The influence of the COVID-19pandemic on the digitaltransformation of work

Lisa NagelUniversity of Bremen, Bremen, Germany

Abstract

Purpose – This study investigates whether the COVID-19 pandemic has led to an acceleration of the digitaltransformation in the workplace.Design/methodology/approach – This study is based on a survey conducted during the COVID-19pandemic from March to April 2020 on the crowdsourcing platform Amazon Mechanical Turk.Findings – The findings show an increase of people working from home offices and that many people believethat digital transformation of work has accelerated in response to the COVID-19 pandemic. People who notedthis acceleration can imagine working digitally exclusively in the future. Moreover, the importance oftraditional jobs as a secure source of income has decreased, and digital forms of work as a secure source ofincome have increased because of the COVID-19 pandemic. Workers believe that digital work will play a moreimportant role as a secure source of income in the future than traditional jobs.Research limitations/implications –Because the surveywas conducted online, respondentsmayhave hada certain affinity for digital work.Originality/value – This study assesses the consequences of the COVID-19 pandemic on the future of work,showing that changes in the perception of digital transformation and the willingness to work exclusively in adigital manner have arisen as result of the COVID-19 pandemic. To estimate the long-term consequences of thepandemic on the digitisation of work, research that includes macroeconomic consequences in its forecast isnecessary.

Keywords COVID-19, Digital transformation, Future of work, Income security

Paper type Research paper

1. IntroductionThe COVID-19 pandemic took the world by surprise in early 2020, and the economy hascontinued to face a substantial downturn, which has implications for working situations(Adams-Prassl et al., 2020; B�eland et al., 2020; Bick andBlandin, 2020; Coibion et al., 2020). Theworld has faced several global economic crises in recent decades, but the current crisis hasaffected the introduction of digital technologies in all areas of human activity moreprofoundly than any before (Shkalenko and Fadeeva, 2020). Voluntary precautions againstCOVID-19, as well as mandatory government restrictions, have forced companies toincreasingly offer employees the option of working at home, and thus a large number ofpeople exclusively working from home have integrated existing technologies into their dailywork routines (B�eland et al., 2020; Spurk and Straub, 2020; St€urz et al., 2020).

Although no one can foresee how the rapid change to digital work will affect the worksituation and spread of digital work forms in the future, the use of digital technologies hasclearly increased, at least temporarily, as a result of the COVID-19 pandemic. Therefore, thequestion arises: Has the COVID-19 pandemic accelerated digital transformation?

Influence of theCOVID-19pandemic

861

The author would like to thank Mona Schw€orer for her comments and Lars Hornuf. The authoracknowledges the Amazon Mechanical Turk workers who completed the surveys. The author also thanksthe editors of the journal as well as the reviewers, who have given up valuable time during the COVID-19crisis.

This article evolved as part of the research project “Crowdsourcing as a new form of organizing laborrelations: regulatory requirements and welfare effects” and was financially supported by the GermanResearch Foundation (Deutsche Forschungsgemeinschaft) under grant HO 5296/3-1.

The current issue and full text archive of this journal is available on Emerald Insight at:

https://www.emerald.com/insight/0144-333X.htm

Received 27 July 2020Revised 8 August 2020

Accepted 9 August 2020

International Journal of Sociologyand Social Policy

Vol. 40 No. 9/10, 2020pp. 861-875

© Emerald Publishing Limited0144-333X

DOI 10.1108/IJSSP-07-2020-0323

2. Theory: the COVID-19 pandemic and the digital transformation of workFor several years now, the political, economic and societal realms have been involved in theprocess of digital transformation. In 2017, the European Commission noted that the debate onthe impact of digital transformation on the economy and society has become considerablymoreimportant in recent years. The term digital transformation of labour describes the digitisationofwork previously carried out by individuals in the enterprise (Eberhard et al., 2017). This leadsto digital work, which includes the use of new technologies and the possibility of workingremotely from the employer. Thereby individuals can perform their work in a variety oflocations using new professional skill (Wilks and Billsberry, 2007; Sullivan, 2003). Digitaltransformation is considered to help turn the challenge of the COVID-19 crisis into anopportunity. To ensure an effective response to the COVID-19 crisis, the European Commissionestimates that, in 2020–2021, at least V1.5 trillion must be invested in green and digitaltransformation (EuropeanUnion, 2020). Thus, digital transformation is one of the key sectors ofEurope’s future. Many elements of technological change are created at the workplace, whichleads to a general social acceleration (Rosa, 2014).

Organisations expect digital transformation to increase productivity and efficiency, whichshould give them a competitive advantage over other market respondents (Vial, 2019). Toachieve this goal, organisations are encouraging their employees to work in new ways, usingtechnology while taking on more autonomy. Digital transformation leads to a worktransformation, which involves a reorganisation of work and ultimately changes the waypeople work (Anderson-Connolly et al., 2002). In this context, the acceptance of new technologyas part of the daily routine is essential (Momani and Jamous, 2017). Technology acceptance isconsidered one of the main success factors of new technologies (e.g. Molino et al., 2020; Schereret al., 2019; Taherdoost, 2018; Venkatesh et al., 2003). Acceptance and implementation of newbehaviour due to new technologies can take a long time under normal circumstances (e.g.Baturay et al., 2017; Gelbrich and Sattler, 2014). Many organisations have had to adapt to maketechnologies part of their everyday work routines. However, COVID-19 caused this adaptationto be implemented faster than under normal circumstances. It is conceivable that people whowould not otherwise have been so quick to integrate technologies in newways (e.g. technologyin the home office) into their daily work routine were forced to adapt more rapidly. Firms oftenrespond to crises by making short-term adjustments and organisational changes, using thesestrategies to actively deal with environmental changes in the most effective possible way. Thischange in organisations often occurs when financial matters are central to the survival andcompetitiveness of the organisation (Men�endez and Castro, 2002). Therefore, firms andworkerswill aim to be more flexible to deal with a possible shock in the future (Brakman et al., 2020). Inthe current situation, this flexibility could extend to digital forms of work.

Because personal contact with other individuals correlates with the probability ofcontracting COVID-19, a regular working day is no longer possible for many employees(B�eland et al., 2020). Voluntary precautions against COVID-19, as well as mandatorygovernment restrictions, have forced companies to increase offers towork at home, which hasincreased remote work substantially (B�eland et al., 2020; Spurk and Straub, 2020; St€urz et al.,2020). This increase has made clear that a large part of working from home requiresintegrating existing technologies into daily work routines. In turn, the lockdown has createdgreater awareness that working from a distance, using the existing technologies, is possibleeven for jobs traditionally carried out in the office (Brakman et al., 2020).

Many employees who work from home offices are currently organising their workinghours more flexibly, which can be viewed as adapting to the new situation. As a result, VonGaudecker et al. (2020) have observed a general decline in total working hours. In addition,employees and superiors are not present in the home office, which could lead to greaterautonomy – an important predictor for job satisfaction (Finn, 2001; Fried and Ferris, 1987;Hackman and Oldham, 1975; Naqvi et al., 2013).

IJSSP40,9/10

862

Because people working remotely have less contact with other people than professionalswhowork at their actual place of work, such as nurses or supermarket employees, and personalcontact with other individuals correlates with the probability of contracting COVID-19, remoteworkers should be at lower risk of infection. This decreased risk could lead to an impression ofbeing looked out for and valued and increase feelings of security, thus leading to greater jobsatisfaction (Danish andUsman, 2010; Tessema et al., 2013). It seems that companies andpeoplemay have adapted to the new work situation more rapidly than they would have if thepandemic had not occurred. The question arises: Has the COVID-19 pandemic accelerateddigital transformation?

3. Hypotheses and research questionsGiven the current COVID-19 crisis situation, employers and employees will likely try to createmore leeway and react flexibly to new challenges (Brakman et al., 2020). Both companies andindividuals must realise that digital transformation is possible given the feasibility of the rapidtransition to digital work. But digital transformation requires workers with a digital skill set.Employees who are already familiar with digital technologies will find it easier to use themeffectively. (Kohnke, 2017). People who have already had experience with home office may findit easier to work in the home office over a longer period of time. In times of COVID-19, this couldlead to people with experience in digital work being more likely to switch to home office workthan others. A rise in the home office because of COVID-19 is expected (B�eland et al., 2020;Spurk and Straub, 2020; St€urz et al., 2020), but the question still remains:

RQ1. Have individuals who work in the home office during COVID-19 already hadprevious experience with this form of work?

The increase in digital work suggests that traditional work forms are less frequentlyperformed during the COVID-19 pandemic. People might perceive digital work in the currentsituation as a secure source of income. This could also have an impact on the perception of theimportance of digital work forms as a source of income in the future. It is also unclear whichimpact the increase in home offices will have on the perception of the importance of incomefrom traditional jobs as a secure source of income. The questions arise:

RQ2. Do people predict that digital jobs are more likely to be a secure source of income inthe future than before and during the COVID-19 pandemic?

RQ3. Has the importance of traditional and digital jobs as a secure source of incomechanged given the COVID-19 pandemic?

Given the current state of research and the changes in the work context due to the COVID-19pandemic already described, the first hypothesis is formulated as follows:

H1. People believe that digital transformation of work will spread faster, due to theirexperience with the COVID-19 pandemic.

The increase in technology use in everyday work (B�eland et al., 2020; Spurk and Straub, 2020;St€urz et al., 2020) and changes in working hours (Von Gaudecker, 2020) imply that employeescould be working in new ways, using technology to a greater extent and taking on moreautonomy. Moreover, people working from home have a lower risk of being infected withCOVID-19, which could lead to greater job satisfaction (Hirsh et al., 2012; Tessema et al., 2013).These assertions lead to the second hypothesis:

H2. People working exclusively from home during the COVID-19 pandemic have greaterjob satisfaction than people not working exclusively from home during the COVID-19pandemic.

Influence of theCOVID-19pandemic

863

In addition to the experience with digital work gained through the COVID-19 pandemic,European Commission funding to promote digital change could provide a positive impact ontechnological change (European Commission, 2020). This funding could also influenceworkers’ predictions for the future of work, in the sense that secure sources of income mightbe expected with digital work in the future. Following this logic, the last hypothesis isformulated as follows:

H3. The more people believe in an increased spread of digital transformation due to theCOVID-19 pandemic, the more likely they are to imagine working exclusivelydigitally in the future.

4. Method4.1 RespondentsThe data were collected online fromMarch to April 2020. The study sample comprised adultsregistered as “workers” on theAmazonMechanical Turk platform. AmazonMechanical Turkis a crowdsourcing platform on which virtual tasks are processed that require humanintelligence. Workers on Amazon Mechanical Turk have the possibility to work on varioustasks. These tasks can be performed flexibly in terms of time and location. Respondentsresided in the United States, Italy, Spain, France, United Kingdom and Germany. The surveywas conducted in English. The total sample size was 554, including 95 respondents from theUnited States, 103 from Italy, 91 from Germany, 95 from Spain, 82 from the United Kingdomand 88 from France. Other demographics are as follows: 62% of the respondents were maleand 37% female; most respondents were between 25 and 34 years of age (42%), followed bythe 18–24 (24%) and 35–44 (23%) age groups; only 9%were 45–59 years of age and 1%were60 years or older; 16% of the respondents declared that their primary source of income wascrowdsourcing; 32% stated that digital jobs are their main source of income; and 51%claimed traditional jobs as primary source of income.

4.2 ProcedureBefore they began the survey, respondents learned about data protection and agreed toparticipate voluntarily in the survey. After they had given their consent, they answeredquestions about life satisfaction; the influence of COVID-19 on everydaywork life; predictionsabout the influence of COVID-19 on the digital transformation of work; income security ofcrowdsourcing, digital and traditional jobs (before COVID-19, now, future); experience withCOVID-19 and demographic variables. An attention checkwas included to exclude bots. Eachparticipant received $0.40, and responding to all questions took on average 6 min.

4.3 Measures4.3.1 Satisfaction with current situation. To measure the satisfaction with different parts oflife, life satisfactionwasmeasuredwith a questionnaire based on theGerman Socio-EconomicPanel (2020). Respondents responded on a ten-item scale from 1 (“not at all satisfied”) to 10(“very satisfied”) to the question “How satisfied are you todaywith the following areas of yourlife?” with regard to ten variables covering various parts of everyday life (e.g. job, personalincome, free time).

4.3.2 Influence of COVID-19 on everydaywork life. Seven questionsmeasured the influenceof the pandemic on the working reality. Some questions (e.g. “Do you work from home on aregular basis?” “Do you work from home because of COVID-19?”) could be answered with“yes”, “no” and “from time to time”. Other questions asked, for example, about the extent to

IJSSP40,9/10

864

which respondents’ work life and income had been influenced. These questions weremeasured on a ten-point Likert scale ranging from 1 (“no influence”) to 10 (“major influence”).

4.3.3 Predictions about the influence of COVID-19 on the digital transformation of work.Respondents next evaluated how COVID-19 could change work. A seven-point Likert scalefrom 1 (“totally disagree”) to 7 (“totally agree”) measured level of agreement with sevensentences (e.g. “Based on my experience with COVID-19, I believe that digital forms of workwill establish faster”; “Based on my experience with COVID-19, I believe that in the futurethere will be more situations that require digital work”).

4.3.4 Income security. Respondents were provided with the definitions of traditional jobs,digital work and crowdsourcing. Then, they were asked to provide their opinion on thesentence, “Tome digital work is a secure source of income right now”, on a seven-point Likertscale from 1 (“totally disagree”) to 7 (“totally agree”). They also had the option to state that thesentence was “not applicable”. The question was adapted to measure the perceived incomesecurity of traditional jobs and crowdsourcing. In addition, the time varied. The questionasked whether the three work forms were a secure source of income before COVID-19, duringCOVID-19 and if they will be in the future.

4.3.5 Experience with COVID-19 and demographic variables. As a control variable, thequestionnaire measured personal experience with COVID-19. Respondents also indicated theextent to which they were concerned about contracting COVID-19 on a five-point Likert-typescale from 1 (“not at all concerned”) to 5 (“very concerned”). The survey concluded withquestions about age, gender, education, main source of income (traditional job, digital work orcrowdsourcing), marital status and number of people living in the household.

5. Analyses and results5.1 Statistical analysesThe data were analysedwith paired t-tests andmultiple regression. To test the first hypothesis,I determined the amount of people working remotely before and during COVID-19. To analysethe second hypothesis, respondents were divided into two groups with regard to their answersto the statement, “Based on my experience with COVID-19, I believe that digital forms of workwill establish faster”. Then, I determined the significance of group differences.

I used multiple regression to explore whether working remotely had an influence on jobsatisfaction (H3). The analysis comprised four stages. In addition, a multiple regression withtwo models was used to explore whether people believing in an increased spread of digitaltransformation due to COVID-19 are more likely to imagine working exclusively from homedigitally in the future (H4). To answer RQ1 and RQ2, I analysed the variable income securityusing paired t-tests.

5.2 Results5.2.1 More people working in the home office. First, I analysed whether individuals who workin the home office during COVID-19 already had previous experience with this form of work(RQ1). Figure 1 shows that before the COVID-19 crisis, 33% of the respondents worked fromhome on a regular basis, 24%worked from the home office from time to time and 42%did notwork from home at all. Figure 2 shows that since COVID-19, 59% reported working fromhome, 5% worked from home from time to time and 35% did not use the home office. Thenumber of people working from home because of the virus increased by 27%. At the sametime, the amount of people working in the home office from time to time and the amount ofpeople not working at home decreased by 19%and 8%, respectively. These results show thatthe increase is mostly due to people who already have experience in working from a home.

Influence of theCOVID-19pandemic

865

5.2.2 Changes in secure source of income. Figure 4 shows the results for RQ2 (“Has theimportance of traditional and digital jobs as a secure source of income changed given theCOVID-19 pandemic?”) and RQ3 (“Do people predict that digital jobs are more likely to be asecure source of income in the future than before and during the COVID-19 pandemic?”).I used a t-test to determine whether the mean values for the perception of traditional jobs anddigital work forms in the past and during COVID-19 differ (Note that for this analysis, thevariable digital work forms does not include crowdsourcing). Figure 3 shows a significantdifference in the importance of traditional (1% level) and digital (5% level) jobs before andduring COVID-19, as a secure source of income. Therefore, I conclude that the importance oftraditional jobs as a secure source of income decreased and the importance of traditional jobsincreased slightly. Figure 4 also shows the prediction for digital work and traditional work

Figure 1.Amount of peopleworking in the homeoffice before COVID-19crisis (N 5 554)

Figure 2.Amount of peopleworking in the homeoffice during COVID-19crisis (N 5 554)

IJSSP40,9/10

866

forms as a secure source of income in the future. There is a significant (1% level) increase inthe importance of digital work over time. Therefore, people predict that digital jobs are morelikely to be a secure source of income in the future than before and during the COVID-19pandemic. Furthermore, people predict that traditional jobs will again increase in importancein the future, but they are considered significantly (1% level) less important as a secure sourceof income than before the pandemic.

Note(s): ***p < 0.01; **p < 0.05; *p < 0.10

Figure 3.Importance of

traditional and digitalwork forms as a securesource income (mean)

Figure 4.Digital work will

establish faster due toCOVID-19 (N 5 554)

Influence of theCOVID-19pandemic

867

5.2.3 Digital work forms establish faster due to COVID-19. The descriptive analysis of theitem “Based on my experience with COVID-19, I believe that digital forms of work willestablish faster” (H1) shows that more people agree with this statement than reject it(Figure 4), though 13.9% of the statements are in the centre of the Likert scale, indicating notendency towards either side. 77 Individuals without a tendency were excluded in theanalysis. The results of the Shapiro–Wilk test show that the sample is normally distributed.Therefore, the requirements for a paired t-test are fulfilled.

A paired t-test on a sample of 477 shows a significant difference (p<0.001) between peoplewho believe in an increase of digital work forms (M5 0.67; SD5 0.021) and peoplewho do not(M 5 0.32; SD 5 0.021). H2 is therefore accepted.

5.2.4 Home office and job satisfaction.To test H2, I calculated a linear regression with fourmodels (Table 1). The analysis of the Pearson correlation coefficient and the Spearmancoefficient shows a linear relationship between the variables, therefore a linear modeldescribes the experimental data adequately. I did not take into account people who reportedworking in their home office from time to time, because they cannot be clearly assigned totheir place of work. Model 1 represents the focal effect of the variable home office throughCOVID-19 (yes, no) and satisfaction with job situation, showing that people reportingworking from home (ß 5 1.03) are significantly more satisfied with their job situation thanpeople not working from home at a 1% level. The adjusted R-square shows, however, thatonly approximately 3% of the variance can be explained by the included variables.

Model 2 includes the variables fear of infection with COVID-19, primary source of income(i.e. crowdsourcing, traditional jobs or digital work), increase of digital transformation, moreremote work necessary in the future and preference of a home office job in the future. Theinfluence of working remotely remains highly significant, but no additional variance isexplained.

When I include the variables satisfaction with personal income and household income inModel 3, the effect of the variable home office disappears. Instead, a low significant, positiveeffect (10% level) of household income and a high significant, positive effect (at the 1% level)of personal income on job satisfaction can be observed. Accordingly, people who are satisfiedwith their financial situation are also more satisfied with their job situation. Personal income(ß 5 0.62) has a stronger effect on satisfaction with job situation than household income(ß 5 0.08). In Model 3, the adjusted R-square increases to 47%.

The variables country, gender and age, which increased in Model 4, clear up 48% of thevariance. Here, the effect of the variable household income disappears. However, the influenceof satisfaction on personal income (ß 5 0.58) remains highly significant (1% level). Inaddition, people living in Italy, Germany, Spain and the United Kingdom are significantlymore dissatisfied with their current job situation than people living in the United States. Theeffect can be observed at the 1% level for Germany, 5% level for Italy and Spain and 10%level for the United Kingdom. Age and gender have no significant influence on satisfactionwith the job situation. Accordingly, country and satisfaction with personal income have aninfluence on the satisfaction with the job situation. Home office has no influence; therefore, H2is rejected.

5.2.5 More digital transformation and greater willingness to work remotely. To test H3,I calculated a multiple linear regression with two models (Table 2). The analysis of thePearson correlation coefficient and the Spearman coefficient shows a linear relationshipbetween the variables, therefore a linear model describes the experimental data adequately.To control for home office, primary source of income and preference for a home office job inthe future, these variables were included as covariates in Model 2. Model 1 shows a stronglysignificant influence (1% level) of believing that COVID-19 has accelerated the digitaltransformation of work (ß5 0.53) and believing that more situations in the future will requireremote work (ß5 0.20) on likelihood of exclusively working digitally in the future. These two

IJSSP40,9/10

868

variables account for 51% of the variance in this model, meaning that people who believe in adigital future in the near future are also more likely to imagine working digitally exclusively.After adding the variables preference for a home office job in the future, working remotelybecause of COVID-19 and the primary source of income, these effects remain stronglysignificant in Model 2. The stronger the preference of a person to work remotely in the future(ß5 0.20), the more likely he or she is to imagine exclusively working digitally (1% level). Inthis analysis, I distinguished between people who already worked from home before COVID-19 and those who only began working from home when the COVID-19 pandemic began. Theresults show that people who already worked from home (ß5 0.31) can imagine themselvessignificantly (5% level) more likely towork exclusively digitally in the future than peoplewhohave notworked remotely in the past. For peoplewho are new toworking remotely because of

(1) (2) (3) (4)Sit. job satis. Sit. job satis. Sit. job satis. Sit. job satis.

Home office (Ref. No home office)Yes 1.03*** 1.04*** 0.29 0.25

(0.23) (0.24) (0.19) (0.19)Scared being infected 0.04 �0.05 �0.09

(0.11) (0.09) (0.09)Primary income (Ref. crowd)Digital work 0.31 �0.14 �0.14

(0.34) (0.25) (0.25)Traditional job 0.02 �0.14 �0.12

(0.32) (0.24) (0.24)Digitalisation faster �0.03 �0.04 �0.01

(0.12) (0.09) (0.09)Fut. more home office 0.08 0.15 0.14

(0.11) (0.09) (0.08)Fut. job home office �0.04 �0.01 0.01

(0.09) (0.07) (0.07)Satisfied household income 0.08* 0.08

(0.05) (0.05)Satisfied personal income 0.62*** 0.58***

(0.05) (0.05)Country (Ref. USA)Italy �0.70**

(0.28)Germany �0.96***

(0.30)Spain �0.67**

(0.28)UK �0.51*

(0.31)France �0.45

(0.31)Sex 0.30

(0.17)Age 0.12

(0.09)N 506 501 477 477Adj. R2 0.03 0.03 0.47 0.48Root MSE 2.50 2.50 1.83 1.81Constant 5.27 4.98 1.69 1.66

Note(s): *p < 0.10; **p < 0.05; ***p < 0.01 (Std. Err.)

Table 1.Linear regression onsatisfaction with thecurrent job situation

Influence of theCOVID-19pandemic

869

the COVID-19 pandemic, no significant effect emerges. Besides the effect of working at homediminishes if the country of the respondents is included in the analysis (Appendix, Table A1).The preference to work digitally exclusively in the future does not differ significantlydepending on the current primary source of income. This result shows that the more a personbelieves in fast digital change, the more he or she can imagine working exclusively digitally.Thus, the data confirm H3.

6. DiscussionThe aim of this research was to investigate whether the COVID-19 pandemic has influencedthe acceleration of digital transformation of labour. I observed a significant increase in peopleworking from home, using technologies in their daily work life, consistent with previousstudies (B�eland et al., 2020; Spurk and Straub, 2020; St€urz et al., 2020; Von Gaudecker et al.,2020). However, these studies do not verify the extent to which these people have previouslyused technology in their everyday work. Figures 1 and 2 show that the increase in workingremotely on a regular basis due to the COVID-19 pandemic ismainly a result of the changes inthe working behaviour of people who occasionally worked remotely before the pandemic,possibly because these people were more likely to have the necessary infrastructure andcompetence to implement a quick change without problems. Even if the increase in workingremotely is a short-term effect of COVID-19 on daily work routines, the data also show thatpeople predict digital work forms to be significantly more important in the future than theywere before the pandemic.

The results capture a moment in time during the COVID-19 pandemic, and predictionsabout, for example, secure sources of income and development of digital jobs reflectrespondents’ point of view. This study did not investigate consequences of the pandemic thatcould influence this development (e.g. rising unemployment, economic downturn); future

(1) (2)Exclusively digital work Exclusively digital work

Digitalisation faster 0.53*** 0.53***(0.06) (0.06)

Fut. more home office 0.20*** 0.19***(0.06) (0.05)

Fut. job home office 0.20***(0.04)(0.05)

Home office (Ref. No home office)Yes, due to COVID-19 0.26

(0.15)Yes 0.31**

(0.17)Primary income (Ref. crowd)Digital work 0.16

(0.16)Traditional job 0.08

(0.18)N 552 517Adj. R2 0.53 0.56Root MSE 1.82 1.24Constant 0.70 �0.20

Note(s): *p < 0.10; **p < 0.05; ***p < 0.01 (Std. Err.)

Table 2.Linear regress onexclusively workingdigitally

IJSSP40,9/10

870

studies could investigate this topic at a later point in time. The results, however, show a quickassessment of the obstacles of technological change and the willingness to adopt digitalforms of work. Willingness to change is a construct that could be helpful in understandingand predicting behaviour at an organisational level (Metselaar, 1997). Willingness to changerepresents a positive behavioural intention towards the implementation of changes in thework processes of an organisation, which leads to efforts of the organisation’s members tosupport, improve and thus drive the change process (Metselaar, 1997). The data can thereforebe interpreted as the basis or prerequisite for change.

The results show that people consider digital work forms significantly more likely to be asecure source of income than traditional jobs. Regarding the influence of the COVID-19pandemic, it should be taken into account that the digital transformation has been in processfor several years (European Commission, 2017), and digital jobs could have become moreimportant in the future even without COVID-19. However, the data show that most peoplebelieve that the pandemic has accelerated the digital transformation of work. These peopleare alsomore likely to imagineworking exclusively digitally. This result remains robust aftercontrolling for the primary source of income, which shows that those who have experienceengaging in digital work forms are able to imagine doing so exclusively.

The results show that many people are willing to take part in the digital job transformationand that personal income has a substantial influence on job satisfaction (Table 1). However, nosignificant effect of homeoffice on job satisfaction could be found in the data. Since the datawascollected at the beginning of the pandemic, it is possible that individuals need to get used to thisnew work situation. It is also possible that working remotely is not yet efficient enough at thispoint (e.g. availability of right technologies, consultation with superiors and colleagues).A survey at a later date, which will examine the working conditions in the home office moreclosely, is necessary to get a more concrete overview.

Companies should investigate how to ensure the job satisfaction of people in the homeoffice. One way could be to invest more in remote work technology to make the use of thisform of work more efficient. Overall, a balance between traditional and remote models shouldbe considered in the transformation of work. As remote work spreads, the development ofremote work policies by human resource departments and policymakers must also beaccelerated. This is important to ensure the protection of employees.

7. LimitationsThis research has three limitations, which should be considered when drawing conclusionsfrom the analyses. First, the data were collected on a crowdsourcing platform. Even if themajority of the respondents donot state crowdsourcing as their primary source of income, it canbe assumed that theymay have already had a certain affinity and experiencewith digital work.

Second, the data were collected at early stages of the COVID-19 pandemic. The spread ofthe pandemic was at different stages in the countries in which surveys were collected. Inaddition, the governments of these countries exhibited significant differences in themeasurestaken. Considering 66% of the data set reported an age of 18–34 years, the respondents wererather young, which might have influenced their acceptance of digital work forms andwillingness to implement them in their lives.

Third, the participants of the study see the conditions under which they are working on atask before they process it. Amazon Mechanical Turk provides them with the average time ittakes to process a task and the salary paid. This leads to self-selection of the participants andto a non-probability sample.

8. ConclusionThis study shows that the basis for digital change in the time of COVID-19 is solid. Thepandemic has increased the number of people working remotely, and people view it as an

Influence of theCOVID-19pandemic

871

accelerator of digital transformation. In addition, people perceive that their experience withthe pandemic has made themmore likely to work digitally exclusively, especially people whoperceive that the pandemic has caused rapid change. Furthermore, the importance of digitalwork as a secure source of income has increased. Job satisfaction does not differ betweenpeople who work remotely and those who continue to work at their workplace; satisfactionwith personal income has a great influence. The results show that people perceive a change inthe importance of different job forms through COVID-19. Based on respondents’ assessments,it appears that more people are willing to switch from a job exclusively to digital work. Giventhe assessments of the respondents and the promotion of digital transformation, it appearsthat more people are willing to switch from going to a workplace to exclusively living fromdigital work. Although the results confirm the influence of the COVID-19 pandemic on theacceleration of digital transformation, further studies are necessary to confirm this statementin the long run.

References

Adams-Prassl, A., Boneva, T., Golin, M. and Rauh, C. (2020), “The large and unequal impact ofCOVID-19 on workers”, VoxEU.org. Library Catalog: VoxEU, available at: https://voxeu.org/article/large-andunequal-impact-covid-19-workers.

Anderson-Connolly, R., Grunberg, L., Greenberg, E.S. and Moore, S. (2002), “Is lean mean? Workplacetransformation and employee well-being”, Work, Employment and Society, Vol. 16 No. 3,pp. 389-413.

Baturay, M.H., G€okçearslan, S. and Ke, F. (2017), “The relationship among pre-service teachers’computer competence, attitude towards computer-assisted education, and intention oftechnology acceptance”, International Journal of Technology Enhanced Learning, Vol. 9No. 1, pp. 1-13.

B�eland, L.-P., Brodeur, A. and Wright, T. (2020), “The short-term economic consequences of Covid-19:exposure to disease, remote work and government response”, IZA Institute of LaborEconomics, available at: https://www.iza.org/publications/dp/13159/the-short-term-economic-consequences-of-covid-19-exposure-to-disease-remote-work-and-government-response.

Bick, A. and Blandin, A. (2020), “Real time labor market estimates during the 2020 coronavirusoutbreak”, working paper, Arizona State University, available at: https://ssrn.com/abstract=3692425.

Brakman, S., Garretsen, H. and van Witteloostuijn, A. (2020), “The turn from just-in-time to just-in-case globalization in and after times of COVID-19: an essay on the risk re-appraisal of bordersand buffers”, Social Sciences and Humanities Open, Vol. 2 No. 1, pp. 1-24.

Coibion, O., Gorodnichenko, Y. and Weber, M. (2020), “Labor markets during the Covid-19 crisis: apreliminary view”, NBER Working Paper No. 27017, National Bureau of Economic Research.

Danish, R.Q. and Usman, A. (2010), “Impact of reward and recognition on job satisfaction andmotivation: an empirical study from Pakistan”, International Journal of Business andManagement, Vol. 5 No. 2, pp. 159-167.

Eberhard, B., Podio, M., Alonso, A., Radovica, E., Avotina, L., Peiseniece, L., Caama~no Sendon, M.,Gonzales Lozano, A. and Sol�e-Pla, J. (2017), “Smart work: the transformation of the labourmarket due to the fourth industrial revolution (I4. 0)”, International Journal of Business andEconomic Sciences Applied Research, Vol. 10 No. 3, pp. 47-66.

European Commission (2017), A Concept Paper on Digitalisation, Employability and Inclusiveness,D.-G.f.C.N., Content and Technology, available at: ec.europa.eu.

European Commission (2020), “European construction plan”, available at: https://ec.europa.eu/info/live-work-travel-eu/health/coronavirus-response/recovery-plan-europe_de (accessed 20July 2020).

IJSSP40,9/10

872

European Union (2020), ““The EU budget powering” the recovery plan for Europe”, available at:https://ec.europa.eu/info/sites/info/files/factsheet_1_en.pdf (accessed 12 July 2020).

Finn, C.P. (2001), “Autonomy: an important component for nurses’ job satisfaction”, InternationalJournal of Nursing Studies, Vol. 38 No. 3, pp. 349-357.

Fried, Y. and Ferris, G.R. (1987), “The validity of the job characteristics model: a review and meta-analysis”, Personnel Psychology, Vol. 40 No. 2, pp. 287-322.

Gelbrich, K. and Sattler, B. (2014), “Anxiety, crowding, and time pressure in public self-servicetechnology acceptance”, Journal of Services Marketing, Vol. 28 No. 1, pp. 82-94.

Hackman, J.R. and Oldham, G.R. (1975), “Development of the job diagnostic survey”, Journal ofApplied Psychology, Vol. 60 No. 2, pp. 159-170.

Hirsh, J.B., Mar, R.A. and Peterson, J.B. (2012), “Psychological entropy: a framework for understandinguncertainty-related anxiety”, Psychological Review, Vol. 119 No. 2, pp. 304-320.

Kohnke, O. (2017), It’s It's not just about technology: the people side of digitization, in Oswald, G. andKleinemeier, M. (Eds), Shaping the Digital Enterprise, Springer, Waldorf, pp. 69-91.

Men�endez, L.S. and Castro, L.C. (2002), “Coping with environmental pressures: Public ResearchOrganizations responses to funding crisis”, Documentos de Trabajo (CSIC. Unidad de Pol�ıticasComparadas), Vol. 19 No. 1, pp. 1-24.

Metselaar, E.E. (1997), “Assessing the willingness to change: construction and validation of theDINAMO”, doctoral thesis, Vrije Universiteit, Amsterdam.

Molino, M., Cortese, C.G. and Ghislieri, C. (2020), “The promotion of technology acceptance and workengagement in industry 4.0: from personal resources to information and training”, InternationalJournal of Environmental Research and Public Health, Vol. 17 No. 7, p. 2438.

Momani, A.M. and Jamous, M. (2017), “The evolution of technology acceptance theories”, InternationalJournal of Contemporary Computer Research, Vol. 1 No. 1, pp. 51-58.

Naqvi, S.R., Ishtiaq, M., Kanwal, N. and Ali, M. (2013), “Impact of job autonomy on organizationalcommitment and job satisfaction: the moderating role of organizational culture in fast foodsector of Pakistan”, International Journal of Business and Management, Vol. 8 No. 17,pp. 92-102.

Rosa, H. (2014), “From work-life to work-age balance? Acceleration, alienation, and appropriation atthe workplace”, in The Impact of ICT on Quality of Working Life, Springer, Berlin, pp. 43-61.

Scherer, R., Siddiq, F. and Tondeur, J. (2019), “The technology acceptance model (TAM): a meta-analytic structural equation modeling approach to explaining teachers” adoption of digitaltechnology in education”, Computers and Education, Vol. 128, pp. 13-35.

Shkalenko, A. and Fadeeva, E. (2020), “Analysis of the impact of digitalization on the development offoreign economic activity during COVID-19 pandemic”, in 2nd International Scientific andPractical Conference “Modern Management Trends and the Digital Economy: from RegionalDevelopment to Global Economic Growth”(MTDE 2020), Atlantis Press, Paris, pp. 1190-1195.

Socio-Economic Panel (2020), “Socio-economic panel questionnaires”, doi: 10.5684/soep.v3y (accessed 2March 2020).

Spurk, D. and Straub, C. (2020), “Flexible employment relationships and careers in times of theCOVID-19 pandemic”, Journal of Vocational Behavior, Vol. 119, pp. 2-4.

St€urz, C.S., Mendel, U. and Harhoff, D. (2020), “Digitalisierung durch Corona? Verbreitung undAkzeptanz von Homeoffice in Deutschland”, working paper, Bavarian Research Institute forDigital Transformation, available at: https://www.bidt.digital/studie-homeoffice/.

Sullivan, C. (2003), “What’s in a name? Definitions and conceptualisations of teleworking andhomeworking”, New Technology, Work and Employment, Vol. 18 No. 3, pp. 158-165.

Taherdoost, H. (2018), “A review of technology acceptance and adoption models and theories”,Procedia Manufacturing, Vol. 22, pp. 960-967.

Influence of theCOVID-19pandemic

873

Tessema, M.T., Ready, K.J. and Embaye, A.B. (2013), “The effects of employee recognition, pay, andbenefits on job satisfaction: cross country evidence”, Journal of Business and Economics, Vol. 4No. 1, pp. 1-12.

Venkatesh, V., Morris, M.G., Davis, G.B. and Davis, F.D. (2003), “User acceptance of informationtechnology: toward a unified view”, MIS Quarterly, Vol. 27 No. 3, pp. 425-478.

Vial, G. (2019), “Understanding digital transformation: a review and a research agenda”, The Journalof Strategic Information Systems, Vol. 28 No. 2, pp. 118-144.

Von Gaudecker, H.-M., Holler, R., Janys, L., Siflinger, B. and Zimpelmann, C. (2020), Labour Supply inthe Early Stages of the CoViD-19 Pandemic: Empirical Evidence on Hours, Home Office, andExpectations, IZA Institute of Labor Economics, IZA DP No. 13158, available at: https://ssrn.com/abstract=3579251.

Wilks, L. and Billsberry, J. (2007), “Should we do away with teleworking? An examination of whetherteleworking can be defined in the new world of work”, New Technology, Work and Employment,Vol. 22 No. 2, pp. 168-177.

Corresponding authorLisa Nagel can be contacted at: lisa.nagel@uni-bremen.de

IJSSP40,9/10

874

Appendix

(1) (2) (3)Excl. digital work Excl. digital work Excl. digital work

Digitalisation faster 0.53*** 0.53*** 0.56***(0.06) (0.06) (0.06)

Fut. more home office 0.20*** 0.19*** 0.18***(0.06) (0.05) (0.05)

Fut. job home office 0.20*** 0.20***(0.04) (0.04)

Home office (Ref. No home office)Yes, due to COVID-19 0.26* 0.22

(0.14) (0.15)Yes 0.31* 0.23

(0.16) (0.17)

Primary income (Ref. crowd)Digital work 0.14 0.26

(0.17) (0.18)Traditional job 0.06 0.14

(0.16) (0.17)Satisfied personal income �0.03

(0.04)Satisfied household income �0.04

(0.03)Satisfied free time 0.02

(0.02)Satisfied job situation �0.01

(0.03)

Country (Ref. USA)Italy �0.29

(0.20)Germany �0.54***

(0.20)Spain �0.26

(0.19)UK �0.25

(0.20)France �0.07

(0.20)Sex �0.03

(0.12)Age �0.04

(0.06)N 552 518 472R2 0.51 0.54 0.57Root MSE 1.82 1.24 1.21Constant 0.70 �0.49 0.13

Note(s): *p < 0.10; **p < 0.05; ***p < 0.01 (Std. Err.)

Table A1.Linear regression onexclusively working

digitally controlling forcountry

Influence of theCOVID-19pandemic

875