**4. Technology adoption**

The emergence of novel technologies promotes the development of human social civilization [38]. Therefore, the impact of technological transformation has been prominent and multi-dimensional. From a business perspective, the opportunities for innovation are endless in developing products and services adapting to customers' needs, given that technology can optimize any point in the value chain in any industry. Changes in the offerings, more market-like forms of production and distribution, delivery service, payment methods, and communication channels are just some possible transformations [39, 40]. From the customer's perspective, technology can also contribute at any stage of their purchasing decision process, offering the possibility of having everything in an accessible, fast, and adaptable manner to any segment profile. Based on this background, the benefits in terms of productivity, efficiency, competitiveness, and growth for private and public organizations globally by technological evolution are unquestionable [41].

However, as pointed out, the scenario is quite different in emerging markets, especially for these countries' most vulnerable sectors. Moreover, new technologies have demonstrated that more than they are needed to generate well-being in the lives of individuals and organizations because many innovations are not widely available and used as expected. This suggests that, despite digital innovations being a global phenomenon, their impact must still be globally equitable. The reasons for explaining these inequalities in terms of development are diverse; however, from the end-user outlook, adoption has become a hot issue in understanding how to promote a symmetrical impact [38]. Technology adoption refers to the stage in which technology is selected for use

*Technological Adoption in Emerging Economies: Insights from Latin America and the Caribbean… DOI: http://dx.doi.org/10.5772/intechopen.112004*

by individuals and organizations [42]. The study of this process has a long-standing research tradition. Still, it was not until the introduction of Rogers' Diffusion of Innovations Theory (DOI) that it gained widespread use and recognition in the academic field [43].

According to Rogers, diffusion can be defined as the process by which an innovation is communicated through various channels over time among individuals in a social system. Invention, on the other hand, refers to an idea, practice, or object perceived as new by an individual or other unit of adoption. Rogers developed DOI based on five elements - innovation, communication channels, time, and social system - that can be identified in all research on diffusion, and a process of Innovation Decision divided into several stages, which individuals or organizations must overcome to achieve the final degree of adoption of an innovation [44].

Since its introduction, this model has been embraced by various fields and disciplines to understand how individuals and organizations adopt innovations. Due to its prominence and versatility, the application of this model in understanding technological innovations has been extensive, leading to the emergence of specific models and theories that attempt to address the technology use and acceptance process.

### **4.1 Models of technology adoption**

The Technology Acceptance Model (TAM) by [45] was the first theoretical approach for understanding technology acceptance, focusing on predicting user disposition and use of new technology. TAM is an adaptation of the Theory of Reasoned Action (TRA), which is part of the assumption that a person's reaction and perception of something will determine that person's attitude and behavior. TAM was grounded in the proposition that the acceptance and use of technology can be explained by an individual's internal cognitive constructs, including beliefs, attitudes, and intentions.

Five primary constructs form the basis of the Technology Acceptance Model: (a) Perceived Usefulness (PU), (b) Perceived Ease of Use (PEOU), (c) Attitude (Att), (d) Behavioral Intention to Use (BI), and (e) Actual Usage (AU) (see **Figure 2**). PU refers to a user's perception of the subjective probability that the use of technology will help improve their performance when using an information system. Alternatively, PEOU refers to the individual's appreciation that mastering a particular technology involves the least possible effort.

Following TAM, PEOU, and PU are beliefs that directly and indirectly affect attitude or disposition, while PU also directly affects PEOU. Yoon [46] proposed a direct causal relationship between Attitudes, Perceived Usefulness, and Intention, where Intention is the primary determinant of behavior. Many researchers' empirical studies have replicated and tested the model under different conditions for TAM's extended

**Figure 2.** *Technology acceptance model [45].*

variables as general measures by explicitly including IT acceptance variables, such as extrinsic and intrinsic motivators.

A significant number of researches have confirmed that perceived usefulness (PU) and perceived ease of use (PEOU) may be influenced by user-related external variables, such as user experience [47], customer satisfaction [48], motivation [49], self-efficacy [50], and demographic factors [51]. Similarly, technology-related variables, such as system quality [52], interface design [53], and compatibility [54], among other factors, may also influence the prediction of behavioral intention. Venkatesh and Davis [55] subsequently introduced a revised version of the Technology Acceptance Model (TAM), known as TAM2, which omitted the construct of attitude towards use and incorporated additional variables such as experience and subjective norm in which recognizes the role of social influence and intrinsic variables in the process. However, the fundamental principles of the model remained intact. TAM2 was tested using longitudinal data collected regarding four different systems at four organizations considering voluntary usage and involving mandatory usage. The findings of this model extension have generated significant practical implications. Mandatory, compliance-based strategies for introducing new systems demonstrate diminishing effectiveness over time compared to harnessing social influence to facilitate positive shifts in perceived usefulness. Therefore, exploring feasible alternatives to usage mandates that capitalize on social information is recommended. For instance, they are developing and evaluating methods that enhance the credibility of social data to encourage internalization or the creation of communication campaigns that elevate the perceived prestige linked to system utilization to foster identification.

Over a decade, the proliferation of research on TAM and TAM2 has led to confusion among researchers, as they often found themselves compelled to pick and choose features from a wide array of competing models. In response to this confusion and to integrate the literature on technology acceptance, [56] developed a unified model that proposes an alternative approach to user and innovation acceptance: The Unified Theory of Acceptance and Use of Technology (UTAUT) [57].

UTAUT consists of four core constructs: (a) performance expectancy (PE), (b) effort expectancy (EE), (c) social influence (SI), and (d) facilitating conditions (FC), applied to determine behavioral intention (BI), which in turn, predicts usage behavior (UB) [58]. PE refers to the level consumers perceive technology to provide benefits in performing specific activities. EE is defined as the degree of ease associated with consumers' utilization of technology. SI (Social Influence) represents the extent to which consumers perceive those influential individuals (e.g., family and friends) to believe they should adopt a particular technology. Finally, FC refers to "consumers' perceptions of the resources and support available to perform a behavior.

The UTAUT proposes that these fundamental constructs (PE, EE, SI, and FC) directly influence behavioral intention and behavior. Furthermore, these constructs are moderated by gender, age, experience, and voluntariness of use [56, 58]. In 2012 [58] proposed and tested UTAUT-2, new constructs, specifically Hedonic motivation (HM), Price Value (PV), and Habit (HB). HM refers to the positive emotion of individual immediate satisfaction, PV refers to the return on investment that the consumer is aware of, and Habit refers to "the degree to which the consumer automatically performs actions with technology (see **Figure 3**).

Since their inception, UTAUT and UTAT-2 have emerged as widely utilized theoretical frameworks in technology adoption and diffusion research. However, despite its prominence, the scientific literature on this concept also reveals disparities in study contexts and samples.

*Technological Adoption in Emerging Economies: Insights from Latin America and the Caribbean… DOI: http://dx.doi.org/10.5772/intechopen.112004*

### **Figure 3.**

*A unified extended theory of acceptance and use of technology (UTAUT2) [56].*

In a literature review conducted by [57], 10 years after the initial development of the UTAUT model, an examination of UTAUT research conducted from 2004 to June 2011 was performed. This review was based on a search in ISI Web of Knowledge and Google Scholar, yielding 174 usable research papers. The analysis revealed that the model had been applied to address various purposes and in diverse contexts, incorporating additional constructs. However, despite the model's popularity, the analysis indicated that the scientific production surrounding the model was concentrated in the United States (25%) and Asia (26%) for primary data collection. Approximately 47% of the research was dispersed among developed economies, predominantly in Europe. Additionally, the study found that only around 20% of the studies were conducted in emerging economies. Regarding the systems used in UTAUT studies, the review established 52%.

Lastly, the review revealed that performance expectancy and social influence emerged as the strongest predictors of behavioral intention in the literature examined. A subsequent study by [59] also confirmed the predictive power of PE and SI and the central role of individuals' attitudes or dispositions. However, although the contribution of these constructs may vary according to the context, user profile, or platform under study, the evidence generally supports their contribution to the acceptance of a new system. Regarding the weight of the variables, a post-review study established that UTAUT explains approximately 70% of the variation in behavioral intention, surpassing previous models [60]. The result is that essential variables in adopting a new system are the expectation of potential users to benefit from the technology and the influence of those surrounding the user who urges its adoption.

### **4.2 Adoption of new technologies in emerging economies?**

The extensive use of DOI, TAM, and UTAUT models in the literature on technology adoption is widely accepted [61]. In addition, these investigations have allowed us to ascertain that cultural variability can influence individual behavior, explaining the gaps in technology usage and acceptance across different cultures [62, 63].

However, one factor contributing to deepening this disparity is the asymmetry of scientific contribution in emerging economies, as most research, except India, has been conducted in developed or developing economies. A clear example of this is the meta-analysis conducted by [64] on the drivers of digital transformation adoption, which revealed that out of 88 evaluated articles representing a total of 34,485 samples studied in 33 countries, 51% of the samples came from India (22%), United States (13%), Germany (8%), and China (8%). The remaining samples were distributed across 29 countries, predominantly in Europe. The reduced participation of specific research from emerging economies is a common factor in studies reviewing the topic.

This situation is even more acute in the case of Latin America and the Caribbean (LAC), despite representing 64% of the Americas and 9% of the world population [2]. Only some studies have dealt with these contexts. Considering that over 60 million people could benefit from fostering digital adoption initiatives in this region [65], several authors who have found evidence supporting cultural differences have emphasized the importance of focusing on understanding this area [20, 63, 66]. Additionally, not only is the regional evidence for Latin America and the Caribbean scarce, but also studies focusing on the most representative sector in emerging economies, low-income consumers. Although the figures may vary by nation, approximately 32% of the population lives in poverty or extreme poverty, while 39% has medium income levels [67].

On the other hand, the proliferation of digital transformation in diverse industries and sectors has resulted in a growing body of research on technological adoption. However, instead of emphasizing the profile of potential users, these studies predominantly concentrate on platform usage to generalize model findings. This trend is evident in research endeavors that assess various areas such as digital payment [68, 69], mobile apps [70, 71]; e-commerce [72, 73], free and open-source software [74], on-demand service platforms [75, 76], artificial intelligence [77, 78], social media [79, 80] virtual reality [81, 82], Business Intelligence and Analytics [83], among others.

Despite the diversity of sectors in which a wide range of technologies can intervene to contribute to the development of emerging economies, health and education constitute key pillars due to their direct impact on a country's economic growth. Research in these sectors was significantly boosted by the COVID-19 crisis enabling substantial progress in utilizing technology-mediated services in various formats and platforms.

Given the high occurrence of chronic diseases in Latin America and the Caribbean, implementing telemedicine and technology-based educational pro- grams for health prevention could have significant positive impacts. The latest data from the Global Burden of Disease study (2019) reveals that conditions such as diabetes, hypertension, obesity, respiratory diseases, and mental health disorders, which account for eight out of 10 premature deaths worldwide, are more prevalent in low- and middleincome countries, including those in Latin America [84, 85].

The evidence in the case of the healthcare sector in emerging economies in Latin America indicates that, although mobile telemedicine options have significantly expanded, allowing these services to reach rural areas and vulnerable populations,

### *Technological Adoption in Emerging Economies: Insights from Latin America and the Caribbean… DOI: http://dx.doi.org/10.5772/intechopen.112004*

they remain a privilege adopted by a minority group of people. In Latin America, mainly due to vast distances, telemedical consultations could improve access to healthcare for populations residing in remote areas far from major medical centers. The Pan American Health Organization/World Health Organization (PAHO/WHO) supports with over 900 virtual rooms remote communication through its Virtual Collaboration program, which provides training on various virtual communication methods and collaborates with those in need of utilizing these tools to disseminate health knowledge where it is most needed. The increasing digitization and availability of telemedicine services in countries like Chile and Argentina present a significant opportunity for Latin America and the Caribbean to export these services across borders, including to neighboring countries. However, there are several challenges that the region must address to seize this opportunity. To deepen the knowledge of these barriers, the Integration and Trade Sector of the Inter-American Development Bank [86] has led a study on International Telemedicine in Latin America, which explores the motivations, uses, results, strategies, and policies that lead to a diagnosis of the sector in the region. This report includes an extensive literature review, an online survey with 1443 healthcare professionals from 19 countries, and in-depth interviews with 29 telemedicine experts.

The report's findings demonstrate a positive correlation between the utilization of international telemedicine and the productivity and efficiency of healthcare professionals. For instance, statistical analysis corroborates that 49% of survey participants reported enhancing their professional skills linked directly to crossborder telemedicine services. Moreover, international telemedicine is associated with improved outcomes for national health systems. Statistical analysis confirms that 43% of respondents connect it to a reduction in social health inequalities, 42% perceive an enhancement in the provision of national health services, and 40% recognize improvements in their countries' overall health status. Nevertheless, the survey reveals that despite these benefits, only 17% of healthcare professionals utilize international telemedicine systems. However, a slightly higher proportion (20%) intend to start using them.

Additionally, there are slight variations in these percentages across different countries in the region. Nevertheless, the potential in terms of volume and impact is enormous. It is projected that by the year 2025, the estimated value of the telemedicine market in Latin America will grow 120%, increasing its value from US\$ 1570 million in 2020 to US\$ 3480 million in 5 years [87]. As more services and products shift towards digital platforms, telemedicine has emerged as a continuously growing trend, closely linked to the increasing internet penetration rates. However, the fundamental challenge lies in the adoption and acceptance of these services by the healthcare system for their delivery and by users for their utilization.

The education landscape bears many similarities to the healthcare sector in emerging economies. LAC has approximately 193 million children and adolescents of school age, encompassing early childhood, primary, and lower secondary education. However, 14 million are not enrolled, and 15.6 million attend school while facing failures and signs of inequality, manifesting in two or more years of lag in grade-age alignment or educational delay [88]. Children in Latin America and the Caribbean experienced some of the most prolonged and consistent school closures due to COVID-19 worldwide. On average, since the pandemic's beginning, students in the region have lost, either partially or entirely, two-thirds of in-person school days, resulting in an estimated loss of 1.5 years of learning [89]. The pandemic and economic needs have excluded over 3 million school-aged children from education in the

past 3 years [90]. Exclusively considering primary and secondary education, according to data from the World Bank and the United Nations Children's Fund (UNICEF), 15 million children and adolescents are out of school, equivalent to a country's population in a country like Ecuador.

In addition to the conditions of poverty that impede access to education, it is estimated that there are 8 million children with disabilities, of which approximately 30% do not attend school due to a lack of physical and technological infrastructure that can accommodate them. This situation exposes them to a high risk of complete dropout from the education system [88]. The primary factors driving online learning are enhancing access to education, training, and the quality of learning, reducing costs, and improving education's cost-effectiveness [91]. Implementing e-learning tools could play a pivotal role in closing these gaps by promoting inclusion and expanding the reach of the education system, particularly for those residing in rural areas. However, beyond the technical requirements, the adoption of e-learning by children and members of the education system remains the next barrier to overcome in harnessing the power of online education. As illustrated, substantial improvements in the education system could be achieved with the widespread availability of Internet access.

Regarding previous research in a literature review on the acceptance of online learning conducted by [92] and an analysis of 14 research studies published between 2005 and 2021 that utilized integration of the TAM model allowed for the conclusion that Course Information, Perceived Usefulness, Attitude, System Quality, User Satisfaction, Perceived Ease of Use, and Academic Performance are the crucial drivers for the acceptance and continued usage of online learning systems. However, the study highlights limitations in the included research, particularly the generalizability of the results, as the studies were conducted on samples from specific countries, none of which encompassed the more vulnerable sectors of Latin America or the Caribbean.

The review emphasizes limitations and suggestions derived from the examined research, highlighting the need for future studies to be conducted in diverse contexts and with varied populations. Additionally, it underscores the importance of undertaking longitudinal studies that account for individual factors to comprehensively understand how this process unfolds. Such research endeavors will provide a broader perspective and shed light on the dynamic nature of technology adoption and its implications. By exploring different contexts and incorporating longitudinal approaches, researchers can delve deeper into the complexities of technology acceptance and uncover valuable insights that contribute to advancing knowledge in this field. Furthermore, a limitation of this review is that it needs to specify how the reported findings may vary according to the level of education. Considering that individual factors influence adoption, it is reasonable to expect differences across various educational levels. Exploring these variations can provide valuable insights into the nuances of technology adoption and its relationship with educational attainment. Future research should consider incorporating analyses examining individual factors' differential impact on adoption within different educational contexts. Addressing this aspect, a more comprehensive understanding of technology adoption's complexities concerning academic levels can be achieved.

The analysis of over 100 articles on eLearning Acceptance and Adoption Challenges in Higher Education, retrieved from significant databases between 2012 and 2022, reveals similar findings. The predominant use of TAM and ITAU models, integrated with other variables and models, highlights the impact of perceived

*Technological Adoption in Emerging Economies: Insights from Latin America and the Caribbean… DOI: http://dx.doi.org/10.5772/intechopen.112004*

usefulness and perceived efficacy on adopting new technologies. However, more literature must specifically address vulnerable sectors in emerging economies [1]. The authors suggest undertaking studies aimed at identifying potential resolutions to these challenges.
