Adoption of Sustainable Technologies during Crisis: Examining Employees’ Perception and Readiness across Cultures

Abstract

Studies on technology adoption have generally found significant variations across cultures, with the literature suggesting a strong reluctance to adopt new technologies, particularly in non-western countries. Given the accelerated increase in remote working and collaboration during the COVID-19 crisis, this paper compares the determinants of sustainable technology adoption by employees across Western and Non-Western countries. Using a survey of 302 participants from 13 Western and non-Western countries, four proposed hypotheses were tested using structural equation modelling and multi-group comparisons. The empirical results suggest a significant positive relationship between perceived ease of use and usefulness, influencing employees’ attitudes towards using sustainable technologies. We also found a significant positive effect between attitude towards using sustainable technologies and actual use. The indirect effect of perceived usefulness and ease of use on actual use via attitudes towards using was also positive and significant. We, however, found no significant differences between Western and non-Western countries in terms of the adoption of sustainable technologies.

1. Introduction

Since the outbreak of the COVID-19 pandemic in late 2019, millions of people in the Western and non-Western world have been forced to work from home, making it the new standard format of working [1,2]. Due to social distancing requirements, the only option companies have had to implement sustainable technologies to stay afloat while maintaining their social responsibility of keeping staff employed. A wide range of sustainable technologies such as Zoom, Skype, Microsoft Teams, Google Meet, and other related technologies that support online meetings, collaborations, and video calls have been implemented. According to Microsoft Inc. [1], nine out of ten firms in Australia have taken on sustainable technologies to ensure continuity of production and employment. Microsoft Teams’ use has increased by over 70% since the working from home models were implemented. In South Africa, the sustainable model has been widely implemented, and 40% of surveyed companies indicated the desire of their employees to continue working from home in the long term.

Reports in different media outlets on adopting sustainable technologies by employees in Western and non-Western countries seem to experience a similar trend. For example, while there was limited usage among employees in Western countries during the early stage of the pandemic [3], the situation was no different in non-Western countries such as Uganda, where some employees revealed limited usage of stainable technologies around the same period [4]. Given that working from home using relevant technologies is likely to continue in the new future, factors influencing the adoption of sustainable technology must be investigated to inform company and government decisions on suitable strategies for ensuring work continuity and economic and environmental sustainability [5].

The adoption of sustainable technology in this crisis is a matter of survival for firms as it does not only impact the way business is conducted [5,6] but also reduces CO₂ emissions significantly [7,8]. Sustainable technologies consider the long-term and short-term impact of business and human activities on the environment. These technologies are designed to positively impact the environment and help address other public health issues arising from the pandemic. Zoom, for example, estimates that “enabling millions of users to work from home during the COVID-19 pandemic, the platform helped customers reduce their CO₂ emissions by more than 55 million metric tons in 2020—roughly equal to taking 11 million cars off the road” [7,8].

Existing literature on sustainable technology adoption focuses on the cost components [9,10], risk factors [11,12], international environmental standards, regulations, and customer expectations [13,14], utilisation by large enterprises and small-medium enterprises [15,16] and reasons behind adoption and usage of these technologies with limited attention on employees [17,18]. Again, a large body of research has investigated the adoption of various technologies across different sectors [7,9,11]. However, there is a scarcity of empirical research on adopting sustainable technologies during a crisis. Employees have had no option but to use sustainable technologies in isolation. In investigating technology use during the pandemic, the focus has instead been on the pandemic’s impact on businesses or how businesses have applied technology to survive [13], with little attention paid to understanding the determinants of employee technology adoption. Thus, additional research is essential for improving our understanding of the determinants of sustainable technology adoption. Further investigation of the determinants will also contribute to the literature on technology adoption across cultures [15,17]. Existing studies [19,20,21] have found that cultural differences account for variations in technology adoption in Western and non-Western countries; thus, additional studies across different cultures contribute to this body of knowledge.

This paper addresses the limitation in research on the determinants of technology use during a crisis period. It contributes to the body of research on technology adoption across cultures by investigating the adoption of sustainable technology among Western and non-Western countries. The Western countries include Australia, Canada, New Zealand, the United Kingdom (U.K.), and the United States of America (USA). The non-Western countries are Ghana, Nigeria, Uganda, Indonesia, China, and India. Based on the Technology Acceptance Model (TAM) [22], this paper argues that sustainable technology is influenced by perceived ease of use, perceived usefulness, and attitude towards the technology. Specifically, the paper seeks to answer these research questions (1) What is the impact of perceived ease of use of sustainable technologies on the perceived usefulness of sustainable technologies in Western and non-Western countries? (2) What is the impact of perceived ease of use and usefulness of sustainable technologies on the attitude towards using sustainable technologies in Western and non-Western countries? (3) What is the impact of perceived ease of use, perceived usefulness, and attitude towards using sustainable technologies on the actual use of sustainable technologies in Western and non-Western countries? (4) Does attitude towards using sustainable technologies mediate the relationships between perceived ease of use and perceived usefulness in the actual use of sustainable technologies in Western and non-Western countries?

This paper makes two key theoretical contributions concerning the contextual factors across Western and non-Western countries that have influenced technology usage in a situation where sustainable technology is the only viable option for companies to keep operating. First, we contribute to TAM by demonstrating that culture, a known obstacle, is no longer impossible when adopting technologies becomes the only viable alternative for employees to keep their jobs while helping their companies remain competitive. Second, we add to the growing body of studies investigating technology adoption from a cross-cultural perspective by providing comparative evidence of technology adoption.

This paper is organised as follows: the next section presents the study’s theoretical background, followed by the research methods in Section 3. The results are presented in Section 4, while the study’s discussion and implications are presented in Section 5. This is followed by the limitations, future research directions, and the study’s conclusion.

2. Theory and Hypothesis

2.1. Sustainable Technologies

Sustainable technology refers to “technology or services that have the potential to radically reduce natural resource use” [23]. They are mainly adopted to create a better quality of life given the minimal use of natural resources [24] with small waste and emissions [25]. While adopting sustainable technologies reduces our dependence on non-renewable energy resources [26], it significantly improves working conditions and efficiency, particularly during critical times like global pandemics [27]. The United Nations Environmental Program (UNEP) categorises sustainable technologies into technologies reducing carbon dioxide and other greenhouse gas emissions, material and fuel substitution, material or energy efficiency, and recycling [28]. For this study, we focus on technologies reducing carbon dioxide and other greenhouse gas emissions where a wide range of technologies such as Zoom, Skype, Microsoft Teams, and Google Meet falls. These technologies are critical because COVID-19 has forced employees to adapt the way work is done while conserving energy and reducing waste. In short, they are eco-friendly and support businesses and employees during critical times.

2.2. Technology Acceptance Model

Over the years, studies on technology have made efforts to understand technology integration in businesses. This prompted the authors to consider the appropriate means to examine these factors. In this spirit, the Technology Acceptance Model (TAM) was proposed by Davis [22]. Evidence suggests that the TAM model is the most widely used framework to study technology adoption at the organisational or individual levels [20,21,22]. Drawing insights from these studies, it can be concluded that TAM is an efficient tool to examine people’s perceptions and attitudes regarding technology adoption. Proponents of TAM have argued that behavioural attitudes significantly impact the technology acceptance level of users.

According to Ajzen [29], these behavioral attitudes are associated with individuals’ intentions to adopt the technology. Several theories such as the Planned Behaviour Model [29], Self-Efficacy Model [30], and Diffusion of Innovation Framework [31] have been employed to analyse technology adoption in the business, management, and education fields [32,33,34,35]. A literature review also reveals a strong association between culture and technology adoption [36,37,38]. Of interest among competing theories is Hofstede’s cultural model, which has gained popularity in technology adoption studies [39,40]. Dominating these studies are Hofstede’s cultural dimensions: individualism/collectivism, uncertainty avoidance, power distance, and masculinity/femininity. Several studies [19,20,41,42] confirm that local cultures substantially affect users’ intention to accept or adopt technology in their activities. Therefore, this suggests that the differences between an individual or institutional adoption of technology can be explained by culture.

When the world is experiencing partial or total lockdown due to the COVID-19 pandemic, investment in new information technology (I.T.) has escalated an exciting challenge for employers, employees, and technological innovators. Not only has this new development triggered working from home strategies, but companies have committed to providing high-quality services to clients, hence a remarkable spread of technology adoption across countries. While previous technology adoption has often centered on theoretical and empirical factors [29,35,43,44,45,46], technology adoption in 2020 has mainly been influenced by COVID-19 and not necessarily theoretical and empirical evidence. Consequently, both employers and employees have faced some difficulties in the initial stages of sustainable technology adoption.

A study by [47] shows that technology adoption by organisations in 2020 has taken a quantum leap, which is an indication that employees have had to move towards working online and mostly from home dramatically. Studies on technology adoption have generally found significant variations in adoption across cultures [20,42]. Given that the COVID-19 crisis has accelerated remote working and collaboration irrespective of geographical locations [47], we argue in this paper that there will be no significant variation in the determinants of technology adoption across Western and non-Western countries.

2.3. Culture and Technology Adoption

TAM addresses two fundamental issues affecting individual intention: perceived usefulness and ease of use. From the view of Davis [22], the perceived usefulness and ease of use drive the end user’s technological motivation. Despite the widespread concerns, no consensus has been reached regarding the fundamental determinants of technology adoption. So far, existing studies integrate TAM with psychological factors to predict individual adoption of a specific technology form [44,45]. In particular, TAM reveals that a sound understanding of technology use plays a crucial role in determining its usefulness from the user’s perspective. Notwithstanding, designing an effective strategy to promote users’ acceptance of technologies has been challenging. According to Davis [22], people by nature resist change unless they formulate an attitude towards using innovations and confirm using the technology. This, however, depends on perceived ease of use [46].

In other words, employees’ competence, and confidence to adopt or use a system are explained by behavioural intention, which is, in turn, influenced by the degree of perceived usefulness and perceived ease of use. Ajzen [29] expanded this theory within the social and community network framework to show that while perceived ease of use plays a critical role in enhancing technology adoption, external factors such as support and training or system features are crucial in explaining technological acceptance. Previous studies have widely used this model to examine the relevance of an individual’s perceived ease of use on technological acceptance [37,43,45,48]. Notwithstanding, the empirical evidence remains complex, unresolved, and varies based on context. This study argues that even though there is enough evidence that culture drives an individual’s intention, it is limited to regular times. Our argument stems from the fact that individuals are likely to ignore their culture to accept what is convenient to keep their jobs and companies afloat during pandemics.

Hypothesis 1.

Perceived usefulness of sustainable technologies will be positively and significantly influenced by perceived ease of use.

Empirically, perceived ease of use describes the user’s perception of the sum of effort required to use the system [22]. Also, if users believe that the technology will improve their activities, they tend to achieve its intended benefits. Previous studies have confirmed that when the perceived usefulness is high, positive attitudes of technology users are enhanced [20,21]. Additionally, Moon and Kim [49] confirm that the perceived usefulness and ease of use encourage positive attitudes towards technology. In conclusion, we argue that perceived usefulness and ease of use will strongly impact technology adoption.

Hypothesis 2a.

Perceived usefulness of sustainable technologies will be positively and significantly related to attitudes towards using the technology.

Hypothesis 2b.

Perceived ease of using sustainable technologies will be positively and significantly related to attitudes towards using the technology.

Attitudes towards the adoption of technology may be positive or negative. This negative or positive attitude affects how users respond to the technological change in their work environment. Empirically, a study by Teo et al. [21] confirmed the influence of technology on peoples’ attitudes. Drawing insights from this, we argue that the importance of the technology on employees’ productivity will drive their desire to exhibit a positive attitude toward the use of this technology. On the other hand, negative attitudes will not support technology’s adoption. In effect, technology implementation or adoption will be successful when positive attitudes are exhibited by users [50].

Hypothesis 3a.

Perceived usefulness of sustainable technologies will be positively and significantly related to actual technology use.

Hypothesis 3b.

Perceived ease of use of sustainable technologies will be positively and significantly related to the actual use of technology.

Hypothesis 3c.

Attitudes towards using sustainable technologies will be positively and significantly related to actual technology use.

Further, it is established from previous studies that technologies with a high level of perceived usefulness attract more users. Simply put, when users trust that using technology will improve their performance at work, the adoption levels of that specific technology will be higher. On the other hand, when users perceive that it will not significantly impact productivity, they are more likely to reject it. High perceived usefulness can induce a positive attitude towards the use of technology. Moon and Kim [49] posit that users’ attitudes towards using the technology mediate the relationship between perceived usefulness and ease of use. We, therefore, hypothesize below:

Hypothesis 4a.

Attitudes toward using sustainable technologies mediate the relationships between perceived usefulness and actual technology use.

Hypothesis 4b.

Attitudes toward using sustainable technologies mediate the relationships between perceived ease of use and actual technology use.

Following the discussion above, TAM has been widely employed to investigate the acceptance and actual use of technologies, where perceived use (P.U.), perceived ease of use (PEOU), and attitude (ATT) are significant determinants of actual use [22]. Therefore, based on the research hypotheses, the proposed conceptual framework in Figure 1 is derived. The framework is based on Davis’s [22] argument that P.U. and PEOU influence individuals’ attitudes towards the actual use of a particular technology. Also, while PEOU impacts P.U., both factors directly impact actual use [51].

This study utilises the Technology Acceptance Model (TAM) to identify the factors that influence the actual use of sustainable technology. In particular, the research examines the relationship between perceived usefulness, ease of use, attitude towards technology, and actual use of “sustainable technology” by employees across different countries. The constructs of P.U., PEOU, ATT, and A.U. are theory-based and adopted from TAM, as shown in Figure 1.

3. Materials and Methods

3.1. Data

Given that this study focused on testing hypotheses derived from existing theory, the positivist approach was used [52]. Subsequently, data were collected using quantitative methods so that collected data could be analysed using statistical methods [53]. Data for this study were collected from respondents in 13 countries from May to October 2020. The respondents’ selection was based on their experience with “sustainable technology,” The collection period was selected because most organisations had adopted such technologies to ensure continuous operations. Furthermore, various countries were selected to ensure that diverse perspectives were collected [54]. The survey link was shared with respondents from different countries, and responses/were received from 13 countries, as shown in

Table 1. Countries of Respondents.

S/No.	Countries	Observations
Panel 1: Western Countries
1.	Australia	90
2.	UK	33
3.	US	26
4.	Canada	5
5.	New Zealand	3
Panel 2: Non-Western Countries
1.	Ghana	33
2.	Nigeria	38
3.	Uganda	57
4.	South Africa	3
5.	Kenya	2
6.	Indonesia	4
7.	China	5
8.	India	3

Note: Western countries are described in this study as high individualism, low power distance, high on masculinity, low uncertainty avoidance, and high long-term orientation. Non-western countries are described in this study as countries low on individualism, high power distance, low masculinity, high uncertainty avoidance, and low long-term orientation.

. We followed a four-step procedure to collect the data for analysis [53]. This process was selected to increase response rates [55].

First, a pre-testing of the study instrument was conducted to ensure the questions were accurate and easy for respondents to answer. During the pre-testing, we sampled 30 respondents, and their feedback was incorporated into the final questionnaire. Pretesting the survey ensured that content validity was met [56]. Second, the authors targeted employees from their networks. During this stage, the people identified were consulted to ascertain whether they use/have used sustainable technology. Based on their responses, some of them were excluded. Through this process, we identified about 700 employees. Third, we sent a copy of the questionnaire to the identified groups with experience using sustainable technology. They were sent through emails or social media platforms such as WhatsApp, Facebook, Linked In, and Twitter. Respondents were given about a week to respond to the questionnaire. The online survey ensured anonymity, confidentiality, objectivity, and the ability to reach a larger audience of respondents [54]. Furthermore, completing the survey online was the most suitable method given the lockdown regulations requiring people to stay home most of the time and only leave home for essential reasons.

The authors also posted on our respective social media platforms to get others to respond. The target was the unidentified friends who may be interested in participating. Eligibility criteria for respondents were added to the post. A total of 344 responses were received. About forty-two (42) cases were deleted during the cleaning up of the data because they did not meet the selection criteria. In particular, these respondents had no prior knowledge or experience with the use of sustainable technology. This was done to ensure we had a cleaned data for the analysis. The 344 responses were considered appropriate based on Roscoe’s [57] criteria, suggesting a sample size between 30 and 500 for behavioral studies. We categorised the data into two groups, where group one represents Western countries and two Non-Western Countries. This categorisation was based on Hofstede’s cultural dimension, as shown in Table 1 above.

3.2. Instrumentation

We designed our questionnaire based on previous studies focused on the technology adoption model [22]—the questionnaire comprised five (5) sections. Sections A focused on demographic characteristics, and sections B to E focused on the variables investigated in this study. Previous studies from which the measurement items were obtained are presented in

Table 2. Instrumentation and Justification.

S/No.	Section	Description	Interpretation	Source
1.	A	Demographic information	Measures the respondents’ background, such as age, gender, educational level, and others.	[59]
2.	B	Perceived Usefulness	Measures how useful respondents find using sustainable technology.	[22,59,60]
3.	C	Perceived Ease of use	Measures how easy respondents find sustainable technology.	[22,59,60]
4.	D	Attitude	Measures respondents’ attitude towards sustainable technology.	[59,60]
5.	E	Actual Use	Measures how sustainable technology affects employees’ activities—i.e., productivity, targets, etc.	[59]

. Using measurement items adapted from previous studies, ensures content validity [56]. The questionnaire was designed using google documents, making it easier to share it online for the respondents to complete. Furthermore, using an anonymous online survey ensured that respondents felt safe providing objective responses at a time and place that was convenient for them [58]. Table 2 summarises the sections of the questionnaire.

3.3. Analytical Technique

Due to the self-reporting nature of the study, the data was checked for Common Methods Bias (CMB) using Haman’s [61] Single Factor test [62]. CMB was not a challenge for this study because the first extracted factor in a Principal Component Analysis (PCA) did not account for more than 50% of the variance (Podsakoff et al., 2003). Given the model’s complexity, a two-step modelling approach was adopted [63]. We first estimated the measurement part of the model and noted the parameter estimates, after which the full model was estimated using the parameter estimates determined in step one. To estimate the measurement, we conducted a series of one-factor congeneric models to clean up each construct while ensuring that each model is well-fitting. We conducted a multi-factor confirmatory factor analysis on all the variables to ensure no cross-loadings. After finalising each construct’s set of items, we used the factor score weights generated from congeneric models to create a weighted composite measure for each construct. To determine the fitness of the models, the following indices were used χ2 with p-value > 0.05, RMSEA < 0.05, CFI ≥ 0.90, TLI ≥ 0.95, and GFI ≥ 0.90 [64,65,66,67]. We used path analysis to test the proposed hypotheses and multi-group comparisons. All the analysis was done using AMOS version 27.

4. Results

The demographic attributes of the respondents are presented in

Table 3. Demographic attributes of respondents.

Attribute	Frequency	Percent (%)
Age (years)
Below 20	1	0.33%
20–30	43	14.24%
31–40	162	53.64%
41–50	85	28.15%
51–60	11	3.64%
Position within organisation
Operational staff	93	30.79%
Middle management/Middle-level staff	111	36.75%
Senior management/Top management staff	65	21.52%
others	33	10.93%
Duration of employment (years)
Less than one year	23	7.62%
1–5	104	34.44%
6–10	51	16.89%
11–15	62	20.53%
16–20	45	14.90%
More than 20	17	5.63%

and Figure 2, Figure 3 and Figure 4. Most of the respondents were females. About fifty-four percent of respondents were females, while about forty-six percent were males, and the remaining preferred not to identify their gender. About fifty-four percent of the respondents were between the ages of 31–40, followed by those between 41–50 and 51–60, constituting about twenty-eight percent and fourteen percent, respectively. Only one respondent was below twenty years. More than half of the respondents have a postgraduate degree (approximately seventy-two percent of the respondents).

Regarding the employment sector, nearly half of the respondents were in education and training, followed by those in finance and technology who accounted for thirty-three and thirty-two percent of the distribution, respectively. The sector with the lowest number of respondents was logistics, accounting for two percent of the distribution. Moreover, about thirty-six and thirty-one percent of the workers were Middle-level staff and operational staff, respectively. Furthermore, most of the staff has worked for 1–5 years in their employment sector. Few respondents (seventeen percent) have worked for more than twenty years.

Table 4. Technology use.

Technology Use	Frequency	Percentages
I feel confident using the sustainable technology
Agree	118	39.07%
Disagree	16	5.30%
Not Sure	21	6.95%
Strongly Agre	137	45.36%
Strongly Disagree	10	3.31%
I have the required skills to use the sustainable technology
Agree	119	39.40%
Disagree	18	5.96%
Not Sure	21	6.95%
Strongly Agree	136	45.03%
Strongly Disagree	8	2.65%
I understand the different features of the sustainable technology
Agree	131	43.38%
Disagree	18	5.96%
Not Sure	27	8.94%
Strongly Agree	118	39.07%
Strongly Disagree	8	2.65%
I am confident to help others solve problems they are facing with the sustainable technology
Agree	134	44.37%
Disagree	27	8.94%
Not Sure	46	15.23%
Strongly Agree	88	29.14%
Strongly Disagree	7	2.32%
The sustainable technology has improved (improved) my effectiveness)
Agree	115	38.08%
Disagree	60	19.87%
Not Sure	65	21.52%
Strongly Agree	52	17.22%
Strongly Disagree	10	3.31%
Sustainable technology has improved (improved) my productivity)
Agree	103	34.11%
Disagree	55	18.21%
Not Sure	68	22.52%
Strongly Agree	65	21.52%
Strongly Disagree	11	3.64%
I think learning to use sustainable technology is easy
Agree	159	52.65%
Disagree	27	8.94%
Not Sure	26	8.61%
Strongly Agree	83	27.48%
Strongly Disagree	7	2.32%
I think using the sustainable technology is easy
Agree	162	53.64%
Disagree	21	6.95%
Not Sure	30	9.93%
Strongly Agree	81	26.82%
Strongly Disagree	8	2.65%
Using the sustainable technology is a wise idea
Agree	151	50.00%
Disagree	15	4.97%
Not Sure	30	9.93%
Strongly Agree	100	33.11%
Strongly Disagree	6	1.99%

shows that most respondents were confident in using sustainable technology. Most respondents, constituting about forty-five percent, strongly agreed to feel confident using sustainable technology, while only about three percent strongly disagreed. Also, nearly half of the respondents strongly agreed to have the required skills to use sustainable technology. Similarly, about forty-three percent and thirty-nine percent of respondents either agreed or strongly agreed to understand the different sustainable technology features, respectively. Moreover, about thirty-eight percent of the respondents agreed that sustainable technology makes them more effective in their work delivery. Most respondents also agreed to feel confident about helping others solve problems with sustainable technology. Overall, more than half of the respondents agreed that learning to use and use sustainable technology was easy. In contrast, approximately eighty percent of the respondents strongly agreed that using sustainable technology was a wise idea (see Table 4).

Table 5. Means, Standard deviations, and Correlations of TAM variables.

	Mean	Std. Dev.	1	2	3	4
Perceived Usefulness	1.46	0.42	1.00
Perceived Ease of use	2.19	0.49	0.54 ***	1.00
Attitude towards using	3.76	0.81	0.57 ***	0.74 ***	1.00
Actual use	2.95	0.62	0.50 ***	0.73 ***	0.75 ***	1.00

Note: *** denote significance at 1% level.

presents the means, standard deviations, and correlations of all the variables. Significant association levels were found, and given that all correlations were below 0.85, multicollinearity was not present in this study [68]. The results of the one-factor congeneric model for all the constructs are presented in

Table 6. Congeneric model results.

Construct	χ2	df	p-Value	RMSEA	CFI	TLI	GFI
Perceived Ease of use	2.77	2	0.25	0.04	1.00	0.99	0.99
Perceived usefulness	1.44	2	0.48	0.00	1.00	1.00	0.99
Attitude towards using	0.14	2	0.71	0.00	1.00	1.00	1.00
Actual Use	5.87	4	0.21	0.04	0.99	0.99	1.00

χ2: Chi-square; df: degrees of freedom; RMSEA: root mean square error of approximation; CFI: comparative fit index; TLI: Tucker-Lewis index; GFI: Goodness of fit index.

. All four models fitted the data very well, and the results are presented in Table 6.

The results also show adequate convergent validity, given that all the standardised factor loadings are more significant than 0.5. Additionally, Cronbach’s alpha for all the constructs is greater than 0.70, thus confirming construct reliability [69]. The factor loadings are presented in

Table 7. Factor matrix.

Items	Perceived Ease of Use	Perceived Usefulness	Attitude towards Using	Actual Use
D1	0.55
D2	0.90
D3	0.91
D4	0.88
C1		0.54
C2		0.87
C3		0.93
C4		0.94
E1			0.71
E2			0.98
E3			0.92
E4			0.53	0.72
F1				0.88
F2				0.82
F3				0.87
F4				0.72
F5				0.72

.

Table 8. Results for mediating effects.

	Perceived Usefulness		Attitude towards Using		Actual Use
	Group 1	Group 2	Group 1	Group 2	Group 1	Group 2
Direct effects
Constant	0.716 ***	0.376 ***	0.890 ***	0.906 ***	0.302	0.607 ***
	(0.222)	(0.100)	(0.284)	(0.162)	(0.206)	(0.129)
Perceived Ease of use	0.342 *** (0.097)	0.496 *** (0.045)	1.100 *** (0.125)	0.951 *** (0.089)	0.527 *** (0.118)	0.449 *** (0.081)
Perceived usefulness			0.312 ** (0.129)	0.533 *** (0.107)	0.074 (0.091)	0.086 (0.084)
Attitude towards using					0.388 *** (0.073)	0.320 *** (0.051)
Indirect Effects
PEOU → PU → ATT			0.107 ** (0.053)	0.264 *** (0.058)
PU → ATT → AU					0.121 **	0.170 ***
					(0.055)	(0.044)
PEOU → ATT → AU					0.494 *** (0.099)	0.431 *** (0.067)
Observations	302

PEOU: perceived ease of use; PU: perceived usefulness; ATT: attitude towards using; AU: actual use. Standard errors in parentheses ** p < 0.05, *** p < 0.01.

reports the structural model results comparing the adoption of sustainable technologies in the Western (group 1) and non-Western (group 2) countries. The structural model results show a well-fitted model with the following fit indices (a χ2 of 13.49 with a p-value of 0.34; RMSEA: 0.02, CFI: 0.99 and TFI: 0.99). The results indicate a significant positive relationship between perceived ease of use and usefulness for Western (0.342 ***) and non-western (0.496 ***) countries. This confirms Hypothesis 1. As predicted in Hypothesis 2a, perceived usefulness positively and significantly related to employees’ attitudes towards using sustainable technologies in Western (0.312 **) and non-western (0.533 ***) countries. The result again shows a significant effect of perceived ease of use on attitude towards using sustainable technologies, supporting Hypothesis 2b. While perceived ease of use had a significant positive impact on actual use, the effect of perceived usefulness was positive but insignificant. We also found a significant positive effect between attitudes towards using sustainable technologies and actual use for employees in western (0.388 ***) and non-western (0.320 ***) countries. These results, therefore, provide support for Hypotheses 3b and 3c, whereas Hypothesis 3a was not supported.

Regarding Hypotheses 4a and 4b (thus the indirect effect of perceived usefulness and ease of use on actual use via attitudes towards using), the results showed a positive indirect relationship between perceived usefulness and perceived ease of use via attitudes towards using sustainable technologies. Specifically, the results suggest that the impact of perceived usefulness on actual use entirely operates through attitudes towards using sustainable technologies for western (0.121 **) and non-western (0.170 ***) countries, supporting Hypothesis 4a. On the other hand, attitudes towards using sustainable technologies partially mediate the relationship between perceived ease of use and actual use for Western (0.494 ***) and non-western (0.431 ***) countries employees.

Table 9. Disaggregated Results based on Gender.

	Perceived Usefulness		Attitude towards Using		Actual Use
	Group 1	Group 2	Group 1	Group 2	Group 1	Group 2
Direct effects
Constant	0.313 **	0.379 **	0.890 ***	1.196 ***	0.302	0.728 ***
	(0.145)	(0.131)	(0.284)	(0.162)	(0.206)	(0.163)
Perceived Ease of use	0.434 *** (0.057)	0.494 *** (0.060)	1.110 *** (0.095)	0.902 *** (0.106)	0.433 *** (0.097)	0.530 *** (0.096)
Perceived usefulness			0.513 *** (0.118)	0.419 *** (0.116)	0.123 (0.092)	0.036 (0.089)
Attitude towards using					0.389 *** (0.097)	0.279 *** (0.058)
Indirect Effects
PEOU → PU → ATT			0.225 *** (0.059)	0.210 *** (0.063)
PU → ATT → AU					0.199 ***	0.117 **
					(0.057)	(0.044)
PEOU → ATT → AU					0.429 *** (0.077)	0.254 *** (0.060)
Observations	138	162

PEOU: perceived ease of use; PU: perceived usefulness; ATT: attitude towards using; AU: actual use. Standard errors in parentheses ** p < 0.05, *** p < 0.01. Note: Group 1 = (female), Group 2 = (male).

presents the full results.

Previous studies have documented the impact of gender [70,71,72] and educational qualification [73,74] on technology adoption. Given that there are limited studies on sustainable technologies, we further examine whether gender and educational level make any difference in adopting sustainable technologies. The full results are presented in Table 9 and

Table 10. Disaggregated Results based on Educational level.

	Perceived Usefulness			Attitude towards Using			Actual Use
	Group 1	Group 2	Group 3	Group 1	Group 2	Group 3	Group 1	Group 2	Group 3
Direct effects
Constant	0.089	0.508 **	0.477 ***	−0.166	0.663 **	1.206 ***	0.120	0.033	0.882 ***
	(0.269)	(0.170)	(0.117)	(0.284)	(0.162)	(0.162)	(0.206)	(0.129)	(0.129)
Perceived Ease of use	0.585 *** (0.097)	0.448 *** (0.077)	0.448 *** (0.052)	1.250 *** (0.317)	1.111 *** (0.125)	0.908 *** (0.087)	0.527 *** (0.118)	0.509 *** (0.114)	0.476 *** (0.081)
Perceived usefulness				0.639 (0.129)	0.456 ** (0.159)	0.413 *** (0.098)	0.216 (0.227)	0.075 (0.105)	0.068 (0.078)
Attitude towards using							0.760 *** (0.131)	0.435 *** (0.075)	0.255 *** (0.052)
Indirect Effects
PEOU → PU → ATT				0.383 (0.249)	0.207 * (0.079)	0.187 *** (0.049)
PU → ATT → AU							0.469 (0.324)	0.197 *** (0.079)	0.105 ** (0.033)
PEOU → ATT → AU							0.947 *** (0.297)	0.487 *** (0.100)	0.233 *** (0.052)
Observations	16	70	216

PEOU: perceived ease of use; PU: perceived usefulness; ATT: attitude towards using; AU: actual use. Standard errors in parentheses. * p < 0.10, ** p < 0.05, *** p < 0.01. Note: Group 1 = (high school certificate and diploma), Group 2 = (Bachelors degree), Group 3 = (Postgraduates).

. Specifically, we found no differences between males and females in adopting sustainable technologies. Regarding the impact of educational level. We found some differences in adoption. For example, while the impact of perceived usefulness on attitudes towards using was significant across groups 2 and 3, the effect was insignificant in group 1. Again, the indirect effect of perceived ease of use on attitudes towards using via perceived usefulness was insignificant for group 1, while groups 2 and 3 reported significant effects. We also found similar effects in perceived usefulness and actual use via attitude towards using.

5. Implications of the Study

5.1. Discussion

This paper examines the determinants of sustainable technology adoption during the crisis, focusing on cross-cultural variations. First, we find no significant differences between western and non-western cultures in adopting sustainable technologies and challenge the arguments of previous studies that tend to frame culture as a stumbling block in the adoption of technology. For example, previous studies (e.g., [75,76,77] have found that culture can significantly affect the adoption of technologies such as mobile phones and mobile health applications. For example, Lee et al. [77] found that while individuals in individualistic cultures rely on information from direct and formal sources, individuals from collectivist societies rely more on subjective evaluation of an innovation during its adoption, which ultimately influences their decision to adopt it. Our results can be explained by circumstances in the time the technology was adopted. We note that during critical times such as pandemics, the attention of individuals is much more on survival rather than values. Therefore, individuals can put aside their differences to adopt technologies that directly impact their survival. Additionally, when governments and international organisations such as the World Health Organisation (WHO) mandate work from home to keep economies running while keeping the virus at bay, people are likely to have no option but adopt the technology as a form of compliance despite their perceptions towards the technology or its usage. In this case, it can be shown that government decisions during pandemics eliminate the impact of individual differences on technology adoption.

The results also indicate a significant positive relationship between perceived ease of use and usefulness. We also found that perceived usefulness positively and significantly affects employees’ attitudes towards using sustainable technologies. These results confirm previous studies [78,79,80] and show that perceived ease of use and usefulness influence employees’ quest to adopt sustainable technologies. The result again shows a significant positive effect between attitudes towards using sustainable technologies and actual use for employees. The results showed a positive indirect relationship between perceived usefulness and ease of use via attitudes towards using sustainable technologies. Our results confirm the findings of previous studies [81,82] adopting TAM and therefore point to the relevance of the model in explaining the adoption of sustainable technologies.

Regarding the impact of gender on sustainable technology adoption, our results confirm the findings of previous studies [70] that argue that the adoption rate of both males and females are similar. This finding is significant as most studies have significant differences in males and females in technology adoption. This may be explained by the fact that the adoption of such technologies was largely unplanned and in response to the dire situation. Our results on the level of education are another important contribution of this study. The effect of educational qualification has been discussed in the literature [73,74]; however, our results report fluctuations among different groups highlighting the importance of educational qualifications even during crisis.

5.2. Theoretical Implications

This study makes three theoretical contributions. First, by undertaking a comparative study across Western and non-Western countries, this study contributes to the literature on technology adoption from a cross-cultural perspective. In finding no disparities in technology adoption across the two categories of countries, this study shows that in times of crisis, when companies and employees have no option but to adopt technology to keep their jobs quickly, culture does not significantly impact technology adoption.

Second, unlike other studies [83,84] investigating technology adoption in situations where it is not compulsory for economic survival, this study has investigated technology adoption in a situation where companies and employees must retain their jobs and ensure economic sustainability during a worldwide crisis. Thus, this study has highlighted the impact of technology adoption determinants in a crisis and extended TAM testing in a crisis context across different countries. Additionally, this study has addressed the need for more empirical studies on technology adoption in a crisis where adoption is obligatory.

Lastly, in finding that for both the Western and non-Western countries, the perceived usefulness of the technology does not have a significant impact on technology use, this study shows that in crisis contexts, when technology adoption is required to retain jobs and ensure financial sustainability, users will make use of the technology whether they perceive it as useful or not. However, perceived ease of use of the technology will impact technology when adoption is mandatory in a crisis.

5.3. Practical Implications and Recommendations

Our study has shown that perceived ease of using sustainable technologies improves the technology’s attitude and usage. Therefore, across both western and non-Western countries, the focus should be on making sustainable technology usage easy, especially in crisis times. This study has five implications for creating positive perceptions regarding the ease of using sustainable technology. First, employers should create awareness amongst employees regarding sustainable technologies to create positive feelings about the technology. Companies can have awareness workshops where aspects such as benefits of sustainable technology, collaboration, or teamwork in the sustainable context and challenges of using the technology are addressed. For instance, during the workshop, for users who find it challenging to use sustainable technologies, perceived ease of use can be enhanced by explaining that sustainable technology is like automation and, therefore, requires minimum effort like clicking buttons on a mobile phone. Such simple comparisons can enhance understanding to create positive perceptions of use.

Second, employers should work with technology firms to provide relevant information, training, and adequate technical support for users within organisations. This will ensure that users are knowledgeable about the technology and feel more confident when using it to perform their required tasks. Third, employers should regularly get feedback from users on suggestions for making the technology easy to use. Once this feedback is received, it should be provided to the technology developers, who should work together with employers to improve the sustainable technology suggested by the users. Fourth, employers should encourage staff on the same team to use the collaborative and team platforms available in the sustainable technologies to engage with team members face-to-face and contribute to each other’s work. This will create a positive perception regarding the ease of use of the technology since it minimises the feeling of isolation.

Lastly, governments should put favourable policies that support companies designing sustainable technologies and companies implementing the technologies. For example, the government can extend financial support through low-interest rate bank loans, reduced taxes, and financial bonuses to developers so that they can design cutting-edge technology that will meet the needs of users. For companies implementing sustainable technology, financial support from the government implies that they can afford high-quality technology and the necessary support for employees, making it easy for them to use the technology.

6. Conclusions, Limitations, and Future Research Directions

This study adopts the traditional TAM that incorporates perceived usefulness, ease of use, and attitude as determinants to examine their impact on the actual use of sustainable technologies. The study employed a structural equation modeling approach to analyse data collected from 13 countries from May to October 2020. The results revealed that perceived ease of use positively affected perceived use significantly. Also, perceived ease of use and usefulness positively and significantly impact attitude towards the technology and its usage. Furthermore, attitude towards the technology has a direct positive and significant impact on the actual use of sustainable technology. However, the magnitude of the impact of the technology usage determinants varies across Western and Non-Western countries. For instance, the significant impact of perceived ease of use on perceived usefulness is higher in non-Western countries than in Western countries. However, its impact on attitude is higher in magnitude in Western countries than in non-Western countries. Whereas perceived usefulness highly mediates the impact of attitude on actual use in non-Western countries relative to the Western countries, perceived ease of use highly mediates the impact of attitude on actual use in Western countries relative to non-Western countries.

This study has some fundamental limitations, which create opportunities for future research. First, this study focuses on a range of sustainable technologies used by employees, without investigating specific technologies. Therefore, the generalization of the findings in this study should be done with caution, as various technologies may influence employees’ adoption and productivity differently. Future studies should apply the TAM to investigate the adoption of specific technologies. Second, this study considered a comparative analysis of sustainable technology use by respondents in Western and Non-Western countries. Although both groups showed positive impacts of perceived usefulness, ease of use, and attitude towards technology on actual use, there are significant differences in these factors’ magnitude. Several factors might influence the relationships between attitude and actual use. Therefore, future studies could explore factors that moderate the relationship between attitude and actual use. Third, this study did not undertake comparisons across age groups, income levels or even professions and yet it is likely that specific factors within these groups influence technology adoption. Future studies can consider undertaking more detailed comparisons of technology adoption across different respondent groups. Fourth, this study did not consider the impact of moderating variables in technology adoption. Forthcoming studies should consider a range of moderating variables to determine how they influence relationships between determinants and technology adoption.