SAJHRM SA Journal of Human Resource Management 1683-7584 2071-078X AOSIS SAJHRM-20-1693 10.4102/sajhrm.v20i0.1693 Original Research Flexible work options in higher educational institutions in times of crisis https://orcid.org/0000-0001-9364-3774 Atiku Sulaiman O. 1 https://orcid.org/0000-0002-7690-7886 Ganiyu Idris O. 2 Harold Pupkewitz Graduate School of Business, Namibia University of Science and Technology, Windhoek, Namibia Discipline of Human Resource Management, School of Management, IT and Governance, College of Law and Management, University of KwaZulu-Natal, Durban, South Africa Corresponding author: Idris Ganiyu, ganiyui@ukzn.ac.za 03082022 2022 20 1693 05062021 21092021 © 2022. The Authors 2022 Licensee: AOSIS. This work is licensed under the Creative Commons Attribution License. Orientation

The association between academic staff position and attitudes towards specific flexible work options in times of crisis.

 Research purpose

This study examined employees’ perceptions towards flexible work options in times of crisis in institutions of higher learning operating in Namibia.

 Motivation for the study

Despite the wide-ranging studies that have examined attitudes towards flexible work options in many organisations, little is known about attitudes towards flexible work options in higher education institutions in times of crisis.

 Research approach/design and method

This study adopted a cross-sectional survey following a quantitative approach, using a structured questionnaire to gather information from the participants. The target population (956) of this study comprised academics and administrative staff working in the participating institutions. Data were analysed from a sample of 465 respondents using the Chi-square test of independence and the Mann–Whitney U test to test the research hypotheses.

 Main findings

Results show that academic staff position is positively associated with attitudes towards specific flexible work options in times of crisis. Findings further indicate a significant association between gender and attitudes towards ‘early start-normal go, then Friday afternoon off’.

 Practical/managerial implications

Insights from the research findings could be used to improve the implementation of flexible work options in the post-pandemic period.

 Contribution/value-add

The study offers a perspective on the attitudes towards flexible work options in higher education institutions during a pandemic.

 attitudes flexible work options flexi-time options gender higher education institutions COVID-19 pandemic Introduction

The coronavirus disease (COVID-19) emerged in Wuhan, China, in late 2019 (Tirumalaraju, 2020). As a result of the global footprint of the virus in 2020, the World Health Organization (WHO) declared the COVID-19 outbreak as a pandemic. The COVID-19 could be adjudged as the worst pandemic and health crisis witnessed in the first three decades of the 21st century (Burgess & Sievertsen, 2020). The emergence of the global health crisis, otherwise referred to as COVID-19, resulted in the disruption of work with most global economies forced into total or partial lockdown to break the chain of transmission thereby curtailing the spread of the pandemic. The global lockdown was informed by the safety precautions outlined by WHO (Karatayev, Anand, & Bauch, 2020). The regulatory disruption by many governments across the globe to curtail the spread of COVID-19 led to an economic crisis. The major crisis associated with COVID-19 is health and economic crises. Many businesses and educational institutions had no other option than to adjust their operations to militate against the COVID-19 impact (Karatayev et al., 2020; Verma et al., 2020). The disruption in work implies that only businesses that provided essential services were allowed to continue to operate from their physical location, whilst non-essential businesses went into lockdown in compliance with the social distancing regulation of government. The global lockdown forced many businesses to adopt flexible work options to stay afloat. ‘Flexibility’ refers to the measures put in place by employers for the employees to determine where and when to carry out job responsibilities (Allen, Johnson, Kiburz, & Shockley, 2013). Therefore, flexible work options refer to the human resource management strategy aimed at helping organisations to cushion the adverse effect of environmental uncertainties by adopting variation on where and when job roles are performed (Ganiyu, 2021; Giannikis & Mihail, 2011; Weideman & Hofmeyr, 2020).

Before the emergence of COVID-19, flexible work options were adopted by organisations as work–life balance strategies to help employees cope with work and family stressors (Ganiyu, Fields, Atiku, & Derera, 2020; Voudouris, 2004; Weideman & Hofmeyr, 2020). Using flexible work options as work–life balance strategies enable organisations to retain and attract a high performing workforce. Previous studies have examined the relationship between flexible work options and constructs such as employee productivity, employee commitment, employee engagement, and organisational outcomes (Azar, Khan, & Van Eerde, 2018; Choi, 2018; Giannikis & Mihail, 2011). However, the global lockdown brought about a shift in focus as flexible work options are being adopted by many organisations and institutions of higher learning globally as an intervention strategy in compliance with lockdown regulations rather than a work–life balance strategy. Higher education institutions across the globe were affected by the pandemic because of the lockdown of universities. The lockdown led to the transition from the traditional face-to-face modes of delivery to online teaching and learning approaches and providing academic support to students through virtual interaction. Consequently, the use of technology for teaching and learning became essential for the advancement of academic activities across the globe during the crisis. There is a dearth of empirical studies on the use of flexible work options in times of crisis in institutions of higher learning in Namibia. Hence, it becomes imperative to provide empirical evidence on attitudes towards flexitime options in higher education institutions in times of crisis in Namibia. Therefore, this study examines employees’ perceptions towards flexible work options in times of crisis in institutions of higher learning operating in Namibia.

 Literature review Flexible work options

The global lockdown as a result of the COVID-19 pandemic has stirred up unavoidable debate about flexible work options. Managements of higher education institutions have realised that the adoption of appropriate flexible work options for different cadres of academic and non-academic staff could be an effective tool to remedy the adverse effect of the pandemic or lockdown on the educational system. Therefore, flexible work options are perceived as a viable short-term measure to remedy the adverse effect of the lockdown on the educational system by transitioning to online teaching on an unprecedented scale whilst academic and non-academic staff work remotely (Burgess & Sievertsen, 2020). However, flexible work options are not limited to remote working. In other words, the flexible work option is more encompassing as it transcends the traditional 8 h a day work structure. The following are some of the flexible work options identified in the literature.

 Remote working

Remote working, also known as telecommuting, is a situation whereby an employee is allowed to work outside of the office location (Ganiyu, 2021; Giannikis & Mihail, 2011). The global lockdown and technological innovations are the major factors influencing businesses and higher education institutions to explore alternative work environments in which employees are allowed to work remotely. Noonan and Glass (2012) argued that remote working has been a catalyst for the expansion of work hours in response to employees’ need for additional work time in a developed country such as the United States of America (US). The expansion of work hours may result in work–family conflict. However, Ansong and Boateng (2018) examined the benefit of remote working in developing countries using Ghana as a reference point; the finding of the study suggests that both the employers and the workforce benefit from the adoption of remote working. Consistent with this finding, Ganiyu (2021) suggested that remote working could be helpful in reducing employees’ carbon footprint on the environment as emissions resulting from regular travel to work are reduced. Online teaching in higher education institutions may bring about a reduction in the amount of stationery used by the various institutions as all assessments are conducted online. In addition, the amount of emission produced as a result of staff and students commuting to the various study locations will equally be reduced.

Remote working is an approach to job scheduling made possible by new technological innovations such as mobile communication and the internet of things (Warnich, Carrell, Elbert, & Hatfield, 2018). For instance, Belzunegui-Eraso and Erro-Garcés (2020) posited that employees use terminals to create dial-up connections or to sustain uninterrupted online communications, which allow them to perform most or all of their assigned duties from home. Employees may also use cloud storage and drop boxes to share data and documents from any location (Warnich et al., 2018). However, an empirical study suggested that remote working does not work for certain people as it can promote feelings of loneliness, stagnation, work–family conflict, and even compulsive overworking (Belzunegui-Eraso & Erro-Garcés, 2020).

 Teleworking

Chiru (2017) argued that the interest in teleworking began in the 1970s when the word telecommuting was used to describe working away from the workplace, mainly using telephone communication as a replacement for physical proximity. Teleworking became popular in the 1990s, and recent studies show that it has become one of the most prominent bases of flexibility systems (Mahler, 2012) with the hope that it will become much more adopted in the post-pandemic period. Similarly, Lyttelton, Zang and Musick (2020) claimed that the global pandemic has resulted in an unparalleled transition to remote work. Before the COVID-19 crisis, 16% of employees hardly spent quality time at home on an ordinary day and only one-third of all workers reported the ability to telework for most of the day.

Teleworking promotes flexibility in the workplace and reduces the environmental impact of carbon emissions through transportation to and from workplaces (Baker et al., 2007; Baltes et al., 1999; Belzunegui-Eraso & Erro-Garcés, 2020). In other words, teleworking helps employees reduce regular travel to work thereby reducing the impact of such travel on energy consumption and the environment. Teleworking has been commonly viewed as a more sustainable mode of working during the global lockdown as compared with the traditional work arrangement because of its decreased reliance on transportation and consolidated office facilities, which results in sustained social distancing amongst the workforce (Atiku, Jeremiah, & Boateng, 2020; Chiru, 2017). Empirical studies indicated a significant positive relationship between teleworking and job characteristics such as productivity and a lower risk of burnout (Baert, Lippens, Moens, Weytjens, & Sterkens, 2020). However, Lebopo, Seymour and Knoesen (2020) argued that whilst teleworking provides various benefits to firms, society and the workforce, it has not achieved the anticipated levels of adoption.

 Shift work

Vedaa et al. (2016) explained that this style of work schedule rotates employees through the day and night shifts. A shift work option is enforced on a position or occupation such as security service, police, hotel or the health sector, where services are required at all times. Employers are typically responsible for providing transportation to workers from their home, if necessary, to the workplace at the start of a shift and from the workplace to the residence at the end of a shift or paying a transportation allowance if the employee accepts this (Podratz, 2004; Rodgers, 1992; Vedaa et al., 2016). Atiku et al. (2020) suggested that shift work may not be categorised as a flexible work option, but may be regarded as a non-standardised work schedule.

One of the benefits of the shift work option is that it allows the workforce to rotate their work schedule thereby having the time to honour other personal responsibilities (Ganiyu, 2021; Nakrošienė, Bučiūnienė, & Goštautaitė, 2019; Vedaa et al., 2016). However, the shift work option can be challenging for employees as it alters their sleeping patterns, eating habits, and the amount of time they spend with their family and friends. Based on the foregoing flexible work options, the following hypotheses are proposed:

Hypothesis 1: There is a significant association between age and attitudes towards specific flexible work options in times of crisis.

Hypothesis 2: There is a significant association between gender and attitudes towards specific flexible work options in times of crisis.

Hypothesis 3: There is a significant association between academic staff position and attitudes towards specific flexible work options in times of crisis.

Hypothesis 4: There is a significant association between administrative staff position and attitudes towards specific flexible work options in times of crisis.

 Flexitime options

The dynamic nature of the world of work and the pursuit of organisational excellence have resulted in many firms continually seeking superior capabilities, operational capacity and better work-related attitude required for gaining a competitive edge (Nwekpa, Offor, & Ezezue, 2020; Warnich et al., 2018). This leads to increased workload for the employees who must work past regular working hours, resulting in work–family conflict. The flexitime option was adopted as a work–life balance strategy to cushion the adverse effect of work–family conflict (Ganiyu et al., 2020). The flexitime option is a structured system in which organisations plan a work schedule that allows employees to have autonomy on their working time within the overall period of the work specifications (Atiku et al., 2020; Nwekpa et al., 2020; Tamunomiebi, 2018). Matilal (2020) argued that flexitime is a situated practice rooted in a diverse adaptive sociotechnical environment. The flexitime options considered in this study include flexible lunchtime, early start-early go, early start-long lunch, early start-normal go, then Friday afternoon off, and late start-late go. Each of the flexi-options is discussed next.

Flexible lunchtime option

The flexible lunchtime option is a job arrangement that enables workers to choose when they start and finish their workday, as well as how long they take their breaks, under agreed-upon condition established by management (Bailyn, 1993; Barber et al., 1992; Janza, 2020). The flexible lunchtime option helps employees to schedule work around their other personal responsibilities thereby enhancing the employees’ work–life harmony. Adopting the flexible lunchtime work option is often regarded as part of creating a family-friendly working atmosphere (Choi, 2018; Eaton, 2003; Janza, 2020; Pierce & Dunham, 1992). According to Yong (2015), these agreements have no impact on workers’ duties, the expectations that must be met or the average hours employed. Empirical evidence revealed that the flexible lunchtime option promotes job versatility and organisational commitment (Hill, Miller, Weiner, & Colihan, 1998; Janza, 2020; Lewison, 2006).

 Early start-early go

Most people need 7 to 8 h of sleep a night to feel rested and to be at their best. However, if the shift begins by 6 am, getting 7 or 8 h of sleep may be difficult (Grzywacz & Marks, 2000; Totterdell, 2005). The commute is frequently the driving force behind the early start-early go times. Totterdell (2005) argued that if you live in a city with heavy traffic, commuting between 8 am and 9 am could double or even triple your travel time. As a result, an earlier start time reduces commute time with both the night crew driving home and the day crew heading to work. According to Warnich et al. (2018), flexible functioning must be managed effectively.

 Early start-normal go, then Friday afternoon off

According to Warnich et al. (2018), flexible working hours should be managed. If an employee wishes to work beyond regular business hours, that must be decided in advance by the employee and the management, and if there is inadequate or no work to be completed at the times the employee wants to work, they will not be allowed to work at the times they want (Nwekpa et al., 2020). This style of work schedule would raise staff productivity whilst having few negative effects on the bottom line. According to Totterdell (2005), versatility encourages staff to fulfil personal and family responsibilities whilst preventing burnout.

 Early start-long lunch

According to Totterdell (2005), allowing workers to take longer lunch breaks during the day may contribute to improved productivity. This improves staff productivity by allowing employees to work around their family needs and other life commitments.

Miron (2014) concluded that whilst providing flexible scheduling can benefit both staff and the corporation, it also has drawbacks. Allowing workers to take longer lunch breaks or work various hours in the office means that managers must keep a closer watch on them. Managers must have confidence that their workers can finish tasks on time to fulfil all deadlines. Miron (2014) and Totterdell (2005) argued that if there is no consistent structure in place, this will potentially lead to misunderstandings and miscommunication between staff and supervisors. Based on the foregoing flexitime options, the following hypotheses are proposed:

Hypothesis 5: There is a significant association between age and attitudes towards specific flexitime options in times of crisis.

Hypothesis 6: There is a significant association between gender and attitudes towards specific flexitime options in times of crisis.

Hypothesis 7: There is a significant association between academic staff position and attitudes towards specific flexitime options in times of crisis.

Hypothesis 8: There is a significant association between administrative staff position and attitudes towards specific flexitime options in times of crisis.

 Research design Research approach

This study adopted a case study research design following a quantitative approach. A cross-sectional survey was incorporated using a structured questionnaire to gather information from respondents (Creswell & Hirose, 2019) concerning their perception of flexible work options in higher educational institutions during the pandemic. This study was conducted at institutions of higher learning in Namibia. The participants of this study were all categories of academics and administrative staff in the institutions. The rationale behind collecting data from all staff categories was to gather information on the preferred flexitime options for further development of flexible work options in the post-COVID-19 period.

 Research participants

The target population of this study comprised the academic and administrative staff in institutions of higher learning in Namibia. The estimated population of the academic and administrative staff in the institutions was 956. This study adopted a convenience sampling technique following the ethical guidelines in social science research, which stipulate that no respondents should be forced to participate in a survey. The convenience sampling method is a non-probabilistic sampling technique (Hayman, 2005; Kossek et al., 1999; Saunders & Townsend, 2018) that helps in choosing respondents who are willing to participate in the survey. Thus, convenience sampling was used in reaching out to respondents via their institutional email addresses. The link to complete the online survey and the survey introduction and the consent form were provided to respondents in the email. After 4 weeks of follow-up and gentle reminders to respondents regarding completion of the survey electronically if they had not done so, a total of 465 responses were retrieved.

 Measuring instruments

This study adopted a structured questionnaire to collect information on employees’ perception of flexible work options in the institutions of higher learning. The first section of the online survey contains three items gathering information on age group, gender and the position of respondents in the institutions. The second section contains 10 items, which were adapted from the Flexible Work Options Questionnaire (FWOQ version 2) developed by Albion (2004) and on the 17 statements developed by Charron and Lowe (2005). The items were adapted to gather information on two sub-sections: (1) perception of flexible work options in higher education institutions during the pandemic, and (2) the preferred flexitime options. The items on these subsections were designed on a 5-point Likert rating scale, ranging from ‘1 – strongly disagree’ to ‘5 – strongly agree’. The last section contains an open-ended question useful in gathering additional comments from respondents regarding other opinions on flexible work options in higher education during the pandemic, relevant to the survey. The result of this grouping of statements helps to examine in detail the attitudes of employees towards flexible work options. The questionnaire was designed using eSurveysPro, which offers an online survey software tool. Respondents were able to complete the survey electronically using their smartphones, tablets and other personal computers or devices. The online survey tool was chosen to reach out to respondents whilst maintaining social distancing and encouraging virtual interaction during the pandemic.

 Research procedure and ethical considerations

The online survey tool (eSurveysPro) adopted in this study ensured the anonymity of all participants by only providing a link to the survey in which anonymised data were obtained and downloaded in an Excel format. This survey does not collect any information that discloses the identity of the participant or the identity of the participant’s workplace. The survey began with an introduction and an informed consent form emphasising that participation is voluntary. Participants have the right to refuse to participate in this study and may withdraw from the study at any time. It was pointed out that the survey responses are confidential and anonymous, only aggregate information (no individual responses) was reported. Based on the sampling techniques adopted in this study, the link to complete the survey online was provided to respondents. A total of 465) responses were retrieved online after 4 weeks of follow-up and gentle reminders to participants regarding completion of the online survey.

 Statistical analysis

This study adopted both descriptive and inferential statistics for data analysis. The data downloaded on an Excel file was imported into the Statistical Package for Social Sciences (SPSS) version 27 for descriptive statistics (simple percentages, cross-tabulations, mean scores and standard deviation) and other preliminary analyses. Perception of flexible work options was calculated using Pearson’s Chi-square test of association to discover if there is a relationship between the two categorical variables such as age and gender scores (Franke, Ho, & Christie, 2012; Herbst, 2020). Also, Pearson’s Chi-square test was utilised to test the association between gender and preferred flexitime options in the institutions. The Mann–Whitney U test (Pallant, 2020) was used in this study to examine the differences between two independent groups on a continuous measurement scale. The two independent groups assessed against the continuous measurement scale in this study are male and female.

 Ethical considerations

Ethical clearance was obtained from the Namibia University of Science and Technology, REC/0320/061.

 Results

Flexible work options were operationalised as remote working, teleworking, shift work and flexitime options. The flexitime options were categorised as: flexible lunchtime option, early start-early go, early start-long lunch, early start-normal go, then Friday afternoon off and late start-late go. Pearson’s Chi-square test of association was conducted to examine the relationship between gender and the categories of flexible work options and flexitime options based on the perception of staff in the institutions. Chi-square test of association compares the observed (count) frequencies of responses collected on each of the categories with the values that would be expected if there was no association between the categorical variables under investigation (Pallant, 2020). The results reported in Table 1 showcased the categorical variables (e.g. age group, gender and positions) and continuous variables (flexible work options such as remote working, teleworking, shift work and flexitime options) analysed using the Chi-square tests of independence. The effect size of results was determined using Cohen’s (1988) benchmarks (small = 0.01, medium = 0.30, large = 0.50) for effect size. Cramer’s V (φc) reported in Tables 1 and 2 were instrumental in determining the effect sizes of the Chi-square tests of independence.

Comparisons of characteristics by flexible work options.

Characteristic Remote working Teleworking Shift-work Flexitime Overall sample Chi-square tests of independence
n % n % n % n % n % x2 p φc n
Age in years
19–29 years 14 28.0 10 20.0 4 8.0 22 44.0 50 11.3 9 = 14.902 > 0.05 0.109 443
30–39 years 39 23.6 30 18.2 22 13.3 74 44.8 165 37.2 - - - -
40–54 years 43 25.0 55 32.0 14 8.1 60 34.9 172 38.8 - - - -
55 years and above 14 25.0 16 28.6 2 3.6 24 42.9 56 12.6 - - - -
Gender
Male 49 27.8 37 21.0 14 8.0 76 43.2 176 39.7 3 = 4.147 > 0.05 0.097 443
Female 61 22.8 74 27.7 28 10.5 104 39.0 267 60.3 - - - -
Academic staff position
Professor 0 0.0** 2 18.2 0 0.0 9 81.8** 11 4.8 15 = 33.403 < 0.01 0.220 231
Associate professor 7 41.2 7 41.2 0 0.0 3 17.6 17 7.4 - - - -
Senior lecturer 10 33.3 15 50.0 0 0.0 5 16.7 30 13.0 - - - -
Lecturer 42 35.0 32 26.7 5 4.20 41 34.2 120 51.9 - - - -
Junior lecturer 16 32.0 11 22.0 3 6.0 20 40.0 50 21.6 - - - -
Tutor 0 0.0 1 33.3 1 33.3 1 33.3 3 1.3 - - - -
Administrative staff position
Senior management 1 7.7 5 38.5 0 0.0 7 53.8 13 5.5 15 = 31.224 0.01 0.209 238
Middle management 20 26.7 20 26.7 7 9.3 28 37.3 75 31.5 - - - -
Specialised/skilled/senior supervisory 9 11.0** 12 14.6 14 17.1 47 57.3** 82 34.5 - - - -
Skilled 15 24.2 7 11.3 15 24.2 25 40.3 62 26.1 - - - -
Semi-skilled 1 50.0 1 50.0 0 0.0 0 0.0 2 0.08 - - - -
Unskilled 0 0.0 0 0.0 1 25.0 3 75.0 4 1.7 - - - -

, Standard residual is significant at p < 0.01;

, standard residual is significant at p < 0.05, φc = effect size (Cramer’s V).

Comparisons of characteristics by flexitime options.

Characteristic Flexible lunchtime option Early start-early go Early start-long lunch Early start-normal go, then Friday afternoon off Late start-late go Overall sample Chi-square tests of independence
n % n % n % n % n % n % x2 p φc n
Age in years
19–29 years 0 0.0 6 18.8 0 0.0 21 65.6 5 15.6 32 11.9 12 = 15.257 > 0.05 0.138 268
30–39 years 4 4.0 19 18.8 3 3.0 59 59.0 10 9.9 101 37.7 - - - -
40–54 years 12 12.0 13 13.0 3 3.0 60 34.9 13 13.4 100 37.3 - - - -
55 years and above 3 8.6 6 17.1 2 5.7 16 45.7 8 22.9 35 13.1 - - - -
Gender
Male 5 4.5 23 20.9 5 4.5 55 50.0** 22 20.0 110 41.0 4 = 14.660 < 0.01 0.234 268
Female 14 8.9 21 13.3 3 1.9 106 67.1** 14 8.9 158 59.0 - - - -
Academic staff position - - - -
Professor 2 22.2 0 0.0 2 22.2 3 33.3 2 22.2 9 7.3 20 = 37.734 < 0.05 0.220 123
Associate professor 1 11.1 4 44.4 0 0.0 1 11.1 3 33.3 9 7.3 - - - -
Senior lecturer 1 8.3 1 8.3 0 0.0 5 41.7 5 41.7 12 9.8 - - - -
Lecturer 4 6.1 17 25.8 1 1.5 35 53.0 9 13.6 66 53.7 - - - -
Junior lecturer 0 0.0 7 28.0 0 0.0 15 60.0 3 12.0 25 20.3 - - - -
Tutor 0 0.0 1 50.0 0 0.0 1 50.0 0 0.0 2 1.6 - - - -
Administrative staff position
Senior management 2 20.0 0 0.0 0 0.0 6 60.0 2 20.0 10 6.1 20 = 21.925 > 0.05 0.182 165
Middle management 6 12.8 3 6.4 2 4.3 31 66.0 5 10.6 47 28.5 - - - -
Specialised/skilled/senior supervisory 4 6.3 6 9.4 3 4.7 46 71.9 5 7.8 64 38.8 - - - -
Skilled 0 0.0 8 21.1 0 0.0 24 63.2 6 15.8 38 23.0 - - - -
Semi-skilled 0 0.0 1 50.0 0 0.0 1 50.0 0 0.0 2 1.2 - - - -
Unskilled 0 0.0 1 25.0 0 0.0 3 75.0 0 0.0 4 2.4 - - - -

, Standard residual is significant at p < 0.01;

, standard residual is significant at p < 0.05, φc = effect size (Cramer’s V).

A Chi-square test for independence indicated no significant association between age and attitudes towards flexible work options in the institutions, x2 (9, n = 433) = 14.902, p > 0.05, φc = –0.109. Similarly, there was no significant association between gender identification and attitudes towards flexible work options in the institutions, x2 (3, n = 433) = 4.147, p > 0.05, φc = –0.097. Conversely, a significant association was found between categories of academic staff position and attitudes towards flexible work options, x2 (15, n = 231) = 33.403, p < 0.01, φc = –0.220. The study found a significant association in the proportion of academic staff in professorial cadre favouring flexitime (81.8%) in the institutions. In line with Cohen’s (1988) benchmarks for effect size determination (φc = –0.220), one can infer that there was a small relationship between academic staff position and attitudes towards flexible work options in the institutions. Pearson’s Chi-square test of independence also revealed a significant association between categories of administrative staff position and attitudes towards flexible work options, x2 (15, n = 238) = 31.224, p < 0.01, φc = –0.209. A significant difference was found in the proportion of administrative staff (in senior supervisory cadre) favouring remote working and flexitime options (68.3%) in the institutions. In line with Cohen’s (1988) benchmarks for effect size determination (φc = –0.209), one can infer that there was a small relationship between administrative staff position and attitudes towards flexible work options in the institutions.

The results presented in Table 1 show that demographic characteristics such as age and gender exert no statistical association with the perception of flexible work options in the institutions. Academic and administrative staff positions provide a significant association with the attitudes towards remote working and flexitime options in the institutions. The comparisons of demographic and job characteristics by five flexitime options are presented in Table 2.

As indicated in Table 2, the Chi-square test of association indicates that age has no statistical influence on attitudes concerning flexitime options in the institutions, x2 (12, n = 268) = 15.257, p > 0.05, φc = –0.138. Therefore, there is no significant association between age and attitudes concerning different flexitime options in the institutions. Statistically, the Pearson Chi-square test indicates a significant relationship between gender identification and attitude towards flexible time options in the institutions [x2 (4, n = 268) = 14.660, p < 0.01, φc = –0.234]. The adjusted residuals comparing responses regarding early start-normal go, then Friday afternoon off by males (t = –2.8) and females (t = 2.8) point to where the significant associations are between gender and flexitime options. The adjusted residual for males and early start-normal go, then Friday afternoon off (t = –2.8) implies that the observed value (55) is lower than the expected (66.1). Conversely, the adjusted residual for females and early start-normal go, then Friday afternoon off (t = 2.8) implies that the observed value (106) is higher than the expected (94.9). There is a significant difference between gender identification and attitude towards early start-normal go, then Friday afternoon off in the institutions. In line with Cohen’s (1988) benchmarks for effect size (φc = –0.234), one can conclude that there was a small relationship between gender and attitude towards specific flexitime options in the institutions.

The Chi-square test of association between academic staff positions and attitudes towards specific flexitime options revealed a significant relationship between academic staff position and flexitime option [x2 (20, n = 123) = 37.734, p < 0.05, φc = –0.220]. The adjusted residuals for the levels of academic positions and flexitime options [professor and early start-long lunch (4.0); associate professor and early start-normal go, then Friday afternoon off (–2.3); senior lecturer and late start-late go (2.3)] point to where the significant associations are between academic positions and preference for flexitime options. The effect size of the significant association was small (φc = –0.220) according to Cohen’s benchmarks. Hence, there is a significant association between academic staff positions and specific flexitime options in the institutions. The Chi-square test of independence testing the association between administrative staff position and attitude towards flexitime options reveals that there is no significant association between administrative position and flexitime [x2 (20, n = 165) = 21.925, p > 0.05, φc = –0.182]. The mixed results imply that academic staff are the core staff of any higher educational institution. The use of flexitime options is more applicable to the academic staff in the institutions. The comparisons of responses on continuous variables by gender identification in the study are illustrated in Table 3.

Comparisons of the responses from continuous variables by gender.

S. No. Items Gender N Median Mean rank Mann–Whitney U/independent samples t-test
U p z r n
1 Flexible work options could assist me to balance my personal and work commitments. Male 193 5.00 221.43 24015 0.076 −1.774 0.082 465
Female 272 5.0 241.21 - - - - -
2 Information technology plays a huge role in the implementation of flexible work options. Male 193 5.00 222.03 24130 0.064 −1.854 0.086 465
Female 272 5.0 240.79 - - - - -
3 My current information technology infrastructure is sufficient to support flexible work options. Male 193 4.0 212.69 22329 0.003 −2.949 0.137 465
Female 272 4.0 247.41 - - - - -
4 Flexible work options will enhance my performance. Male 193 4.0 214.07 22594 0.006 −2.766 0.128 465
Female 272 5.0 246.43 - - - - -
5 Flexible work options will reduce team engagement. Male 193 3.0 241.18 24669 0.255 −1.139 0.053 465
Female 272 3.0 227.20 - - - - -

r = correlation coefficient effect size (Cohen’s d).

The Mann–Whitney U test on the third item produced a significant difference in the perception of information technology (IT) infrastructure in implementing flexible work options by males (Md = 4, n =193) and females (Md = 4, n = 272), U = 22329, z = –2.949, p = 0.003, r = 0.137. Similarly, the Mann–Whitney U test for the fourth item measuring the influence of flexible work options on performance produced a significant difference in the responses by males (Md = 4, n = 193) and females (Md = 5, n = 272), U = 22594, z = –2.766, p = 0.006, r = 0.128. These results imply that males and females differ in their responses on the role of IT infrastructure in implementing flexible work options and in their responses to the influence of flexible work options on performance in the institutions of higher learning. The results of items (1, 2 and 5) show that males and females do not differ in their responses to flexible work options. Decisions reached on the hypotheses tested in this study are summarised in Table 4.

Summary of results from the hypotheses.

Hypothesis Variable Chi-square tests of independence Decision
x2 p φc n
H1 Association between age and attitudes towards specific flexible work options in times of crisis. 9 = 14.902 > 0.05 0.109 443 Rejected
H2 Association between gender and attitudes towards specific flexible work options in times of crisis. 3 = 4.147 > 0.05 0.097 443 Rejected
H3 Association between academic staff position and attitudes towards specific flexible work options in times of crisis. 15 = 33.403 < 0.01 0.220 231 Accepted
H4 Association between administrative staff position and attitudes towards specific flexible work options in times of crisis. 15 = 31.224 < 0.01 0.209 238 Accepted
H5 Association between age and attitudes towards specific flexitime options in times of crisis. 12 = 15.257 > 0.05 0.138 268 Rejected
H6 Association between gender and attitudes towards specific flexitime options in times of crisis. 4 = 14.660 < 0.01 0.234 268 Accepted
H7 Association between academic staff position and attitudes towards specific flexitime options in times of crisis. 20 = 37.734 < 0.05 0.220 123 Accepted
H8 Association between administrative staff position and attitudes towards specific flexitime options in times of crisis. 20 = 21.925 > 0.05 0.182 165 Rejected
Discussion

The main objective of this study was to examine employees’ perceptions of flexible work options adopted in institutions of higher learning during the COVID-19 pandemic in Namibia. This study tested the influence of categorical variables on flexible work options and the specific flexitime options in institutions of higher learning during the COVID-19 pandemic. Many studies have established the place of flexible work options in addressing work–family stressors and as a work–life balance strategy in times of peace (Allen et al., 2013; Giannikis & Mihail, 2011; Tamunomiebi, 2018). Similarly, attitudes towards flexible work options were investigated in developed countries before the pandemic (e.g. Albion, 2004; Giannikis & Mihail, 2011). There is a dearth of studies that have investigated the attitudes towards flexible work options in higher education institutions during a pandemic. The unique contribution of this study to the existing body of literature is a piece of empirical evidence on the association between categorical variables and attitudes towards flexible work options in higher education institutions in times of crisis.

This study established a significant relationship between academic staff position and attitudes towards specific flexible work options. The specific flexible work options empirically verified amongst the academic staff in times of crisis are remote working and flexitime options. Similarly, a significant association is established between administrative staff position and attitudes towards specific flexible work options in times of crisis. The administrative staff in supervisory positions demonstrates a positive attitude towards remote working and flexitime options in times of crisis. The findings from a measure of attitudes towards flexible work options in times of crisis in higher educational institutions enhance understanding of the FWOQ version 2 developed by Albion (2004). The gap in gender differences (Albion, 2004) is closed in this study based on the fact that males and females differ in their responses on the role of IT infrastructure in implementing flexible work options. Also, males and females differ in their responses to the influence of flexible work options on performance in institutions of higher learning. Consistent with these findings, Weideman and Hofmeyr (2020) revealed that flexible work options such as flexitime options and remote working have a significant positive association with constructs such as employee engagement, job performance and employee well-being. In a similar vein, the finding of the study by Atiku et al. (2020) suggested that the adoption of flexible work arrangements during the lockdown mediates the relationship between employers’ support and employees’ job performance in selected African countries.

On account of the association between categorical variables and attitudes towards specific flexitime options in higher education institutions in times of crisis, this study established a significant association between gender and attitudes towards a specific flexitime option. The contribution to the existing body of literature on the specific flexitime options widely accepted by all categories of employees in higher educational institutions in times of crisis in Africa is established through this study.

 Practical implications

The findings of this study suggest practical implications for human resources (HR) and management concerning the adoption of flexible work options in higher institutions of learning. Specifically, this study found a significant association between academic staff position and attitude towards specific work options (remote working and flexitime option) for full professors in the institutions. For effective utilisation of staff members in this category in times of crisis and the post-pandemic period, it becomes imperative for HR to adopt flexible work options. Professors are conscious of the professional codes of conduct in higher education and can be targeted for the effective implementation of flexible work options in higher education institutions.

Insights from the significant association between administrative staff in supervisory positions and attitudes towards specific work options (remote working and flexitime options) could be used to improve the implementation of flexible work options in the post-pandemic period. The administrative staff in supervisory roles preferred the use of remote working and flexitime options in institutions of higher learning operating in Namibia. The HR departments may consider engaging the administrative staff in this category for effective institutionalisation of flexible work options and performance monitoring or evaluation. Therefore, there is a need to develop performance management systems suitable for flexible work options in the post-pandemic period. For example, a performance management system that gives room for flexibility and involves employees, and their line managers in setting specific, measurable, attainable, relevant and time bound objectives could enhance employees’ performance in the post-pandemic period.

In terms of attitudes towards specific flexitime options in the participating institutions of higher learning in Namibia, this study found a significant association between gender and a specific flexitime option. This study shows that gender identification is positively associated with attitudes towards early start-normal go, then Friday afternoon off. The practical implication is that both academic staff and administrative staff in selected institutions of higher learning support the use of the early start-normal go, then Friday afternoon off option by management. Adoption of this flexitime option might produce a positive impact on work–life balance satisfaction and employee performance in the institutions.

 Limitations and recommendations

The results reported in this study emanated from statistical analysis based on attitudes towards flexible work options in the institutions of higher learning during the pandemic in Namibia. The major limitation of this study is the use of a case study research design, which implies that the finding cannot be generalised to reflect the situations across higher education institutions in Namibia. Future research may require other private institutions of higher learning in the country to participate in the study to generalise the research findings in Namibia. The other methodological limitation of this study could be traced to the use of a non-probability sampling technique (convenience sampling) because of ethical consideration and the use of an online survey tool based on the need to observe social distancing during the pandemic. Therefore, future research should consider adopting a simple random sampling technique, which is more appropriate for the Chi-square test of independence and Mann–Whitney U test carried out in this study.

Conclusion

This study aimed at investigating the perception of flexible work options and attitudes towards different categories of flexitime options during the pandemic in the institutions of higher learning in Namibia. The originality of this study dwells on the fact that there is a dearth of studies on the perception of flexible work options during a pandemic in Namibia. Based on the statistical evidence reported in the analysis section, this study holds that there is a significant relationship between gender identification and attitude towards flexitime options in higher education institutions. A larger percentage of academic and administrative staff preferred the flexitime option (early start-normal go, then Friday afternoon off).

There is statistical evidence to conclude that there is a significant difference in the attitude towards the role of IT infrastructure in the implementation of flexible work options by male and female staff in the institutions. Conclusively, this study submits that there is a significant association between flexible work options and employee performance in the institutions. Hence, institutions of higher education operating in Namibia need to embrace flexibility by putting in place state-of-the-art technology for proper implementation of remote working and teleworking in the post-pandemic period.

 Acknowledgements

The authors would like to express their gratitude to the HR Business Partners for their kind assistance during data collection.

Competing interests

The authors have declared that no competing interests exist.

 Authors’ contributions

Both the authors contributed equally to this work.

 Funding information

The research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.

 Data availability

Data sharing is not applicable to this articles as no new data were created or analysed in this study.

 Disclaimer

The views and opinions expressed in this article are those of the authors and do not necessarily reflect the official policy or position of any affiliated agency of the authors, the publisher.

 References Albion, M.J. (2004). A measure of attitudes towards flexible work options. Australian Journal of Management, 29(2), 275–294. https://doi.org/10.1177/031289620402900207 Allen, T., Johnson, R., Kiburz, K., & Shockley, K. (2013). Work-family conflict and flexible work arrangements: Deconstructing flexibility. Personnel Psychology, 66(2), 345–376. https://doi.org/10.1111/peps.12012 Ansong, E., & Boateng, R. (2018). Organisational adoption of telecommuting: Evidence from a developing country. The Electronic Journal of Information Systems in Developing Countries, 84(1), e12008. https://doi.org/10.1002/isd2.12008 Atiku, S.O., Jeremiah, A., & Boateng, F. (2020). Perceptions of flexible work arrangements in selected African countries during the coronavirus pandemic. South African Journal of Business Management, 51(1), 1–10. https://doi.org/10.4102/sajbm.v51i1.2285 Azar, S., Khan, A., & Van Eerde, W. (2018). Modelling linkages between flexible work arrangements’ use and organizational outcomes. Journal of Business Research, 91, 134–143. https://doi.org/10.1016/j.jbusres.2018.06.004 Baert, S., Lippens, L., Moens, E., Weytjens, J., & Sterkens, P. (2020). The COVID-19 crisis and telework: A research survey on experiences, expectations and hopes. Retrieved from https://www.iza.org/publications/dp/13229/the-covid-19-crisis-and-telework-a-research-survey-on-experiences-expectations-and-hopes Baker, E., Avery, G.C., & Crawford, J. (2007). Satisfaction and perceived productivity when professionals work from home. Research and Practice in Human Resource Management, 15(1), 37–62. Baltes, B., Briggs, T.E., Huff, J.W., Wright, J.A., & Neuman, G.A. (1999). Flexible and compressed workweek schedules: A meta-analysis of their effects on work-related criteria. Journal of Applied Psychology, 84(4), 496–513. https://doi.org/10.1037/0021-9010.84.4.496 Bailyn, L. (1993). Breaking the mold: Women, men, and time in the corporate world. New York, NY: The Free Press. Barber, A.E., Dunham, R., & Formisano, R.A. (1992). The impact of flexible benefits on employee satisfaction: A field study. Personnel Psychology, 45(1), 55–76. https://doi.org/10.1111/j.1744-6570.1992.tb00844.x Belzunegui-Eraso, A., & Erro-Garcés, A. (2020). Teleworking in the context of the COVID-19 crisis. Sustainability, 12(9), 1–18. https://doi.org/10.3390/su12093662 Burgess, S., & Sievertsen, H.H. (2020). Schools, skills, and learning: The impact of COVID-19 on education. Retrieved from https://voxeu.org/article/impact-covid-19-education Charron, F.K., & Lowe, J.D. (2005). Factors that affect accountant’s perceptions of alternative work options. Accounting Forum, 29, 191–206. https://doi.org/10.1016/j.accfor.2004.10.002 Chiru, C., 2017. Teleworking: Evolution and trends in USA, EU and Romania. Economics, Management & Financial Markets, 12(2), 222–229. Choi, S. (2018). Managing flexible work arrangements in government: Testing the effects of institutional and managerial support. Public Personnel Management, 47(1), 26–50. https://doi.org/10.1177/0091026017738540 Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). Hillsdale, NJ: Erlbaum. Creswell, J.W., & Hirose, M. (2019). Mixed methods and survey research in family medicine and community health. Family Medicine and Community Health, 7(2), 1–6. https://doi.org/10.1136/fmch-2018-000086 Eaton, S.C. (2003). If you can use them: Flexible policies, organisational commitment, and perceived performance. Industrial Relations, 42(2), 145–166. https://doi.org/10.1111/1468-232X.00285 Franke, T.M., Ho, T., & Christie, C.A. (2012). The chi-square test: Often used and more often misinterpreted. American Journal of Evaluation, 33(3), 448–458. https://doi.org/10.1177/1098214011426594 Ganiyu, I.O. (2021). Flexible work arrangements for green manufacturing. In S.O. Atiku & T. Fapohunda (Eds.), Human resource management practices for promoting sustainability (pp. 212–228). Pennsylvania: IGI Global. http://doi:10.4018/978-1-7998-4522-5.ch012 Ganiyu, I.O., Fields, Z., Atiku, S.O., & Derera, E. (2020). Measuring the effectiveness of work-life balance strategies in the manufacturing sector. SA Journal of Human Resource Management, 18(1), 1–10. https://doi.org/10.4102/sajhrm.v18i0.1216 Giannikis, S.K., & Mihail, D.M. (2011). Flexible work arrangements in Greece: A study of employee perceptions. The International Journal of Human Resource Management, 22(2), 417–432. https://doi.org/10.1080/09585192.2011.540163 Grzywacz, J.G., & Marks, N.F. (2000). Reconceptualizing the work-family interface: An ecological perspective on the correlates of positive and negative spillover between work and family. Journal of Occupational Health Psychology, 5(1), 111–126. https://doi.org/10.1037/1076-8998.5.1.111 Hayman, J.R. (2005). Psychometric assessment of an instrument designed to measure work/life balance. Research and Practice in Human Resource Management, 13(1), 85–92. Herbst, T.H. (2020). Gender differences in self-perception accuracy: The confidence gap and women leaders’ underrepresentation in academia. SA Journal of Industrial Psychology, 46(1), 1–8. https://doi.org/10.4102/sajip.v46i0.1704 Hill, J.E., Miller, B.C., Weiner, S.P., & Colihan, J. (1998). Influences of the virtual office on aspects of work and work/life balance. Personnel Psychology, 51(3), 667–683. https://doi.org/10.1111/j.1744-6570.1998.tb00256.x Janza, N. (2020). What is flexitime (flexible work) and what are its advantages and disadvantages? Spica Online Marketplace, 20 November 2020. [Blog]. Retrieved from https://www.spica.com/blog/flexitime-advantages-disadvantages Karatayev, V.A., Anand, M., & Bauch, C.T. (2020). Local lockdowns outperform global lockdown on the far side of the COVID-19 epidemic curve. Proceedings of the National Academy of Sciences, 117(39), 24575–24580. https://doi.org/10.1073/pnas.2014385117 Kossek, E.E., Barber, A.E., & Winters, D. (1999). Using flexible schedules in the managerial world: The power of peers. Human Resource Management, 38(1), 33–46. https://doi.org/10.1002/(SICI)1099-050X(199921)38:1%3C33::AID-HRM4%3E3.0.CO;2-H Lebopo, C.M., Seymour, L.F., & Knoesen, H. (2020, September). Explaining factors affecting telework adoption in South African organisations pre-COVID-19. In Conference of the South African Institute of Computer Scientists and Information Technologists 2020 (pp. 94–101), Cape Town: SAICSIT. Lewison, J. (2006). The work/life balance sheet so far. Journal of Accountancy, 202(2), 45–50. Lyttelton, T., Zang, E., & Musick, K. (2020). Gender differences in telecommuting and implications for inequality at home and work. New Haven, CT: Yale University. Mahler, J., 2012. The telework divide: Managerial and personnel challenges of telework. Review of Public Personnel Administration, 32(4), 407–418. https://doi.org/10.1177/0734371X12458127 Matilal, O. (2020). Time matters: Flexitime and women’s retention in the 24/7 workplace. In Proceedings of 18th European Conference on Computer-Supported Cooperative Work Germany, 13 – 17 June 2020 (pp. 111–127). European Society for Socially Embedded Technologies (EUSSET), Siegen. Miron, A. (2014). Employee relations management. eSkill Talent Assessment Platform, 23 July 2014. [Blog]. Retrieved from https://www.eskill.com/blog/getting-to-work-late/ Nakrošienė, A., Bučiūnienė, I., & Goštautaitė, B. (2019). Working from home: Characteristics and outcomes of telework. International Journal of Manpowerm, 40(1), 87–101. https://doi.org/10.1108/IJM-07-2017-0172 Noonan, M.C., & Glass, J.L. (2012). The hard truth about telecommuting. Monthly Labor Review, 135(6), 38–45. Nwekpa, K.C., Offor, P.G., & Ezezue, B.O. (2020). Work schedule flexibility and employee commitment: A study of Nigerian Breweries, Ama, Enugu, Nigeria. International Journal of Development and Management Review, 15(1), 1–16. Pallant, J. (2020). SPSS survival manual: A step by step guide to data analysis using IBM SPSS. Oxfordshire: Routledge. Pierce, J.L., & Dunham, R.B. (1992). The 12-hour workday: A 48-hour, Eight-day week. Academy of Management Journal, 35(5), 1086–1999. https://doi.org/10.2307/256542 Podratz, L.T. (2004). The nature of work-personal life balance (Dissertation Abstracts International), University of Houston. Rodgers, C.S. (1992). The flexible workplace: What have we learned? Human Resource Management, 31(3), 183–199. https://doi.org/10.1002/hrm.3930310305 Saunders, M.N.K., & Townsend, K. (2018). Choosing participants. In C. Cassell, A. Cunliffe, & G. Grandy (Eds.), Handbook of qualitative business and management research methods (pp. 480–494). London: Sage. Tamunomiebi, M.D.P. (2018). Flexi-time work practice and employee productivity in tertiary institutions in rivers state. International Journal of Economics and Business Management, 4(3), 1–10. Tirumalaraju, D. (2020). Covid-19 pandemic, declared by the World Health Organisation (WHO). Pharmaceutical Technology, 12 March 2020. Retrieved from www.pharmaceutical-technology.com/news/who-declares-covid-19-pandemic/ Totterdell, P. (2005). Work schedules. In J. Barling, E.K. Kelloway, & M.R. Frone (Eds.), Handbook of work stress (pp. 89–112). Thousand Oaks, CA: SAGE Publications. https://doi.org/10.4135/9781412975995.n3 Vedaa, O. Harris, A., Bjorvatn, B., Waage, S., Sivertsen, B., Tucker, P., & Pallese, S. (2016). Systematic review of the relationship between quick returns in rotating shift work and health rotating shift work and health related outcomes. Ergonomics, 59(1), 1–14. https://doi.org/10.1080/00140139.2015.1052020 Verma, B.K., Verma, M., Verma, V.K., Abdullah, R.B., Nath, D.C., Khan, H.T., & Verma, V. (2020). Global lockdown: An effective safeguard in responding to the threat of COVID-19. Journal of evaluation in clinical practice, 26(6), 1592–1598. https://doi.org/10.1111/jep.13483 Voudouris, I. (2004). The use of flexible employment arrangements: Some new evidence from Greek firms. The International Journal of Human Resource Management, 15(1), 131–146. https://doi.org/10.1080/0958519032000157384 Warnich, S. Carrell, M.R., Elbert, N.F., & Hatfield, R.D. (2018). Human resource management in South Africa (6th ed.). Cape Town: Cengage. Weideman, M., & Hofmeyr, K.B. (2020). The influence of flexible work arrangements on employee engagement: An exploratory study. SA Journal of Human Resource Management, 18(1), 1–18. https://doi.org/10.4102/sajhrm.v18i0.1209 Yong, S.M. (2015). Job related factors and moderating effect of flexible work arrangement on job satisfaction among Malaysian offshore outsourcing support employees (Doctoral dissertation). University of Utara.

How to cite this article: Atiku, S.O., & Ganiyu, I.O. (2022). Flexible work options in higher educational institutions in times of crisis. SA Journal of Human Resource Management/SA Tydskrif vir Menslikehulpbronbestuur, 20(0), a1693. https://doi.org/10.4102/sajhrm.v20i0.1693