Abstract
Purpose
This study aims to identify factors influencing attitudes towards remote work, categorise employed Latvians into proponents and opponents of remote work and analyse these groups in the work-family-community-self integration.
Design/methodology/approach
This study adopts the job demands-resources theory. Empirical research is based on a survey of employed Latvians (Feb–Mar 2021, n = 1,052, n = 853,200). The focus is on employed Latvians with remote work experience, constituting 534 individuals (50.7% of the sample). The sample aligns with the demographic profile of employed Latvians, with data weighted by age and sex (across 12 age–sex combinations) from the Central Statistical Bureau of Latvia. Research hypotheses include identification of “discriminatory” factors influencing the attitudes towards remote work, distinguishing between proponents and opponents; examination of distinct job demands and resources related to the work-family-community-self integration within the groups of proponents and opponents of remote work.
Findings
Survey results indicate that 11.2% respondents worked remotely before the COVID-19 pandemic, typically without formalisation. Among those with remote work experience, 40% support it, whereas 60% oppose it. Rather than social and demographics or employer support, work-related values play the most significant role in shaping attitudes. Proponents generally acquire more job resources than demands through remote work, fostering the work-family-community-self integration; conversely, opponents experience the opposite trend.
Originality/value
This study provides empirical insights into the attitudes of employed Latvians towards remote work in the work-family-community-self integration, using the job demands-resources model. Notably, it innovatively evaluates the institutionalisation of remote work.
Keywords
Citation
Mietule, I., Komarova, V., Lonska, J., Litavniece, L., Arbidane, I. and Matisane, L. (2024), "Latvian employees’ attitudes towards remote work in the framework of work-family-community-self integration: a survey using the job demands-resources model", Journal of Enterprising Communities: People and Places in the Global Economy, Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/JEC-06-2023-0091
Publisher
:Emerald Publishing Limited
Copyright © 2024, Iveta Mietule, Vera Komarova, Jelena Lonska, Lienite Litavniece, Iluta Arbidane and Linda Matisane.
License
Published by Emerald Publishing Limited. This article is published under the Creative Commons Attribution (CC BY 4.0) licence. Anyone may reproduce, distribute, translate and create derivative works of this article (for both commercial & non-commercial purposes), subject to full attribution to the original publication and authors. The full terms of this licence may be seen at http://creativecommons.org/licences/by/4.0/legalcode
1. Introduction
During the coronavirus disease 2019 (COVID-19) pandemic, several employed individuals worldwide have experienced forced remote work, which significantly influences work–family (life) balance and work-family-community-self integration (the participants of most modern studies on the interconnection between work and other dimensions of life). In this study, remote work is understood as work that occurs at home or at any location that is not a formal employer site (e.g. a café or third-party co-working space) on a full-time or near-full-time basis (i.e. four or more days a week; Soroui, 2021). This aligns with various stakeholders’ definitions of remote work (Gartner, 2022; Law Insider, 2022; Wrike, 2022).
Previous research results and their interpretations in several countries show the different attitudes of the employed population towards remote work and its [attitudes] determining role in the process of integrating work, family [home], public and private life (Monakhova, 2016; Uresha, 2020). Most likely, every society has groups of employed individuals, proponents and opponents of remote work that are comparable in number and significance. The scientific problem lies in the lack of research identifying the factors that divide the employed population into proponents and opponents of remote work. The level of work-family-community-self integration within the groups of proponents and opponents of remote work has also not been analysed in comparative terms.
This study aims to identify the factors that determine attitudes towards remote work, divide employed Latvians into proponents and opponents of remote work and analyse the groups of proponents and opponents of remote work in the context of work-family-community-self integration. The objects of this study were Latvians, particularly employees, entrepreneurs and self-employed persons (n = 1,052, n = 853,200), focusing on employed Latvians with remote work experience (n = 534, 50.7% of the sample). The sample aligns with the demographic profile of employed Latvians, and the data were weighted by age crossed with sex (in 12 age–sex combinations) from the Central Statistical Bureau of Latvia.
The remainder of this article is structured as follows: Section 2 reviews and analyses the literature containing research results on remote work in the context of work-family-community-self integration. Subsequently, we describe the conceptual framework of the study (Section 3) and the research methodology (Section 4) and present the research results (Section 5), which are organised around two main research questions:
What factors determine the attitude of respondents towards remote work, dividing them into proponents and opponents?
Which group (proponents or opponents of remote work) integrates the work-family-community-self dimensions better?
In Section 6, the results are discussed and compared to those of previous studies. Based on these results, we draw certain conclusions (Section 7), including the contributions and novelty of the study and possible future lines of research in this field.
2. Literature review
Work–life balance, work–family balance, work–family conflict and work–life conflict have been the subjects of many recent studies on the interconnection between work and other dimensions of life (McNamara et al., 2013; Davis et al., 2014; Kinman et al., 2016; Gravador and Teng-Calleja, 2018; Liu et al., 2019; Rahman et al., 2020; Uresha, 2020; Mary and Ramesh, 2020; Kengatharan, 2020; Lonska et al., 2021; Magadley, 2021). In the 2000s, the new work–family integration approach occurred in the scientific literature, for example, in the “Handbook of Work-Family Integration” (2008). It explores whether the dominant view of the work–family integration is negative. Deeply entrenched beliefs that individuals have a finite amount of time and energy and that work and family compete for these finite resources have contributed to a nearly exclusive focus on work–family conflict (Ayoko et al., 2021). However, the distinction between work–family conflict and work–family integration is essential. All existing instruments purporting to measure work–family conflict measure work–family interference. Distinguishing these concepts is more than merely semantic because instruments assessing work–family integration confound experiences where work and family exert mutually incompatible pressures (Carlson and Grzywacz, 2008).
The work–family integration approach is based on current empirical evidence, for example, the study on the relationship between work and family conflict and work–life integration among academic migrants of higher educational institutions in Bengaluru (Mary and Ramesh, 2020). This drop-off survey was conducted using a structured questionnaire (five-point Likert scale). The findings show that although there are significant differences in some of the conflicts associated with family and work, there is still empirical evidence that there is an impact on each other (Mary and Ramesh, 2020). The current research investigates whether work–family integration preferences and organisational supplies jointly affect work–family balance (Liu et al., 2019). For example, the results of the polynomial regressions on 393 employees support the congruence effect hypotheses. In particular, the results show that employee work–family balance is higher when work–family integration preferences and organisational supplies are congruent, as opposed to incongruent. An individual’s balance is higher when preferences and supplies are aligned at higher rather than lower levels (Liu et al., 2019).
However, we adhere to the position of Friedman, a founder of the work-family-community-self-integration approach in organisational studies (Friedman, 2008, 2014): “A commitment to better ‘work–life balance’ is not the solution. As I have long argued, balance is a bunk. It is a misguided metaphor because it assumes that we must always make trade-offs among the four main aspects of our lives: work or school, home or family (however you define that), community (friends, neighbours, religious or social groups), and self (mind, body, spirit). A more realistic and gratifying goal is better integration between work and the rest of life through pursuing four-way wins, improving performance in all four dimensions” (Friedman, 2014). There is much discussion about work–life balance, but Friedman suggests a couple of ways in which he thinks this approach is different. Firstly, it starts with the statement that one can find ways of creating value, improving performance in all four domains – what he calls a “four-way win”: work, home, community and self – by making intelligent choices about how they use their time and attention that do not necessarily require a trade-off (Friedman, 2008).
We believe that work-family-community-self integration (rather than balance) is achievable with the help of such a way of organising work as remote work. The findings of many studies show that the office environment has enough distractions that interfere with the work conversations of colleagues, such as coffee breaks and breakdowns of office equipment. It is not about them but the so-called structuring behaviour (Raghuram and Wiesenfeld, 2004), the employed individual’s ability to structure their working day. In remote work, employees have more possibilities (options) for integrating work-family-community-self dimensions than when working in the office, especially in closed organisations. Thus, remote work can increase the capability of employed persons, especially in the context of work-family-community-self integration: “The ability to balance work and home life has become the key to feeling happier and more productive while at work. Saving time that would otherwise be spent on a long commute allows employees to have better work-life balance and adds hours back into their days” (WeWork, 2020).
In recent years, there has been much scientific research on remote work: differences between various groups of remote workers, and implications of remote work from a local perspective; the impact of remote work on commuting in cities (Donati et al., 2021; Lonska et al., 2021; Soroui, 2021; Sweet and Scott, 2022), and some attempts to gain a deeper understanding and explain the phenomenon of accepting or rejecting remote work. For example, the German company “Statista”, a provider of market and consumer data, conducted a worldwide two-stage (Jan–Feb 2020, n = 3,000+; Feb–Mar 2021, n = 3,900) online survey of adult professionals who work remotely or have the option to work remotely and are in roles with digital output. K. Mlitz, the research expert, comments on the results of this survey as follows: “In 2021, 80% of respondents would recommend working remotely to a friend. This is a 10% decline compared with the previous year. Overall, attitudes towards remote work are positive if employees are given appropriate tools and technology to work remotely” (Mlitz, 2021).
Salomaa and Caputo (2021) conducted a case study investigating how the swap to remote work has affected RDI activities at Tampere University of Applied Sciences, one of the biggest University of Applied Sciences in Finland with intense regional linkages. Firstly, the above case study introduced an expanded theoretical approach for assessing the external and internal factors having an impact on the RDI activities beyond academic entrepreneurship. Secondly, it shared insights and good practices for optimising high-quality innovation support, knowledge transfer activities and co-creation of new knowledge in exceptional circumstances (Salomaa and Caputo, 2021). Tavares et al. (2020) found that in Portugal, adapting to remote working was easy or very easy and that it happened very quickly. The main difficulties encountered by the individuals were the lack of professional interaction/communication with co-workers, the lack of resources related to support infrastructures, such as the internet or a printer and the reconciliation of teleworking with family life/household chores/dedication to children and time/schedule management (Tavares et al., 2020).
The results of the abovementioned studies indicate that there are some factors (work-related values (Hofstede, 1980, 2001; Hofstede et al., 2010), support from the employer with the appropriate tools and technology to work remotely (Tavares et al., 2020; Mlitz, 2021; Salomaa and Caputo, 2021) and social and demographic factors (Tavares et al., 2020; Lonska et al., 2021)), which can determine the attitudes of the employed population to remote work and work–life balance. Nonetheless, they [factors] have a statistically significant discriminatory potential to divide the employed population into proponents and opponents of remote work, which has not been empirically tested. Thus, Mlitz (2021) studied attitudes towards remote work in companies worldwide from 2020 to 2021 and found that these attitudes are somewhat positive if employees are provided with appropriate tools and technologies (technological support). Regarding social and demographic factors, Lonska et al. (2021) found that women in the 18–44 age group and respondents with minor children were more likely to face difficulties in remote work.
However, of particular interest is Hofstede’s cultural dimensions approach to remote work, and some recent studies (Wojcak and Barath, 2017; Rahman et al., 2020; Beno, 2021) suggest that Hofstede’s cultural dimensions offer a comprehensive model for capturing different expressions of cross-cultural values and exploring motivations for remote work in the framework of work-family issues in various countries. Important, that even testing the mediation effect of work–family balance in the relationship between work–family conflict and job satisfaction of Malaysian employees the authors of the study emphasised that Malaysia is a collectivist society (Rahman et al., 2020). This fact shows that researchers around the world consider Hofstede’s cultural dimensions when studying issues such as work–family balance, work–family conflict and job satisfaction. Beno (2021) studied 28 different cultures in European countries with six cultural dimensions concerning remote working and argued that hierarchy is considered culturally less critical. Notwithstanding, co-operation and support for remote work and well-being are the optimum solutions.
According to Van den Broeck et al. (2013), the psychological well-being and occupational health of workers became a central topic in work and organisation studies in the past decades of the 20th century, leading to various models such as the job demand-control [Support] model (Karasek, 1979) and the Effort-Reward Imbalance model (Siegrist, 1996). Recently, these were integrated and developed into the Job Demands-Resources (JD-R) model (Demerouti et al., 2001; Bakker et al., 2003; Schaufeli and Bakker, 2004; Bakker and Demerouti, 2007) and linked to the well-being and health of remote workers even before, but especially during and after the COVID-19 pandemic (Crawford et al., 2011; Rizwan and Sivasubramanian, 2022; Wells et al., 2023). However, there have been no attempts to use the JD-R model to study the attitudes of the employed population to remote work in the framework of work-family-community-self integration. We seek to address this gap within this study.
Based on the literature review, we propose the following hypotheses, which are verified in a quantitative analysis of the empirical data in this study:
Certain “discriminatory” factors determine respondents’ attitudes towards remote work, dividing them into proponents and opponents. This hypothesis will be tested using discriminant analysis to help us answer the first research question: What factors determine respondents’ attitudes towards remote work, dividing them into proponents and opponents?
The groups of proponents and opponents of remote work are characterised by different ratios of job demands and resources related to work-family-community-self integration. This hypothesis will be tested by comparing mean job demands and resource ratios. This will help us answer the second research question: Which group (proponents or opponents of remote work) integrates work-family-community-self dimensions better?
3. Conceptual framework
We distinguished three groups of factors that characterise the object of this study (employed Latvians with remote work experience):
Work-related values of respondents (what is essential at work and expectations from work);
Support for respondents (support from employer and bonuses received when working remotely); and
profile of respondents (socio-demographic characteristics).
Due to the different influences of these factors, the employed population with remote work experience was divided into two main typological groups (Figure 1):
proponents of remote work, who want to continue it after the COVID-19 pandemic; and
opponents of remote work, who do not wish to continue it after the COVID-19 pandemic.
Typological groups of proponents and opponents of remote work are presumably characterised by work-family-community-self integration or disintegration.
The conceptual framework for investigating work-family-community-self integration within this study, based on the JD-R model, is widely used to explore satisfaction with the balance between work and all other aspects of the lives of employed individuals (Voydanoff, 2005; Monakhova, 2016), including a tool for human resource management (Bakker et al., 2003; Bakker and Demerouti, 2007). The main idea of the model is to classify material and non-material elements that underlie the process of integrating work and all other aspects of an employed individual’s life into the demands of the person and the resources available to them. For example, job resources include the level of wages and professionalism, whereas demand refers to family responsibilities, which include childcare and housework. We believe that excessive dominance of job demands over resources leads to work-family-community-self disintegration and, on the contrary, significant dominance of job resources over demands contributes to work-family-community-self integration.
The main concepts used in the JD-R model are job demands and resources. A. Bakker and E. Demerouti, leading researchers within this theoretical approach, defined job demands as the physical, psychological, social or organisational aspects of work that require constant physical or psychological costs (effort and skills). Job resources are work aspects that are functional in achieving goals, reducing job demands and physical and psychological costs and stimulating personal growth and development (Bakker and Demerouti, 2007). The methodological JD-R approach has evolved into the JD-R theory (Bakker and Demerouti, 2014; Bakker and de Vries, 2021).
In her study of the factors of satisfaction with work–family balance using freelancers, Monakhova (2016) defined the concepts of job demands and resources as empirically interpretable and applicable categories rather than abstract theoretical constructs. Current work–family research, work, family and community demands and resources are derived from various work, family and community characteristics (Voydanoff, 2008). In the present study, job demands related to the work-family-community-self dimensions are interpreted as workers’ losses from remote work and job resources related to the work-family-community-self dimensions as benefits of remote work. The empirical interpretations of job demands and resources are provided in Table 1.
4. Research methodology
4.1 Measures
The empirical research on Latvians employed in this study was based on data from a large-scale survey conducted by Rīga Stradiņš University (RSU, 2021). This study reflects only part of the results of the empirical research carried out within the project:
Data on employed populations with remote work experience, including proponents and opponents;
Data on the employed population’s benefits of remote work and losses from remote work; and
Data on factors potentially differentiating the attitudes of the employed population towards remote work.
A structured survey of employed Latvians was conducted to obtain the data required for this research. The survey was disseminated via an internet link on publicly available websites, social networks and direct emails from 22 February 2021 to 23 March 2021. At the beginning of the survey, filtering questions were applied to recruit only paid workers employed during the previous year (1,576 of 1,722 respondents, i.e. 91.5% of the initial sample). The following exclusion criteria were used: working without a salary in family businesses, working without a salary on the family farm, being on maternity leave, being unemployed, being only retired, being a housewife and being only schoolchildren or students during the survey period.
Based on a conceptual, analytical description of the object of the empirical research (Figure 1), the factors potentially differentiating the attitudes of the employed population towards remote work were empirically interpreted within three groups with a numerically equal set of factors – with ten factors in each group.
The design of the questionnaire used for the survey is as follows:
Defining the share of remote workers among employed Latvians (Figure 2).
The question of determining the level of the institutionalisation of remote work (Table 3).
The question defines typological groups of proponents and opponents of remote work within employed Latvians with experience in remote work (Figure 3).
The question about the factors’ group “work-related values” (10 values) potentially differentiating the attitudes of the employed population towards remote work (Table 4).
The question about the factors’ group “support” (10 types of support) potentially differentiating the attitudes of the employed population towards remote work (Table 5).
The question about the factors’ group “profile” (10 socio-demographic characteristics) potentially differentiating the attitudes of the employed population towards remote work (Table 6).
A total of 13 job demands (13 losses from remote work) and 13 job resources (13 benefits from remote work) were related to work-family-community-self integration (Table 1).
All these questions formed a separate block of the questionnaire of a large-scale survey conducted by RSU (2021). This set of questions was created specifically to study the attitudes of employed Latvians towards remote work in the context of work-family-community-self integration.
4.2 Participants and sampling
The snowball effect and social network advertising were used to disseminate the survey, adapting the advertisement to maximise the recruitment of the missing groups of respondents. The survey sample size was calculated using the following formula (Cochran, 1963):
SS = sample size, respondents;p = the share of answers of interest, decimal;
Z-score (tabular value for each confidence level (CL]); ande = margin of error, decimal.
The minimum sample size is 657 according to the following parameters:
the share of answers of interest (standard deviation) was taken by default – 0.5 (Kish, 1965);
confidence level for this sociological survey was 96%, and the Z-score for such a CL was 2.05 (LTCC Online, 2021); and
the margin of error for the confidence level of 96% is 0.04, which means +−4% (Cochran, 1963).
To increase the probability of finding statistically significant results and considering the survey period, we made the Web link available for one entire calendar month or until there were 1,000 fully completed answers, whichever occurred first. In this case, the link to the Web survey was locked on the next working day after 1,000 respondents answered all survey questions. In total, 1,576 employed individuals (employees, self-employed and entrepreneurs) took part in the survey, but considering that the questionnaire was relatively long, only 1,051 respondents answered all the questions (response rate: 66.7%).
Data were weighted by age crossed with sex (in 12 age–sex combinations) to obtain data representative of the demographic profile of employed Latvians. The weighting targets included used population estimates for the first quarter of 2021 from the Central Statistical Bureau of Latvia by age group and gender (Central Statistical Bureau of Latvia, 2021). The weighting results are presented in the following Table 2.
4.3 Methods
The Web survey data were collected and managed using the Research Electronic Data Capture (REDCap) tool for electronic data collection and compilation. Data analysis was conducted using quantitative methods, particularly discriminant analysis and a comparison of means (using the independent samples t-test method). All survey data were weighted and analysed using the SPSS Windows software version 26.0.
5. Results
Although the survey was conducted at the beginning of 2021, it focused on earlier developments. This was when the Latvian Government decided to reduce the spread of COVID-19 on 12 March 2020 by declaring a state of emergency. This lasted until 10 June 2020 (the first wave of COVID-19). During this time, the education process in schools took place remotely, as did the work of state and local government institutions where possible. The availability of kindergarten services is restricted. Similarly, the private sector had to organise work as remotely as possible. For the second time, the COVID-19 pandemic was declared on 9 November 2020 and continued at the time of the survey (the so-called second wave of COVID-19).
In this article, the presentation of the study results is organised according to the research hypotheses, which are verified through a quantitative analysis of empirical data:
Certain “discriminatory” factors determined respondents’ attitudes towards remote work, dividing them into proponents and opponents; and
The groups of proponents and opponents of remote work are characterised by different ratios of job demands and resources related to work-family-community-self integration.
5.1 What factors determine the attitude of respondents to remote work, dividing them into its proponents and opponents?
To answer the above question and test the first hypothesis of this study, we calculated the share of workers with remote work experience in the sample because only these respondents will be the focus of further empirical analysis. Survey data (n = 1,052, Feb–Mar 2021) shows that the share of remote workers among employed Latvians is 50.7%, of which 11.2% started working remotely before the COVID-19 pandemic. Further, 27.1% started working amid the first wave of the COVID-19 pandemic in the spring of 2020, and 12.4% amid the second wave of the COVID-19 pandemic in the fall of 2020 (RSU, 2021). Only Latvians with remote work experience (n = 534) participated in the empirical analyses.
A specific feature of the Latvian labour market is the fact that remote work, even when the employee started working remotely before the COVID-19 pandemic, in most cases, is not institutionalised. For instance, there is no written agreement with the employer about performing the work remotely (e.g. an additional agreement to the employment contract and changes in the employment contract Table 3). Notably, the largest share of non-institutionalised remote work is observed in the group of “experienced remote workers”, for instance, those employed persons who worked remotely before the COVID-19 pandemic (Table 3).
The data in the following figure represent the distribution of respondents with remote work experience concerning their willingness to continue working remotely in the future (without a COVID-19 emergency) (Figure 2). Respondents were asked to choose from four answers:
I want to continue working remotely more often than now;
as often as now;
less often than now; and
I would not want to work remotely in the future.
The first two groups of respondents, per the conceptual, analytical description of the object of empirical research (Figure 1), are combined by the authors of this article into the group of “proponents of remote work”, the second two groups – into the group of “opponents of remote work”.
As the data in Figure 3 show, 206 respondents (38.5%) with remote work experience wanted to continue working remotely (as often or even more often than now) in the future after the COVID-19 emergency. For instance, they were proponents of remote work. In turn, 315 respondents (58.9%) with remote work experience did not want to continue working remotely at all, or at least wanted to work remotely in the future less than they do now; that is, opponents of remote work. Thus, a group of opponents of remote work dominates among employed Latvians, although the group of proponents is also numerous. The groups of proponents and opponents of remote work among employed Latvians are comparable. For their empirical study, it is advisable to use discriminant analysis. This makes it possible to detect discriminatory’ factors (if any) that statistically significantly determine respondents’ inclusion in a group of proponents or opponents of remote work.
One of the main discriminant analysis results was the test of equality of group means, which was carried out to determine the statistical significance of the difference between the variables belonging to both groups. It examines whether dividing (discriminatory) factors make it possible to predict respondents’ belonging to one of two groups: proponents and opponents of remote work. The test was conducted for each group of factors: work-related values of respondents, support for respondents and profile of respondents. The following result of the discriminant analysis was the correlation coefficient (canonical correlation) between the calculated values of the discriminant function and the actual group membership. Next, the Wilks’ lambda test was carried out to determine whether the mean values of the discriminant function in both groups differed significantly (Tables 4, 5 and 6).
The results of discriminant analysis for the factors’ group “work-related values” show that three work-related values have a discriminatory potential to divide the employed Latvians into proponents and opponents of remote work (Table 4):
The importance of the opportunity to work from home (p = 0.000) was higher for proponents of remote work.
The importance of planning one’s working time freely (p = 0.000) was higher for proponents of remote work.
The importance of business trips abroad (p = 0.001) was higher for the opponents of remote work.
One more work-related value is very close to being discriminatory:
The importance of relationships with colleagues (p = 0.050) was higher for opponents in remote work.
In comparing means with the independent samples, the t-test method shows statistically significant differences between proponents and opponents of remote work in the following three work-related values (but not in the fourth, for which p = 0.059):
Importance of the opportunity to work from home (p = 0.000);
Importance of being able to plan your working time freely (p = 0.000); and
Importance of business trips abroad (p = 0.001).
The correlation coefficient between the calculated values of the discriminant function and the actual group membership, 0.418 (Table 4), was satisfactory (Sweet and Grace-Martin, 2012). The test conducted using Wilks’ lambda criteria to determine whether the mean values of the discriminant function differed significantly in both groups of respondents showed a very significant result (p < 0.001; Table 4).
The final result of the discriminant analysis was the average level of correctness of the predictions for each case, which fell into the corresponding group of respondents. Regarding work-related values, 73.7% of the cases correctly predicted falling into the group of proponents of remote work and 66.5% into opponents of remote work. Thus, it is easier to signify the acceptance of remote work than the rejection based on work-related values. The total number of correctly classified, originally grouped cases in this discriminant model was 69.4% (Table 4). This is not a high level of prediction accuracy (Sweet and Grace-Martin, 2012). This shows that in almost 70% of the cases, it is possible to determine if the respondent would like to continue working remotely after the COVID-19 pandemic, knowing only their three “discriminatory” work-related values. One may attempt to explain the moderate level (69.4%) of the correctness of predictions by the fact that both groups (proponents and opponents of remote work) included mixed types (respondents with positions close to proponents or opponents), which are more difficult to classify than pure types.
The discriminant analysis results for the factor’ group “support” show that none of the analysed factors have the discriminatory potential to divide the respondents into proponents and opponents of remote work (Table 5). This means that in Latvia, employer-supportive activities during remote work are not factors that determine employees’ willingness or unwillingness to continue working remotely after the COVID-19 pandemic.
The results of discriminant analysis for the factors’ group “profile” show that only one social characteristic of the respondents has a discriminatory potential to divide them into proponents and opponents of remote work (Table 6):
Duration of work at the current job (p = 0.016) was higher for opponents of remote work.
Comparing means using the independent samples t-test method showed no statistically significant difference between proponents and opponents of remote work regarding the duration of work in the current workplace (p = 0.051). However, the resulting p-value was very close to the threshold (0.05) for the statistical significance of the duration of work at the current job.
5.2 Proponents and opponents of remote work: who integrates work-family-community-self dimensions better?
To answer this question is to prove the second hypothesis of the empirical study, since in this study, work-family-community-self integration is empirically understood as a situation where the number of a respondent’s job resources (benefits from remote work) exceeds the number of job demands (losses from it) (Figure 1). All respondents with experience of remote work (both its proponents and opponents) have been asked to assess their job resources (benefits from remote work) and job demands (losses from it): “Please mark what, in your opinion, are your benefits when working remotely? (multiple answers are possible)” (RSU, 2021). The same question concerned losses from remote work (for both proponents and opponents).
We calculated the ratio of job resource demands (chosen several job resources minus the selected number of job demands) related to the work-family-community-self dimensions (13 job demands and 13 job resources provided for assessment in this survey are shown in Table 1) within the groups of proponents and opponents of remote work. In both groups of respondents (proponents and opponents of remote work), there were those for whom the number of job resources exceeded the number of job demands, stimulated work-family-community-self-integration and respondents with the opposite situation and work-family-community-self-disintegration. Nevertheless, the means of the ratio of job resources-demands related to work-family-community-self dimensions differ statistically significantly (p = 0.000). Among proponents of remote work, job resources obtained from remote work are, on average, 2.35 more than demands and opponents of remote work have job resources obtained from remote work on average 0.53 less than demands.
In descending order, the subsequent two figures (Figures 3 and 4) show that job demands and resources related to work-family-community-self-integration dominate in the groups of proponents and opponents of remote work.
Table 7 compares the most important (more than 50% of the affirmative answers) job demands and resources obtained from remote work between the proponents and opponents of remote work.
The data in Table 7 again confirm the importance of work-related values in work-family-community-self integration. If opponents of remote work much more often than opponents mark the “unregulated work regime, disappeared work-private life balance” as job demand, then for proponents of remote work, the “ability to plan your daily routine, balancing work and private life” is a job resource that helps them integrate work-family-community-self dimensions.
6. Discussion and comparison of the findings with previous studies
Remote work in Latvia cannot be considered a phenomenon that arose during the COVID-19 pandemic since even before the COVID-19 pandemic, almost every tenth of the respondents of the survey analysed in this study worked remotely (RSU, 2021). As noted in the introduction, during the COVID-19 emergency, remote work has become more common and now approximately half of the respondents have this experience (RSU, 2021). This share of Latvian remote workers (around 50% during the COVID-19 emergency) is consistent with the US workforce situation; however, before the COVID-19 emergency, it was 43% of employed Americans in 2016 (Gallup World Poll’s data – Chokshi, 2017) and 50% of the US workforce in 2018 (an estimate of Forbes–Radocchia, 2018). Furthermore, 40.8% of employed Italians had started working remotely, even before the first COVID-19 national lockdown (March–April 2020; Donati et al., 2021). Thus, the COVID-19 pandemic has contributed significantly to the spread of the “remote work culture” in Latvia to the level of Western countries.
This study’s results show that non-institutionalised remote work (without any written agreement with the employer about performing the work remotely) is fairly common in Latvia, ranging from 60% to 80% in different groups of Latvians who have experience with remote work (Table 3). Thus, the phenomenon of remote work in Latvia can be studied only through sociological surveys (the sociological approach to the study of remote workers is also typical for other countries – e.g. Donati et al., 2021; Soroui, 2021), and there is no way to officially monitor this since most employed Latvians informally agree on remote work with their employers. Although, as mentioned in the literature review, many academic studies on remote work have been conducted in recent years (Donati et al., 2021; Lonska et al., 2021; Soroui, 2021; Sweet and Scott, 2022). We found no studies examining the institutionalisation of remote work. Beno (2021) argued that remote working is difficult to measure, partly because of limited official statistics and because the practice is sometimes conducted at the discretion of local management in the absence of company policy. Furthermore, there is no international statistical definition, often no official remote working policy and remote working is a widespread practice operated by employers, usually as part of flexible work policies (Beno, 2021).
The results of the empirical testing of certain “discriminatory” factors that potentially determine the attitudes of respondents towards remote work, dividing them into proponents and opponents, revealed that, for the respondents, employer support during remote work (one of the factors that potentially determines the attitudes of the employed population towards remote work – Figure 1 in the section on the conceptual framework of the study) is not the factor that determines their choice concerning whether they would like to continue working remotely in the future. Moreover, social and demographic characteristics did not influence this choice. Even the presence of minor children in families who study remotely or do not attend kindergarten during the COVID-19 pandemic does not significantly affect whether a person working remotely is a proponent or opponent of remote work. This result is inconsistent with the results of previous studies of employed Latvians (Lonska et al., 2021), which revealed a statistically significant effect of social and demographic factors such as gender, age of respondents and the presence of minor children in the household on work–life balance (but not on their attitudes towards remote work).
The respondents’ positions concerning remote work were determined by their work-related values. Namely, proponents of remote work are most often those for whom the aspect of being able to work from home and freely planning their work schedule is the most important in their work, as well as those for whom foreign business trips are comparatively less significant (most likely, proponents of remote work are ready to replace them with online meetings). Therefore, Hofstede’s cultural dimensions and the investigation of business culture in different countries (Hofstede, 1980, 2001, 2021; Hofstede et al., 2010) are particularly relevant. Thus, an examination of the motives for remote working in selected European countries in 2018 showed that individuals in all the studied cultures could work in different ecosystems: in the office, outside the office, virtually or manually and in other locations. This applies particularly in Nordic and Western countries, where work can be in a different position compared with other monitored cultures that create boundaries between office hours and personal time. In countries where management culture is based on control rather than trust, such as France, Spain, Italy, Greece and the former Eastern Bloc, it seems more logical to manage employee productivity in offices (Beno, 2021).
However, a single factor, when considered in isolation seems to hold a limited explanatory power, and better results would be achieved analysing several factors together (Caputo et al., 2023). Thus, it would be reasonable to say that it is not so much the presence or the intensity of a single factor to determines the outcomes but the co-presence or, conversely, the co-absence of a set of factors that is the key interpretation (Caputo et al., 2023). For example, Caputo et al. (2023) discuss the complexity of conflict in virtual teams by analysing the common impact of several factors. They highlight the interplay between trust, performance, cultural diversity, knowledge management and team management as interconnected factors that significantly influence conflict and conflict management in virtual settings. Thus, the understanding “discriminatory” factors in combination, rather than in isolation, offers a more nuanced and comprehensive understanding of the investigated issue.
The second hypothesis is that the groups of proponents and opponents of remote work are characterised by a fundamentally different ratio of job demands and resources related to work-family-community-self integration, which is fully confirmed by empirical data. In the group of proponents of remote work, job resources obtained from remote work, on average, outweigh demands, contributing to work-family-community-self integration, while in the group of opponents of remote work, the situation is the opposite, leading to work-family-community-self disintegration. Here again, the particular importance of work-related values comes to the forefront. While proponents of remote work especially value and use the “ability to plan your daily routine, balancing work and private life” it [remote work] provides, opponents complain about an “unregulated work regime, disappeared work-private life balance”. This is against the absence of statistically significant differences in social and demographic characteristics and employer support in the groups of proponents and opponents of remote work.
In the modern world, many top companies offered full, half or partial remote work (Radocchia, 2018) before the COVID-19 pandemic. The COVID-19 pandemic has become the “finest hour” for remote work. “Millions of Americans are participating in an unprecedented experiment working from home. Many are happy, more efficient and want to hang onto the benefits when the pandemic ends” (Cramer and Zaveri, 2020). A survey of 50 of the Australian biggest companies conducted by national newspapers “The Age” and “The Sydney Morning Herald” in July 2021 found that major employers are overwhelmingly planning to adopt hybrid work models permanently, and only seven companies will require workers to be in the office a set number of days each week (Koehn and Irvine, 2021). The head of the Productivity Commission and other experts state that increased working from home will unlikely hurt the overall economy (Irvine, 2021). However, “not everyone is enthusiastic about this phenomenon. Younger workers beginning their careers fear missing out on valuable lessons” (Grieve, 2021).
As the above examples demonstrate, interpreting the results of employed population surveys in different countries is subjective and often depends on the authors’ attitudes towards remote work. According to our opinion and the results of previous studies (Wojcak and Barath, 2017; Beno, 2021), these attitudes largely depend on work-related values and behaviours that dominate in a particular country (Hofstede, 1980, 2001; Hofstede et al., 2010). We believe that the largest share of proponents of remote work will be in countries with a relatively high level of individualism and low levels of uncertainty avoidance and power distance (Cultural Dimensions by G. Hofstede). There will likely be fewer proponents of remote work in Russia than in the USA because of the differences in the abovementioned cultural dimensions (Hofstede, 2021). This is also confirmed by the results of a study by Beno, who found that the correlation with remote working is statistically significant for the power distance index (PDI), which is negative. The lower the PDI, the higher the proportion of remote working) and indulgence versus restraint (IVR) index (positive). The higher the IVR index, the higher the proportion of remote working; Beno, 2021). Returning to the example above, Russia has a higher PDI (one of the highest in the world; Komarova et al., 2021) and a much lower IVR than the USA, which gives us a reasonable expectation that there will be fewer proponents of remote work in countries with relatively high PDI and relatively low IDV.
7. Conclusions
Based on a representative sample of employed Latvians, it was found that employees’ work-related values (rather than social and demographic characteristics, as well as employer support) determine their attitudes towards remote work. Approximately 40% of the respondents with remote work experience are proponents, and approximately 60% are opponents (this preponderance towards opponents of remote work in Latvia is reasonably expected, considering its cultural dimensions, according to Hofstede (2021). For proponents, the number of job resources obtained from remote work, on average, exceeds the number of job demands, stimulating work-family-community-self integration; for opponents, the opposite is true. Thus, this study contributes to the research on remote work through an empirical study of the employed population’s attitudes towards remote work in the context of work-family-community-self integration (the subject of most modern studies about the interconnection between work and other dimensions of life) using the JD-R model. Furthermore, this study is innovative in that it assesses the level of institutionalisation of remote work in Latvia.
The research limitations of this study are related to the formation of the sample, as only individuals with access to the internet participated in the Web survey. Consequently, some groups of employed Latvian populations may be excluded from the sample by default (e.g. older adults, individuals living in remote areas and individuals with low education and digital literacy). Furthermore, the questionnaire was available only in Latvian, which might have resulted in a lower response rate in the Russian-speaking population of Latvia. The set of factors in each group (including the setting of groups themselves) is another limitation of this study, as the specific factors in each group may differ. Nevertheless, we considered the number of factors in each group to be sufficient to measure the determinative ability of a particular group of factors to predict whether respondents would fall into a group of proponents or opponents of remote work.
In future global-scale studies on the attitudes of the employed population towards remote work, special attention should be paid to work-related values and the reasons for their differences between societies and within them. In social sciences, there is practically no research on why work-related values in different countries and social groups within a country are precisely what they are. Only famous articles by Hall and Ch. I. Jones’s “Why do some countries produce so much more output per worker than others?” should be mentioned (Hall and Jones, 1999). It focuses on the role of social infrastructure in forming work-related values and the reasons for forming a specific type of social infrastructure in a particular society. The authors suppose that the cultural dimensions research conducted by Hofstede, including the methodology of cultural determinism by M. Weber (Weber et al., 2002), will be applied in the future. This will help understand and explain attitudes (and natural behaviour) towards remote work and work-family-community-self integration in societies with different work-related values.
Today, to study the situation in remote work and implement an effective policy in this area, it is necessary to institutionalise remote work. For Latvia, the institutionalisation of remote work is especially relevant since, in most cases, there is no written agreement with the employer about performing the work remotely (e.g. an additional agreement to the employment contract, changes in the employment contract). The survey results showed that 11.2% of the respondents worked remotely before the COVID-19 emergency. However, their remote work was not institutionalised in most cases. In a situation where remote work is not institutionalised or documented, it can be studied only by sociological methods and cannot be regulated or taxed. Since both this and previous studies show that remote work is becoming an increasingly popular form of work organisation, its institutionalisation is a top priority for labour market policy implementation. All labour market participants and stakeholders need clear and precise “rules of the game” to efficiently realise, manage, support or control remote work.
It would also be helpful to train employees and managers within the proposed by SD Friedman the work-family-community-self integration approach based on “the four-way win”. Given the presence of proponents and opponents of remote work among employees and managers, policymakers and decision makers need to allow employees and managers to choose how to organise their work remotely or in the office. As this study’s results show, this choice depends primarily on the work-related values of the employee, who will work efficiently and be motivated only when their work is as voluntary as possible.
Figures
Empirical interpretation of job demands and resources gained from remote work and related to work-family-community-self integration
Job resources: benefits of remote work | Job demands: losses from remote work |
---|---|
1) Savings in the household budget (e.g. expenditure on transport, clothing and entertainment) | 1) Increase in expenditure in the household budget (e.g. food, communication services, outsourcing and electricity expenditure) |
2) More time to spend with the family, including children, by helping with learning | 2) Less time to spend with family |
3) More time for hobbies and entertainment (e.g. sports, walking, TV, movies and board games) | 3) Less time spent on hobbies and entertainment (e.g. sports, walking, TV, movies and board games) |
4) Ability to plan your daily routine, balancing work and private life | 4) Unregulated work regime, disappeared work-private life balance |
5) Improving family relationships | 5) Deterioration of family relationships |
6) Salary increase (e.g. increase in additional responsibilities, replacement of colleagues) | 6) Salary reduction (e.g. due to workload reduction) |
7) Possibility to acquire new knowledge and improve skills | 7) Lack of learning opportunities |
8) It was easier to focus on work | 8) Lack of self-discipline |
9) Saving time on trips or walks to the workplace | 9) The need to purchase additional equipment to perform work duties |
10) Job satisfaction improved | 10) Sense of loneliness |
11) Possibility to carry out household improvement work (e.g. repairs, mowing) | 11) Restriction on business trips |
12) Possibility to perform daily household duties (e.g. cooking, cleaning the house) during work breaks | 12) Limited opportunities for career development |
13) There was an opportunity to live in the countryside | 13) Lack of communication and socialisation (e.g. with colleagues, friends) |
Sources: Authors’ own compilation based on Bakker and Demerouti (2007), Voydanoff (2008) and Monakhova (2016)
Weighting the sample by age and gender, Feb–Mar 2021
Age groups | Sample before weighting, %, n = 1,051 | Statistical data, first quarter of 2021, %, n = 853,200 | Weights, age-gender | Sample after weighting, %, n = 1,052 | |||||||
---|---|---|---|---|---|---|---|---|---|---|---|
Male | Female | Total | Male | Female | Total | M | F | Male | Female | Total | |
15–24 | 1.2 | 3.3 | 4.5 | 3.0 | 2.2 | 5.1 | 2.47 | 0.65 | 3.1 | 2.2 | 5.3 |
25–34 | 8.9 | 11.9 | 20.8 | 12.1 | 9.9 | 22.0 | 1.36 | 0.84 | 12.2 | 9.9 | 22.1 |
35–44 | 9.6 | 20.9 | 30.5 | 12.3 | 11.3 | 23.6 | 1.28 | 0.54 | 12.3 | 11.3 | 23.6 |
45–54 | 6.3 | 19.8 | 26.1 | 11.5 | 12.4 | 23.9 | 1.83 | 0.63 | 11.4 | 12.4 | 23.8 |
55–64 | 2.7 | 12.9 | 15.6 | 9.4 | 11.2 | 20.6 | 3.47 | 0.87 | 9.3 | 11.2 | 20.5 |
65–74 | 0.4 | 2.0 | 2.4 | 2.0 | 2.8 | 4.8 | 4.95 | 1.39 | 1.9 | 2.8 | 4.7 |
Total | 29.1 | 70.9 | 100.0 | 50.2 | 49.8 | 100.0 | – | – | 50.2 | 49.8 | 100.0 |
Source: Calculations based on Rīga Stradiņš University (RSU) data, 2021 and the Central Statistical Bureau of Latvia, 2021
Respondents’ answers to the question: “is there a written agreement with the employer about performing the work remotely?” %, n = 534, Feb–Mar 2021
Duration of working remotely | Yes | No | Difficult to say | Total |
---|---|---|---|---|
I worked remotely before the COVID-19 emergency in March 2020 – “experienced remote worker” (n = 118) | 16.8 | 78.2 | 5.0 | 100.0 |
I started working remotely during the first emergency (spring 2020) – “mid-term remote worker” (n = 285) | 30.8 | 63.3 | 5.9 | 100.0 |
I started working remotely during the second emergency (autumn 2020–early 2021) – “new remote worker” (n = 131) | 29.8 | 61.8 | 8.4 | 100.0 |
Source: Calculations based on data from Rīga Stradiņš University (RSU), 2021
Results of discriminant analysis for the factors’ group “work-related values” about their discriminatory potential to divide the employed Latvians into proponents and opponents of remote work, n = 534, Feb–Mar 2021
Groups of factors | Factors included in the questionnaire | Results of discriminant analysis |
---|---|---|
Work-related values of respondents (what is essential in work, expectations from work) |
1) Importance of salary | p = 0.928 |
2) Importance of additional benefits | p = 0.794 | |
3) Importance of the opportunity to work from home | p = 0.000 | |
4) Importance of being able to plan your working time freely | p = 0.000 | |
5) Importance of social guarantees | p = 0.245 | |
6) Importance of stable, safe work | p = 0.675 | |
7) Importance of career and growth opportunities | p = 0.242 | |
8) Importance of business trips abroad | p = 0.001 | |
9) Importance of interesting work | p = 0.318 | |
10) Importance of relationships with colleagues | p = 0.050 | |
Canonical correlation | Correlation coefficient between values of the discriminant function and actual group membership | r = 0.418 |
Wilks’ Lambda | Test to determine whether the mean values of the discriminant function in both groups differ statistically significantly | p = 0.000 |
Proponents | The level of correctly classified originally grouped cases | 73.7% |
Opponents | 66.5% | |
Total | 69.4% |
Source: Calculations based on data from Figure 1; Rīga Stradiņš University (RSU), 2021
Results of discriminant analysis for the factors’ group “support” about their discriminatory potential to divide employed Latvians into proponents and opponents of remote work, n = 534, Feb–Mar 2021
Groups of factors | Factors included in the questionnaire | Results of discriminant analysis |
---|---|---|
Support for respondents (support from the employer, bonuses received when working remotely) | 1) Computer and other necessary IT equipment | p = 0.168 |
2) IT support by adapting a computer to work remotely | p = 0.221 | |
3) Training on how to use tools and software I did not use before | p = 0.154 | |
4) Support on how to do my job remotely | p = 0.937 | |
5) I was explained how to arrange a workplace at the computer at home comfortably | p = 0.237 | |
6) The employer explained the conditions under which I would work | p = 0.667 | |
7) Reimbursement for costs | p = 0.431 | |
8) Remote team building events are organised for my team | p = 0.946 | |
9) My line manager was trained to manage employees remotely | p = 0.681 | |
10) Training/seminars on how to reduce stress | p = 0.946 |
Source: Calculations based on data from Figure 1, Rīga Stradiņš University (RSU), 2021
Results of discriminant analysis for the factors’ group “profile” about their discriminatory potential to divide employed Latvians into proponents and opponents of remote work, n = 534, Feb–Mar 2021
Groups of factors | Factors included in the questionnaire | Results of discriminant analysis |
---|---|---|
Profile of respondents (social and demographic characteristics) | 1) Gender | p = 0.857 |
2) Type of residence | p = 0.759 | |
3) Work position | p = 0.812 | |
4) Duration of work at the current job | p = 0.016 | |
5) Number of people in the household | p = 0.494 | |
6) Living with or without a spouse/partner | p = 0.431 | |
7) Children under 18 years of age present in the household | p = 0.826 | |
8) Number of preschool children in the household | p = 0.972 | |
9) Number of elementary school children in the household | p = 0.418 | |
10) Age group | p = 0.136 |
Source: Calculations based on data from Figure 1, Rīga Stradiņš University (RSU), 2021
Comparison of the most critical job demands and resources obtained from remote work, proponents and opponents of remote work, % of answers “yes” and statistical significance of difference (p-value), n = 534, Feb–Mar 2021
Job demands and resources obtained from remote work | Proponents of remote work, % of answers “yes”, n = 206 | Opponents of remote work, % of answers “yes”, n = 315 | Statistical significance of difference, p-value |
---|---|---|---|
Job demands | |||
Lack of communication and socialisation | 50.2 | 73.7 | 0.000 |
Unregulated work regime disappeared work-private life balance | 27.2 | 52.2 | 0.000 |
Job resources | |||
Saving time on trips or walks to the workplace | 78.6 | 69.1 | 0.014 |
Ability to plan your daily routine, balancing work and private life | 75.6 | 49.5 | 0.000 |
Possibility to perform daily household duties | 62.9 | 44.4 | 0.000 |
Savings in the household budget | 57.1 | 47.0 | 0.023 |
Source: Calculations are based on Rīga Stradiņš University (RSU) data, 2021
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