Internet adoption and usage patterns in rural Mexico

Journal Pre-proof Internet adoption and usage patterns in rural Mexico Marlen Martínez-Domínguez, Jorge Mora-Rivera

PII:

S0160-791X(19)30268-4

DOI:

https://doi.org/10.1016/j.techsoc.2019.101226

Reference:

TIS 101226

To appear in:

Technology in Society

Received Date: 28 June 2019 Revised Date:

9 October 2019

Accepted Date: 4 December 2019

Please cite this article as: Martínez-Domínguez M, Mora-Rivera J, Internet adoption and usage patterns in rural Mexico, Technology in Society (2020), doi: https://doi.org/10.1016/j.techsoc.2019.101226. This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. © 2019 Published by Elsevier Ltd.

Internet adoption and usage patterns in rural Mexico

Marlen Martínez-Domínguez Centro de Investigaciones y Estudios Superiores en Antropología Social, Pacífico Sur. Sierra Nevada 347 Col. Loma Linda, Oaxaca. C. P. 68024, Oaxaca. email: [email protected]

Jorge Mora-Rivera Tecnologico de Monterrey, Campus Ciudad de Mexico. Calle del Puente 222 Col. Ejidos de Huipulco, Tlalpan C.P. 14380, Mexico City. email: [email protected]

Internet adoption and usage patterns in rural Mexico Abstract The aim of this paper is to identify the socioeconomic and demographic factors that stimulate Internet adoption and use among Mexico’s rural population. Using an econometric model to deal with potential selection bias problems, and information from Mexico’s National Survey on Availability and Use of Information Technologies in Households (ENDUTIH), our results suggest that the probability of using the Internet is higher for people who have digital skills and for women. Internet usage patterns differ by age, educational level, employment type, and geographic location. Young people are more likely to take part in online activities for entertainment purposes, while people of working age go online for information, communication, and e-commerce-related activities. These findings provide evidence on the existing digital divide in terms of Internet penetration and usage in Mexico's rural sector, which is in the early stages of Internet diffusion.

Keywords: Digital divide; Internet; rural areas; Mexico.

1. Introduction Increasingly, the Internet is used in every sphere of society as it comprises a development tool that strengthens the new modes of social and commercial interaction and provides wider access to a diversity of formal and informal learning opportunities (Alderete, 2019; Manlove & Whitacre, 2019; Park, 2017; Verdegem & Verhoest, 2009). In 2017, the estimated Internet usage rate for the American continent was 65.9%, compared to 79.6% in Europe (ITU, 2017a). Moreover, between 2005 and 2016, the gap of Internet use narrowed in South America and Mexico (OECD, 2017a); Mexico's telecommunications sector, however, has developed slowly, with penetration rates lower than regional averages, in spite of the liberalization process that began in the sector in the 1990s (ITU, 2017a). Most South American users (Uruguay, Argentina, Chile, Brazil, and Colombia) have a broadband connection at home, while Internet speeds in Mexico 1

remain slow (OECD, 2017b). Regarding Internet access, Mexico’s rural areas continue to be at a digital disadvantage.1 According to figures from the National Survey on Availability and Use of Information Technologies in Households (ENDUTIH, Spanish acronym), in 2017, the rate of Internet adoption in Mexico's rural areas was 39.2%, in comparison with 71.2% in urban areas (INEGI, 2017).2 These percentages show the existing divide in digital connectivity in rural areas, due in part to low population densities and the greater distances that must be covered:

aspects

that

discourage market

participants

from

investing

in

telecommunications infrastructure (Onitsuka et al., 2018). Internet access, however, does not imply usage. For the Internet to generate expected benefits, people must use it effectively and efficiently (Park, 2017; Salemink et al., 2015). The aim of this study is to analyze Internet diffusion in Mexico’s rural sector from the perspective of demand by identifying the socioeconomic and demographic determinants for Internet access, adoption, and usage patterns, as well as to identify whether these factors match those observed in previous studies in developing countries. To reach this objective, we use data from the 2017 ENDUTIH survey and implement an econometric model that considers the selectivity inherent in the type of individual decisions made by Internet consumers. Some research on Internet diffusion from a perspective of demand have been previously documented, including recent studies by Manlove and Whitacre (2019), and Quaglione et al. (2018). This article contributes to the debate on the digital divide in the rural areas of developing countries, fundamentally in three aspects. In the first place, studies that address the rural digital gap are limited, since the phenomenon is believed to occur basically in urban areas. In addition, such studies focus primarily on countries in South America, Africa, and Asia (Gwaka et al., 2018; Correa et al., 2017; Onitsuka et al., 2018). In the case of Mexico, existing literature is practically nonexistent (an exception are the articles by Toudert, 2019 and Martínez-Domínguez, 2018),

1 In this study, Internet access and usage refer to the presence of a fixed and/or mobile connection in the home. 2 The percentage of mobile telephone users in the urban sector was 77.7%, while the corresponding percentage in the rural sector was 53.8% (INEGI, 2017).

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although 23% of Mexico's population lives in rural areas, along with 20% of the employed population (INEGI, 2015). Mexico is an interesting country for studying the digital divide because its telecommunications sector was highly concentrated until 2013; the result was low levels of competition and Internet penetration. In addition, Mexico has diverse geographical conditions and extremely variable population densities, especially in rural communities (Ovando & Olivera, 2018; Ayala et al., 2018; Mariscal et al., 2016). Therefore, the current article can be considered as a pioneer for Mexico's case; its results contribute unpublished evidence of the factors that influence the use and appropriation of the Internet in Mexico and in rural areas with similar characteristics in other countries. In the second place, having microeconomic information of the type used in this research, permits clear visualization of the digital divide as an additional form of inequality that permeates rural economies. The digital divide adds to the economic, social, and political inequalities that weigh on rural dwellers and limit their social mobility, and could contribute to decreased levels of well-being. In third place, this study provides solid empirical evidence for designing public policies aimed at increasing the benefits derived from the adequate, efficient handling of information technologies (including the Internet), which are presumably ever more available in the rural areas of developing countries. Currently, around 27 million people live in rural Mexico, making it an ideal setting to analyze Internet diffusion and the digital divide. According to the Mexican census (INEGI, 2015), 23% of Mexico’s population lives in rural areas, and the remaining percentage in urban areas. In terms of socioeconomic characteristics, data from the 2016 National Households Income and Expenditure Survey (ENIGH) indicate that the current average quarterly income in urban areas was double that of rural areas (52,215 and 26,004 Mexican pesos, respectively) (INEGI, 2016). Estimates from the National Council for the Evaluation of Social Development Policy (CONEVAL) show that 58.2% of rural dwellers lived in poverty in 2016 (CONEVAL, 2016). Moreover, Mexico’s telecommunications sector is less developed than that of other Latin American countries, since the entire sector was concentrated in a 3

single company (América Móvil with Telmex and Telcel) until 2013.3 According to research by Ovando and Olivera (2018), and Ayala et al. (2018), the market's concentration in a single dominant firm, high connection costs, and weak regulating agencies explain why the cell phone subscription rate in Mexico (88.51%) is below America’s average (114%)4: In 2017, the landline subscription rate was very low (15.95%), as was the Internet penetration rate (63.9%) (ITU, 2017b). Likewise, the network connection price (wired and wireless) remains high. Thus, around 50% of households do not have home access to this service and instead use the Internet at work or at an Internet café (INEGI, 2017). According to statistics from The Global Information Report 2009-2010 and 2016 for Mexico (Dutta & Mia, 2010; Baller et al., 2016), in 2016 the rate of broadband Internet subscriptions was 10.5%, while the Networked Readiness Index—which evaluates the development of the information and communications technology (ICT) sector—showed a slight increase, rising from 3.61 in 2009 to 4.0 in 2016 (on a scale of 1 to 7). In 2017, the percentage of Internet users within this population and the proportion of households with a network connection was 44.4% and 34.4%, respectively (Baller et al., 2016). Mexico’s rural sector, like other rural regions in developing countries, has experienced a slow Internet diffusion process.5 To analyze this process in detail, it is essential to have access to information such as that contained in the ENDUTIH, a representative survey in a rural setting with data that allow us to determine the profile of Internet users and define various Internet usage patterns (INEGI, 2017). Several studies argue that disparities in Internet use can be attributed to differences in age, gender, educational level, and digital skills (Puspitasari & Ishii, 2016; Penard et al., 2012). According to De la Selva (2015), the digital divide is an expression of twenty-first century inequalities. Other authors, such as Scheerder et

3 In June 2013, a regulatory reform was passed to encourage competition in this sector, reduce the prices of land and mobile phone services, and increase the coverage and penetration of these services (Ayala et al., 2018). 4 This figure suggests that there are 114 mobile telephone subscriptions for every 100 people. 5 The digital divide is very evident in developing countries, where urban dwellers are more likely to have a broadband connection than rural dwellers (ITU, 2017c).

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al. (2017) and Selwyn (2004), suggest that the digital divide plays a significant role in the reinforcement of existing social inequalities. The results of the study in Mexico’s rural sector show that women and individuals with higher educational levels have a greater probability of going online. Internet use is higher for young people and individuals with digital skills and computer literacy. Internet usage patterns vary by age, educational level, and geographic location. Individuals with post-primary education go online for activities such as information searches, while young people are more likely to use the Internet for entertainment. Our results suggest the need to favor digital connectivity in rural areas; yet it is essential to train users, so that they can enhance their online experience and improve the beneficial outcomes derived from more productive and efficient Internet usage. The next section introduces the theoretical approach behind this research. The determinants of new rurality, the digital divide, and Internet access and use are established in the literature review. Section three describes the ENDUTIH survey along with the variables used for the econometric models. Section four includes the results for Internet access, use, and usage patterns in rural Mexico. Lastly, the conclusions and political implications are presented.

2. Theoretical and conceptual perspectives This section outlines the theoretical framework supporting this study. Its objective is to emphasize the key elements associated with the role of information technologies as an essential part of rural development. The new rurality allows us to visualize the rural sector as a space made up of multiple and unique characteristics, among which the digital divide appears as a new expression of its characteristic inequalities. In addition, a literature review that compares the differences in Internet access and use in developing and developed countries is presented.

2.1 The new rurality

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In Latin America, rural societies and economies have undergone structural changes arising from globalization and the implementation of liberal policies, which in turn have caused increasing levels of economic inequality and poverty (Urquijo et al., 2017; Kay, 2016 and 2009). These transformations have led to the development of the new rurality as a novel approach that allows us to analyze more thoroughly the development of rural economies (Pisani & Franceschetti, 2011; De Grammont, 2004). This approach recognizes the pluractivity of rural areas; that is, it emphasizes the multifunctional role of rural spaces due to the growing relevance of non-agricultural activities (industry, commerce, and services), as well as the nexus between rural-urban and local-global dimensions (Blumberg, 2018; Kay, 2009). Among the trends considered in this new rurality is the incorporation and use of ICTs as a key element of change in country life (De Grammont, 2016). Proof of this is how, thanks to the use of the Internet and modern means of transportation, the rural sector has become more connected to urban areas, allowing the transition from the agricultural sector to other sectors (Onitsuka et al., 2018). Regarding digital connectivity, rural areas have fewer providers, higher costs, and slower Internet diffusion (Gwaka et al., 2018; Salemink et al., 2015), as well as limited infrastructure compared to urban areas. This makes rural regions less attractive markets due to the high costs involved when covering greater distances (Whitacre & Mills, 2007; Malecki, 2003), something that consequently creates major disadvantages for rural dwellers who cannot access the benefits of ICT products and services (Gwaka et al., 2018).

2.2 The digital divide The term “digital divide” originated during the 1990s in the United States and quickly became a topic of interest as the use and penetration of ICTs spread (Erdiaw-Kwasie & Khorshed, 2016; Van Dijk, 2006; Gunkel, 2003). Since then, the concept has evolved, generating more complex conceptualizations that now

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include indicators of use and access to ICTs (Van Deursen & Van Dijk, 2011; Selwyn, 2004). Three levels can be discerned within the understandings of this concept. The first alludes to the inequality among those who have material access to ICTs and those who do not. This level refers to both infrastructure and the availability of goods and services associated with ICTs. Initially, the determining factors at this level were considered to be on the supply side (Van Dijk, 2006; Selwyn, 2004), but recent studies have revealed that access is influenced by other socioeconomic factors such as income, geographical location, educational level, age, and digital skills (Forenbacher et al., 2019; Răileanu, 2018; Scheerder et al., 2017). Research on this category shows that Internet penetration is unequal among individuals with different sociodemographic characteristics such as those listed above (Van Dijk, 2017; Van Deursen & Van Dijk, 2011). The second level is linked to both the use and skills needed for the efficient use of ICTs (Zillien & Hargittai, 2009; Hargittai, 2002). Studies focusing on this level have explored the types of activities that people perform online and the skills needed for this purpose (Van Deursen et al., 2017; Van Deursen & Van Dijk, 2014). Regarding Internet use, Van Deursen and Van Dijk (2014) mention the need to acquire new skills when going online due to the enormous amount of data and people’s growing dependency on the exploration of this information. Lastly, the third-level digital divide consists of using the Internet to obtain a specific benefit; therefore, insufficient skills hinder the efficiency to perform certain online tasks (Scheerder et al., 2017; Van Deursen & Helsper, 2015). Research dealing with this category has studied individuals who benefit from Internet use in terms of a wide range of offline outcomes (Van Deursen et al., 2017; TiradoMorueta et al., 2017). According to Van Deursen and Helsper (2015), the ability to turn ICT usage into tangible outcomes depends on the individual’s operational, Internet browsing, and social and creative skills. Additionally, current studies provide further details on the differences in Internet use. These works are based on the assumption that some activities are 7

more beneficial to Internet users as they offer, for example, more opportunities and resources to improve their education, employment, professional life, and social position, compared to activities that offer only consumption or entertainment benefits (Van Deursen & Van Dijk, 2014; Zillien & Hargittai, 2009). According to Hargittai and Hinnant (2008), and DiMaggio et al. (2004), analyzing Internet usage provides greater insight into the differences in equipment, uses, skills, and purposes for which the Internet is employed.

2.3 Literature review: From Internet access to Internet use Research addressing Internet access and use focuses on both developed and developing countries. In the case of Latin America, some authors indicate that the digital gap is present and can be identified through an analysis of groups and individuals, whether segmented by age (Barrantes & Vargas, 2019), gender (Mariscal et al., 2019), or vulnerability, such as the elderly or native speakers of indigenous languages (Galperin, 2017). The first two studies emphasize that the digital gap persists in the analyzed groups and that doing online activities depends on the specific characteristics of each group; they conclude that public policies must be implemented to promote Internet access and use among those individuals who are the most excluded, such as women. Employing information from Colombia, Ecuador, Mexico, and Peru; Galperin (2017) states that the barriers to adopting Internet are associated with high costs, the limited availability of services, and the lack of digital skills. Furthermore, a group of researchers has recently begun to explore the differences in Internet penetration rates in poor and rich countries (Dohse & Cheng 2018; Zhang, 2017; Sujarwoto & Tampubolon, 2016; Srinuan & Bohlin, 2013; Chinn & Fairlie, 2010; Quibria et al., 2003; Kiiski & Pohjola, 2002). These studies highlight that when considering supply and demand perspectives, the main factors that explain Internet access are related to income, educational level, infrastructure, and level of competition among service providers. Based on OECD data from 60 countries, and a focus on supply perspective, Kiiski and Pohjola (2002) found that income, land telephone costs, and years of schooling are the main factors that 8

determine online access. From the same perspective, Chinn and Fairlie (2010) use more recent data with similar results: The divide between developed and developing countries is related to income, telephone density, and legal and institutional environment. Other studies with the same perspective mention that the availability of Internet infrastructure in rural areas is at an incipient stage, due primarily to low population density and high network costs (Park et al., 2019; Gwaka et al., 2018; Salemink et al., 2017) From the demand side, income disparities within a country prevent Internet diffusion (Srinuan & Bohlin, 2013). Furthermore, Dohse and Cheng (2018) consider geographic location, which is particularly important when analyzing the distribution of the digital divide. This finding can be explained as the result of a lack of telecommunications infrastructure in rural and remote areas.6 Some studies have centered on the decision to have an Internet connection at home, a factor that shows a positive correlation with income, educational level, and the presence of children at home (Michailidis et al., 2011; Chaudhuri et al., 2005). Another set of studies has focused on identifying the determinants of Internet uses (Penard et al., 2015; Kilenthong & Odton, 2014; Prieger, 2013). These studies show that socioeconomic factors such as age, income, and educational level influence the decision to use the Internet, but they do not influence the activities that users conduct online. Internet usage patterns like communication, entertainment, social networks, and e-commerce can be largely explained as dependent on digital skills (Garín-Muñoz et al., 2019). Literature focusing on countries in the Latin American region is less extensive (Martínez-Domínguez, 2018; Nishijima et al., 2017; Correa et al., 2017; Grazzi & Vergara, 2012 and 2014; Gutiérrez & Gamboa, 2010). Regarding Internet diffusion, Grazzi and Vergara (2014) found that, in addition to the traditional socioeconomic factors that determine Internet access, network effects also play a central role as does the presence of students in the household. Gutiérrez and Gamboa (2010) identified that the most significant limitation for Internet usage in

6 Pick and Nishida (2015) reveal that Internet use is influenced by the geographic location, in addition to social, economic, governmental, and social openness factors.

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low-income populations in Colombia, Mexico, and Peru, is lack of education. In another study, Grazzi and Vergara (2012) analyzed the effects of language on Internet use in Paraguayan households, and their results suggest that the Guaraní language is a cultural barrier for ICT diffusion in the country. Using data from 2005, 2008, 2011, and 2013, Nishijima et al. (2017) explored the evolution of the digital divide in Brazil and found that the factors that foster Internet usage are linked to a higher level of education, income, employment, and number of household members. In their analysis of 22 communities in Chile, Correa et al. (2017) found that age, income, social capital, and the presence of children at home explain the level of Internet usage. In Mexico’s case, few studies have addressed the digital divide in urban and rural contexts by using microeconomic data (Toudert, 2019). A recent study by Martínez-Domínguez (2018) identified the determinants of Internet access and use at the national level. Yet this research focuses only on general Internet usage, and does not investigate the types of uses (communication, entertainment, social networks, e-commerce, and e-government). The latter task has become central to achieving the study objective. Therefore, in distinguishing among types of Internet usage, the goal is to broaden and deepen knowledge of Internet access, use, and usage patterns among Internet users in Mexico’s rural sector, which presumably is in the early stages of Internet diffusion.

3. Data and methodology

3.1 Data description Data used in this study was collected from the ENDUTIH 2017 survey,7 which was conducted throughout Mexico during the second quarter of 2017. The units of analysis are households and individuals. The methodological procedure is based

7 Since 2017, the sampling design of ENDUTIH has been probabilistic. Therefore, the results can be generalized in the following domains (nation, state, urban setting, rural setting, and city).

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on the current international norm.8 This survey compiles information on the availability and use of ICT by households and household members, who include people aged six and older who reside in Mexico. During the fieldwork, households are visited and personal interviews are carried out with household members selected randomly; their experience with ICT is inputted. Due to the survey's sampling design, the compiled information is statistically representative of the rural Mexican sector. The sample includes information from 74,932 individuals between 12 and 70 years of age, and thus represents Mexico’s rural9 population within this age range. The data contain sociodemographic information such as gender, age, educational level, and occupation. The survey’s main topic is ICT availability and use (desktop computer, laptop or tablet, Internet and mobile telephone).10 Participants were asked about the frequency of usage, connection equipment, online activities, and reasons for using the Internet. The survey also provides information on individuals' digital skills and the electronic devices they own (tablet, computer, and conventional telephone or smartphone). Table 1 shows descriptive statistics from the sample. In terms of gender, 51% of the respondents are female and the rest are male; 48.20% are 32 years old or younger, which reflects the presence of a young population in rural areas. Regarding education, 36.36% were enrolled in primary school, 37.22% in secondary school, 15.86% in high school, and only 4.80% in college. This data reflects the limited opportunities and educational achievements typical of Mexico's rural regions, a factor that deepens inequalities within the sector and increases the exclusion and educational backwardness of the rural population. With regard to work, 50.23% of the respondents are employed mainly in the categories of manual labor and day labor (24.14% and 11.57%, respectively),

8 ENDUTIH concepts and methodology are based on the International Telecommunication Union's manual for measuring ICT use and access by households and individuals (ITU, 2014). 9 In Mexico, the rural sector is defined as towns with less than 2,500 inhabitants (INEGI, 2017). 10 Regarding Internet access at home, respondents were asked about their network connection type (dedicated telephone line, cable Internet, satellite connection, open WiFi signal, and landline).

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which together represent 35.71% of employed individuals.11 The rest are either housewives, retirees, or students. As for digital connectivity in Mexico’s rural areas, although only 7.97% of households had an Internet connection in 2017, 40.51% of the respondents use the Internet in other places such as the workplace, school, an Internet café, free public spaces, another person’s home, and even in their own houses. Additionally, the proportion of rural mobile telephone users is 66.14%.

Table 1. Descriptive statistics for rural Mexico’s population and Internet users, 2017 Variable

Internet access

Internet adoption Gender Age (12-32) Age (33-64) Age (65 and over) No formal education Primary education Secondary education High school education

Definition

The household has a fixed or mobile Internet connection (Yes=1) Has used the Internet in the last 3 months Female=1 Respondents aged 12-32 years (Yes=1) Respondents aged 33-64 years (Yes=1) Respondents aged 65 years and older (Yes=1) Unschooled (Yes=1) Primary school (Yes=1) Secondary school (Yes=1 High school or equivalent (Yes=1)

Mean of rural population (standard deviation)

Mean of rural Internet users (standard deviation)

26.79 (0.442) 39.67 (0.489) 51.13 (0.500) 48.20 (0.499) 47.01 (0.499) 4.80 (0.214) 5.87 (0.235) 36.36 (0.481) 37.22 (0.483) 15.86 (0.365)

51.04 (0.500) 71.38 (0.452) 28.14 (0.450) 0.48 (0.069) 0.40 (0.063) 16.54 (0.372) 43.12 (0.495) 28.99 (0.454)

11 This distinction between the two types of occupations is relevant because, in spite of their coexistence in rural areas, the secondary and tertiary sectors have become in recent decades the main sources of employment and income in rural Mexico (Mora-Rivera et al., 2017).

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University education Day worker Manual worker Business owner Self-employed worker Unpaid work Does not work Wealth index Software or applications Computer Cell phone

University (Yes=1) Works in the agricultural sector (Yes=1) Works in industry, commerce or services (Yes=1) Employer who hires workers (Yes=1) Self-employed and does not hire workers (Yes=1) Unpaid work in a family or nonfamily business (Yes=1) Retiree, housewife, disabled, unemployed, or student (Yes=1) Household wealth index Ability to download software or applications (Yes=1) Owns a computer or similar device (Yes=1) Has a cell phone (Yes=1)

Relatives within household who use the Internet Northwest region

At least one household member uses the Internet (Yes=1) Lives in the Northwest region

Northeast region

Lives in the Northeast region

West region

Lives in the West region

South-Central region North-Central region East region

Lives in the South-Central region Lives in the North-Central region Lives in the East region

Southeast region

Lives in the Southeast region

Southwest region

Lives in the Southwest region

Number of observations

4.80 (0.214) 11.57 (0.320) 24.14 (0.428) 0.57 (0.075) 12.02 (0.325) 1.93 (0.138) 49.77 (0.500) -0.91 (1.934) 5.82 (0.234) 23.25 (0.422) 66.14 (0.473) 42.02 (0.494)

10.95 (0.312) 5.88 (0.235) 31.72 (0.465) 0.79 (0.089) 8.41 (0.278) 1.83 (0.134) 51.37 (0.500) -0.36 (1.567) 12.88 (0.336) 55.62 (0.497) 93.86 (0.240) 66.85 (0.471)

17.82 (0.383) 8.69 (0.282) 12.41 (0.330) 6.99 (0.255) 16.96 (0.375) 13.65 (0.343) 13.52 (0.342) 9.95 (0.299) 73676

21.09 (0.408) 8.76 (0.283) 12.93 (0.336) 8.13 (0.273) 15.37 (0.361) 12.24 (0.328) 14.76 (0.355) 6.72 (0.250) 29224

Source: By author based on data from the ENDUTIH survey, 2017. Note: Yes=1 indicates the presence of the respective attribute or characteristic.

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3.2 Methodological approach To identify the factors that determine Internet usage patterns in rural Mexico, six usage types were identified: information searches, communication, entertainment, social networks, e-commerce, and e-government. Table 2 shows the proportion of Internet users by activity type. Outstanding among these activities are communication (phone conversations, sending emails, and instant messaging) and entertainment (multimedia content, such as videos and music). Overall, ecommerce is the activity that rural users carry out least frequently when going online.

Table 2. Descriptive statistics for Internet use in Mexico’s rural sector, 2017 Variable

Definition

Information

Health, employment, education, travel, blogs, and online courses Phone conversations, emails, and instant messaging Books, magazines, multimedia content, and online games Facebook, Twitter, Instagram, LinkedIn, and Snapchat Buying and selling products or services online Government procedures and finding government information

Communication Entertainment Social networks E-commerce E-government

Frequency of usage (%) 79.90

91.99 80.27 79.83 10.43 29.21

Source: By author based on data from the ENDUTIH survey, 2017.

First, a logistic regression model was used to estimate the determinants of Internet access, where the dependent variable is binary (1 indicates that the household has an Internet connection and 0 indicates that it does not) and the independent variables are a set of socioeconomic and demographic characteristics at the household and individual level. Second, two equations were established to model the Internet adoption decisions and Internet usage patterns in the rural sector. It is noteworthy that the selection of online activities is conditioned by the decision to use the Internet. Given that population characteristics differ in the two 14

models, the second equation may present selectivity problems. To solve the potential presence of such bias, Heckman’s two-stage method (1979) was used, to provide consistent and asymptotically efficient estimates for all parameters in the models. To identify the determining factors of Internet adoption and usage, we have decided to follow the recommendations of some studies that point out that such dependent variables can be explained with a higher confidence level by incorporating the existing differences between individuals and households; in this way, econometric results are more precise and reliable, and permit generating public policy recommendations with a more defined focus and target (Forenbacher et al., 2019; Mascheroni & Ólafsson, 2016; Nishijima et al., 2017; Correa et al., 2017). The first equation represents a probit model, whereby the individual chooses whether to adopt the Internet or not. The basis of this perspective is the utility maximization model, which explains that the usefulness of adopting the Internet depends on a set of individual and household characteristics: a reflection of differences in education, skills in ICT usage, financial circumstances, social capital, and age, among other variables. This theoretical focus has been used in recent studies by Alderete (2019) and Quaglione et al. (2018). Due to the above, the adoption decision is determined by the maximization of utility in using the Internet per individual and can be represented by: ∗ ‫ݕ‬௜଴ = ܺ௜଴ ߚ଴ + ߝ௜଴

Where ܺ௜଴ is a matrix of independent variables such as sociodemographic characteristics, social capital, and digital skills, and ߚ଴ represents the coefficient vector and ߝ௜଴ is the normally distributed random error term. The total utility is not observable, but the decision to adopt the Internet or not is. Consequently, ‫ݕ‬௜଴ is the result of a decision-making process influenced by the explanatory variables ܺ௜଴ . Thus, ‫ݕ‬௜଴ = 1 indicates that the individual has decided to use the Internet and ∗ ∗ ‫ݕ‬௜଴ = 0 indicates otherwise. Accordingly, ‫ݕ‬௜଴ = 1 if ‫ݕ‬௜଴ > 0, and ‫ݕ‬௜଴ = 0 if ‫ݕ‬௜଴ ≤ 0.

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The second equation establishes the selection of online activities, which are conditioned by the decision to use the Internet. Internet usage patterns ݆ (where ݆ = 1, … , ‫ )ܬ‬are defined in the equation ‫ݕ‬௜௝ = ܺ௜௝ ߚ௝ + ߝ௜௝ , where ‫ݕ‬௜௝ measures usage, ܺ௜௝ represents the matrix of independent variables, and ߝ௜௝ is the normally

distributed random error term. To estimate these equations, Heckman’s two-stage method was applied under the assumption that ߝ௜଴ and ߝ௜௝ follow a bivariate normal distribution with zero mean and correlation (ߝ௜଴ , ߝ௜௝ ) = ߩ. As a result, when applying this methodology we can state that if the estimated ߩ(rho) coefficient is significantly different from zero, then it indicates the presence of a bias (Wooldridge, 2010; Maddala, 1983).

3.3 Description of variables The independent variables in the first (Internet adoption) and second (Internet usage patterns) equation are grouped into three categories: respondents’ socioeconomic and demographic characteristics, digital skills, and availability of electronic devices, in addition to social capital. Socioeconomic variables include gender, age, educational level, household wealth index, and the individual’s occupation. With regard to the effect of the gender variable, Gray et al. (2017), and Hilbert (2011) argue that, in the initial stages of diffusion of a new technology, men are the first ones to use it; however, as time goes by and the technology continues to spread, the gap between men and women is narrowed. Thus it is expected that women in Mexico’s rural sector are less likely to use the Internet. Regarding age, studies by Tirado-Morueta et al. (2017), and Hargittai and Hinnant (2008) reveal that Internet users are, to a great extent, young people. Consequently, and in order to identify the effect of age on Internet adoption and use, three age ranges were established: 12-32 years; 33-64 years; 65 years and older. A negative relationship between age and the decision to use the Internet is expected; that is, the older a person is, the less likely that person will use the Internet.

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Another crucial factor is education, since using the Internet requires basic reading and writing skills. A higher educational level is associated with greater benefits when adopting the Internet (Penard et al., 2015). To measure the educational level, five categories were established: primary education, secondary education, high school education, university or higher, and no formal education (level used as a reference category). Therefore, we expect to find that a higher educational level means a greater likelihood of using the Internet. Similarly, respondents’ employment situation was considered by classifying them into the following categories: day worker, manual worker, business owner, unpaid worker, and self-employed worker, the latter being the reference occupation. Evidence indicates that employment in commerce and service-related activities increases the possibilities of having and using the Internet in the workplace. Income is also a key element in explaining Internet adoption (Gray et al., 2017). Since ENDUTIH 2017 does not include information to estimate individual income, a wealth index was calculated using the Principal Component Analysis (PCA) method, which included variables related to household characteristics and ownership of durable goods (Filmer & Pritchett, 2001).12 It is assumed that the wealth index is a suitable proxy variable for income, as it reflects the families’ living conditions. In terms of digital skills, research carried out by Scheerder et al. (2017), and Van Deursen and Helsper (2015) shows the positive effect of these skills when using the Internet. Skill levels were measured in terms of an individual’s ability to download software or applications. Only 5.98% of respondents have sufficient knowledge to install software. This could reflect the low levels of digital skills in Mexico's rural population. As for ownership of electronic equipment and devices, 24.24% of the respondents own a computer and 66.64% have a cell phone. The availability of

12 Variables included in the index are: flooring material, drinking water, sewage, electric power, refrigerator, and washing machine.

17

these electronic devices is complementary to Internet use; in other words, interest in using these technologies should encourage Internet usage. Likewise, social capital influences the decision to adopt new technologies. Studies by Puspitasari and Ishii (2016), Grazzi and Vergara (2014), Hierro et al. (2014), and Franzen (2003) highlight the ways that friends and relatives can influence ICT usage. On this point, Schleife (2010) shows the positive effects of social capital in Germany, where the probability of being a new Internet user is higher for individuals who are surrounded by already experienced users. Therefore, family networks play a crucial role in adopting and learning how to use the Internet by strengthening external networks and increasing the benefits of this technology (Barbosa & Fonseca, 2015; Penard & Poussing, 2010). To measure the effects of family networks, a binary variable was established, where 1 indicates the presence of other household members who use the Internet and 0 indicates otherwise. It is expected that having relatives who go online promotes the frequency of Internet usage and encourages a variety of usage

types,

conversations,

especially in the case emails, and

instant

of

communication through

messaging. As

for

phone

sociodemographic

characteristics and ICTs, Penard et al. (2015) point out that they indirectly influence usage through differences in opportunity cost and digital skills. Lastly, geographic location is essential for Internet penetration in the rural sector. According to data from Mexico's national census of 2010, 23.2% of the nation's inhabitants were living in rural areas; the southern states (Veracruz, Chiapas, Oaxaca, and Guerrero) had one-third of the nation's rural population along with the highest levels of marginalization and poverty (Martínez et al., 2018). In contrast, the states in the central and northern regions had the highest levels of social, economic, industrial, and ICT infrastructure development (MartínezDomínguez, 2018). To incorporate the heterogeneity of Mexico's rural sector into the econometric models, the country was divided into eight regions: south central,

18

northwest, west, northeast, north central, east, southeast, and southwest (reference region).13 By considering the above aspects and variables, the principal objective is that the results of the econometric estimations will allow reliable identification of the factors that determine the most recurrent Internet uses (information search, communication, entertainment, social networks, e-commerce, and e-government).

4. Results and discussion

4.1 Determinants of Internet access The results of the Internet access estimates for Mexico’s rural areas are shown in Table 3. Our findings confirm that wealth index and educational level are key to Internet penetration; that is, households with the highest physical and human capital have greater incentives to use the Internet, a result consistent with the study by Chaudhuri et al. (2005), who mention that such variables positively impact Internet access. As for household characteristics, having a greater number of students at home increases the chances of using this ICT, a finding that suggests that the Internet is used mainly for educational purposes. Similarly, the presence of children under age twelve discourages Internet access, since the greater the number of economic dependents, the lower the Internet access. This evidence contrasts with the findings by Michailidis et al. (2011), who point out that Internet access is influenced by a greater number of underage family members. Regarding geographic location, rural households located in the northeast region are more likely to be connected to the Internet. This coincides with the study by MartínezDomínguez (2018), which reveals that a set of federal and state public policies have been implemented in states located closer to the US border to boost access to ICTs.

13 The 2018 study of Internet Users’ Habits in Mexico was used as a reference to divide the country into geographic areas (Asociación de Internet.mx, 2018).

19

Table 3. Results of logit model for the determinants of Internet access in rural Mexico, 2017 Variables Gender (Female=1) Age Age squared Education (years of schooling) Student Day worker Manual worker Business owner Unpaid worker Self-employed worker Unemployed Household’s wealth index Household size Number of underage children at home Number of elderly people at home Northwest region Northeast region West region South central region North central region East region

Marginal effects (standard error) 1.82*** (0.0039) 0.17** (0.0007) -0.001 (0.0000) 2.04*** (0.0005) 7.20*** (0.0066) -3.84*** (0.0066) 1.99*** (0.0060) 19.43*** (0.0256) -5.02*** (0.0115) Reference -3.19*** (0.0059) 5.52*** (0.0011) 1.97*** (0.0011) -1.66*** (0.0016) -4.51*** (0.0033) 23.99*** (0.0086) -4.88*** (0.0074) 0.19 (0.0076) 6.12*** (0.0091) -5.17*** (0.0066) -7.89*** (0.0064) 20

Southeast region Southwest region Log likelihood Wald chi2 Number of observations

19.37*** (0.0088) Reference -36299.858 10539.15 73676

Note: ***, **: significant at 1% and 5%, respectively.

4.2 Determinants of Internet use Table 4 shows the results for the determinants of Internet use. Overall, deciding whether to use the Internet or not depends on the benefits expected from going online and the monetary and cognitive costs. The likelihood of using the Internet is higher for women, young people, and people with higher educational levels. There is an evident gap in terms of age: The older a person is, the less likely that person is to use the Internet: a finding that indicates that young people are more engaged with technology, while older adults adapt less to new technologies. Material access and affordability are essential when using the Internet given that people with a better economic standing are, to a greater extent, Internet users. A similar result was found by Kilenthong and Odton (2014) for Thailand. As for occupation, business owners have more probabilities of using the Internet, while the opposite happens with day workers. As for digital skills, the likelihood of using the Internet increases when a person possesses sufficient abilities to download software and applications from the Internet. This result is consistent with research conducted by Grazzi and Vergara (2014) for seven Latin American countries, thus highlighting the relevance of digital skills in taking advantage of the Internet’s potential. Likewise, geographic location is essential for Internet usage, since people living in the country’s northern region are more likely to go online, a finding observed in other developing countries in a study by Dohse and Cheng (2018). Lastly, having relatives who go online has a positive effect on individual usage as it encourages using the Internet as a tool for communication, entertainment, the search for information, and social networks. This finding is consistent with research

21

by Hierro et al. (2014), which highlights the influence of friends and relatives on Internet usage.

Table 4. Determinants of Internet use (first stage) Variable Gender (Female=1) Age (12-32 years) Age (33-64 years) Age (65 years and older) No formal education Primary education Secondary education High school education University education Day worker Manual worker Business owner Self-employed worker Unpaid worker Unemployed Household’s wealth index Can download software and applications Owns a computer Owns a cell phone Household members who use the Internet Northwest region

Marginal Effects (Standard error) 2.64*** (0.0058) 21.24*** (0.0053) Reference -18.04*** (0.0122) Reference 16.94*** (0.0196) 29.33*** (0.0191) 35.95*** (0.0207) 44.51*** (0.0229) -6.13*** (0.0095) 2.94*** (0.0086) 16.86*** (0.0326) Reference -2.73 (0.0184) -0.89 (0.0086) 2.85*** (0.0015) 17.71*** (0.0142) 70.36*** (0.0059) 45.50*** (0.0044) 27.59*** (0.0050) 4.45*** 22

Northeast region West region South central region North central region East region Southeast region Southwest region Log likelihood Wald Chi2 Number of observations

(0.0108) 3.40** (0.0123) 3.72*** (0.0115) -1.18 (0.0123) -5.53*** (0.0102) -1.79* (0.0108) 11.41*** (0.0119) Reference -21849.187 16397.74 73676

Note: ***, **, *: significant at 1%, 5% and 10%, respectively.

4.3 Determinants of Internet use Table 5 shows the results of Heckman’s two-stage model on the determinants of the most common Internet uses in Mexico’s rural sector (search for information, communication, entertainment, social networks, e-commerce, and e-government). Internet usage patterns are influenced by gender, age, educational level, occupation, digital skills, and geographic location. Women use the Internet to search for information and to communicate, a finding which coincides with that reported by Penard et al. (2015) for Cameroon. This result suggests that women begin using the Internet to maintain networks of family and friends, an activity that is broadly related to women's roles in traditional settings such as those of rural Mexico. On the other hand, young individuals are more likely to use the Internet for leisure activities (entertainment and social networks) than older age groups. In terms of education, the individuals most likely to use the Internet for searching for information are those who are enrolled in secondary school, which suggests that Internet usage has educational purposes. This matches Grazzi and Vergara’s (2014) results, whose study emphasizes the Internet’s potential to

23

develop human capital. As for occupation, day workers and manual workers are the least likely to conduct activities online. Geographic location is essential to explain Internet usage patterns. The results on the regional scale prove the heterogeneity of Mexico's rural sector. For instance, in the northwest and northeast regions, the Internet is used for ecommerce activities, due to the regions' proximity to the United States (a nation with high levels of ICT access and usage). In addition, the northern states have promoted public policies to favor Internet usage, which in turn has encouraged marked growth in social networks. In contrast, the south central and southeast regions are less likely to show online use for searching for information, communication, entertainment, or social networks, due to the high levels of poverty and lags in education, health, basic services, and housing in these regions. Lastly, having at least one family member at home who uses the Internet increases the probability that other members will perform online activities.

Table 5. Determinants of Internet uses (second stage) Variables

Gender (female=1) Age (12-32) Age (33-64) Age (65 and older) No formal education Primary education Secondary education High school education University education Day worker Manual worker Business owner

Information Searches 1.88*** (0.0028) -0.29 (0.0032) Reference 1.77 (0.0201) Reference 3.98 (0.0286) 5.22* (0.0292) 7.85** (0.0396) 10.18** (0.0482) -3.05*** (0.0052) -1.58*** (0.0043) -0.58 (0.0124)

Communi- EntertainSocial Ecation ment networks commerce Marginal effects (standard error) 3.14*** 0.43 2.10*** -0.08 (0.0029) (0.0029) (0.0024) (0.0006) -0.15 1.01*** 1.53*** -0.12 (0.0031) (0.0033) (0.0024) (0.0009) Reference Reference Reference Reference 4.21** 5.57** -0.68 0.21 (0.0209) (0.0265) (0.0129) (0.0062) Reference Reference Reference Reference -0.58 (0.0180) 1.16 (0.0188) 1.77 (0.0208) 2.18 (0.0227) -1.32** (0.0056) -1.53*** (0.0040) -0.39 (0.0122)

2.95 (0.0266) 3.22 (0.0265) 4.20 (0.0316) 4.83 (0.0353) -0.62 (0.0069) -1.15** (0.0048) -0.56 (0.0134)

1.31 (0.0182) 3.19* (0.0193) 4.68* (0.0251) 4.94* (0.0282) -0.48 (0.0051) -0.79** (0.0036) -0.86 (0.0102)

-0.34 (0.0056) -0.12 (0.0059) 0.38 (0.0080) 1.52 (0.0159) -0.47*** (0.0011) -0.26*** (0.0009) -0.04 (0.0026)

Egovernment -0.74*** (0.0018) 0.71*** (0.0020) Reference 1.36 (0.0170) Reference 9.74** (0.0954) 5.85 (0.0383) 7.20 (0.0574) 16.48* (0.1006) -1.30*** (0.0037) -0.34 (0.0032) 1.35 (0.0120)

24

Self-employed worker Unpaid worker Unemployed Can download software and applications Household members who use the Internet Northwest region Northeast region West region South central region North central region East region Southeast region Southwest region Log pseudolikelihood Rho

Reference

Reference

Reference

Reference

Reference

Reference

-1.89** (0.0081) -0.54 (0.0047) 66.05*** (0.0120)

-2.65*** (0.0070) -2.94*** (0.0047) 81.74*** (0.0106)

-1.94** (0.0089) -1.53*** (0.0052) 73.33*** (0.0109)

-2.23*** (0.0056) -1.66*** (0.0039) 62.34*** (0.0134)

-0.19*** (0.0019) -0.72*** (0.0016) 8.08*** (0.0088)

-0.25 (0.0066) 1.52*** (0.0034) 22.11*** (0.0127)

20.01*** (0.0061)

23.24*** (0.0063)

20.68*** (0.0061)

17.48*** (0.0054)

1.17*** (0.0016)

7.14*** (0.0050)

-0.75 (0.0054) -1.03* (0.0059) -1.37** (0.0054) -0.77 (0.0059) -0.60 (0.0056) 0.70 (0.0065) -1.81*** (0.0051) Reference

-0.47 (0.0054) -0.27 (0.0062) -0.69 (0.0056) -1.91*** (0.0052) -1.30** (0.0052) -0.32 (0.0059) -0.17 (0.0057) Reference

-0.72 (0.0057) -1.26** (0.0062) -1.19** (0.0059) -1.46** (0.0060) -1.03* (0.0058) -0.54 (0.0063) -2.51*** (0.0052) Reference

1.11** (0.0051) 1.32** (0.0060) 0.48 (0.0052) -0.83* (0.0047) -0.09 (0.0047) -0.09 (0.0050) -1.86*** (0.0040) Reference

1.52*** (0.0041) 1.66*** (0.0053) 0.58** (0.0029) 0.37 (0.0027) 0.60** (0.0028) 0.26 (0.0023) 0.17 (0.0021) Reference

-0.06 (0.0036) -0.51 (0.0038) -0.45 (0.0036) 1.53*** (0.0055) 0.16 (0.0039) 0.92** (0.0047) 0.03 (0.0039) Reference

-31920.8

-31993.6

-31529.8

-31945.4

-24941.8

-28012.2

0.0597** (0.0279) 73676

0.4138*** (0.0336) 73676

-0.0446 (0.0301) 73676

0.2709*** (0.0315) 73676

-0.2606*** (0.0454) 73676

-0.3954*** (0.0307) 73676

Number of observations Note: ***, **, *: significant at 1%, 5% and 10%, respectively.

5. Conclusions

The aim of this study was to identify the determinants of Internet availability, Internet use, and Internet usage patterns in Mexico’s rural areas, based on information from the ENDUTIH 2017 survey. The results of the econometric estimates suggest that the factors explaining Internet access and use in rural Mexico are similar to those observed in other developing countries for the initial stage of Internet diffusion. In general, we can deduce that rural Internet users are young and educated people with a good economic standing and knowledge of digital

technologies.

Internet

usage

patterns

(search

for

information,

communication, entertainment, social networks, e-commerce, and e-government) 25

differ significantly by gender, age, educational level, occupation, and geographic location, resulting in a digital divide between those who know how to use and take advantage of the Internet, and those who do not. As mentioned above, the literature has identified three levels within the digital divide: access, usage, and benefits (Van Dijk, 2006; Van Deursen & Van Dijk, 2014; Van Deursen et al., 2017). This research provides empirical evidence on the existence of the first two levels of the digital divide in rural Mexico’s Internet use. This information contributes to a discussion of academic literature on the digital divide by showing the factors that explain individuals’ Internet usage behaviors. It is worthwhile to note that very few studies have looked at this topic in the rural context due to a lack of information at the microeconomic level. The findings of the analysis show that the divide in terms of Internet access is still considerable in Mexico’s rural sector. Nevertheless, Internet use is an equally important challenge since a large portion of the rural population has low educational levels (6.5 years) and is not in contact with ICTs. Therefore, reducing the digital divide requires: improving access conditions by developing adequate infrastructure and providing high-speed Internet service; reducing the costs associated with connecting to the Internet by encouraging greater competition among service providers; and teaching digital literacy to individuals in a way that highlights the advantages and benefits derived from efficient Internet usage. The results also reveal that Internet usage patterns for younger users are related to entertainment and social networks, a factor that poses an important challenge for the Mexican government. On one hand, young people must receive digital training in order to foster efficient Internet use, and ICTs must become an essential part of educational programs from primary school through university. On the other hand, creating local content that promotes the preservation of indigenous languages, local music, and information must be encouraged with the goal of protecting the traditions and cultures of the rural population. In 2017, rural Mexico had mobile telephone and Internet usage rate of 53.83% and 39.16%, respectively. These numbers reflect higher mobile telephone 26

coverage in the past few years, thus making it relevant to research and compare usage patterns. To this end, it is essential to have appropriate data that will allow observing the evolution of the digital divide and identifying user profiles, as well as providing the required elements to design digital policies centered on cell phone diffusion with the purpose of offering employment, education, and health-related services and applications that benefit rural populations in developing countries. It is important to point out that this study does not cover the third level of the digital divide, due to the limitations of the information contained in ENDUTIH. This area represents an opportunity for future research; in other words, databases could be generated to consider the benefits of Internet usage and the element could be added to the analysis of the digital divide. On the other hand, the possibility also exists to employ additional methods to strengthen our findings and support recommendations for public policies that promote the well-being of the rural population in developing countries like Mexico.

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Highlights

In rural Mexico, females are more likely than males to use the Internet. Internet usage patterns differ by age, educational level, and employment type. Younger users are more likely to do online activities for entertainment purposes. Workers go online for information, communication, and e-commerce. Higher educational levels increase the variety of types of Internet usage.