Workplace flexibility and working from home during Covid-19 by the example of a financial technology company

Introduction and problem definition

“I like having the choice to [work from home], but I prefer the office.” (Participant 6) . Although this quotation portrays employees as viewing workplace flexibility in a positive way, this study has found that this is not always the case. Indeed, at the beginning of the Coronavirus-19 pandemic, the world came to a standstill, and humans experienced lockdowns (European Center for Disease Prevention and Control, 2021) and restrictions globally. This also included employees of organizations worldwide who were legally required to work from home (WFH) to help minimize the risk of infection between coworkers and in their home-life (Kramer & Kramer, 2020). With employees encouraged to WFH, their new work modes changed, from going to the office daily to working from home through various computer-mediated communication (CMC) resources, with Zoom, Slack, Microsoft Teams, to name a few (Nolan et al., 2021). This increase in work-from-home during the pandemic has become the new norm around the world. With the introduction of CMC and an increase in workplace flexibility, such factors could influence how an employee feels about working from home, their identification with the company, their motivation, and whether this has an impact on their overall work performance.

Numerous academic papers studying the use of workplace flexibility in different workplace settings have been analyzed to understand whether tensions can arise through this method (Putnam et al., 2014). In the current study, workplace flexibility is defined as the ability and possibility to decide where, when and how one works and encompasses how, as an employee, you are given the opportunity to decide on the time, location and task features of your work in order to create a balance between work- and home-life (Putnam et al., 2014).

Moreover, CMC and new ways of working have also been analyzed throughout the years to understand their impact on employee motivation and engagement. Computer-mediated communication is defined as any communication that can occur through the use of technological devices (Treem, Leonardi & Van den Hooff, 2020), whereas new ways of working can be described as the types of working environments, such as flexible work arrangements and mobile-work, both in person and online, that an employee has in order to facilitate their execution of tasks (Gerards, de Grip & Baudewijns, 2018). Moreover, Tate and colleagues (2019) analyzed the effect of CMC on workplace flexibility and employee engagement. The researchers found that employees who engaged in CMC and had the opportunity to share their knowledge with their colleagues were more likely to increase and maximize their work productivity (Tate et al., 2019). This paper will use this as a foundation to understand how, during the pandemic, organizations have used CMC in order to communicate with their colleagues and teams.

With the increase of employees working from home, their identification with their company could have changed. Identification can be described as the degree to which one identifies with the organization they are working for (Ashforth et al., 2007). Moreover, the autonomy in the work they have could have drastically changed, as there might be a shift between work- and home-life when employees are forced to WFH. Autonomy is defined as the more autonomy that one gets in their work, the more likely they are going to devote more hours to their work, and get less home-life freedom (Mazmanian et al., 2013). This paper will aim to understand how such variables play a role in the workplace flexibility of employees.

Based on previous research on workplace flexibility and computer-mediated communication, and the general importance of this study, the following research question has been formulated:

RQ: How has workplace flexibility during the Covid-19 pandemic affected everyday working life and employee interrelations?

Through the use of qualitative semi-structured interviews, this paper aims to analyze and answer the effect of work-from-home on workplace flexibility, and whether the Covid-19 pandemic plays a role in this. Moreover, the paper aims to understand variables such as autonomy within the workplace, colleague dynamics, and identification with the organization.

Theory and literature

Autonomy paradox

Since Mazmanian et al. (2013) illustrate how technological device usage is a mixed blessing for workers, we were convinced that the autonomy paradox could also play a vital role while working from home. On the one hand, smartphones enable workers to operate flexibly and to be available at all hours (Mazmanian et al., 2013). On the other side, this increment of availability leads to higher inflicted social control and consequently employee overcommitment (Mazmanian et al., 2013). The worldwide pandemic resulted in workplace mobility, since knowledge professionals were physically distanced from colleagues and technological devices used to communicate. Also, social capital was diminished, while individual autonomy increased. In previous research, “buffering and temporal distancing” (Mazmanian et al., 2013, p. 1343) were encountered, collective actions that employees applied to avoid being constantly available. At the same time, technology was attributed to not only boosting efficiency but also flexibility (Mazmanian et al., 2013). Albeit these benefits, it was reported that participants verbalized both negative sentiments and peer pressure (Mazmanian et al., 2013). Moreover, the dynamic of this paradox process allows individuals to feel free, yet restricted via norms and received information, becomes evident. Nonetheless, the terrain of the financial industry limits the finding’s generalizability. Among others, a researcher from the HSE Moscow conducted a quantitative study on the autonomy paradox with his colleagues on freelancers and to what extent the autonomy paradox occurred (Shevchuk et al., 2019). Although the participants were ascribed a high degree of freedom in time management, two-thirds of the participants ended up working at night, which had a negative effect on well-being (Shevchuk et al., 2019).

Overall, we are convinced, showcasing a technology-based industry will contribute to the existing body of literature. Furthermore, this paper adds depth to qualitative research methods which were deployed studying this topic. In this context, we aim to investigate how the environment, namely hardware, software, workplace and arrangements between coworkers, enable the autonomy paradox. Interestingly, this phenomenon was already coined in two studies twenty-five years ago (Huws et al., 1996; Marshall et al., 1996). As this may exert pressure on workers, the next concept reflects the integration of opposing forces in work design.

Tensions around workplace flexibility

Another perspective of contemporary workplace conditions is tensions created through the opposing forces of work features such as time, space and tasks (Putnam et al., 2014). Because company culture (Boyce et al., 2015) is essential in realizing creative solutions of flexible work arrangements on a company-wide, team or individual level, workers become highly dependent on their surroundings, coworkers and management they encounter. Putnam et al. (2014) indicate that implementing workplace policies is similar to two competing expeditions to the North and South pole. In the context of our study, the discrepancies between variable and fixed arrangements and between supportive and unsupportive surroundings (Putnam et al., 2014), are crucial. Nowadays, it is well studied how a negative atmosphere actively threatens a firm’s performance (Schneider et al., 2013). The first tension, variable versus fixed arrangements, shows that flexible arrangements are limited by work demands (Putnam et al., 2014). Company policies could refrain employees from actually working flexibly, which is a strong contradiction. Although the hierarchies and structures of decision-making around flexible working in every organization are unique, it could be argued that clear expectations within a team are an essential component. The second tension, supportive versus unsupportive work environment, states the role of an employee’s surroundings in a work environment (Putnam et al., 2014). When their coworkers support their use of flexible arrangement they will be more comfortable in using them and more likely to use them in the first place (Putnam et al., 2014). In opposition, unsupportive coworkers will discourage people, and they ultimately use arrangements less.

Therefore, management attempts to favor one side, combine tensions, or explore a different angle (Putnam et al., 2014). One could argue that tension management becomes more difficult if workers are expected not to be in the office, as lack of personal interaction makes communication more difficult. Yet, scholars advocate that the expectation to work a significant amount of time from home is a possibility to minimize discussions around working flexibility, ultimately reducing conflicts (Putnam et al., 2014). To sum up, those findings, working from home may present various difficulties for employers, despite allowing the operations to continue. As firms are looking for ways to establish day-to-day operations which go beyond merely functioning, the following theoretical construct examines the relationship employees have with their organization in detail.

Identification

When an individual joins an organization, they join a corporate culture that could either be in line with their identity or different from it (Ashforth et al., 2007). Entering a new organizational culture could consequently affect whether an individual identifies with the company. Identification is defined as the degree to which one identifies as a member of an organization and whether they see themselves within the company values, brand and image (Ashforth et al., 2007). In terms of organizational communication, people order their social environment in terms of the groups within them, which consequently leads them to classify themselves within these groups (Ashforth et al., 2007). People aim to become part of a ‘we’ intergroup perspective to identify with their surroundings, both in their personal and work life (Hatch & Schultz, 2002). This intergroup identification could have an effect on one’s behaviors, which can be either positive or negative, thus impacting how they work (Ashforth et al., 2007). This form of social identity is a part of an individual’s self-categorization, which is taken from their knowledge about a specific group (Ashforth et al., 2007). This social identity consequently influences how one identifies themselves within their work environment, potentially influencing their overall work behavior (Ashforth et al., 2007).

With regards to the current study, the identification of an individual with an organization can be influenced by workplace flexibility (Dastmalchian & Blyton, 2001). This is because, when one has the opportunity to WFH, they are less likely to communicate and identify with their coworkers (Dastmalchian & Blyton, 2001). Indeed, they are less likely to identify with an organization because flexible work arrangements lead them to not being as in touch with their team members, thus impacting whether they see themselves as part of the organization (Rahman et al., 2020). Moreover, with the Coronavirus-19 pandemic forcing employees to WFH to minimize the spreading of the virus, employees were presumably to feel less as a part of an organization as they did not see their coworkers for many months (European Center for Disease Prevention and Control, 2021).

Research design

The research question will be approached by conducting interviews with several employees of company X. Interviews will help find underlying experiences and feelings of the participants about workplace flexibility. Working from home during Covid-19 up to now has been a troublesome and challenging time for people, so interviews will give them more space to express their feelings than a quantitative study could. Moreover, an interview allows for follow-up questions which can help in finding individual reasoning and explore emotions. As measuring flexibility on a scale was not enough for this research, a complete picture of, for example, a workday and the effects of disturbances on that workday needed to be analyzed, in order to align our methods within grounded theory (Charmaz, 2006). The previously mentioned important concepts were operationalized into interview questions and incorporated into the interview guide (see Appendix I). The first concept, the autonomy-control paradox, was operationalized by asking the participants if they felt like they had worked harder or longer during WFH than they would have at home because of the flexible workspace. This included how their hours changed specifically, for example if they took more or less breaks. This topic flowed over into the next topic, supportive versus unsupportive working environment, where participants were asked if their manager and/or coworkers supported the workplace flexibility choices they made during working from home or if they received criticism from people within their teams. Part of this was how the responses of colleagues made them feel, did they actually feel supported or discouraged to use any flexible arrangements? The third topic was operationalized by asking participants if they felt like they were given a flexible working environment during WFH and deadlines were an important part of this operationalization. How was their work day or week affected by the use of deadlines while workplace flexibility was used? Would they have preferred a work week without deadlines, if yes or no, why? In the fourth topic, identification, the interviewees were asked to what extent WFH had affected the way they identified with the company and if they felt like their level of commitment to the company had changed. Was their sense of belonging affected and what measures did company X take to maintain or even increase identification with the company during WFH. Lastly, the concept of CMC was operationalized by asking the interviewees what online communication platforms or means they used to stay in contact with their colleagues and managers. This topic also included questions about how company X supported CMC through material compensation during working from home.

Sample

Ten interviewees were selected from company X from the product and engineering department using a convenience sample. Within this department all the interviewees were employed in the product subdepartment. The interviewees were invited to participate in the research via their corporate email. They received a form in which they could indicate when they would like to be interviewed. Two employees initially agreed to participate but ended up withdrawing, so replacements were found within the same departments. All participants were informed upfront that we were planning to use their data for research purposes outside of company X. Participants were randomly matched to the five interviewers. The final sample consisted of three females and seven males, with an average age of 31,4 (see Figure 1). Nationalities of the participants were varied: The Netherlands (4), Greece (1), Argentina (1), United Kingdom (1), United States (1), Australia (1) and Saudi Arabia (1). The time in which the participants joined company X differed; two interviewees joined the company before the pandemic started, and eight interviewees joined company X during the pandemic. Nine of the participants currently reside in the Netherlands working at the Amsterdam location of company X, and one participant resides in Portugal working at the Lisbon location. Lastly, three of the participants lived alone at the time of the interview, and seven with their partners, among these seven participants two also had children.

Figure 1.

Participant demographics.

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Data collection

Here, four out of ten interviews were conducted online using Google Meets, whereas our team arranged the other six at company X’s headquarters in Amsterdam, where secluded and quiet meeting rooms as well as recording equipment was available. Five interviews were recorded using both video and audio, and the other five recorded only audio. The online interviews were recorded with both video and audio except for one interviewee who only wanted to participate using audio. Because of practical matters, video calls were deployed so that the interviewee and interviewer could see each other even though they were not in the same room. In addition, the interviews lasted an average of 42,4 minutes and ranged from 33 to 58 minutes.

Moreover, the interviews were semi-structured and followed a previously set interview guide. This guide started with a general introduction, information about the recording, and the signing of the informed consent. Secondly came the background questions to paint a picture of the interviewee. The questions were then divided into five categories: pre-pandemic, during pandemic, benefits, adaptation and tensions. These followed a chronological timeline from before the pandemic to during work-from-home caused by the pandemic and finally to their current situation. When the procedure was concluded with a general summary of answers, the participants were thanked for taking part, and a final reminder that the interview was recorded and that they had the possibility to withdraw their participation at any time was stated. Throughout the conversation, probing techniques were used to get more information out of the interviewees; they were asked to elaborate on answers, explain their feelings in more detail or give examples of a situation they encountered that fit the question. This gave a broader picture of their experiences during work-from-home.

Data analysis

All transcribed interviews were processed through ATLAS.ti version 9. Beforehand, a general codebook was prepared to create coherence in language between the coders, but open coding still occurred. Coders were free to add extra codes and differ from the general codebook where needed. After the first round of coding, 156 codes were identified and used for 759 quotations. When merging similar codes for the second round of coding, 68 codes were left used for 751 quotations. Here, those that were too similar or could fall under the same name were merged. In this context, linguistic differences were combined as well to form one unified code. Since some codes appeared more often than others, a general picture of which topics were mentioned most materialized. Thus, the most prominent topics were identified, and a concept indicator model was created to find similarities and differences within the core concepts. The concept ‘flexibility’ from the research question is seen as the starting point, followed by five core concepts: functioning of the company, environment, interactions, adaptation to working from home and personal and group dynamics (see Figure 2). These five overarching concepts consist of all the codes used after the second round of coding and merging.

Quality criteria

Several qualitative quality criteria were kept in mind while developing this study. Reliability of this study was ensured by making sure the interview guide was very clear with the structured questions, example follow-up questions and the order in which the questions needed to be asked. The interviewers were instructed to use the same probing techniques and ask for examples when necessary. When an interview brought forward more important insights this was noted and passed on to the next interviewer to use. When a new study uses this interview guide and the same instructions they will have a stronger change to replicate this study. To achieve validity in this study the interviews were held both in the office of the participants and online through Google Meets in a working from home setting. The participants were studied in their natural environment, the environment we were interested in, their experiences in working from home and how that differed from working in the office. The environment they were interviewed in made sense with the subject and thus increased the validity of the study. Lastly, generalizability of the results is high in the current working environment in the Netherlands. A large part of the corporate offices in the Netherlands were faced with a shift to working from home due to the pandemic. This study has a detailed description of the participants and a strong conceptualization of the used concepts. Knowing that many businesses are in the same situation combined with the extensive description of the participants, concepts and the method create a higher generalisability.

Figure 2.

Concept indicator model

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