Pedro I. Leiva
Edgar E. Kausel
Hector P. Madrid
Rodrigo A. Alday
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- 1Departamento de Administración, Facultad de Economía y Negocios, Universidad de Chile, Santiago, Chile
- 2School of Management, Pontificia Universidad Católica de Chile, Santiago, Chile
- 3School of Business, Universidad Adolfo Ibáñez, Santiago, Chile
- 4Escuela de Ciencias Sociales, Universidad de O'Higgins, Rancagua, Chile
Introduction: The massive implementation of teleworking during the COVID-19 pandemic highlighted its advantages for employees and organizations. Afterwards, transitioning back to the office, some companies are considering hybrid arrangements to sustain the positive effects of teleworking on job performance. This study, performed during the COVID-19 pandemic, argues that effective telework depends not only on organizational support but also on employees' preferences for telework.
Objective: The purpose of the study was to examine predictors of employee telework preference. Drawing on the Theory of Planned Behavior (TPB), we propose that employees' telework preference is influenced by their attitudes and subjective norms regarding teleworking, moderated by their perceptions of telework behavioral control.
Methods: Data was collected with a two-wave survey from 162 employees of two service organizations in Chile, South America.
Results: Our findings reveal that positive attitudes toward teleworking significantly predict telework preference. Additionally, the subjective norm positively influences telework preference when employees perceive high behavioral control.
Conclusion: These findings contribute to TPB and telework management literature broadening the scope of TPB on telework and offering practical insights for enhancing telework management.
Introduction
Telework is defined as “working outside the conventional workplace and communicating with it by way of telecommunications or computer-based technology” (Bailey and Kurland, 2002; p. 384). This work arrangement is typically performed as a “home office” (Golden and Veiga, 2005; Morganson et al., 2010). Telework offers several potential benefits. From an organizational perspective, it reduces costs associated with infrastructure and energy, while enabling the recruitment of geographically diverse employees who may not be able to commute regularly (Allen et al., 2015; Weber et al., 2022). For employees, telework saves time and resources on commuting and fosters a better work-life balance. Furthermore, telework has been associated with increased productivity and cost savings for employers (Bloom et al., 2015; Criscuolo et al., 2021; Gajendran and Harrison, 2007; Hajal, 2022).
Organizations began adopting telework in the 1970s with the development of technologies that facilitated remote communication (Nilles, 1975). However, the advent of the internet in the 1990s marked a turning point for broader telework implementation (Wang et al., 2020). The COVID-19 pandemic served as a massive trial for teleworking, as organizations implemented this arrangement to prevent virus transmission, protect workers, and ensure business continuity (Barrero et al., 2021; González González et al., 2022; Kniffin et al., 2020; Ozimek, 2020). This scenario provided an opportunity to study teleworking while controlling for differences between teleworkers and non-teleworkers.
Implementation of telework posed numerous challenges for workers and organizations, including adjusting to new environmental and working conditions, the difficult access to valuable working tools, work uncertainty, and managing perceived distance from supervisors and colleagues (Carnevale and Hatak, 2020; Graves and Karabayeva, 2020; Ipsen et al., 2018). Concerns discussed in the media further heightened fears about the effectiveness of telework (Guynn, 2013; Humer, 2013; Isidore, 2017; Simons, 2017). Over time, however, teleworkers maintained job performance levels and even reported increased productivity due to fewer distractions and interruptions (Ipsen et al., 2018). This led to positive expectations regarding telework as a sustainable work arrangement (Moens et al., 2022). Managers began to view telework favorably and considered maintaining it, at least in a hybrid mode after pandemic (Barrero et al., 2021; Criscuolo et al., 2021; Johnson, 2021; Ozimek, 2020). Consequently, as many companies transition back to the office, companies face the challenge of arranging telework practices in the post-pandemic era (Wasko and Dickey, 2023).
Emergent research suggests that employee willingness to telework should be important for effectiveness of this kind of work arrangement. For instance, telework was associated with greater task and innovation proficiency (Hackney et al., 2022; Huo et al., 2023). These findings underscore the importance of employee preferences in achieving high job performance in telework contexts. Therefore, the successful adoption of telework depends not only on organizational decisions but also on employee preferences. Employees with stronger telework preferences are more involved in this arrangement, potentially leading to more positive job outcomes (Clark, 1998; Clark and Olfman, 1999; Khalifa and Davison, 2008). Despite this, existing literature on telework largely focuses on environmental work conditions, resources, and direct effects on job performance, motivation, stress, well-being, and work-life balance (Athanasiadou and Theriou, 2021; Gohoungodji et al., 2023; Hackney et al., 2022; Mele et al., 2023). Thus, the factors influencing employee telework preferences remain underexplored in work and organizational psychology.
The purpose of the paper is examining predictors of employee telework preference. Our hypotheses and theoretical framework are guided by the Theory of Planned Behavior (TPB, Ajzen, 1985, 2020). As detailed below, we understand telework preference over working in the office, as behavioral intentions, for which the TPB is particularly well-suited to provide propositions. This theory allowed us to propose that preferences to telework instead of working in the office (i.e., behavioral intentions) are determined by positive appraisal of telework as a work arrangement (i.e., attitudes toward the focal behavior), perception of the coworkers and the supervisor about teleworking (i.e., subjective norms regarding the focal behavior), and the moderation of the individual's perception of performing well when teleworking (i.e., individuals' perception of behavioral control).
Our contributions to the remote work research are three-fold. First, we highlight the construct of employee telework preference, contrasting with prior studies that emphasize organizational perspectives. Second, we extend TPB to explain differences in employee telework preferences, providing insights into this underexplored area. Third, our findings have practical implications for informing telework policies, HR practices, and management strategies that can enhance telework preference and, consequently, job performance. By focusing on employees' attitudes, social norms, and perceptions of control, organizations can better support telework as a viable and successful work arrangement.
Telework preference and the theory of planned behavior
Following Bailey and Kurland (2002), we define telework preference as employees' intention to choose working outside the traditional workplace, over working within it, reflecting individual differences in the desire to work from locations such as home (see also Athanasiadou and Theriou, 2021). Conceptualizing telework preference as a behavioral intention makes the TPB (Ajzen, 1991, 2020) a suitable framework for examining this construct. TPB provides a systematic approach to understanding the preferences, choices, intentions, and readiness to engage in specific behaviors.
TPB is considered a rational behavior model, asserting that individuals are aware of their preferences and make deliberate choices accordingly (Nisson and Earl, 2020). Developed by Icek Ajzen, TPB is grounded in cognitive self-regulation and conscious beliefs that significantly influence human behavior (Ajzen, 2011). Its central premise is that behavioral intentions are the immediate precursor to actual behavior. This principle posits that observable actions are preceded by mental intentions to perform them, as supported by various studies and meta-analyses (e.g., Hagger et al., 2022; Randall and Wolff, 1994; Sheeran, 2002; Sheeran and Orbell, 1998).
The TPB framework identifies three constructs that influence behavioral intentions. The first is attitude toward the behavior, defined as the positive or negative evaluation of the behavior. This attitude is shaped by an expectancy-value calculation, where individuals assess the desirability of the outcomes associated with the behavior and the likelihood of achieving these outcomes (Conner and Armitage, 1998; Sussman and Gifford, 2019; Vroom, 1964). The second construct is subjective norms, which refer to the perceived social pressure to perform or avoid the behavior (Ajzen, 1985). These norms are influenced by normative beliefs about the expectations of important referent individuals, such as friends and family, and/or colleagues and supervisors. Aligned with the principle of social proof (Cialdini, 2007) people often determine the appropriateness of a behavior based on how widely it is practiced among others they respect or identify with. Behaviors endorsed by influential figures are more likely to be adopted, while the absence of support from such figures may reduce the likelihood of adoption. The third construct is perceived behavioral control, which involves beliefs about one's ability to execute the behavior effectively. This factor includes the evaluation of resources, opportunities, and barriers that may facilitate or hinder the behavior (Schmueli, 2021). A strong sense of control increases intentions to perform the behavior, while a lack of perceived control can weaken these intentions (Ajzen and Kruglanski, 2019). Early research on TPB emphasized the main effects of perceived behavioral control on intentions, but more recent studies highlight its moderating role in enhancing the influence of attitudes and subjective norms on intentions (Castanier et al., 2013; La Barbera and Ajzen, 2020, 2021).
TPB has been widely applied in the context of work and organizational psychology to explain work-related behaviors. For example, it has been used to study turnover intentions (Van Breukelen et al., 2004) and the intention to report workplace sexual harassment (Foster and Fullagar, 2018). These examples demonstrate the flexibility and relevance of TPB in understanding various behaviors in organizational settings.
Application of theory of planned behavior to telework
Applying TPB to telework preference suggests that the intention to embrace telework is influenced by telework-related attitudes, subjective norms, and perceived behavioral control. Attitudes toward telework reflect an individual's general evaluation of this work arrangement. Positive attitudes may arise from perceived benefits, such as improved work-life balance, reduced commuting time, increased efficiency, and greater control over work schedules (Ipsen et al., 2018; Laumer and Maier, 2021; Ozimek, 2020). Negative attitudes may stem from disadvantages, such as feelings of isolation, limited access to workplace resources, and blurred boundaries between work and personal life (Golden et al., 2008; Greer and Payne, 2014; Ipsen et al., 2018).
Subjective norms regarding telework are shaped by the social pressures exerted by colleagues, supervisors, and organizational culture (Laumer and Maier, 2021). The influential individuals or groups endorsement of telework within the workplace can construct social conformity (Asch, 1955; Chang and Yamamoto, 2023; Cialdini, 2007) encouraging employees to adopt it. Conversely, limited support for telework within one's social or organizational environment can weaken its perceived acceptability and reduce preference for this work mode.
Subjective norms related to telework refer to the social pressures exerted by relevant referents within an organization, such as colleagues and supervisors, on employees (Laumer and Maier, 2021). Coworkers and leaders who strongly value telework may contribute to the formation of social conformity (Asch, 1955; Chang and Yamamoto, 2023; Cialdini, 2007), encouraging employees to prefer teleworking. The perception that teleworking is a widespread practice within one's social network helps normalize this work arrangement and increases its accessibility. Research by Scott et al. (2012) indicates that workplace colleagues significantly influence employees' teleworking decisions. Conversely, when influential individuals in the workplace show little interest in or provide limited support for teleworking, the social pressure to adopt this arrangement diminishes, thereby reducing employees' preference for telework.
Taking all the above together, we propose the following hypotheses:
Hypothesis 1a: A positive attitude toward telework will be positively related to telework preference.
Hypothesis 1b: Positive subjective norms toward telework will be positively related to telework preference.
Furthermore, in the TPB, perceived behavioral control is posited to moderate how attitudes and subjective norms influence intentions. Thus, perceived behavioral control is a necessary condition for preferences or intentions to occur. Essentially, favorable attitudes and supportive subjective norms contribute to forming strong behavioral intentions, but individuals must also perceive that they are capable of performing the behavior (Ajzen, 2020).
Thus, perceived behavioral control would affect telework preferences because the perception of been capable of performing well would increase the relationship between attitudes toward telework and peer pressure with telework preferences. The capability to telework depends not only on possessing telework skills but also on other factors, such as the nature of the tasks—which should not require in-person performance—and access to essential resources, including an appropriate home workspace, technology, and information systems. However, the perception of one's ability to perform well is shaped by these factors, making it a more immediate and influential variable in explaining telework preference. Having the perception of being able to perform well teleworking would enhance employees' sense of control and confidence in their ability to perform tasks away from the traditional office setting. Conversely, if this sense of control is limited, it might reduce their preference for telework.
We hypothesized that high perceived behavioral control would amplify the positive association of favorable attitudes toward teleworking with a preference to telework. Specifically, a heightened preference to telework is expected when employees value this kind of remote work and feel assured in their ability to meet performance expectations in this setting. Similarly, we expected that high perceived behavioral control would also reinforce the positive relationship between supportive subjective norms regarding telework and telework preference. While psychological pressures from relevant others within the organization might alone increase telework preference, the combination with an individual's confidence in their capability to perform outside the traditional office setting could create a synergetic effect. So, the perception of being able to perform well teleworking would further increase the influence of subjective norms on the intention to telework. In other words, the impact of subjective norms on intentions is often small unless individuals perceive a viable opportunity to act on these intentions, as suggested by research from Park et al. (2009), as well as Umeh and Patel (2004). This theoretical extension proposes that the perceived capability of teleworking acts as a moderator, transforming normative pressures into actionable telework intentions.
Hypothesis 2a: Perceived behavioral control will moderate the relationship between positive attitude toward telework and telework preference, such that this relationship will be stronger when perceived control is high rather than low.
Hypothesis 2b: Perceived behavioral control will moderate the relationship between positive subjective norms toward telework and telework preference, such that this relationship will be stronger when perceived control is high rather than low.
Methods
Procedure and sample
To test our hypotheses, we conducted a two-wave survey study in two small service organizations in Chile. The study was conducted in May 2021, during the midst of the COVID-19 pandemic. At this time, the level of mandatory social confinement in the whole country changed weekly by county according to the level of risk of contagion, and only companies which proved essential services could all their workers to work from the office. Only some schools and universities opened and taught in a hybrid mode (some students in the classroom and some connected from home) because students from counties where still in social confinement, as well as the governmental regulations about the number of students allowed in the classroom. This context denoted a massive teleworking trial that allowed us to observe and test diverse antecedents and implications of this work design (Barrero et al., 2021; Ozimek, 2020). Thus, this was a suitable context for studying our research problem because, in both cases, the nature of the services provided, as well as the nature of tasks, which were able to perform teleworking. Thus, the companies' employees entirely performed their activities as home-based teleworkers due to the lockdown to prevent COVID-19′s spread. Therefore, possible differences in preferences, attitudes, and perceptions about the telework arrangement between teleworkers and non-teleworkers were controlled.
Following Podsakoff et al. (2012), to control the possible problems of common method variance that are sensitive to the analysis of cross-sectional designs, like the one adopted in this study, we adopted a two-wave study design, administering two surveys 15 days apart. At Time 1, participants gave information regarding the antecedents of telework preferences, i.e., telework attitudes, subjective norms, and behavioral control. Also, because people were motivated to telework during pandemic to avoid COVID-19 related health issues, they reported whether they feared getting infected. In addition, they reported sociodemographic and occupational information to be considered covariates in the hypotheses testing. At Time 2, 15 days later, participants reported their telework preference. Before responding to the Time 1 survey, participants signed an informed consent explaining the goals and procedure of the study, together with their voluntary participation in it. The university ethics committee of one of this study's authors reviewed and approved this methodology.
Participants were recruited from organizations that were part of the professional network of one of the researchers. All employees were invited to participate in the study by the organization's HRM department. Data form Time 1 and time 2 data was matched using the company employee ID. The first organization was a management services company for third-party commercial organizations. The second was the Chilean branch of a multinational company dedicated to certifying the health and environmental sustainability of organizations in this country. Both companies were based in Santiago, the country's largest city. Due to the small size of both companies and concerns about statistical power, we merged their data into a single dataset for further statistical analyses. As a result, the data became nested; however, identifying each participant's organizational membership allowed us to account for the variance associated with it.
The sample of the study was comprised of 162 participants who answered the survey in both times (Norg1 = 60; Norg2 = 102). Among the participants of both organizations 49% were females, the average age was 40.01 years (SD = 10.13), and the educational level was 1.2% secondary education, 13% technical studies, 84% university undergraduate, and 1.9% university postgraduate. The average organizational tenure was 3.92 years (SD = 4.57), and the job roles among all participants were 21.6% administrative, 3.1% technician, 29% professional analyst, 30% supervisor, and 16% manager.
Measures and analytical strategy
Based on the Theory of Planned Behavior, and guidelines by Ajzen (2006), we designed a set of scales to measure the variables underlying our hypothesis in the context of the COVID-19 crisis. Measures for telework preference, attitude toward telework, subjective norms about teleworking, perceived control over performing well when teleworking, and COVID fear, which items are shown in Table 1, were based on Likert statements for which participants indicated their degree of agreement or disagreement with each sentence in a range between 1: Strongly disagree and 5: Strongly agree. As reported in results section, the confirmatory factor analysis and the internal consistencies of the scales confirmed the robustness of the measurements.
Table 1
Table 1. Confirmatory factor analysis for telework preferences, attitude, subjective norm, perceived control and COVID fear.
Because the participants were full teleworkers based at their homes during the study, we gathered information on the number of children and care of persons at home needing special attention (e.g., health issues), which may be home demands negatively influencing telework preference. Furthermore, we measured access to childcare and housework support because they are facilitating resources to manage home demands with the potential to increase telework preference. We also control for organizational membership because the study was based on data merged from two different organizations.
A three-step strategy was implemented to analyze the data collected in R Statistical Software. First, we conducted confirmatory factor analyses to examine the construct validity of the measures designed (Brown, 2015). Thus, we compared the theoretical model defined by telework preference, attitude, subjective norm, perceived control, and COVID fear to alternative models to determine if they were different constructs. Second, zero-order correlations were estimated to determine the control variables to be used in the subsequent variables. We selected those variables with a statistically significant correlation to telework preference. Third, ordinary least squares regression and moderated regression were utilized for hypotheses testing, including simple slope tests for interaction effects (Aiken and West, 1991).
Results
Table 2 shows the results of the series of confirmatory factor analyses performed to assess the measurement model. The 4-factor model described by telework preference, attitude, subjective norm, and perceived control had excellent goodness-of-fit. The fit of this model was superior to the alternative models in which all measures were loaded in a single-factor, [Δχ2(df ) = 544,17(6), p = 0.00], or two-factors conveyed by telework preference, as 1 factor, and all the other variables of the theory of planned behavior, as factor 2 [Δχ2(df ) = 355.36(5), p = 0.00]. Furthermore, the 5-factor model, including COVID fear, also showed excellent goodness-of-fit too. All the measures obtained high reliabilities (Cronbach's Alpha, Table 3). These results showed that the variables studied were related but distinct constructs and supported our hypotheses' measurement model.
Table 2
Table 2. Confirmatory factor analysis.
Table 3
Table 3. Means, standard deviations, reliabilities, and correlations.
Means, standard deviations, correlations, and reliabilities are presented in Table 3. Zero-order correlation results showed that among all the candidate control variables, organization membership, gender, job role, and COVID fear were statistically significantly related to telework; thus, they were used as control variables in the subsequent analyses.
Hypothesis 1a stated that a positive attitude toward teleworking would positively relate to telework preference. As expected, the results of regression analyses showed a positive relationship between these variables, b = 0.65, SE = 0.09, p = 0.00 (Model 2, Table 4); thus, hypothesis 1a was supported. Hypothesis 1b proposed that positive subjective norms toward telework would be positively related to telework preference. Contrary to our expectations, the results of the same analyses showed that these variables were not related, b = 0.16, SE = 0.09, p = 0.08; hence, Hypothesis 1b was not supported.
Table 4
Table 4. Regression analysis for telework preference.
Hypothesis 2a stated that perceived behavioral control would moderate the relationship between positive attitude toward telework and telework preference, such that this relationship would be stronger when perceived control is high rather than low. Contrary to our expectations the interaction term between behavioral control and attitude was not related to telework preference, b = −0.14, SE = 11, p = 0.20 (Table 4, Model 3); thus, Hypothesis 2a was not supported. Finally, Hypothesis 2b stated that perceived behavioral control would moderate the relationship between positive subjective norms toward telework and telework preference, such that this relationship would be stronger when perceived control is high rather than low. As we expected, the results indicated that the interaction term between behavioral control and attitude was positively related to telework preference, b = 0.32, SE = 13, p = 0.02. Further simple slope analyses showed that positive subjective norm was positively associated with telework preference when perceived behavioral control is higher, b = 0.32, p = 0.01, [CI 99% 0.03, 0.62], but not lower, b = −0.15, p = 0.32, [CI 99% −0.56, 0.25] (Figure 1).
Figure 1
Figure 1. Interaction effect between telework subjective norm and telework perceived behavioral control on telework preference.
In summary, on one hand, as we expected, the empirical evidence supports that attitudes toward telework correlate with telework preference, even when controlling for the perception of coworkers and supervisors regarding teleworking and fear of COVID-19. However, contrary to our expectations, the relationship between attitudes toward teleworking and telework preference is not moderated by the belief in performing well when teleworking. On the other hand, contrary to our expectations, when controlling for attitudes toward teleworking and fear of COVID-19, the perception of coworkers and supervisors regarding teleworking is not correlated with telework preferences. Yet, as expected, the belief in the capability of performing well when teleworking moderates this relationship. Specifically, the perception of coworkers and supervisors about teleworking correlates with telework preference only among participants who believe they are capable of performing well when teleworking.
Discussion
To contribute to research on telework, this study examined predictors of employee telework preference. Data were collected in May 2021 during the COVID-19 pandemic in Chile, where strict social confinement measures restricted office work, and most employees transitioned to teleworking. This unprecedented context allowed us to investigate telework preferences while controlling for differences between teleworkers and non-teleworkers. Overall, the study's results showed that telework preference was positively associated with employee attitudes toward telework. Preference was also linked to subjective norms but only when employees perceived high levels of telework behavioral control. These findings underscore the role of consistent psychological processes in shaping telework preferences.
A key contribution of this study is its emphasis on the variability of telework preferences. Only 28% of participants expressed strong preferences for telework, while 22% reported low preferences. These findings suggest that organizations should bear in mind that telework preference is not universal, such that their implementation with not considering these individual differences could lead to suboptimal work outcomes (Bloom et al., 2015). Studies are consistent in showing that voluntary telework is associated with better job-related outcomes, such as task performance and innovation (Hackney et al., 2022; Huo et al., 2023).
Another contribution is the application of the TPB framework, a theory-driven approach, to address contemporary workplace challenges within organizational psychology, such as telework preferences. This broadens the scope of TPB. However, our results did not fully support the tenets of TPB (Ajzen, 2002). Specifically, the main effect of subjective norms, as well as the interaction effect between attitudes toward telework and perceived behavioral control, on preference to telework, theoretically expected, was not observed in our study. Based on these results we learnt that in teleworking, attitudes have a pervasive influence on preferences and that social pressure would be a necessary but insufficient condition for preference to telework, if the perception of control over teleworking is limited.
However, future research should revisit these findings in non-pandemic contexts to validate and refine the observed relationships, as the pandemic environment likely introduced unique contextual factors influencing telework preference. Fear of COVID-19 may have amplified the relationship between attitudes and telework preference, as employees could have prioritized staying home to minimize health risks, irrespective of their perceived ability to perform well while teleworking. Moreover, limited social interaction during the pandemic may have diminished the effect of coworkers' and supervisors' perceptions on telework preference, as such interactions were less prominent.
Practical implications
The results of our study offer practical implications for telework management by highlighting the importance of fostering positive attitudes toward telework, building constructive subjective norms, and reinforcing telework behavioral control. Given the study's aim to explore drivers of telework intentions, we propose the following recommendations.
First, to enhance positive attitudes, organizations should implement training programs that communicate the benefits of telework for both employees and the organization (Gajendran and Harrison, 2007; Hajal, 2022). Employees benefit from reduced commuting time, increased flexibility for personal or family commitments, and greater opportunities for leisure (Thompson et al., 2022). For organizations, telework sustains job performance by reducing distractions and improving work-life balance, which boosts employee satisfaction and energy levels (Bloom et al., 2015). Additionally, organizations save on infrastructure and operational costs (Criscuolo et al., 2021), freeing resources to invest in employee well-being and organizational effectiveness. Communication strategies should address potential telework challenges, such as the need for ergonomic home setups and reliable technology (Dimian et al., 2023). Financial support for these needs and regular in-person social events can mitigate such drawbacks.
Second, to leverage the effect of subjective norms on telework preferences for employees who feel competent in teleworking, organizations should build constructive telework standards. Managers play a key role by fostering a collaborative team environment through effective communication, coordination, cooperation, and conflict management, mitigating potential challenges posed by remote work (Kim et al., 2021). Leadership development programs should include training on fostering teamwork in remote settings to ensure employees perceive social pressure to telework as validated and constructive.
Third, because perceived behavioral control becomes a key boundary condition (Busse et al., 2017) for the influence of subjective norms on telework preferences, organizations should enhance it. This can be achieved by providing technical and task-related training, as well as regular feedback. Employees need self-efficacy in telework, which depends on their knowledge of remote work technologies (e.g., cloud-based communication systems) and competencies in planning, time management, and goal-oriented performance (Thompson et al., 2022). Skill-development programs can address these needs effectively (Venkatesh and Speier, 2000). Constructive feedback further enhances perceived behavioral control, as employees gain insights into their performance and areas for improvement. Leaders should hold regular performance discussions, highlighting strengths and addressing gaps to support telework effectiveness (Kim et al., 2021).
Limitations and future research
As with any research, this study has limitations that warrant discussion. The cross-sectional design restricts causal inferences among the variables in our model. Attitudes, subjective norms, and perceived behavioral control theoretically precede telework preference, a longitudinal approach would provide stronger evidence. Endogeneity issues, such as omitted variables, also pose a challenge (Antonakis et al., 2010). For instance, factors like age, personality traits (e.g., agreeableness; Clark et al., 2012), task suitability for telework, prior experience, and skills (e.g., communication, time management; Asgari et al., 2023), as well as past performance may influence attitudes and perception of behavioral control, further challenging causal interpretations. Thus, causality inferences in this study remain theoretical.
The use of self-reports was appropriate given the subjective nature of the constructs in TPB. However, reliance on self-reports introduces potential common-method variance, which may distort statistical estimates. Employing a two-wave design, with predictors and dependent variables measured 15 days apart, mitigated this issue to some extent. Nonetheless, common-method bias may still exist (Podsakoff et al., 2012).
The study context and sampling strategy also present limitations. Conducted during the COVID-19 pandemic, when teleworking was mandatory, the study effectively controlled for differences between work arrangements. However, the pandemic context may limit the generalizability of findings to post-pandemic settings, where telework preferences could shift. For instance, employees may prioritize reducing isolation or avoiding family-related distractions at home. Conversely, telework preferences could increase due to demonstrated benefits and improved organizational support (Asgari et al., 2023). Although COVID-19-related fear was statistically controlled, future studies in psychologically safer environments are needed to confirm these results.
To strengthen and expand on our findings, future research should adopt experimental and longitudinal designs, such as diary studies, and use statistical methods to address endogeneity and common-method variance (e.g., instrumental variables). Samples drawn from diverse organizations in non-pandemic conditions will help evaluate the robustness and generalizability of our findings.
Future studies could also explore related areas. We assumed telework preferences shaped by TPB factors predict job performance through increased engagement and motivation, but this remains untested. Examining this relationship across various performance outcomes—such as task proficiency, creativity, or innovation—would enrich understanding. Moreover, as attitudes toward telework strongly predict preferences, identifying additional factors influencing these attitudes (e.g., beyond reduced commuting and work-life balance) is critical. Lastly, investigating interventions to enhance TPB factors in telework contexts (e.g., socialization, training, feedback) would offer practical insights for people management.
In conclusion, this study introduces telework preferences as a key topic in telework research and organizational practice. By identifying the psychological factors driving these preferences and their implications for management, we aim to support the effective implementation of telework as an increasingly valuable work arrangement.
Data availability statement
The original contributions presented in the study are included in the article, further inquiries can be directed to the corresponding author.
Ethics statement
The studies involving humans were approved by Comité de Ética de la Facultad de Economía y Negocios, Universidad de Chile. The studies were conducted in accordance with the local legislation and institutional requirements. The participants provided their written informed consent to participate in this study.
Author contributions
PL: Conceptualization, Funding acquisition, Investigation, Supervision, Writing – original draft, Writing – review & editing. EK: Conceptualization, Investigation, Writing – original draft, Writing – review & editing. HM: Conceptualization, Formal analysis, Methodology, Supervision, Writing – original draft, Writing – review & editing. RA: Conceptualization, Data curation, Project administration, Writing – review & editing.
Funding
The author(s) declare financial support was received for the research, authorship, and/or publication of this article. This research initiative was supported by CONICYT FONDECYT 1161717 award granted to Pedro I. Leiva by National Commission of Scientific and Technological Research, Chile (CONICYT).
Conflict of interest
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
Publisher's note
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Keywords: telework, preferences, attitudes, Theory of Planned Behavior (TBP), remote work
Citation: Leiva PI, Kausel EE, Madrid HP and Alday RA (2025) Telework preference: an understanding from theory of planned behavior. Front. Organ. Psychol. 3:1431539. doi: 10.3389/forgp.2025.1431539
Received: 12 May 2024; Accepted: 16 January 2025;
Published: 06 February 2025.
Edited by:
Ron Landis, Clemson University, United StatesReviewed by:
Zhenduo Zhang, Dalian University of Technology, ChinaChristine Ipsen, Technical University of Denmark, Denmark
Copyright © 2025 Leiva, Kausel, Madrid and Alday. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: Pedro I. Leiva, cGxlaXZhbkB1bmVnb2Npb3MuY2w=