Evidence of the Great Resignation: Remote Worker Engagement and Intent to Stay or Leave during the COVID-19 Pandemic ()
1. Introduction
As the world experienced the first half of the year 2022, the advantages, disadvantages, and challenges associated with telework and remote management presented in literature provided an enriched stage for observation and reflection in these unprecedented times (Bailey & Kurland, 2002; Tate et al., 2019) . With the advent of the COVID-19 pandemic and the evolution of new communication technologies (ICTs), the virtual organization is born and defined as the new organizational structure. This new structure has become a place of work devoid of centralized buildings and physical plants most characteristic of traditional organizations (Hartman & Guss, 1996) . Tate et al. (2019) argued this new organization must be “reimagined for organizations to effectively harvest the potential benefits this new structure may afford” (p. 342).
With the ongoing pandemic, the year 2021 was coined the year of the “Great Resignation” as scores of employees quit their jobs. Labor economist and Harvard professor of Economics, Lawrence Katz, explained that three main reasons were provided by employers to justify these departures: workers quitting voluntarily, workers being laid off or fired, and other separations including announced retirements (Pazzanese, 2021) . In addition, many people who lost their jobs during the pandemic opted not to get back into the workforce. Overall, this study seeks to find if the wave of voluntary departures and retirements could be anticipated by the level of employee engagement in the now virtual working environment.
The current study strives to add to literature and unveil this reimagined opportunity by investigating early reactions of employees to this new structure, and their own engagement given their new work locations and proximity to fellow workers. This study presents results from data collected in August 2021 across the United States.
2. Literature Review
2.1. Reshaping of Work-Pre and Post Pandemic
For most people the pandemic has affected almost every aspect of their lives. The new normal is characterized by increased incident and exploding numbers of employees working from home. Several major employers such as Microsoft, Google, and Amazon to name a few, announced new work arrangements since the beginning of the pandemic. The situation of working from home is complimented by an acceleration of new and expanded communication technologies making the advent of working from home more possible than ever. The effectiveness of these complimentary communication technologies has served to reshape the work arrangement of literally thousands in the American workplace. The phenomenon is referred to as the hybrid work arrangement wherein the question of the extent and resulting impact on employee engagement is raised, questioned, and investigated.
Pre-Pandemic
Long before COVID-19, working from home had become a varied and surprisingly new work arrangement. Early in the 21st century, businesses had begun installing modified work arrangements such as hoteling and the like. Reportedly, there was a slow movement towards remote work among knowledge workers during these early years (Tate et al., 2019; Lartey & Randall, 2021b) . Workers typically employed in consulting firms, law firms, and universities were those mainly represented. Remote worker opportunities increased in parallel with technology improvement.
Post-Pandemic
This is a period of transformation for the individual worker as well as the organization resulting in multiple work arrangements dominated by work from home scenarios of many forms. The post-pandemic future offers many opportunities for a better understanding and grasp of organizational effectiveness. Reportedly, 45% of people say their own life has been affected “a lot” by the coronavirus situation (Gallup, 2021) . Many organizations have announced plans to introduced hybrid or blended work-home arrangements with attendant hour flexibility. The advent of the pandemic has “accelerated the adoption of flexible work arrangements from use of Zoom for meetings and Microsoft Teams for office chatter” (Ellis, 2021: p. 4) .
Given this expanding, and in many instances, new breed of work arrangements, the worker management and engagement experiences become more complex and warrants investigation and deliberate study. For organizations, the arrangement forbodes reduced office space requirements and associated cost; and for workers, spats of professional isolation and potential disengagement making the understanding of the new work arrangement critically important to all (Cooper & Kurland, 2002) . That is, the assessment and identification of key aspects of experiences workers have when working from home is tantamount to the worker’s and the organization’s future success. An impending question looms for organizations, e.g., how do we maximize lessons learned for a productive and profitable future?
2.2. Employee Engagement (the Opportunity)
Certainly, in these unprecedent times, an engaged employee is clearly a desirable end irrespective of whether the employee is located in-house or remote. Reportedly, employee engagement is highly related to employee retention (Jones & Harter, 2005; Shuck et al., 2014; Schaufeli & Bakker, 2004) . However, when working remotely, a different set of demands and requirements are manifested. For example, flexibility has surfaced as the most important preference among employees (Gandhi & Robison, 2021; Lartey & Randall, 2021a) . In a recent study, Lartey (2022) found that the relationship between the manager and the remote employee, as perceived by the employee, was a significant determinant of remote employee engagement.
For the purposes of this study, employee engagement is defined as set forth by Lartey (2021) as, a two-way relationship between an organization and a worker, in which the organization provides the worker with the environment and conditions to be successful through good leadership and management, and the worker provides the organization with a positive and self-motivated performance leading to the achievement of organizational mission, vision, purpose, and goals (Lartey, 2021: p. 137) . To further illustrate and define the engagement construct, please note the depiction on Figure 1 as presented by Lartey and Randall (2022) , theorizing that highly engaged employees reside at the intersection of self-determination, self-efficacy, and social exchange.
As reported in Gallup’s State of the Global Workplace: 2021 Report, 34% of employees in the United States and Canada are engaged, leaving a remarkably large number who may well be classified as disengaged. This level of disengagement can be costly and certainly serves as a clarion for human resources and human capital professionals alike to take heed. Understandably, disengagement can be costly in terms of dollars and cents. Gallup’s 2021 Report advanced that an estimated disengagement costs about $60.3 million a year for a company of 10,000 employees with an average salary of $50,000 each.
To further clarify the opportunity, in a recent survey conducted by Microsoft, more than 40 percent of employees are considering leaving their employers this year. However, organizational leaders across the country are searching for ways to maintain employee engagement during this emerging era of virtual reality. They are asking themselves, what might this new environment mean for life in the corporate world of work.
2.3. Turnover Intentions
In this turbulent and competitive economy, employers are facing ongoing changes and numerous business challenges that can cause concerns. Among these challenges coupled with the COVID-19 pandemic, employers are confronted with competition, technology advancements, and employee retention that could limit their long-term sustainability. Simultaneously, a shortage of key personnel can exacerbate the situation. Understanding and predicting remote
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Figure 1. Diagram depicting the conceptual view of employee engagement as it relates to the organization through the influence of leadership. As presented, highly engaged employees are characterized by a combined sense of self-determination, self-efficacy, and social exchange (permission granted January 2022).
workers intent to leave or intent to stay can be instrumental in the development of improved conceptual frameworks of employee engagement and remote worker success. Further, understanding and predicting whether a worker may decide to leave or stay can allow an employer to develop implementation of effective retention strategies for remote workers and invest considerable resources in recruitment, business support, wellness, and compensation.
Employee intentions to leave or turnover intentions can be defined as being the same. For example, Yousaf, Sanders, and Abbas (2015) defined employee intention to leave as an employee’s deliberate decision to leave their current job in search for a new job with another company. In another instance, Ngamkroeckjoti et al. (2012) referred employee turnover intention to the likelihood of leaving the current job they are performing. Belete (2018) pointed out the prerequisite for an individual to leave a job or an organization is the intention to leave and can be referenced as turnover intention. However, the uncertainty of whether employees have intentions to leave an organization can be challenging for business decision makers because turnover intentions are not explicit, making it difficult to determine factors that drive employees to leave a job or an organization (Belete, 2018) . Regardless of a business size or nature, considering employee turnover intention can be costly without examining factors that influences employees. Reasons employees stay with employers can be significantly different from reasons they leave. For example, an employee may find a choice job closer to their home, find a better opportunity with work flexibility, or accept an offer with an increase in pay and benefits. These may be good reasons to leave a job; however, these may not be reasons that piqued the employees’ interests or led them to start seeking new opportunities elsewhere. Although work flexibility, pay and benefits are critical factors, there are other determinants that can play a critical role in retention.
2.4. Turnover Impact and Influencing Factors
Recently, a job opening, and labor turnover summary released by the U.S. Bureau of Labor Statistics reported on August 9, 2021, employee separations in June 2021 totaled 5.6 million, an increase of 254,000 including layoffs, quits, discharges and other separations. The same report showed the quit levels and rates increased by 239,000 (U.S. Bureau of Labor Statistics, 2021) . Despite these sky-scraping rates being alarming, underlying causes that drastically impacts these employees, businesses, and economy remains a mystery.
There can be different factors affecting employee turnover intention including but not limited to employee job engagement, personality, job satisfaction, organizational commitment, promotional opportunities, job stress, salary, work flexibility, performance, and organizational culture. Among these determinants, Jha (2009) stated no specific or single factor can be attributed to turnover intentions and proposed following a holistic approach in examining factors affecting employee turnover intentions.
2.5. Intent to Stay
Companies can create programs to promote employee engagement, job satisfaction and other influencing variables to increase retention. Since COVID-19, in a SHRM report according to Maurer (2021) , LinkedIn reported internal mobility increased by 20%. Employees laden with making decisions to remain employed at a company can find it daunting in some instances. While in other cases, the concept of staying is not considered an option. Further, as the ubiquitous pandemic fluctuates, given the competitive economy and uncertainty of potential employment opportunities, employees are remaining in place. Essentially, there could be many reasons employees intend to stay with a company. For instance, there may be a commitment to their occupation, not the organization. Allen and Meyer (1990) referred affective organizational commitment to an employee’s emotional attachment, involvement, and identification to the organization. Essentially, employees with this type of commitment remain with the company because they chose to stay (Allen & Meyer, 1990) . Affective occupational commitment refers to an individual’s emotional identification with their occupation or work goals (Lee et al., 2000) .
Through an extensive investigation, Yousaf et al. (2015) found a negative relationship between affective organizational commitment and organizational turnover intention. However, the authors pointed out there was a buffer amid the relationship between affective organizational commitment and organizational turnover intention, which was affective occupational commitment. This means employees or individuals who are more committed to their occupation, will identify with their occupation, and intends to stay in their occupation, hence reflects diminished turnover intentions. Therefore, occupational turnover intention is critical due to its potential connection to retention.
3. Data Analysis
3.1. Sample and Procedure
Data were collected through an online survey of 601 participants, all remote workers in the United States of America (U.S.). To avoid bias, a random selection of the participants was conducted using services of an online research firm. There was no missing value in the collected data as all data fields were informed. The participants in this study were 18 years or older as shown on Table 1 with a breakdown by gender in Table 2. Four age groups were identified: Baby Boomers (BOOMERS): 6.8%; Generation-X (GENX): 13.1%; Generation-Y or millennials (GENY): 58.1%; and Generation-Z or i-Generation or Centennials (GENZ) representing 22% of the sample. The age groups were based on a recommendation from the University of Southern California’s (2020) research guidelines. Further, genders were analyzed, illustrating that this sample was composed of 39.3% males, 60.1% females, and .7% identified as non-binary. Table 2 summarizes this view of the sample by gender.
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Table 1. Demographic breakdown of the sample by age group.
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Table 2. Demographic breakdown of the sample by gender.
3.2. Measurements
In seeking to understand if there was a relationship between employee engagement and both the intention to leave and the intention to stay, a hypothetical model was constructed. This model shows the presence of one independent variable (employee engagement) and two dependent variables: intent to leave and intent to stay. This representation is depicted in Figure 2.
For this study, each component of the hypothesized model was measured using a specific instrument.
Employee Engagement
Employee engagement was measured using a scale called EENDEED, standing for Enhanced Engagement Nurtured by Determination, Efficacy, and Exchange Dimensions. EENDEED is a nine-item engagement instrument developed by Lartey and Randall (2022) , specialized in measuring remote employee engagement. EENDEED is based on three theories 1) Self Determination, 2) Self Efficacy, and 3) Social Exchange. Together, these theories were identified by Lartey and Randall to explain remote employee engagement. A calculation of the Cronbach Alpha of the instrument in this study showed an alpha value of .84, well above .7, which is considered good. As such, it was confirmed that this instrument measured a common concept, that of remote employee engagement. A Cronbach alpha reliability score was calculated for each of the two factors of EENDEED, showing that PERFORMANCE had an alpha of .80 and SELF-RELIANCE had an alpha of .74, both above the .70 considered good.
Intent to Stay
Intent to stay was measured using a seven-item instrument developed by Mayfield and Mayfield (2007) . The seven items are organized in two factors: positive intentions and negative intentions. The value of Cronbach’s alpha for
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Figure 2. Hypothesized model showing the relationship between engagement and both intention to stay and intention to leave.
the scale was .69, deemed acceptable for the study. Further analysis of the reliability of its components revealed a Cronbach alpha of .72 for the positive intentions factor, and .86 for negative intention factor.
Intent to Leave
The intent to leave was defined as a person’s desire to voluntarily leave their current job. It was measured using an instrument developed by Martin and Hafer (1995) . Each of the three items was standardized and converted to a z score in a process proposed by Martin and Hafer (1995: p. 317) . The standardization was done using the SPSS function Analyze > Descriptive Statistics > Descriptives and saving the standardized values. The resulting Cronbach alpha score of the standardized scale as processed was .68. This was deemed acceptable for the scale to be included in the study.
3.3. Reliability of the Survey Questionnaire
The reliability score of the entire survey questionnaire containing the three instruments used was calculated. A Cronbach alpha score of .82 was obtained, confirming the questionnaire was reliable.
3.4. Hypothesized Model
A structural equation model (SEM) was hypothesized to ascertain the relationship between remote employee engagement measured by EENDEED and 1) the intention to stay; and 2) the intention to leave. The hypothesized SEM model is presented in Figure 3. Circles are used in this model to represent latent variables and rectangles indicate measured variables. This hypothesized model seeks to find if engagement can explain the variances in the intent to stay as well as the
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Figure 3. Hypothesized model with lines between variables suggesting interest in their direct relationship. rectangles are measured variables, while ovals represent factors or unobserved variables or constructs. Circles or ovals named ex represent error estimates.
intent to leave. As presented, the model has one independent variable (IV) named EENDEED, and two dependent variables ITS (Intent to Stay) and ITL (Intent to Leave). Like EENDEED, ITS has two factors, while ITL has none.
3.5. Assumptions of the SEM
Prior to proceeding with SEM, various assumptions needed to be validated. These included 1) sample size and missing data; 2) normality and linearity; 3) univariate and multivariate outliers; 4) absence of multicollinearity and singularity; and 5) residuals, as suggested by Tabachnick and Fidell (2013) and implemented by Randall et al. (2020) .
Sample Size and Missing Data
The sample size was validated using the a-priori sample size calculator for the SEM developed by Soper (2021) . The parameters used included: 1) medium effect size of .3, where .1 and .5 respectively represent small and large effect size; 2) the number of latent variables or factors of 7; 3) total observed or measured variables of 21; 4) a probability level of .05; and 5) a minimum power of .80. The results suggested a minimum recommended sample size of 200 cases. As such, the sample size of 601 cases was sufficient for SEM. There were no missing data.
Normality and Linearity
Normality of the measured variables was observed using SPSS through the examination of skewness and kurtosis, along with histograms. No variable had a standardized skewness or kurtosis greater than 3.75 as recommended by Tabachnick and Fidell (2013) .
Linearity among pairs of observed variables was validated using scatter plots in SPSS. Because linearity was not feasible to validate all scatterplots created by each possible pairs of observed variables, few variables were randomly evaluated. Each pair evaluated showed existence of a slope confirming a linear relation among the variables, which confirmed that the assumption of linearity was met for this study.
Univariate and Multivariate Outliers
Using SPSS function Analyze > Descriptive Statistics > Descriptives, 13 records were identified with a z-score over the absolute value of 3.29. Further analysis showed that these were all the participants who answered, “strongly disagree” to the question, “I successfully complete difficult tasks and projects”. Decision was made to keep these records, because a review of their answers to other questions did not reveal any suggestion of bias. In addition, this decision was made because their z-scores were all at 3.39, not too far from the maximum of 3.29. Multivariate outliers were assessed using the Mahalanobis distance. Eight cases of multivariate outliers were detected and deleted (p < .001). This brought the total number of cases for the study to 593.
Absence of Multicollinearity and Singularity and Residuals
Multicollinearity was validated by analyzing the variance inflation factor (VIF) and the tolerance. All values of the VIFs were below 10 and all tolerance values were above .2. Singularity was assessed using the determinant of the correlation matrix which was confirmed to be greater than zero. This is a condition required by IBM Amos to execute SEM. Similarly, residuals were analyzed as part of the model construction in IBM Amos.
3.6. Model Estimation
A SEM was created using IBM Amos version 20 with data from 593 cases. An estimation of the initial model showed the variance e23 was negative and estimated at −.104. Because the variance cannot be negative, the model was considered unacceptable. To remediate and make the model acceptable for SEM, the unobserved variable ITS was removed and two relationships were created, one going from EENDEED to Positive Intent to Stay, and the other going from EENDEED to Negative Intent to Stay. The resulting model had one IV and 3 DVs as presented on Figure 3. A rerun of the SEM showed an acceptable model. This acceptable model investigated the hypothesis that employee engagement measured by EENDEED had a significant relationship with employees’ positive intent to stay (ITS_POS), employees’ negative intent to stay (ITS_NEG), and employees’ intent to leave (IT_LEAVE); all three being dependent variables for this study.
The resulting model was estimated using maximum likelihood estimation. Even though the chi-square for the model was significant, χ2 (148, N = 593) = 669.70, p < .05, alternative fit indices showed an acceptable fit to the data CFI = .874, NFI = .845, GFI = .887. The root mean squared error approximation (RMSEA) showed good fit RMSEA = .077 where a poorly specified model has a RMSEA greater than .1 (Tabachnick & Fidell, 2013) . Having had a model deemed acceptable, an interpretation of the model was necessary.
The SEM results are shown in Figure 3 where the values associated with each path are standardized regression coefficients. These scores confirmed existence of a stronger relationship between employee engagement and positive intent to stay (ITS_POS) as compared to ITS_NEG and IT_LEAVE. Further, they suggest an increase by one standard score of employee engagement (EENDEED) would result in an increase of positive intent to stay by about .79 standard points, while accounting for an increase of IT_LEAVE by .53 standard point, and an increase of ITS_NEG by .04 standard point.
An analysis of the output from IBM AMOS confirmed a statistically significant relationship between EENDEED and ITS_POS (p < .001). It showed the relationship between EENDEED and ITS_NEG was not significant (p = .375), and the relationship with IT_LEAVE was significant (p < .001). In other words, there is evidence that employee engagement as measured by EENDEED influences remote employees’ positive intention to stay and also influences their intention to leave (Figure 4).
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Figure 4. Model with standardized loadings showing the relationships between eendeed and positive intent to stay (ITS_POS), negative intent to stay (ITS_NEG), and intent to leave (ITL).
Further analysis was conducted by linking the error variables to ascertain the impact on the model. The resulting model with standardized loadings is presented on Figure 5.
The resulting model was estimated using maximum likelihood estimation and the fit indices showed a slightly improved fit of the model to the data with CFI = .893, NFI = .861, GFI = .903 and RMSEA = .070. In addition, χ2/df = 3.84, which is under the limit of 4, thus confirming the acceptability of the model and calling for its analysis and interpretation.
4. Discussions
The results of the SEM as shown in Figure 5 confirmed the existence of a stronger relationship between remote employee engagement and positive intent to stay (ITS_POS) as compared to negative intent to stay (ITS_NEG) and intent to leave (IT_LEAVE). They suggest that an increase by one standard point of remote employee engagement (EENDEED) would result in an increase of positive intent to stay by about .85 standard points, while accounting for an increase of intent to leave by .65 standard point. The relationship between remote employee engagement and negative intent to stay was not statistically significant.
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Figure 5. Model with standardized loadings and independent variable errors linking, showing the relationships between eendeed and positive intent to stay (ITS_POS), negative intent to stay (ITS_NEG), and intent to leave (ITL).
One key finding in this study is the positive relationship between engagement and intent to leave. In other words, the more a remote employee was engaged during the COVID-19 pandemic, the more likely did they intend to leave the company. This is contrary to previous findings claiming that higher engagement levels led to higher employee retention, suggesting lower intent to leave. For example, an employee engagement survey study conducted by the Corporate Leadership Council (2004) found that increasing employee engagement levels could result in a reduction of the departure probability by up to 87%. Likewise, in another study of employee engagement and turnover in the United Kingdom, Smith and Macko (2014) concluded that higher levels of employee engagement resulted in reduced turnover, suggesting a lower intent to leave the company. Similarly, in a research study on employee engagement and turnover among the 2015 US Federal Government workforce, McCarthy et al. (2020) concluded that employees with higher engagement levels were less likely to report an intention to leave their jobs as compared to employees with lower engagement levels.
Given the preponderance of prior research aligning on a negative relationship between employee engagement and intent to leave, this questions what was special about the current population to obtain a positive intent to leave when employees were engaged. It should be noted that all previous studies cited were conducted on employees working in the traditional office space prior to the COVID-19 pandemic. The need to leave the current job even when employees are engaged was something common during the COVID-19 pandemic. This study confirmed the existence of a phenomenon known as “the great resignation” and seen in the United States and around the world during the COVID-19 pandemic (Allman, 2021; Avitzur, 2021; Parker & Clark, 2022; Telford & Gregg, 2021) . During the pandemic, scores of employees, while engaged in their current jobs, where still leaving their employers either to stay at home or to pursue different opportunities. Based on existing literature, this study provides an empirical evidence of the effect of the “great resignation” on engaged workers, which generally follows the intent to leave.
4.1. Theoretical Contribution
This study contributes to employee engagement literature by examining strengths of the social contract between virtual employee and organization. Burns (1973) theorized that social exchange minimized the transactional nature of workplace engagement, instead focusing on rights and obligations inherent in roles such as worker and employer. Homans (1958) established the worker as primarily responsible for controlling their environment. Ababneh et al. (2019) articulated an engagement relationship could be modified by altering conditions of employment. Finally, Lartey (2021) expanded the engagement relationship to include the virtual worker’s provision of a “positive and self-motivated performance leading to the achievement of the organizational mission, vision, purpose, and goals” (p. 137), while good leadership and management fulfill the organization’s obligations and conditions of employment.
This study reveals that the relational contract between virtual workers and their employers—worker engagement—is corollary with positive intent to stay. In an expression of initiative, engaged remote workers intend to remain in a relationship with the organization, but could as well leave as confirmed by the positive relationship of remote employee engagement with the intent to leave.
Various researchers have previously studied the relationship between employee engagement and the intent to leave or stay with the organization. Examples of such studies include the work of Gull et al. (2020) , Jones and Harter (2005) , McCarthy et al. (2020) , Shuck et al. (2014) , Saks (2006) , Harter et al. (2002) , Schaufeli and Bakker (2004) , Smith and Macko (2014) , and many others. The findings of all these studies confirmed the existence of a positive relationship between engagement and the intent to stay. The prior studies were conducted with samples of traditional office employees. In other words, the employees in the study worked in an environment where they met regularly with their managers and colleagues. In such configuration, the employees had face-to-face and in-person meetings with their managers, allowing them to socialize and empathize with others in the workplace.
With the advent of the COVID-19 pandemic, many employees started working remotely. Some were hired without any face-to-face meeting with their new supervisors. Such working context questions the findings from previous studies on traditional workplace employees were still true for the new population of remote workers during the COVID-19 pandemic.
While the findings of this study confirmed previous findings of the existence of a positive relationship between the engagement of employees in a remote setting as well as traditional setting, the study uncovered new knowledge. Indeed, it confirmed that while there was a positive relationship between engagement and intent to stay, there was also a positive relationship between engagement and intent to leave. In other words, while engaged remote employees had the intention of staying with their organizations during the pandemic, they did not feel committed to the organization and would entertain the idea of leaving for other opportunities.
These findings are aligned with a phenomenon known as the “Great Resignation” during which employees left their jobs in droves either for other positions, early retirement, or simply to stay home and take care of their families (Faccini et al., 2022; Laskowski-Jones & Castner, 2022; Serenko, 2023) . These employees did not leave because they were not engaged, but for many different reasons. Hence, this study demonstrated that remote employees being engaged and having the intent to stay did not necessarily mean they did not have an increased intent to leave during the COVID-19 pandemic.
4.2. Practical Contribution
As virtual workers continue to explore the relationship nuances arising from their post-pandemic working environment, they are learning to manage their own engagement with newly dynamic connections to resources, organizational leadership, and fellow workers. Armed with the knowledge that measured engagement drives positive intent to stay, organizations are better able to tailor the elements that undergird favorable engagement with remote workers. As organizations solidify opportunities for employees to work remotely, corporate decision makers can craft an inclusive corporate culture that recognizes and engages remote work in a meaningful fashion, resulting in employees electing to remain with the organization.
4.3. Limitations and Future Research
This study was conducted among remote workers in the United States. As such, findings from this study should not be generalized to other countries. Additional research might be conducted with remote workers based in countries other than the United States, assessing the role of engagement with employers. Research might be conducted to understand the role of corporate culture in remote worker engagement. Research might also be conducted to understand the influence of an effective engagement relationship on sense of belongingness among remote workers. Additionally, longitudinal as well as comparative studies at different cultural levels are needed because this study was cross-sectional. In other words, this research does not account for the situation and/or the experience over time. There is thus another opportunity for the same study to be conducted after the pandemic. Furthermore, a study could be conducted to analyze any possible moderating or mediating effect on the intention to leave. Other studies could also be conducted to examine the effects of different dimensions of engagement (i.e., performance and self-reliance) on remote employee turnover intention. Finally, the uniqueness of the data collected during the COVID-19 pandemic undoubtedly has its own limits for consideration rendering it more difficult to generalize. It should be noted that the intent to leave does not always materialize with the action of leaving, as engagement could still contribute to retention. Further study could help understand the relationship between the intent to leave and the action of leaving.
5. Conclusion
Amid these unprecedented times, the engagement of employees in general and the engagement of remote employees in specific offers a critical time for organizations to embark upon new approaches to foster employee engagement and their intent to leave or stay. While the preceding study’s discussion addresses notably the remote employees specifically, worker instability is not a new phenomenon; however, it has been severely aggravated by the advent of the COVID-19 pandemic. Make note, the results and the response of this study are applicable to all employees in the face of what has been characterized in print as the period of the “Great Resignation” (Telford & Gregg, 2021) . The opportunity for organizational leadership to forge a way forward is undoubtedly foreboding and likely to be fraught with missteps.
Albeit it appears unlikely that the ongoing COVID-19 pandemic will be resolved quickly. It is clearly a critical time for the mobilization and demonstration of ways to effectively engage workers throughout the organization in all activities performed in-house or remotely. As reported, occupational turnover intention is important to understand and embrace, given its potential connection to retention. It is a better course of action for organizations to understand the conditions of remote worker engagement, and consequently, design a more effective course of action to address this new opportunity. The resulting content of this study offers viable prospects for that opportunity.
Acknowledgements
We wish to acknowledge that funding support for the data collection of this research was provided by Saurage Research, Inc., a global research organization located in Houston, TX, USA.