29.

Hejjas

, Miller

, Scarles

. It’s like hating puppies! Employee disengagement and corporate social responsibility, Journal of Business Ethics. 2019;157:319–37. DOI: 10.1007/s10551-018-3791-8

30.

Kahn

. Psychological conditions of personal engagement and disengagement at work, Academy Management Journal. 1990;33:692–724. DOI: 10.5465/256287

31.

Bhappu

, Schultze

. Implementing an organization-sponsored sharing platform to build employee engagement, MIS Quarterly Executive. 2018;17(2):109–20.

32.

Moyo

. Antecedents of employee disengagement amid COVID-19 pandemic, Polish Journal of Management Studies. 2020;22(1):323–34.

33.

Aguinis

, Villamor

, Gabriel

. Understanding employee responses to COVID- A behavioral corporate social responsibility perspective, Management Research: Journal of the Iberoamerican Academy of Management. 2020;18(4):421–38.

34.

Al-bdour

, Nasruddin

, Lin

. The relationship between internal corporate social responsibility and organizational commitment within the banking sector in Jordan, International Journal of Human and Social Sciences. 2010;5(14):932–51.

35.

Turker

. How corporate social responsibility influences organizational commitment, Journal of Business Ethics. 2009;89(2):189–204.

36.

Rupp

, Shao

, Skarlicki

, Paddock

, Kim

, Nadisic

. Corporate social responsibility and employee engagement: The moderating role of CSR-specific relative autonomy and individualism, Journal of Organizational Behavior. 2018;39(5):559–79.

37.

Aguinis

, Glavas

. On corporate social responsibility, sensemaking, and the search for meaningfulness through work, Journal of Management. 2019;45(3):1057–86.

38.

Balliester

, Elsheikhi

. The future of work: A literature review. ILO Research DepartmentWorking Paper; 2018, p. 29.

39.

Ismail

FLM

, Wahab

NAA

, Ismail

, Latiff

. Job Satisfaction and Work Life Quality among employees of hotel industry in Malaysia, International Journal of Civil Engineering and Technology. 2019;10(4):62–70.

40.

Al Mehrzi

, Singh

. Competing through employee engagement: A proposed framework, International Journal of Productivity and Performance Management. 2016;65(6):831–43. DOI: 10.1108/IJPPM-02-2016-0037

41.

Kumar

, Pansari

. Competitive advantage through engagement, Journal of Marketing Research. 2016;53(4):497–514.

42.

Schaufeli

, Salanova

. Work engagement: On how to better catch a slippery concept, European Journal of Work and Organizational Psychology. 2011;20(1):39–46.

43.

Tripathi

, Srivastava

, Singh

, Kapoor

, Solanki

. A JD-R perspective for enhancing engagement through empowerment: A study on Indian hotel industry, Journal of Hospitality and Tourism Management. 2021;46:12–25. DOI: 10.1016/j.jhtm.2020.11.007

44.

Akgunduz

, Alkan

, Gök

ÖA

. Perceived organizational support, employee creativity and proactive personality: The mediating effect of meaning of work, Journal of Hospitality and Tourism Management. 2018;34:105–14.

45.

Carmeli

, Brammer

, Gomes

, Tarba

. An organizational ethic of care and employee involvement in sustainability-related behaviors: A social identity perspective, Journal of Organizational Behavior. 2017;38(9):1380–95.

46.

Macey

, Schneider

, Barbera

, Young

. Employee Engagement: Tools for Analysis, Practice, and Competitive Advantage. New York, NY: Blackwell Press. 2009. DOI: 10.1002/9781444306538

47.

Kipkebut

. Human resource management practices and organizational commitment in higher educational institutions: A kenyan case, IUP Journal of Organizational Behavior. 2010;9:45–70.

48.

Lin

CYY

, Wei

. The role of business ethics in merger and acquisition success: An empirical study, Journal of Business Ethics. 2006;69:95–109. DOI: 10.1007/s10551-006-9070-0

49.

Jamieson

, Tuckey

. Mindfulness interventions in the workplace: A critique of the current state of the literature, Journal of Occupational Health Psychology. 2017;22(2):180–93. DOI: 10.1037/ocp0000048

50.

Bekir

KUL

. Impact of COVID-19 on work life: A study for public sector, International Journal of Social Political and Economic Research. 2021;8(1):68–88.

51.

Yayla

, Eskici İlgin

. The relationship of nurses’ psychological well-being with their coronaphobia and work–life balance during the COVID-19 pandemic: A cross-sectional study, Journal of Clinical Nursing. 2021;30(21-22):3153–62.

52.

Faul

, Erdfelder

, Buchner

, Lang

. Statistical power analyses using G* Power 3.1: Tests for correlation and regression analyses, Behavior Research Methods. 2009;41(4):1149–60.

53.

Memon

, Ting

, Cheah

, Thurasamy

, Chuah

, Cham

. Sample size for survey research: Review and recommendations, Journal of Applied Structural Equation Modeling. 2020;4(2):1–20.

54.

Podsakoff

, MacKenzie

, Podsakoff

. Sources of method bias in social science research and recommendations on how to control it, Annual Review of Psychology. 2012;63:539–69.

55.

MacKenzie

, Podsakoff

. Common method bias in marketing: Causes, mechanisms, and procedural remedies, Journal of Retailing. 2012;88(4):542–55.

56.

Jordan

, Troth

. Common method bias in applied settings: The dilemma of researching in organizations, Australian Journal of Management. 2020;45(1):3–14.

57.

Kock

. Common method bias in PLS-SEM: A full collinearity assessment approach, International Journal of e-Collaboration (IJEC). 2015;11(40):1–10.

58.

Sarstedt

, Ringle

, Cheah

, Ting

, Moisescu

, Radomir

. Structural model robustness checks in PLS-SEM, Tourism Economics. 2020;26(4):531–54.

59.

Wold

. Encyclopedia of statistical sciences. Partial least squares. Wiley, New York; 1985, pp. 581–91.

60.

Sarstedt

, Ringle

, Hair

. Partial least squares structural equation modeling, Handbook of Market Research. 2017;26(1):1–40.

61.

Sarstedt

, Danks

. Prediction in HRM research–A gap between rhetoric and reality, Human Resource Management Journal. 2021:1–29. DOI: 10.1111/1748-8583.12400

62.

Urbach

, Ahlemann

. Structural equation modeling in information systems research using partial least squares, Journal of Information Technology Theory and Application. 2010;11(2):5–40.

63.

Hair

, Risher

, Sarstedt

, Ringle

. When to use and how to report the results of PLS-SEM, European Business Review. 2019;31(1):2–24.

64.

Henseler

, Ringle

, Sarstedt

. A new criterion for assessing discriminant validity in variance-based structural equation modeling, Journal of the Academy of Marketing Science. 2015;43(1):115–35.

65.

Gold

, Malhotra

, Segars

. Knowledge management: An organizational capabilities perspective, Journal of Management Information Systems. 2001;18(1):185–214.

66.

Cohen

. Statistical power analysis, Current Directions in Psychological Science. 1992:98–101.

67.

Chin

, Cheah

, Liu

, Ting

, Lim

, Cham

. Demystifying the role of causal-predictive modeling using partial least squares structural equation modeling in information systems research. Industrial Management & Data Systems. 2020.

68.

Geisser

. A predictive approach to the random effect model, Biometrika. 1974;61(1):101–7.

69.

Diamantopoulos

, Siguaw

. Formative versus reflective indicators in organizational measure development: A comparison and empirical illustration, British Journal of Management. 2006;17(4):263–82.

70.

Hayes

, Preacher

. Statistical mediation analysis with a multicategorical independent variable, British Journal of Mathematical and Statistical Psychology. 2014;67(3):451–70.

71.

Shmueli

, Sarstedt

, Hair

, Cheah

, Ting

, Vaithilingam

, Ringle

. Predictive model assessment in PLS-SEM: Guidelines for using PLSpredict, European Journal of Marketing. 2019;53(11):2322–47. DOI: 10.1108/EJM-02-2019-0189

72.

Miller

, Eden

, Li

. CSR reputation and firm performance: A dynamic approach, Journal of Business Ethics. 2020;163(3):619–36.

73.

Nordt

, Warnke

, Seifritz

, Kawohl

. Modelling suicide and unemployment: A longitudinal analysis covering 63 countries, 2000–11, The Lancet Psychiatry. 2015;2(3):239–45.

74.

Clark

. Factors contributing to employee engagement in an aquaculture organisation in the Eastern Cape (Doctoral dissertation, Nelson Mandela Metropolitan University).

75.

Barrick

, Thurgood

, Smith

, Courtright

. Collective organizational engagement: Linking motivational antecedents, strategic implementation, and firm performance, Academy of Management Journal. 2015;58(1):111–35.

76.

Hofman

, Sharma

, Watts

. Prediction and explanation in social systems, Science. 2017;355(6324):486–8. DOI: 10.1126/science.aal3856

77.

Kaplan

. The conduct of inquiry, Et Cetera. 1967;24:349.

78.

Jung

, Jung

, Yoon

. COVID- The effects of job insecurity on the job engagement and turnover intent of deluxe hotel employees and the moderating role of generational characteristics, International Journal of Hospitality Management. 2020;92:102703.

79.

Ibua

. Effect of employee engagement on performance of small and medium size enterprises in mombasa county, Kenya, Multidisciplinary Journal of Technical University of Mombasa. 2021;1(2):5–17.

80.

Cheah

, Roldán

, Ciavolino

, Ting

, Ramayah

. Sampling weight adjustments in partial least squares structural equation modeling: Guidelines and illustrations, Total Quality Management & Business Excellence. 2021;32(13-14):1594–613.

81.

Low

, Cham

, Chang

, Lim

. Advancing on weighted PLS-SEM in examining the trust-based recommendation system in pioneering product promotion effectiveness, Quality & Quantity. 2021:1–30.

82.

Aldabbas

, Pinnington

, Lahrech

. The influence of perceived organizational support on employee creativity: The mediating role of work engagement, Current Psychology. 2021:1–15.

83.

Hair

, Sarstedt

. Explanation plus prediction—the logical focus of project management research, Project Management Journal. 2021;00(0):1–4. 8756972821999945.

84.

Ducharme. World Health Organization Declares COVID-19 a ‘Pandemic.’ Here’s What That Means. 2020. https://time.com/5791661/who-coronavirus-pandemic-declaration/. Accessed 13 March 2022.

85.

Tan

, Sia

, Tang

. To verify or not to verify: Using partial least squares to predict effect of online news on panic buying during pandemic. Asia Pacific Journal of Marketing and Logistics. 2021.

86.

Alhozi

, Hawamdeh

, Al-Edenat

. The impact of employee empowerment on job engagement: Evidence from Jordan, International Business Research. 2021;14(2):1–90.

87.

Fadhal

, Absah

, Gultom

. The effect of employee empowerment, work collectivity, and employee engagement on organizational citizenship behavior of BKPSDM, in Langsa City, International Journal of Research and Review. 2021;8(3):692–702.

88.

Dade

, Esmi

, Lidya

, Supendi

, Narsih

. The significance of job involvement, and employee engagement in increasing organizational effectiveness, Int J of Adv Res. 2021;9:164–74.

89.

Saks

, Gruman

, Zhang

. Organization engagement: A review and comparison to job engagement. Journal of Organizational Effectiveness: People and Performance. 2021.

90.

Low

, Bu

. Examining the impetus for internal CSR Practices with digitalization strategy in the service industry during COVID-19 pandemic, Business Ethics, the Environment & Responsibility. 2022;31(1):209–23.

91.

Carballo-Penela

. Enhancing social sustainability at a business level: Organizational attractiveness is higher when organizations show responsibility towards employees, Business Strategy & Development. 2019;2(4):372–83.

92.

Dash

, Paul

. CB-SEM vs PLS-SEM methods for research in social sciences and technology forecasting, Technological Forecasting and Social Change. 2021;173:121092.

93.

Sarstedt

, Hwang

. Advances in composite-based structural equation modeling, Behaviormetrika. 2020;47(1):213–7.

94.

Rigdon

, Sarstedt

, Ringle

. On comparing results from CB-SEM and PLS-SEM: Five perspectives and five recommendations, Marketing: ZFP–Journal of Research and Management. 2017;39(3):4–16.

95.

Hwang

, Sarstedt

, Cheah

, Ringle

. A concept analysis of methodological research on composite-based structural equation modeling: Bridging PLSPM and GSCA, Behaviormetrika. 2020;47(1):219–41.

96.

Holbrook

, Krosnick

, Pfent

. The causes and consequences of response rates in surveys by the news media and government contractor survey research firms, Advances in Telephone Survey Methodology. 2007:499–528.

97.

Armstrong

, Overton

. Estimating nonresponse bias in mail surveys, Journal of Marketing Research. 1977;14(3):396–402.

98.

Brown

. Just how credible are your market estimates?Journal of Marketing. 1969;33(3):46–50.

99.

Schwirian

, Blaine

. Questionnaire-return bias in the study of blue-collar workers, The Public Opinion Quarterly. 1966;30(4):656–63.

Direct Relationship				95% BCa CI
	Std Beta	Std Error	t-value	LL	UL	R²	Adjusted R²	VIF	f ²	Q²
H1a: Employee Empowerment						0.444	0.436			0.318
->Job Engagement	0.451	0.071	6.338	0.344	0.569			1.694	0.216 (M)
H2a: Employee Involvement
->Job Engagement	0.274	0.082	3.329	0.146	0.407			2.145	0.063 (S)
H3a: Employment Stability
->Job Engagement	– 0.014	0.058	0.232	– 0.113	0.08			1.748	0.000
H4a: WLB
->Job Engagement	0.171	0.067	2.561	0.287	0.066			2.013	0.026 (S)
H5a: Working Environment
->Job Engagement	0.181	0.067	2.724	0.063	0.279			2.242	0.027 (S)
H1b: Employee Empowerment						0.663	0.588			0.474
->Organizational Engagement	0.052	0.058	0.888	– 0.045	0.14			1.694	0.068 (S)
H2b: Employee Involvement
->Organizational Engagement	0.313	0.07	4.499	0.195	0.43			2.145	0.193 (M)
H3b: Employment Stability
->Organizational Engagement	0.126	0.047	2.693	0.041	0.195			1.748	0.020 (S)
H4b: WLB
->Organizational Engagement	0.064	0.049	1.305	– 0.014	0.145			2.013	0.000
H5b: Working Environment
->Organizational Engagement	0.101	0.06	1.695	0.004	0.200			2.242	0.030 (S)
H6: Job Engagement
->Org Engagement	0.367	0.062	5.908	0.259	0.467

	PLS-SEM			LM			PLS-LM
	RMSE	MAE	Q²_ predict	RMSE	MAE	Q²_ predict	RMSE	MAE	Q²_ predict
JobEn3	1.188	0.876	0.289	1.157	0.881	0.325	0.031	–0.005	–0.036
JobEn5	1.045	0.824	0.399	1.042	0.804	0.403	0.003	0.020	–0.004
JobEn4	1.138	0.891	0.333	1.085	0.843	0.393	0.053	0.048	–0.060
JobEn2	1.219	0.935	0.209	1.235	0.955	0.188	–0.016	–0.02	0.021
JobEn1	1.099	0.870	0.289	1.120	0.881	0.262	–0.021	–0.011	0.027
OrgEn6	1.060	0.756	0.492	1.071	0.794	0.481	–0.011	–0.038	0.011
OrgEn5	1.074	0.810	0.430	1.042	0.788	0.464	0.032	0.022	–0.034
OrgEn4	1.160	0.864	0.408	1.101	0.842	0.466	0.059	0.022	–0.058
OrgEn1	0.986	0.695	0.482	0.999	0.719	0.469	–0.013	–0.024	0.0130
OrgEn3	1.019	0.743	0.485	0.995	0.739	0.509	0.024	0.004	–0.024
OrgEn2	0.973	0.713	0.499	1.002	0.743	0.469	–0.029	–0.03	0.030