Promoting effectiveness of “working from home”: findings from Hong Kong working population under COVID-19

Ada Hiu Kan Wong (School of Graduate Studies, Lingnan University, Tuen Mun, Hong Kong)
Joyce Oiwun Cheung (School of Graduate Studies, Lingnan University, Tuen Mun, Hong Kong)
Ziguang Chen (Derby Business School, University of Derby, Derby, UK)

Asian Education and Development Studies

ISSN: 2046-3162

Article publication date: 26 October 2020

Issue publication date: 10 March 2021

8313

Abstract

Purpose

Working-from-home (WFH) practice has been adopted by many companies of a variety of industries in a diverse manner; however, it is not until the recent outbreak of the coronavirus disease 2019 (COVID-19) pandemic WFH gains worldwide popularity. With so many different views out there and based on work–family balance theory, this study aims to find out the factors which affect peoples' WFH effectiveness and whether they want the extended WFH practice when the pandemic crisis is over.

Design/methodology/approach

This paper adopted an online survey approach by posting questionnaires on the university website and different social media channels to collect views from full-time Hong Kong workers who have had WFH experience during the coronavirus outbreak. A total of 1,976 effective responses were collected for the data analysis.

Findings

The findings of this study indicate that WFH effectiveness is improved by personal and family well-being but reduced by environmental and resource constraints. When workers are experiencing higher WFH effectiveness, they have a higher preference for WFH even after the pandemic; the female workers preferred WFH twice per week, while the male workers more often preferred WFH once per week. Finally, workers from the management and the self-employed levels demonstrated a lower preference for WFH, compared to the front-line and middle-grade workers.

Originality/value

This paper fulfils to provide a timely reflection on workers' post-pandemic WFH preference, the factors affecting their WFH effectiveness and the demographic differences inducing to the differentiated preferences.

Keywords

Citation

Wong, A.H.K., Cheung, J.O. and Chen, Z. (2021), "Promoting effectiveness of “working from home”: findings from Hong Kong working population under COVID-19", Asian Education and Development Studies, Vol. 10 No. 2, pp. 210-228. https://doi.org/10.1108/AEDS-06-2020-0139

Publisher

:

Emerald Publishing Limited

Copyright © 2020, Emerald Publishing Limited


Introduction

Working from home (WFH), which is also known as home office, telework, telecommuting and flexible/agile work arrangement allows employees a certain extent of flexibility to complete their job duties at a location other than the office (e.g. home). According to the International Labour Department, WFH can be regularly based at home, highly mobile in several locations or just occasionally working outside office. Employees may work fully or occasionally a number of days from home with the same benefits of those who work in traditional office settings; alternatively, employees may work as “independent contractors” who receive neither benefits nor equipment sponsorship (International Labour Department, 2011). Since WFH has been implemented in a variety of ways (i.e. fully work from home, intermittently work from home a number of days per week and shifting duty rosters with colleagues) and has blended with other flexible work arrangements (FWAs) (e.g. flexible working hours, splitting job duties amongst colleagues, etc.), WFH is a complex organizational model which is agile and distinctive in different countries, regions and industries. Despite the various models of WFH arrangement, this research focusses on the purely WFH arrangement because this is the practice that has been widely practised worldwide during the coronavirus disease 2019 (COVID-19) pandemic. With many workers experienced WFH for several months since the pandemic, the goal of this study is to examine how WFH is being perceived by workers in Hong Kong. Specifically, this study aims at identifying factors that affect an individual's WFH effectiveness and investigating whether workers prefer to continue the WFH practice when the pandemic is over.

Work from home and the pandemic coronavirus disease 2019

In the high time of maintaining social distancing during COVID-19, many countries have imposed various degrees of WFH policies to minimize virus contraction amongst colleagues. In the USA, 34.1% of around 8,000 survey participants in Brynjolfsson et al. (2020) have switched to home office, and 37% of American jobs, according to Dingel and Neiman (2020) can be conducted at home (e.g. finance, corporate management, professional and scientific services). However, Dingel and Neiman (2020) pointed out that jobs like agriculture, hospitality and retail are unlikely possible to be completed at home. In fact, Baker (2020) found that 75% American workers (usually in healthcare, manufacturing, retail and food catering) cannot work at home, while only 25% (usually in technology, computer, management, administration, finance and engineering) can do so. Companies which were hit hard by the isolation or failed to adapt to WFH arrangement were forced to shut down, lay-off or put employees on furlough. Brynjolfsson et al. (2020) estimated that 16 m Americans are hence out of work; worse still, Kahn et al. (2020) concluded that job vacancies have contracted in all sectors except nursing and food-selling retail. In China, Zhang et al. (2020) observed a slightly higher rate of WFH – 38% have worked from home. That said, 25% also ceased working. This brought huge physiological and mental impact on people in both countries. Unlike the statutory isolation imposed by the Chinese Government, Zhong (2020) noted that the neighbouring country Japan only set up a Telework Comprehensive Portal Site which offered citizens information and a discussion platform that WFH is purely voluntary. Compared to the USA, China and Japan, much stricter policies have been in place in Belgium. According to de Baker (2020), the Belgium Ministerial decree on March 18, 2020, stipulated that all non-essential jobs (i.e. jobs other than ministers, hospitals, elderly homes, universities, media, police and military forces, courts and tribunals, legal professions and food sellers) shall either switch to home office or maintain 1.5 m distancing between staff members. Violators were forced to shut down. Different extent of isolation polices (which ultimately led to the emergent adaptation of WFH in companies) may be due to various factors. Dingel and Neiman (2020) found a positive correlation between a country's income level and the number of jobs that can be completed at home. While Mexico and Turkey have less than 25% WFH-able job share, Sweden and the UK have more than 40%. In short, the wealthier a country, the more likely WFH can take place in it.

Work from home pros and cons

In replacement of or blending with the traditional office setting, WFH arrangement has been highly praised for some benefits and criticized for some shortcomings. Martin and MacDonnell (2012) found that WFH helps boost productivity, retain employees and enhance their commitment and performance. Other benefits include emission reduction (due to reduction in commute), office cost reduction and work–family balance (Guyot and Sawhill, 2020), increased efficiency and lower burnout risk (Baert et al., 2020), positive influence on the speed and quality of the development of new products (Coenen and Kok, 2014). That said, Baert et al. (2020) also found that WFH employees worried about weakening colleague relationship and diminishing promotion opportunities or negative career development (Guyot and Sawhill, 2020; Maruyama and Tietze, 2012). This sets against the general belief that career advancement (often in the form of job promotion and increments) is dependent on strong colleague/supervisor recommendations. When employees WFH, it is unclear, to their mind, how they can display their commitment, competence and performance without face-to-face interactions. Due to the distinctive natures, highly paid professional occupations (such as the aforementioned technology and management jobs) are more likely WFH-able (Guyot and Sawhill, 2020; Saltiel, 2020); due to the age stratification, 60–69 years old workers in the UK are usually in the front line and prone to risks (Glynn, 2020) that Ichino et al. (2020) proposed sending the older workforce to work at home, while attracting the younger cohort (20–49 years old) to voluntarily resume work to sustain economy. Some vulnerable groups like the young, the least educated and minorities (Bell and Blanchflower, 2020) or working mothers (Alon et al., 2020) probably work in industries which does not allow WFH, inducing to dissatisfaction over the “telework divide” (Mahler, 2012). Telework divide is a term which describes the widening opportunity gap between people whose job nature allows WFH and those whose not. Since a universal WFH plan which is applicable to every industry sector may not be feasible, granting more jobs freedom to WFH will inevitably erode the existing injustice that some front-line employees are left with little to no choices at all. Apart from the worries over promotion, colleague relation and vulnerable groups, some research pinpointed the potential problem of many companies being unprepared for handling WFH cybersecurity and data protection (Ahmad, 2020; Belzunegui-Eraso and Erro-Garcés, 2020; Martins, 2020). For example, many employees working from home connect to domestic broadband network, but the security of data encryption and spam filtering may not be on par with that of company servers. Both employers and employees worry about information leakage, especially those in the commercial and public service sectors. Security also concerns safety issues since employees are not working in the employers' premises (Erikson, 2020); in other words, employees' safety measures can hardly be monitored unless being surveilled. Last but not least, Weinert et al. (2015) pointed out that WFH employees may experience “telework exhaustion” related to information, autonomy and isolation. Employees need to stand by and handle ad hoc duties; meanwhile, they may lack sufficient support such as instruction, feedback and social interaction. These problems should be carefully solved in order to ensure effective WFH practice.

Work-from-home (WFH) suggestions by extant research

In Baert et al. (2020), 85% of the Flemish Belgium participants believed that WFH will persist in the post-pandemic era; Guyot and Sawhill (2020) also predicted that WFH will continue as the home working habit has been established. In order to facilitate WFH, Gálvez, Martínez and Pérez (2012) warned that mutual trust must exist between employers and WFH employees to avoid conflicts and that companies must have the organizational commitment to sustain WFH (Hunton and Norman, 2010). Instead of a full swing of WFH arrangement, Coenen and Kok (2014) found that basic face-to-face contact is necessary to remediate the disadvantages mentioned above. Therefore, learned from the success in Australia, Bosua et al. (2012) suggested a hybrid work arrangement which requires employees to work one to two days from home each week. Based on trust, employers and employees would reach agreement on individual and team deliverables as well as the provision of information technology (IT) equipment. Bosua et al. (2012) believed the hybrid model empowers the employees by giving them control over their work and families, an undisturbed work environment, work–life balance and a positive vibe. This hybrid model was also recommended by Sewell and Taskin (2015) and Vega et al. (2015), in which the latter spot better job performance, satisfaction and creation amongst 180 US Government employees who work from home on an average of 2.13 days per week. Finally, del Rio-Chanona et al. (2020) proposed a remote work index (RWI) calculating the likelihood of remote working based on 740 occupations listed on the O*NET work activity list. An RWI close to 1 indicates high remoteness, while an RWI close to 0 means low remoteness. Employers can utilize the index to decide how likely a job can be done at home.

Work–family balance and the effectiveness of working from home

Work–family balance is defined as “accomplishment of role-related expectations that are negotiated and shared between an individual and his or her role-related partners in the work and family domains” (Grzywacz and Carlson, 2007, p. 458). Helping workers to improve their work–life or work–family balance is increasingly viewed as a centric benefit from the successful implementation of WFH practice. Work–family balance theory has received a lot of attention from the human resources literature, with ample potential benefits proposed or identified such as helping to attract and retain talents (US Department of Labor, 1999), enhancing organizational commitment and job satisfaction (Allen et al., 2000; Aryee et al., 2005; Carlson et al., 2009), reducing turnover intention (Allen et al., 2000), improving individual health and well-being (Frone, 2000; Grzywacz and Bass, 2003), reducing sickness absence (Jansen et al., 2006), fostering greater organizational citizenship behaviour (Bragger et al., 2005) and improving employees’ performance (Allen et al., 2000; Kossek and Ozeki, 1999). Regardless of the abundant benefits reported, WFH has yet to be a common option for employees as a way to improve work–family balance. One of the possible reasons is that employers worry about employees’ performance if allowing them to WFH, especially in the Asian context which emphasizes on the traditional physical attendance (Fung, 2019). As such, this study explores the factors that contribute to work effectiveness when WFH.

Factors affecting working-from-home effectiveness

Referring to work–family balance (Carlson et al., 2009) and role theories (Grzywacz and Carlson, 2007), the option of WFH will likely reduce an individual's role conflict in performing different roles in a more flexible manner. Hence, WFH will reasonably result in several personal and family well-being-related benefits. Nonetheless, WFH also comes with various problems as reported in recent studies, such as the limited office supplies, restricted access to company's internal files, reduced communication quality, etc. A total of three broad themes of factors were identified to affect WFH effectiveness, a summary of which is provided in Table 1. Accordingly, this study hypothesizes that

H1.

Personal and family well-being is positively related to WFH effectiveness.

H2.

Environmental constraint is negatively related to WFH effectiveness.

H3.

Resource constraint is negatively related to WFH effectiveness.

Work-from-home pre-pandemic policies

Although WFH is no stranger to some commonwealth countries like the UK, Australia and Canada and some Scandinavian countries like The Netherlands and Finland, it is still a novel concept to many countries and cities. Take Hong Kong as an example – back in the late 1990s – the Planning Department already conducted a survey enquiring people's willingness to adopt WFH practice. However, less than 10% preferred WFH (Study on the Propensity for Office Decentralisation and the Formulation of an Office Land Development

Strategy [OLDS]) and only 0.3% companies adopted the said practice (Second Survey to Ascertain the Parameters for Forecasting Employment Distribution [SAPFED II]). Baruch and Yuen (2000) found negative reception of WFH in terms of both company and self-interests. In HK2030 study, Planning Department (2002) concluded that clients back then had no confidence in home business. Since then, the Hong Kong Government has not publicized any WFH-related surveys or guidelines. The closest information is the “Five-day work week” and “Flexitime” leaflets released by the Labour Department (2017) which promotes five-day work week and flexitime (i.e. flexible working hours). By adopting five-day work week, employees work five days and take two days leave per week. Employers and employees can decide on taking leaves on weekdays or weekends, depending on the corporates' operation need. On top of this, under the flexitime suggestion, employers can set up a core working hours and let employees flexibly work on the non-core hours as long as the total number of work hours remains the same. Although Hong Kong employers and employees are now familiar with five-day work week and flexitime, moving the workplace to home is still a novel concept. Recent surveys summarized Hong Kong people's concerns over WFH, such as technostress (Leung, 2016; Recruit May 29, 2020) and limited access to internal resources (Fastlane April 29, 2020), work–family conflict (Leung, 2016) and particularly the interruptions from children (Recruit May 29, 2020), lower productivity (Choi March 26, 2020; Morgan McKinley, 2020; Randstad, 2020; Recruit May 29, 2020), as well as being less respected (Chan July 4, 2020) due to the bad impression of non-commitment (Fung, 2019) and mistrust (Recruit May 29, 2020). Multinational incorporates like Adidas were chosen by the Labour Department (2009) as exemplars to share their WFH management decision based on individual employee's reason, department, work type, service years, maturity and self-discipline; Adidas also shared the use of key performance indicators (KPIs) to monitor the output based on schedule, progress and instructions and provided WFH employees with secure laptops to avoid information leakage. Besides, HSBC and Sanofi are two more companies which stories exemplified that their employees can apply for and discuss with supervisors their options of WFH (e.g. WFH or job sharing by two or more people) (Labour Department, 2015). Having said that we argue that the Hong Kong Government has yet officially endorsed WFH.

Japan is similar to Hong Kong that WFH was briefly mentioned under the aspect of “family friendliness” of their work–life balance charter (“Shigoto to seikatsu no chouwa (waaku raifu baransu) kenshou”) (Japan Institute for Labour Policy and Training, 2013), while Taiwan made no mention of any WFH policies except flexible work hours in the Article 30 of the Labour Standards Act (Ministry of Labor Republic of China (Taiwan), 2018). Taking one step forward is the non-statutory guidelines set up by Singapore: the Tripartite Standards specified that, under the (Singapore) FWAs, employers can adjust three types of arrangements (i.e. flexi-load (full-/part-time), flexi-time (staggered/compressed hours) and flexi-place). In view of flexi-place, which is equivalent to remote/home office, employers can refer to the Singapore FWA templates to discuss with employees the number of work hours, tasks, communicative tools, expenditures, appraisal parameters, monitor frequency and take-home resources, etc. (Tripartite Alliance for Fair and Progressive Employment Practices, n.d.). Still, WFH agreement is not protected by law in Singapore. The Ireland Government officially made WFH an essential feature of its Smarter Travel 2007 initiative which aims at reducing or eliminating the daily commute to workplace and the pollution. However, as Hynes (2014) and Hynes (2016) criticized, WFH has not been received well not because of the lack of official endorsement but for the official failure in legitimatizing the benefits and introducing the seamless incorporation of WFH. WFH is much better received in Australia, where statutory law guarantees the legitimacy of WFH, though coming with great restrictions. According to the Fair Work Ombusman (n.d.) – under the (Australia) Fair Works Act – FWAs, individuals who are parents, caregivers, disabled, aged 55 years or above, victims of domestic violence and caregivers of family members are eligible to request WFH, after which the employers are bound to reach an agreement on the work hours, work patterns and work locations in 21 days. However, employees other than the said categories are not entitled to such request power. Their counterparts in the UK, The Netherlands and Canada can apply for WFH if so they wish. The UK Government stipulates that employees, regardless of background, can write to request for flexible work in terms of WFH and their employers must write back to reach an agreement within three months. Employees reserve the right to lodge complaints to the employment tribunals (Gov.uk, n.d.). A similar practice is guaranteed in Canada that, under the Canada Labour Code, employees can freely write to request changes on working locations and the employers must reply with an approval or denial. Employees can also appeal cases to the Canadian Industrial Relations Board (Government of Canada, 2019). Better yet, since 2016, employees in The Netherlands can resort to the Flexible Working Hours Act to request changes on their working locations, upon which their employers must agree unless business interests will be threatened (Loyens and Loeff, 2015). Ultimately, Finland is one of the most WFH-friendly countries where, under the New Working Hours Act effective in 2020, employees can decide at least half of the working hours and the corresponding work locations on their own (Nevalainen and Toivonen, 2019).

Working-from-home effectiveness and post-pandemic working-from-home preference

Many governments announced various levels of isolation measures in wake of the coronavirus outbreak, which encouraged employers to allow employees to WFH. This large-scale “WFH trial run” allows both employees and employers to experience both the pros and cons brought by WFH. This is hypothesized that individuals who achieved better WFH effectiveness will more likely desire an extension of WFH option as a normal job practice. Not only would they require an option of WFH but also a longer duration of WFH per week, when the COVID-19 pandemic is over. Hence,

H4.

WFH effectiveness is positively related to post-pandemic WFH preference.

According to Maruyama and Tietze (2012), female teleworkers exceptionally benefited from WFH in which they can cope with caring responsibilities at home. For family-oriented female workers, they may face role conflicts resulting from the different roles that they play (e.g. a mother at home versus a supervisor at work) according to role theory (Grzywacz and Carlson, 2007). To reduce the role conflicts, an individual may try to achieve work–family balance by engaging in ongoing, flexible role-related negotiations (e.g. discussion with the company about flexible work arrangement). As such, we assumed that female workers are more likely to have a greater WFH preference than their male colleagues when the COVID-19 pandemic is over. Hence, we hypothesize that

H5.

Female workers hold a greater post-pandemic WFH preference than their male counterparts.

The research methodology

The sample and procedure

An online survey questionnaire was developed and posted on the university website to collect views from full-time Hong Kong workers who have had WFH experience during the coronavirus outbreak. Invitation to join the survey was extended to the public via different social media channels. Data collection was done between 8 Apr 2020 and 26 April 2020. A total of 2,573 questionnaires were collected, with 1,976 (i.e. 76.8%) effective responses for the data analysis. All these respondents indicated that they had a full-time job at the time they completed the survey and had WFH experience during the COVID-19 pandemic.

Measures

Question items were developed based on a review on a wide range of literature (e.g. academic papers, industry reports, newspaper commentaries, etc.). Hence, question items are not sourced from factors reported in Table 1, which only summarizes a selected number of studies. All measures in this study used a five-point Likert scale, where 1 = “strongly disagree” and 5 = “strongly agree”, unless otherwise indicated. The composite measures for each variable were the average of all items of the construct, except for “Resource constraint”, whose composite score was the sum of its items (i.e. this is a formative scale).

Personal and family well-being was measured by a six-item scale that captures various benefits of WFH. WFH effectiveness was assessed by a three-item scale that describes various work efficiency and effectiveness conditions. For items of these two constructs, respondents were asked to indicate their agreement to each of the statements about WFH benefits, compared to working at office.

Environmental constraint was assessed by a five-item scale that captures the commonly known challenges of WFH. For these two constraint factors, respondents were asked “as compared to working at office, do you find the following a challenge when WFH?” Items were initially scored as 1 = “Yes”, 2 = “No” and 3 = “Neutral”. To match the other five-point scale measures in this study, these items were recorded to a five-point scale as 1.5 = “No”, 3 = “Neutral” and 4.5 = “Yes”.

Resource constraint was measured by a two-item formative scale (not reflective scale); hence, the composite score of this scale was the sum of the two items but not their average.

Before testing our hypotheses, we conducted an exploratory factor analysis (EFA) to see whether the underlying factor structure matches our theoretical model as shown in Figure 1. In this study, we test two models as shown in Figure 1. There are four variables in model 1, namely, personal and family well-being, environmental and resource constraints and WFH effectiveness, while there are three variables in model 2, namely, WFH effectiveness (this is the same as in model 1), gender and WFH preference. Since gender is a categorical variable and WFH preference is a single-item measured variable, we conducted the EFA employing the principal component analysis by using Varimax rotation (Gerbing and Anderson, 1988) on the above-mentioned measure items of the four variables in model 1. As a result, four factors were generated with eigenvalues exceeding 1. The suitability of this approach was supported by a sufficiently high Kaiser-Meyer-Olkin (KMO) value of 0.89 and a statistically significant Bartlett's result. The four-factor structure matched our theoretical models as presented in Figure 1, which means that all variables loaded substantially on their relevant components. Loadings on other components in no case exceeded 0.38, indicating that the measurement procedures used were sufficiently discriminating. Table 2 shows the results of this EFA. We used an unweighted index to calculate the four variables' scores.

Respondents were asked to indicate their gender by selecting 1 = “Male” and 2 = “Female”. Another dependent variable in this study was WFH preference, which was assessed by asking the respondents, “when the current coronavirus crisis is over, would you still want to continue working from home?” Choice options include 1 = “No”, 2 = “Yes, once a week”, 3 = “Yes, twice a week” and 4 = “Yes, 3 days or more a week”.

Control variables include gender (except in conceptual model 2), age, marital and residential status (living alone or with others) and job position. These variables were included in the data analysis to reduce spurious effects owing to the potential influence of demographic characteristics.

Descriptive statistics are provided in Table 3, the general demographic characteristics of respondents are presented in Table 4 and interconstruct correlations of key variables are provided in Table 5.

Results

What factors impact the effectiveness of WFH? The regression analysis was performed to test H1 to H3 in this study (Table 6). Results revealed that a total of 37% of variance of WFH effectiveness was explained by the three independent variables, namely, personal and family well-being (H1), environmental constraint (H2) and resource constraint (H3). Specifically, personal and family well-being shows greatest positive effect (β = 0.48, p < 0.01) on WFH effectiveness, followed by moderate negative effect by environmental constraint (β = −0.18, p < 0.01) and a small but statistically significant effect by resource constraint (β= −0.03, p < 0.01). Hence, all H1H3 are supported. The moderated regression analysis was performed for each of the control variables (i.e. gender, age, marital status, job position and residential status) to explore the potential moderation effect but no statistically significant result was identified. Such results suggest that the relationships between all the three independent variables (IVs) and WFH effectiveness are robust, regardless of different demographic characteristics.

While many of the working people were either forced or encouraged to WFH, is the WFH practice still preferred by the working class even after the pandemic? Table 7 shows the breakdown of preference indicated by the respondents. A majority of respondents (35.6%) indicated that they prefer to continue to WFH twice a week, followed by 29.7% who want to WFH once a week. Only 16.3% respondents indicated a post-pandemic WFH preference of three days or more a week. Amongst the WFH options, 18.4% respondents indicated that they do not want to continue the WFH arrangement after the pandemic. In a word, majority of Hong Kong workers (65.3%) preferred to WFH one to two days per week.

Who would have a greater preference of WFH when the current COVID-19 pandemic is over? Another regression analysis was performed to explore the effects of WFH effectiveness and gender on WFH preference. As shown in Table 8, when the three IVs (i.e. personal and family well-being, environmental and resource constraints) of WFH effectiveness were controlled for analysis, WFH effectiveness (H4) and gender (H5) together explained 3% of variance, with the whole model explaining 29.5% of variance in post-pandemic WFH preference. A greater positive effect of WFH effectiveness was observed (β = 0.24, p < 0.01) on WFH preference, compared to gender difference (β = 0.08, p < 0.05). To further explore the effect of gender on post-pandemic WFH preference, independent sample t-test was performed. Results indicate that there was a significant difference in the scores for male (M = 2.43, SD = 0.99) and female (M = 2.53, SD = 0.96); t (1974) = −2.00, p = 0.046. These results suggest that female workers slightly more often preferred to WFH for two days per week, while the male workers slightly more often preferred to WFH for one day per week. Hence, H4 and H5 are supported.

Post hoc analyses

As identified from the regression analysis results in Table 8, age regressed negatively on WFH preference (β = −0.08, p < 0.01), meaning that younger age group has a higher preference to WFH when compared to the older age group. Another interesting finding is that workers from the management and the self-employed levels demonstrated a lower preference to WFH, compared to the front-line and middle grade workers. Such observation is supported by the significant difference in the scores for “frontline and middle grade” group (M = 2.52, SD = 0.96) and “management and self-employed” group (M = 2.30, SD = 1.07); t (1965) = 2.96, p = 0.003.

Conclusion and implications

Based on the data collected from 1,976 Hong Kong working people, we conclude that WFH effectiveness is improved by the personal and family well-being, as a benefit of WFH. However, environmental and resource constraints would reduce the effectiveness of WFH. Furthermore, when workers are experiencing higher WFH effectiveness, they have a higher preference on WFH arrangement even after the pandemic. Such preference is also higher amongst female workers, as compared to their male colleagues. Front-line and middle grade workers also showed higher preference to WFH compared to the management level workers and self-employed people. These findings have implications for both researchers and managers.

Implications for researchers

Research findings are consistent with work–family balance and role theories, which suggest that achieving work–family balance would help reduce the role conflict and improve well-being, which then enhances job performance. In this study, personal and family well-being was found to enhance the effectiveness of WFH. These findings contribute to the work–family balance and role theory literature by providing empirical evidence of the benefits of WFH (as a way to achieve work–family balance and reduce role conflict) and its positive effect on WFH effectiveness. WFH arrangement allows an individual to quickly switch between different roles (the role at work versus that in family), workers can therefore fulfil their different role-related expectations relatively easier and quicker than working at office. The convenience in role switching not only improves personal and family well-being but is also found to improve WFH effectiveness in this study.

Another contribution to the literature is the gender effect on post-pandemic WFH preference. Consistent with Maruyama and Tietze's (2012) study, which found that female teleworkers exceptionally benefited from WFH in which they can cope with caring responsibilities at home, the present study also shows that female showed a higher preference to WFH than male did. Specifically, female workers showed a greater preference to WFH for two days a week, while male workers were slightly more inclined to WFH for one day per week. Such findings shed light on the characteristics of Asian society that female is more family oriented than male, even with a lot of female workers participating in the workforce in the modern society today.

Implications for managers

The literature suggests that it is important for an organization to design and implement work–family balance strategies, as a way to attract and retain talents (Martin and MacDonnell, 2012). Our findings indicated that an individual who perceives greater personal and family well-being as a result of WFH would have higher WFH effectiveness, which in turn increases post-pandemic WFH preference.

Although management and self-employed persons showed lower preference to WFH after the COVID-19 crisis, managers are suggested to note the trend of having WFH as an HR strategy to attract and retain talents. Specifically, this is observed from this study that female and younger workers have a higher preference for WFH. Hence, having WFH as an option, in particular allowing a worker to WFH from one to two days per week, should be helpful for a company to attract and retain female or younger generation workers.

Our findings also confirmed that this is important for a company to provide hardware and software support to workers to improve their WFH effectiveness. Examples include providing cash allowance for purchasing IT equipment or office supplies, lending out IT equipment to employers when they are WFH, strengthening IT software and network support, using software that facilitates communications amongst colleagues, improving accessibility to internal network drives via secured online platforms, etc. Such findings echo those reported in previous studies about the difficulties of WFH in the Hong Kong context (e.g. Fastlane, 2020; Leung, 2016; Recruit, 2020).

It is surprising to find that managers and self-employed less preferred WFH, compared to the front-line and middle-grade workers. Mistrust has been identified as one of the key factors that discourage WFH practices' implementation (Recruit, 2020); therefore, it is important for the HR department to do something to strategically change the mindset of the senior management and get their support on the implementation of WFH arrangement as a way to promote work–family balance of employees. Referring to Gálvez, Martínez and Pérez (2012), organizing activities to build mutual trust between senior management and their subordinates would also help facilitate the implementation of WFH practice.

Limitations and future research

Our study, like any other, is not without limitations. First, the scales for measuring each of the concepts were developed based on their logicality and results of EFA, which lends support to scale discriminant and convergent validity. Scale reliability of each scale was also checked and respective Cronbach's alpha passed the recommended threshold of 0.70. However, it would be better for future studies to adopt well-developed scales to key concepts like “well-being” or “work-family balance” to examine its potential effects on WFH effectiveness.

Second, in addition to WFH effectiveness, more variables shall be investigated in future studies about the potential benefits of WFH. Organizational-level benefits of WFH have received very little attention in the literature which should be explored in future studies. Findings of such should help promote WFH and other work–family balance practice amongst managers, so as to seek their support on the implementation of such HR policies.

Third, the findings of this study show the clear voices of employees that they prefer to have the WFH option even after the pandemic. However, this is equally clear that the senior management takes the opposite stand. It is therefore critically important for future research to investigate for the ways to deal with the worries of the senior management. Common examples of worries about WFH include lower productivity (Choi, 2020; Morgan McKinley, 2020; Randstad, 2020; Recruit, 2020), bad impression of non-commitment (Fung, 2019), lack of IT support (Erikson, 2020), etc. All these require further investigation to offer practical solutions that facilitate WFH arrangement.

Finally, the cross-sectional design limits the ability to draw firm conclusions on the causal relationships studied. Is it possible that WFH effectiveness will be diminished with a longer WFH duration per week? Or would it be strengthened as an employee gained a certain period of WFH experience? Would WFH preference be changed after an individual is promoted to a more senior position? What is the optimal WFH duration for the best job performance? Future study using a longitudinal research design may offer insights into the above-mentioned questions and provide further theoretical and practical suggestions for effective implementation of WFH policies.

Figures

Conceptual models of this study

Figure 1

Conceptual models of this study

Three themes of factors contributing to working-from-home effectiveness

StudyContext (industry)Sample sizeContributing factors
Baruch and Yuen (2000)Hong Kong and the UK (small companies)36 Hong Kong and 38 the UK
  • (1)Flexible working hours (A)

Chen and McDonald (2014)The USA (networked workers)703
  • (1)Perceived benefits of information and communication technology (C)

Choi (2020)Hong Kong300
  • (1)Dedicated workspace (B)

  • (2)Take a break (A)

  • (3)Cybersecurity (C)

Fastlane (2020)Hong Kong (SMEs)200
  • (1)Access to internal documents and communication tools (C)

Fonner and Roloff (2010)No mention192
  • (1)Less work–life conflict (A)

Maruyama and Tietze (2012)The UK (British Telecommuincations PLC)394
  • (1)Female more likely find WFH beneficial to caring responsibilities (A)

Recruit (2020)Hong Kong313
  • (1)Companies provide laptops and software (C)

  • (2)Companies allow remote desktop control (C)

Sardeshmukh et al. (2012)The USA (supply chain management company)417
  • (1)Clear job description (B)

  • (2)Clear communication (B)

  • (3)Feedback (B)

Sun Life Hong Kong (2020)Hong Kong810
  • (1)Regular communication (B)

  • (2)Online gathering (B)

Valmohammadi (2012)Iran (28 state-owned organizations)190
  • (1)IT infrastructure (C)

Weinert et al. (2015)No mention310
  • (1)Information undersupply (B)

  • (2)Autonomy (A)

Note(s): A: well-being factor; B: environmental factor; C: office resource factor

Reliability and factor analyses for main constructs

ItemsCronbach's alphaItem-to-total correlation
Personal and family well-being0.89
Reduce work stress 0.67
Get more time to rest 0.85
Get more time to exercise 0.77
Improve work–life balance 0.80
Bring a better quality of life 0.84
Maintain a better relationship with family members 0.66
Environmental constraint0.75
Lack of working space at home 0.59
Can not communicate timely with colleagues 0.57
Easily disturbed by family members, children or others who live together during work 0.85
Easily distracted by household chores during work 0.83
Resource constraint*0.67
Lack of office hardware 0.82
Lack of office software 0.84
WFH effectiveness0.81
Achieve better concentration 0.85
Improve work efficiency 0.84
Get more time to work 0.65

Note(s): *This is a formative, instead of a reflective scale. Its Cronbach's alpha is for reporting purpose only

Descriptive statistics

VariablesMinimumMaximumMeanStd. deviation
Control variables
Gender121.680.47
Age173.561.01
Marital status131.460.53
Residential status163.471.00
Job position151.630.78
Independent variables
Well-being1.005.003.550.84
Environmental constraint1.504.503.411.00
Resource constraint3.009.007.082.29
Dependent variables
Work efficiency1.005.003.060.86
Work-from- home preference142.500.97

Demographic information of respondents

ItemsCountPercentage
Gender
Male63832.3
Female1,33867.7
Age
Below 18 years50.3
18–25 years23812.0
26–35 years78939.9
36–45 years62931.8
46–55 years22911.6
56–65 years773.9
66 years or above90.5
Marital status
Single1,09955.6
Married85043.0
Single parent271.4
Job position
Front-line or basic level1,01051.1
Middle grade76938.9
Management1226.2
Self-employed663.3
Others90.5
Residential status
Alone874.4
With friends321.6
With family1,15158.2
With spouse but no children27914.1
With spouse, children and/or family member(s)42121.3
Others60.3
Company type
Government21410.8
Public bodies including hospitals and schools52726.7
Private enterprise80240.6
Small and medium enterprises32516.4
Self-employed693.5
Others392.0

The correlation matrix

MeanSD12345678910
1. Gender1.680.471.00
2. Age3.561.01−0.07**1.00
3. Marital status1.460.53−0.06**0.43**1.00
4. Residential status3.471.00−0.040.27**0.61**1.00
5. Job position1.630.78−0.07**0.21**0.16**0.08**1.00
6. Personal and family well-being3.550.840.01−0.04−0.020.02−0.031.00
7. Environmental constraint3.411.00−0.030.030.030.09**−0.04−0.35**1.00
8. Resource constraint7.082.290.03−0.01−0.07**−0.04−0.09**−0.16**0.44**1.00
9. WFH efficiency3.060.86−0.01−0.05*−0.05*−0.07**−0.010.56**−0.41**−0.25**1.00
10. WFH preference2.500.970.05*−0.10**−0.02−0.00−0.020.49**−0.30**−0.20**0.44**1.00

Note(s): n = 1,976, *p < 0.05, **p < 0.01 ( two-tailed)

Regression results for working-from-home effectiveness

Model 1Model 2
Constant3.37 (0.12)2.44 (0.14)
Control variables
Gender−0.03 (0.04)−0.04 (0.03)
Age−0.03 (0.02)−0.01 (0.02)
Marital status0.00 (0.05)−0.01 (0.04)
Residential status−0.05 (0.03)*−0.05 (0.02)*
Job position−0.00 (0.03)−0.01 (0.02)
Independent variables
Well-being 0.48 (0.02)**
Environmental constraint −0.18 (0.02)**
Resource constraint −0.03 (0.01)**
Adjusted R20.000.37
F2.15147.16
ΔF significance0.060.00

Note(s): Unstandardized coefficients are shown with standard errors in parentheses; n = 1,976, *p < 0.05, **p < 0.01 ( two-tailed)

Post-pandemic working-from-home preference (n = 1,976)

Question: when the current coronavirus crisis is over, would you still want to continue working from home?CountPercentage
No36418.4
Yes, once a week58729.7
Yes, twice a week70335.6
Yes, three days or more a week32216.3

Regression results for working-from-home preference

Model 1Model 2
Constant1.56 (0.16)0.83 (0.18)
Control variables
Age−0.08 (0.02)**−0.08 (0.02)**
Marital status0.04 (0.05)0.04 (0.05)
Residential status0.01 (0.02)0.02 (0.02)
Job position−0.00 (0.03)0.00 (0.02)
Well-being0.50 (0.02)**0.38 (0.03)**
Environmental constraint−0.11 (0.02)**−0.06 (0.02)**
Resource constraint−0.04 (0.01)**−0.03 (0.01)**
Independent variables
Gender 0.08 (0.04)*
Work efficiency 0.24 (0.03)**
Adjusted R20.270.30
F103.1393.01
ΔF significance0.000.00

Note(s): Unstandardized coefficients are shown with standard errors in parentheses; n = 1,976, *p < 0.05, **p < 0.01 ( two-tailed)

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Further reading

Mercer (n.d.), “Prevailing from Coronavirus (COVID-19): coronavirus response survey results”, available at: https://www.mercer.com.hk/our-thinking/healthy-people-healthy-business/prevailing-from-covid19.html.

Ming Pao Finance (2020), Sun Life Survey: 80% Employees Feel Happier for Meeting Supervisors Less Often, (in Chinese). available at: https://www.mpfinance.com/fin/instantf2.php?node=1589959795709&issue=20200520.

The Standard (2020), “Working from home a favored choice, survey says”, available at: https://www.thestandard.com.hk/breaking-news/section/2/147654/Working-from-home-a-favored-choice,-survey-says.

Corresponding author

Ada Hiu Kan Wong can be contacted at: adawong@Ln.edu.hk

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