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Article

Impact of Organizational Culture on Academics’ Readiness and Behavioral Intention to Implement eLearning Changes in Kuwaiti Universities during COVID-19

by
Sarah Al-Shamali
1,*,
Ahmed Al-Shamali
2,
Ahmad Alsaber
1,
Anwaar Al-Kandari
3,
Shihanah AlMutairi
1 and
Amer Alaya
4
1
College of Business and Economics, American University of Kuwait, P.O. Box 3323, Salmiya 13034, Kuwait
2
College of Business, Gulf University for Science and Technology, P.O. Box 7207, Mubarak Al-Abdullah 32093, Kuwait
3
Business Management, Kuwait Technical College, P.O. Box 232, Abu-Halifa 54753, Kuwait
4
The Faculty of Business and Law, British University in Dubai, Block 11, 1st and 2nd Floor, Dubai International Academic City, Dubai P.O. Box 345015, United Arab Emirates
*
Author to whom correspondence should be addressed.
Sustainability 2022, 14(23), 15824; https://doi.org/10.3390/su142315824
Submission received: 23 October 2022 / Revised: 17 November 2022 / Accepted: 21 November 2022 / Published: 28 November 2022
(This article belongs to the Special Issue Technology Enhanced Learning and Resilience in Higher Education Institutions during COVID-19 and Beyond: Challenges and Opportunities)
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Abstract

:
A comprehensive review of the literature indicates that there is a lack of research on the influence of all the organizational culture (OC) types on academics’ readiness and behavioral intention to implement eLearning changes in higher education institutions (HEIs). To address this gap, this study empirically investigates the impact of OC on academics’ readiness and behavioral intention to implement eLearning changes within HEIs in Kuwait during the COVID-19 pandemic. A 218 self-administered survey was distributed to public and private HEIs. The analysis of collected data reveal that the most prominent OCs are hierarchy and market types which support readiness for change. The contribution of this study lies in further understanding the impact of OC on academics’ readiness for eLearning changes and behavioral intention to support eLearning implementation. The findings further offer an original contribution by confirming the mediating role of academics’ readiness for eLearning changes in the relationship between OC and behavioral intention. This paper adds to the change management literature by collecting data during the COVID-19 pandemic within the interesting context of HEIs in the Gulf Cooperation Council (GCC), which is currently scarce. The implications of this study contribute to the sustainability of Kuwaiti HEIs.

1. Introduction

eLearning uses electronic resources mainly composed of computers and the Internet, taking place on campus or in remote locations [1]. The popularity of eLearning has provided an opportunity for HEIs to meet the diverse lifestyles of students, compete with local and international competition, and deal with unprecedented circumstances [2,3]. In addition, sustainable learning has become the focus of eLearning [4,5,6]. Especially in HEIs, eLearning has provided the flexibility to have lectures online and sometimes prerecorded so that students can access them later [5,6]. Such access to information showcases the importance of eLearning being a more sustainable approach to students with different lifestyles and locations, in addition to saving time and providing more opportunities for leisure [5]. With that, this research aims to benefit HEIs by investigating elements that impact decision makers’ use of eLearning for higher education sustainability.
The World Health Organization (WHO) announced that the COVID-19 virus was a global pandemic on the 11th of March 2020 [7]. As a response to increasing infection rates, HEI campuses across the GCC shut down and rolled out online learning programs to continue classes [8]. Private HEIs in Kuwait adapted quickly, and some had students attending regular online classes within a matter of weeks. Due to their technological resources and quick decision making, delays to the academic calendar were not major. On the other hand, public education institutions were slower to adapt to online learning [9].
One of the main components to ensure that distance learning can be implemented is a stable internet connection, which exceeds 90% penetration in the GCC region [10,11]. In addition to Kuwait’s good infrastructure, students can easily obtain scholarships to private HEIs or attend public institutions free of charge along with receiving a monthly student allowance from the government for educational supplies [12]. On the other hand, challenges facing Kuwait’s public education system have been reported by [9], which mentions that though there are no issues with funding, online education has been on the to-do list of the Ministry of Education (MOE) for some 18 years. Attempting to execute online learning has failed mainly due to no or minimal digital infrastructure and a lack of decision making and professionalism. This was evident during the handling of the MOE sector during COVID-19, as the education sector was one of the first to close on the 26th of February 2020, with deadlines to reopen being constantly postponed due to outdated IT systems and no formal plan. In addition, communication coming from the MOE was silent for months, and students in public schools were idle for approximately 8 months, with high school students resuming their semester at the end of June 2020 [9]. In addition, ref. [13] explains that digital literacy was nonexistent in Kuwaiti public schools before the pandemic. Hence, the MOE offered short online sessions to public school teachers, but it was not adequate to familiarize them with the software. In addition, onsite training was provided in schools, but this had major challenges due to social distancing rules, lockdowns, and nationwide curfews, which meant teachers could not attend the training [14]. As a result, ref. [14] reports that 60% of teachers in public Kuwaiti schools “initially felt overwhelmed because of a lack of preparation and shifting of educational directives”. Hence, though students have access to resources and Kuwait’s internet infrastructure is adequate for eLearning, the issue lies with institutions and the government.
The job description of an academic usually includes research, HEIs’ community services, and, of course, teaching. Once lockdown orders were implemented, HEIs promptly started preparing for online learning, eager not to disrupt education. However, some academics were not well-prepared [15]. Though such technologies and software capabilities have been available to HEIs for some years, their usage before and after the pandemic does not compare. In the GCC and international teaching environment, using technology is now a necessity [16].
Reference [13] evaluated technological integration in the time of COVID-19 in public schools. However, the literature indicates a lack of studies, and this research is one of the very few papers to examine the readiness of academics and their behavioral intentions during COVID-19, in both private and public HEIs in Kuwait. In addition, ref. [17] has advised that studies focus on organizational cultures and the impact they have on employee readiness for change in the different sectors. Furthermore, ref. [18] explains that seldom has the organizational culture of HEIs been examined, and those that have were mainly European institutions [19,20]. Though [18] has contributed to this gap by examining the culture at Tabuk University in Saudi Arabia (reporting a dominant group culture), it is still seen as one study investigating a single university. Hence, findings are not generalizable, and such a deficiency in research is concerning, considering not only the amount of change HEIs have experienced in the past few decades but also the expeditious modifications academics in these workplaces have had to implement as a response to COVID-19. In addition, HEIs have the responsibility to graduate qualified students into the workforce and numerous industries, which they do through their academics. Therefore, understanding what type of organizational culture academics are working within can give a better understanding on how to deal with such transformations [18]. Consequently, the objective of this research is to first identify the organizational characteristics of HEIs in Kuwait and how this impacts the level of academics’ readiness for change and behavioral intention.
The structure of the paper is as follows: the literature review covers the role of eLearning in education sustainability (which serves as the context of our study) and the four types of organizational cultures and individual readiness for change. This leads to the development of the present study’s six hypotheses. Section 3 is then responsible for explaining the research design, which includes how data were collected, choice of analysis methods, and their subsequent results. It is later followed by a discussion which delves further into the results and outcomes of the analysis provided, which leads to the present study’s theoretical contributions and empirical implications. The last section of this paper revises the conclusions of this research along with detailing its limitations which other studies can build upon.

2. Literature Review and Hypotheses Development

2.1. Importance of eLearning for Higher Education Institution Sustainability

Though the objectives of HEIs have not changed since their establishment, over the past few decades they have had to acclimate to volatile technological political and social environments [21]. The true value of online learning and how it can sustain education regardless of circumstances was proven during the COVID-19 outbreak [22]. Education could not have continued during this time without technological assistance [1,2]. Some students were stuck at home for months, either due to lockdowns or restrictions on movement [23]. Additionally, ref. [24] explains that “higher education institutions are the knowledge incubators, and they serve as a backbone of innovation and prosperity. HEIs also contribute to society while providing skilled human resources as input to the industry” (p. 23). With this role and social responsibility, the halting of education is not an option. The authors of [25] write that “with the eLearning laboratories and applications, most education bodies have managed to sustain their curricula delivery. eLearning has emerged as a successful tool that sustains Higher Education in crisis and emergency times” (p. 361). Thus, if HEIs and students were equipped with eLearning capabilities, access to learning opportunities mostly continued [26]. Reference [27] recommends eLearning as an effective and sustainable learning solution not only during COVID-19, but also post-COVID-19. Though traditional learning methods offline may be favored by students [22], refs. [23,27] found that students are still willing to partake in eLearning in some form even if restrictions on physical classrooms are lifted. Reference [6] also endorses the flexibility eLearning provides and how it enables sustainable education, thus leading to its popularity. While we have reviewed the benefits of eLearning and its essentialness to higher education sustainability, challenges such as “engaging students, catering to students’ needs, and providing opportunities for holistic learning” have been noted in the literature, e.g., in [23], (p. 13), in addition to difficulty in understanding lessons and a lack of interaction with classmates from college students in developing countries [22].
This research will first examine what types of organizational culture exist in Kuwaiti HEIs and how this impacts their readiness for change with regards to eLearning during the COVID-19 outbreak. Then, we will evaluate the behavioral intention of teaching staff to continue to use eLearning after the pandemic. With this information, managerial implications on how to lead a more sustainable operation of HEIs will be proposed.

2.2. Organizational Culture

Organizational culture has been described as the value and belief system that is shared among members of an organization [28]. Organizational culture implies the objectives, set of beliefs, and principles practiced by members which are usually not defined explicitly by name but guide business practices nonetheless [29]. These systems impact how individuals act and conduct themselves in an organization. Organizational culture has become a widely explored topic, with much research focused on highlighting the effects of culture on organizational performance [30,31,32]. Yet, there is growing amount of research within the domain of change management underlining the impact that organizational culture has on change implementations [17,33,34]. For instance, ref. [35] highlights that organizational culture is key to the successful implementation of change initiatives. The authors of [36] claim that disregarding the impact of organizational culture is a major hurdle that management faces when implementing change initiatives. Thus, they recommend that organizations first determine what type of culture they practice before executing any change plans.
Given the vast amount of research conducted on organizational culture, many instruments have been developed to assess the construct. The Competing Values Framework (CVF) is one of the most widely applied models used to measure organizational culture [37] and has been used on an array of studies to identify culture as well as its impact on other organizational functions, e.g., [38,39]. The framework is based on two axes that reveal different value orientations. The horizontal axis indicates the degree to which a corporation focuses its attention on its external versus internal operations and functioning. On the other hand, the vertical axis reveals the degree to which an organization has a control versus flexibility behavior [40]. As a result of these two scopes, there are four types of organizational cultures developed, which include group, developmental, hierarchical, and rational cultures. However, it is important to note that these different types of culture are dominant and not mutually exclusive. As a result, rather than organizations comprising a single dominant culture, they may consist of a mix of all four cultures [40]. Several studies have applied the scale and found it to be reliable [38,41,42,43].
With regards to the organizational cultures found in HEIs, ref. [18] reports the dominant culture among academic staff and employees in Tabuk University, Saudi Arabia, as the group culture. Within this sample, a Mann–Whitney U test confirmed that the presence of characteristics of the clan culture type in the university was more strongly perceived by academic staff. A dominant group culture is echoed in other studies of individual and collectivist societies, as noted by the authors of [44] in a study that took place in American universities and colleges and [19], which took place in public HEIs in Malaysia. Reference [18] reflects that the dominant group culture found in their sample may be attributed to the wider national culture of Saudi Arabia, based on the work of [45], and can also be extended to Malaysia [19]. However, it contradicts [44]. Hence, we posit that regardless of the geographic location, it may or may not be reflected within the educational institution itself.

2.3. Individual Readiness for Change

When undergoing any change, organizations must have the support of their employees. It has been established that employees often dictate the outcome of implementing change. Similar to [46], this research adopts readiness for change from an individual-level perspective as opposed to an organizational-wide viewpoint. Not attaining the backing of employees in such transformations can lead to failure in implementing substantial organizational change [47]. Therefore, change initiatives cannot be carried out in an environment where staff are reluctant to support and cooperate in change implementation [48]. When decision makers are aware of their culture, they can customize their actions to better engage employees in change initiatives [49].
Individual readiness for change (IRFC) is generally defined as the “beliefs, attitudes, and intentions regarding the extent to which changes are needed and the organization’s capacity to successfully undertake those changes”, [46], (p. 681). IRFC involves employees evaluating the benefits that they themselves and other employees may attain from executing the change, the abilities the individual and organization have for implementing the change, and whether there is a need for the change to occur in the first place [50,51]. As employees play a major role in the success or failure of implementing change, ref. [46] writes that low levels of change readiness can be the main reason why organizations do not implement change successfully. Therefore, proper IRFC and how organizations plan, introduce, and execute change are crucial in gaining the support of employees and ultimately increasing the likelihood of successful change.
Earlier studies in the field of IRFC regarded the variable as one-dimensional. The authors of [51] examined IRFC as multidimensional, stating that it includes four dimensions: employees’ belief in their ability to carry out the proposed change, management support for the change, the appropriateness of change, and, lastly, personal belief of the change.
Though the impact organizational culture has on IRFC has been established [47,52], only a few studies have examined this relationship. References [17,47,53] all examined the impact that group, adhocracy, market, and hierarchy cultures have on IRFC in an array of sectors and countries. Firstly, the study conducted by [47] took place in Australia with a sample of government employees. Results showed that group culture was the only significant and positive culture on IRFC. The remaining culture types (adhocracy, market, and hierarchy) were reported as insignificant and negative when correlated to IRFC. In [17], the authors examined one key employee in organizations within the manufacturing industry located in Syria. The outcome conveyed that both group and adhocracy were significant and positively correlated with IRFC, while market and hierarchy culture are significant but negative. Lastly, ref. [53] chose to study the organizational changes taking place in a large Indonesian family firm that had decided to become a publicly listed company. They conducted this by distributing 264 surveys to 21 different departments, and the results showed that all four cultures had a significant positive effect on IRFC.

2.4. Organizational Culture Types and Readiness for Change

An organization’s culture can impact the degree to which employees feel ready for a change implementation [52]. Organizations must understand what type of OC exists within their organization prior to implementing change to better customize and address their change initiatives before execution [36]. Hence, it is surprising that there is a deficiency of inquiry on the effect different OC types can have on readiness for change, given its importance [47].
A popular framework developed by [30] describes how organizations’ culture can be sorted into four categories based on factors such as their flexibility, focus (internal or external), stability and control, and levels of differentiation and integration. In the section below, we review four types of OC as adapted from [30] and hypothesize their impact on academics’ readiness for change.

2.4.1. Adhocracy Culture

An adhocracy culture is often described as being externally focused. When partaking in outward-looking, organizations become aware that they need to be innovative and accustomed to risk-taking to outperform the market or become trendsetters [54]. To accomplish this, organizations foster a creative, entrepreneurial, and flexible culture where unique initiatives are encouraged and the organization has a fast-moving ability [55]. Organizations that report having high adhocracy culture levels support commitment to experimentation and acquisition of the latest resources and skills. In congruence with this, employees in such organizations are more likely to have higher levels of readiness for change. Based on this argument, the following can be hypothesized:
H1. 
The adhocracy culture in HEIs will be positively associated with the level of an academic’s readiness for change.

2.4.2. Group Culture

Group culture (also referred to as “clan culture”) can be described as a collaborative organization with open team spirit [54]. Group culture places importance on teamwork, where consensus is attained [20]. These organizations practice internal cooperation and relationship-building. Human resources development plays an active role by providing training to employees to better equip them for the change initiative [51,56]. By developing an internal focus on employees, group culture promotes acceptance of change among its employees because they trust their workplace and believe the change is for the good of the organization [55]. Moreover, employees believe they will personally gain benefits when participating in the change initiative. Such cultures are likely to lead to employees feeling confident that they can achieve change due to their participation and awareness of the change proposals and processes. Morale in group culture organizations is also high, and the workplace can feel like an extended family. Hence, organizations with a group culture are more likely to be ready for change [47]. Based on the literature, the following hypothesis is developed:
H2. 
The group culture in HEIs will be positively associated with the level of academics’ readiness for change.

2.4.3. Hierarchy Culture

Hierarchy cultures function through bureaucracy and coordinated processes, which often stem from upper management. This culture is guided by procedures and rules [55]. As decision making is usually centralized, there is little opportunity for employees to express creativity, and change is often resisted. As hierarchy-dominant cultures are mainly focused on their inward setups, they may prioritize stability, efficiency, and the smooth running of their operations [56,57]. As a result, they may be uninformed of market changes and demands and/or stagnant regarding changes that should occur. Based on this review, it can be hypothesized that:
H3. 
The hierarchy culture in HEIs will be negatively associated with the level of academics’ readiness for change.

2.4.4. Market Culture

Market culture tends to prioritize increasing profits and market share [30,56]. This can be a result of competitive or hostile environments and/or management goals [55]. As a result of this bottom-line culture, employee morale and delivering supporting resources to employees to equip and prepare them for change may not be viewed as an urgent matter [57]. However, they are more internally focused than other cultures, due to their prioritization of market position, which requires some level of internally focused efforts to ensure the overall goal of customer satisfaction and profitability is reached. Employees operating within a market culture are hypothesized to have lower levels of readiness when approaching change initiatives. Therefore, it can be hypothesized that:
H4. 
The market culture in HEIs will be negatively associated with the level of academics’ readiness for change.

2.4.5. Behavioral Intention to Implement eLearning Changes

Behavioral intention refers to predicting the probability of an individual performing a particular kind of action in the future. The behavioral intention of students using eLearning has been studied in developing countries using different models (e.g., [58], where one took place in Saudi Arabia; ref. [59] used the Technology Acceptance Model (TAM)). However, little on academic staff in HEIs has been included as a sample. Even so, the objectives of the studies vary in comparison to this research. For example, ref. [60] examined academics’ intention and behavioral patterns in implementing eLearning in Malaysia via the unified theory of acceptance and the use of technology (UTAUT) with an additional academic’s ethical component. Reference [61] also used TAM to measure post-COVID-19 online teaching intention of academics working at universities and colleges in India. Keeping in mind that it is the decision of the professor and not the student on how much work would be allocated to eLearning or a physical classroom, studies examining different aspects of how this is impacted are important for decision makers.
Studies indicate that readiness for change has direct positive impact on the behavioral intention to support eLearning changes’ implementation [62,63]. Thus, it is proposed that:
H5. 
Academics’ readiness for change has a positive impact on their behavioral intention to support eLearning changes’ implementation.

2.4.6. The Impact of Readiness on Behavioral Intention to Implement eLearning Changes

Previous studies reported that employee readiness for change is significant as a mediator and fully mediated the relationship between transformational leadership and affective commitment to change [64]. Similarly, ref. [65] establishes readiness of employees to change as a significant mediator in the relationship between change leadership and affective commitment to change. Reference [24] also reports that readiness for change can influence organizational performance in HEIs as a mediating role. Furthermore, readiness for change is the most contributed variable to ‘commitment to change’ in comparison to organizational readiness for change, which was positive, and change leadership, which was not significantly correlated to ‘commitment to change’. As a response to these results, it is recommended by the authors of [66] that organizations should be attentive when it comes to employees’ needs to ensure their commitment to change.
A thorough review of the literature indicates that organizational culture has a significant impact on employees’ readiness for change, e.g., [47,53], and that readiness for changes has a positive impact on behavioral intention to change’s implementation. Therefore, this research proposes academic readiness for change as a mediator through which the organizational cultures have an indirect impact on behavioral intentions:
H6. 
Academics’ readiness for eLearning changes mediates the relationship between OC and behavioral intention to support eLearning changes’ implementation.

3. Materials and Methods

Based on the framework discussed in the literature review [30], this study aims to identify the cultures that HEIs in Kuwait operate within and their impact on academic readiness for change as displayed on the conceptual framework in Figure 1. This section will describe the tools used to collect data as well as justification for the sample and its size. Moreover, the reliability and validity of the data collection instrument and the methods used for analysis (e.g., multiple regression analysis and structural equation model) are further outlined. This section also reports the results of the hypotheses.
The research instrument employed was based on the previous works of other studies with similar objectives, e.g., [17,47,53]. The survey was adapted from [30] to develop the cultural profile and the organization assessment part of the survey. To measure the readiness components, the present study utilized an instrument developed by [51]. In addition, the demographics collected from the sample (academic position, experience, educational qualifications) were adapted from [18].
The change initiative studied in this research includes to which degree respondents felt positive about and prepared for the implementation of online learning due to COVID-19 implications. A 5-point Likert scale was used to assess 25 items. These included teaching faculty evaluating the benefits of online learning, their individual capabilities, HEIs’ capabilities, and the need for this change. To customize the survey for the sample and type of change, an HEIs context and online learning change initiative were included. A pilot study was conducted, and the survey was distributed to a group of academics. Once minor changes were made, the final survey version was distributed to teaching staff at two public institutions (Kuwait University and the Public Authority for Applied Education and Training (PAAET)) and approximately 12 private institutions. A sample of 218 surveys were usable and analyzed. This study approached faculty, as they would have all taught online and implemented eLearning due to restrictions on conducting virtual classes. Hence, we can consider this sample to be the key agent of change and a reliable source of information for readiness for online learning during the time of COVID-19.

3.1. Analysis and Results

This section will explain the steps taken to complete the data analysis. Structure equation modeling with partial least squares was used to analyze data by using SmartPls 3 software. The total number of usable surveys gathered was 218. PLS path modeling evaluated the model for construct reliability, convergent validity (average variance extract), and discriminant validity. The structural model was then used to determine the significance and relevance of the hypothesized relationships.
Table 1 shows that all the constructs, i.e., ADH, BI, GRO, HIE, employee readiness for change (ERFC), and MAR, met the required standard limits of composite reliability and Cronbach’s Alpha, with values greater than 0.6 and 0.7 [67], respectively, corresponding to each construct, which confirms the construct reliability. In addition, the average variance extracted (A.V.E.) values were greater than 0.5, confirming convergent validity [68].

3.2. Descriptive Statistics

With regards to the demographics of our sample (as shown in Table 2), females made up the majority of respondents (54.6%). Most respondents were between the ages of 31–40 (41.7%), followed by 41–50 years old (37.2%) and 51 years and above (11.9%), and the remaining were aged between 21–30 years old (9.2%). For the place of employment, 54.6% of respondents were from a private institution, while 45.4% worked in a public institution. The majority of respondents had experience ranging between 1–5 years (31.2%), followed by 11–15 years (22.9%), 16–20 years (18.3%), 6–10 years (16.1%), and 21 years and above (11.5%).

3.3. Correlation Analysis

GRO, ADH, MAR, HIE, ERFC, and BI were all subjected to a Pearson correlation analysis to measure how those factors are correlated with each other. In order to assess the strength of the associations, Cohen’s standard was applied, with coefficients between 0.10 and 0.29 denoting a small effect size, 0.30 to 0.49 denoting a moderate effect size, and coefficients above 0.50 denoting a large effect size [69]. Additionally, an alpha value of 0.05 was used to analyze the correlation results. With a correlation of 0.23, which denotes a small effect size (p < 0.001, 95.00% CI = [0.10, 0.36]), a significant positive association between GRO and ERFC was found. This shows that ERFC tends to increase as GRO increases. Furthermore, a small effect size was seen between BI and GRO, with a correlation of 0.28 showing a significant positive correlation between the two variables (p < 0.001, 95.00% CI = [0.15, 0.40]). This implies that BI tends to increase as GRO increases. Moreover, ERFC and BI showed a significant positive relationship, with a correlation of 0.74, indicating a large effect size (p < 0.001, 95.00% CI = [0.67,0.79]). This implies that BI tends to increase when ERFC increases. The correlational results are shown in Table 3.

3.4. Multiple Regression Analysis

The data are analyzed through partial least squares structural equation modeling (PLS-SEM). The empirical results indicated that HIE (β = 0.292, t = 2.959, p = 0.003) and MAR (β = 0.329, t = 2.603, p = 0.010) are significant predictors of ERFC. Moreover, the significant influence of ERFC on BI (β = 0.751, t = 19.918, p = 0.000) was also observed. Nevertheless, ADP and GRO were shown to be insignificant determinants of ERFC. The indirect effect of MAR on BI (MAR → ERFC → BI) (β = 0.247; t = 2.452; p < 0.05) and HIE on BI (HIE → ERFC → BI) (β = 0.219; t = 2.992; p < 0.05) was also found to be significant. The structure of the model is demonstrated in Figure 2. Constructing the structural model is the next step after confirming the measurement model. This can be accomplished by estimating path coefficients via a bootstrapping procedure [68].
Table 4 demonstrates the results of path analysis. The results revealed that there is an insignificant direct influence of ADH on ERFC (β = −0.138, t = 0.845, p = 0.399) and GRO on ERFC (β = −0.034, t = 0.254, p = 0.800). Therefore, H1 and H2 were rejected. Moreover, the impact of HIE on ERFC was found to be positively significant (β = 0.292, t = 2.959, p = 0.003). Hence, H3 was supported. The direct influence of ERFC on BI was also tested, and it was found that there is a positive and significant influence of ERFC on BI (β = 0.751, t = 19.918, p = 0.000). Thus, H6 was supported. The results also recognize the positive, significant effect of MAR on ERFC (β = 0.329, t = 2.603, p = 0.010). Therefore, H4 was also accepted.
This study was also able to collect information about the mediating role of ERFC (H5). The indirect effect of MAR on BI (MAR → ERFC → BI) (β = 0.247; t = 2.452; p < 0.05) and HIE on BI (HIE → ERFC → BI) (β = 0.219; t = 2.992; p < 0.05) was significant. However, the indirect impact of GRO on BI (GRO → ERFC → BI) (β = −0.026; t = 0.254; p > 0.05) and ADH on BI (ADH → ERFC → BI) (β = −0.104; t = 0.830; p > 0.05) was found to be insignificant.
We also find that there are significant differences between private and public universities for GRO, ADH, MAR, and ERFC, as can be seen in Table 5. For GRO, the result of the two-tailed independent samples t-test was significantly based on an alpha value of 0.05, t(216) = 2.27, p = 0.024, indicating that the null hypothesis can be rejected. This finding suggests the mean of GRO was significantly different between the private universities and public universities. Additionally, the same results were found in ADH; the result of the two-tailed independent samples t-test was significant based on an alpha value of 0.05, t(193.62) = 2.69, p = 0.008, indicating that the null hypothesis can be rejected. This finding suggests that the mean of ADH was significantly different between the private university and public university. However, HIE and BI were not found to be significant between private universities and public universities.

4. Discussion

The findings of this study have shown that ERFC is strongly influenced by hierarchy and market culture, which negates most previous studies [18]. For example, ref. [55] used the CVF approach for data collection among lecturers and reported that group culture was the most dominant among private universities in an Indonesian province. This dominant group culture is even preferred by students, as found by [56], who linked the CVF organizational culture to students’ commitment to the university and found that the stronger the clan culture, the more the students identified with the university and thus were more amiable to change. They also found that market culture, which fosters ideas of competition, and hierarchy culture, which is based on formal procedures, are likely to be predicters of a decrease in students’ commitment to change. A study in Turkey similarly reported that the most common type of organizational culture that academicians associate with their institution is the hierarchy culture [70]. However, we note that it took place before the pandemic and thus findings may not be generalizable.
Results also demonstrated that ERFC had a strong positive influence on behavioral intention. The paper also found that all CVF culture types positively correlated with ERFC as well as BI, supporting the argument found within the literature. We can infer from the analysis of this paper that out of all the CVF culture types, market and hierarchy culture types are the most supportive for ERFC and BI components. This indicates that organizations dominated by market and hierarchy culture facilitate better acceptability of change. Academics are more likely to have higher levels of readiness for change when they perceive their work environment to have the characteristics associated with hierarchy and market culture types. Hence, procedures and instructions are more effective from the top-down and when staff are given goals that are set in quantitative economic terms and based on external competitors [30]. In addition, teaching staff working in such environments intend to use elements from online learning even after COVID-19 restrictions are lifted.
The present finding has negated previous hypotheses in the literature, in which our study empirically demonstrates that in the context of the region, examples such as formal rules, policies, and procedures are better facilitators of people’s acceptance of change. In contrast to the literature that proposes that a lack of rules can enable creativity and, thus, change [17,47], our findings find that fixed rules and a structured focus incentivize people within organizations toward change and acceptance of these changes if it comes as a form of policy and standard procedural processes. Moreover, the findings suggest that the focus on profit margin and market share can help galvanize the members within the organization toward a common purpose, better efficiency, and, thus, improvement of the organization as a whole. The seemingly contradicting results of the present study to some of the literature may be attributed to the region and the sample represented. The sample representing the Middle East region is also a representation of its national culture, which may have affected the results of the present study, such that the national culture is considered to be highly collective and high on power distance and uncertainty avoidance [45]. A region high on power distance and uncertainty avoidance will certainly not respond favorably to sudden changes and vague responses not coming via a top-down approach. As such, our results find that hierarchy and market culture values rather than group culture or adhocracy are better indicators that organizational members are more likely to implement and accept change within their organizations.

5. Theoretical Contribution

A comprehensive review of the literature indicates that there is a lack of research on the influence of all the organizational culture types on academics’ readiness and behavioral intention to implement eLearning changes in HEIs. This study is one of the few to examine the readiness for change of academics during COVID-19 and their behavioral intentions after the pandemic to use eLearning components. The contribution of this study lies in further understanding the impact of organizational culture on academics’ readiness for eLearning changes and behavioral intention to support eLearning implementation. In addition, although organizational culture in HEIs has been investigated by previous studies, they often include respondents from a single HEI, or they have academics and staff compose their samples. This study, however, collects data solely from academics, as they would be considered the change agents of eLearning, and contrasts results from public and private HEIs. The findings further offer an original contribution by confirming the mediating role of academics’ readiness for eLearning changes in the relationship between OC and behavioral intention.

6. Empirical Implications

This research offers recommendations to management and decision makers in Kuwaiti HEIs. Firstly, eLearning is a crucial tool for the industry, and while the COVID-19 pandemic accelerated the adoption of eLearning, it is predicted that eLearning will be more normalized even after the pandemic. From the results attained, the behavioral intention of academics points toward the HEI environment being transformed into a hybrid of traditional and online learning. Other reasons for the adoption of eLearning could be another pandemic, natural disasters, programs set up to be taught online, or simply for convenience. Therefore, we suggest that decision makers should ensure their academics have adequate training to keep up with new methods and versions of eLearning due to the fast pace of technological advances. In addition, HEIs should warrant the availability of funding for equipment and supporting infrastructure to cope with such changes and the smooth running of teaching processes. Lastly, reflecting and maybe even altering Kuwaiti HEIs’ cultures to those with more adhocracy or group traits would also be recommended. The empirical suggestions made above focus on the capabilities of academics and rapid advances in external organization technology. Therefore, this requires constant upgrading and adaptation to reflect the external environment to ensure the sustainability of HEIs, which is not currently attained in organizational cultures of Kuwaiti HEIs but is present in organizations that have predominant adhocracy and group cultures.

7. Conclusions and Limitations

This paper empirically examined the effect of all four organizational culture types of the CVF model on the components of ERFC as well as BI, which few studies have shed light on. Moreover, these concepts were examined in the State of Kuwait’s’ public and private HEIs, providing the literature on change management with a sample and region that have been otherwise excluded and under-represented in the literature.
Respondents were asked if they were employed in public or private institutions. Based on this, we were able to identify that the dominant culture in the public sector is hierarchy, while private organizations are dominated by both hierarchy and market cultures. Such findings contradict not only the general change management literature but also studies conducted in HEIs which report group culture as being significant [18]. Private HEIs in Kuwait are often owned by private or publicly listed companies. The objective of any company is to gain profits. These HEIs do so by competing to gain internal student scholarships from the Public Universities Council (PUC). Internal scholarship students attending HEIs make up a sizeable amount, if not most, of the student population in the private sector. These students often apply for internal scholarships because public institutions simply reach their full capacity and cannot accept all high school graduates. In addition, staff of private HEIs, who are mainly expatriates, are expected to comply with changes to ensure the operation and profitability of the institution. Not doing so can result in employee turnover. Therefore, a predominant market culture in the private higher education sector conforms to such organizational objectives. The public sector, on the other hand, has no competition, which has been to blame for its downward trajectory of rankings in the past decade, in addition to the large number of student applications that by far exceed faculty members. It has also been asserted that teaching overloads and budget deficits have resulted in staff neglecting research. Similar issues have been reported in PAAET and Kuwait University. Faculty in the public sector, who are mainly Kuwaiti, secure their jobs by applying for postgraduate scholarships abroad once they graduate from the public university. Then, once they secure their postgraduate degree from abroad, lifelong employment from their sponsor (e.g., Kuwait University) is basically guaranteed, regardless of individual performance. When operating in such conditions, it makes sense as to why the market culture is not dominant in the public higher education sector and only in private HEIs.
A limitation of this research is its cross-sectional approach. A longitudinal study would benefit the literature by detecting developments within the CVF model cultures’ impact overtime. It is recommended that this research is similarly replicated in other sectors in Kuwait to highlight discrepancies between the public and private sectors. This is especially important due to two main reasons. Firstly, the Kuwaiti government is the biggest employer in the country. Most workplaces are digitalizing their workflow, and this has been communicated by the Kuwaiti government through the “Kuwait 2035 Vision” strategic plan. Hence, it would be beneficial for authorities to be aware of how ready their employees are to accomplish such a crucial part of the country’s strategy.

Author Contributions

Conceptualization, S.A.-S. and A.A.-S.; methodology, A.A.-K.; formal analysis, A.A. (Ahmad Alsaber); writing—original draft preparation, S.A.-S. and A.A.-S.; writing—review and editing, S.A.; supervision, A.A. (Amer Alaya). All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

The study was conducted in accordance with the Ethics Committee of Kuwait Technical College (date of approval 1 June 2022).

Informed Consent Statement

Informed consent was obtained from all subjects involved in the study.

Data Availability Statement

The data presented in this study are available on request from the corresponding author.

Conflicts of Interest

The authors declare no conflict of interest.

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Sustainability 14 15824 g001 550
Figure 1. Conceptual framework.
Figure 1. Conceptual framework.
Sustainability 14 15824 g001
Sustainability 14 15824 g002 550
Figure 2. Structural Equation Model (SEM).
Figure 2. Structural Equation Model (SEM).
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Table
Table 1. Convergent validity result.
Table 1. Convergent validity result.
Factor Cronbach’s AlphaRho_AC.R.A.V.E.
ADH0.8770.9210.9130.723
GRO0.9240.9460.9390.721
HIE0.8050.8200.8840.717
MAR0.8210.8320.8930.737
ERFC0.8700.8760.9070.661
BI0.8880.9020.9310.818
Table
Table 2. Descriptive Statistics.
Table 2. Descriptive Statistics.
BasisCategoriesF%
GenderMale9945.4
Female11954.6
Age21–30209.2
31–409141.7
41–508137.2
51 and above2611.9
EducationBachelor’s4319.7
Master’s6429.4
Doctorate11150.9
EmploymentPrivate University11954.6
Public University9945.4
Academic rankInstructor7936.2
Adjunct2310.6
Assistant Professor7333.5
Associate professor219.6
Professor2210.1
Experience1–5 years6831.2
6–10 years3516.1
11–15 years5022.9
16–20 years4018.3
21 years and above2511.5
Table
Table 3. Pearson correlation results.
Table 3. Pearson correlation results.
Org. Culture GROADHMARHIEERFCBI
GRO—
ADH0.764 ***—
MAR0.637 ***0.689 ***—
HIE0.606 ***0.537 ***0.424 ***—
ERFC0.234 ***0.209 **0.341 ***0.328 ***—
BI0.28 ***0.208 **0.441 ***0.238 ***0.74 ***—
Note. ** p < 0.01, *** p < 0.001.
Table
Table 4. Direct impact path analysis of ERFC and hypothesis testing.
Table 4. Direct impact path analysis of ERFC and hypothesis testing.
HypothesisPathβStandard Deviationt-Valuep-ValueResult
Direct
Relationship		H1ADH → ERFC−0.1380.1640.8450.399Not Supported
H2GRO → ERFC−0.0340.1360.2540.8Not Supported
H3HIE → ERFC0.2920.0992.9590.003Supported
H4MAR → ERFC0.3290.1262.6030.01Supported
H6ERFC → BI0.7510.03819.9180Supported
Indirect
Relationship		H5.1ADH → ERFC → BI−0.1040.1250.830.407Not Supported
H5.2GRO → ERFC → BI−0.0260.1020.2540.799Not Supported
H5.3HIE → ERFC → BI0.2190.0732.9920.003Supported
H5.4MAR → ERFC → BI0.2470.1012.4520.015Supported
Table
Table 5. Comparison between private and public universities in Kuwait for study variables.
Table 5. Comparison between private and public universities in Kuwait for study variables.
Private Universities (n = 119)Public Universities (n = 99)Total (n = 218)p-Value
GRO 0.0241
Mean (SD) 3.4 (1.0) 3.1 (1.1) 3.3 (1.0)
Range 1.0–5.0 1.0–5.0 1.0–5.0
ADH 0.0071
Mean (SD) 3.3 (1.0) 3.0 (1.1) 3.2 (1.1)
Range 1.0–5.0 1.0–5.0 1.0–5.0
MAR <0.0011
Mean (SD) 3.6 (0.9) 3.1 (1.1) 3.3 (1.0)
Range 1.0–5.0 1.0–5.0 1.0–5.0
HIE 0.1771
Mean (SD) 3.6 (0.9) 3.4 (1.1) 3.5 (1.0)
Range 1.0–5.0 1.0–5.0 1.0–5.0
ERFC 0.0481
Mean (SD) 3.9 (0.8) 3.6 (1.0) 3.8 (0.9)
Range 1.0–5.0 1.0–5.0 1.0–5.0
BI 0.0781
Mean (SD) 4.0 (0.8) 3.8 (1.1) 3.9 (0.9)
Range 1.0–5.0 1.0–5.0 1.0–5.0
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Al-Shamali, S.; Al-Shamali, A.; Alsaber, A.; Al-Kandari, A.; AlMutairi, S.; Alaya, A. Impact of Organizational Culture on Academics’ Readiness and Behavioral Intention to Implement eLearning Changes in Kuwaiti Universities during COVID-19. Sustainability 2022, 14, 15824. https://doi.org/10.3390/su142315824

AMA Style

Al-Shamali S, Al-Shamali A, Alsaber A, Al-Kandari A, AlMutairi S, Alaya A. Impact of Organizational Culture on Academics’ Readiness and Behavioral Intention to Implement eLearning Changes in Kuwaiti Universities during COVID-19. Sustainability. 2022; 14(23):15824. https://doi.org/10.3390/su142315824

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Al-Shamali, Sarah, Ahmed Al-Shamali, Ahmad Alsaber, Anwaar Al-Kandari, Shihanah AlMutairi, and Amer Alaya. 2022. "Impact of Organizational Culture on Academics’ Readiness and Behavioral Intention to Implement eLearning Changes in Kuwaiti Universities during COVID-19" Sustainability 14, no. 23: 15824. https://doi.org/10.3390/su142315824

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