Frugal innovation and the digital divide: Developing an extended model of the diffusion of innovations

International Journal of Innovation Studies xxx (2018) 1e12

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Frugal innovation and the digital divide: Developing an extended model of the diffusion of innovations Xiaoqun Zhang Department of Media Arts, University of North Texas, 1155 Union Circle #310589, Denton, TX, 76203, USA

a r t i c l e i n f o

a b s t r a c t

Article history: Received 15 January 2018 Accepted 20 June 2018 Available online xxx

Based on diffusion of innovation (DOI) theory and economic consumption analysis as well as the concept of frugal innovation, this study develops an extended DOI model that theorizes the characteristics of the diffusion of frugal information communication technologies (ICTs) and their impacts on the Internet diffusion. This model posits that frugal digital ICTs diffuse more rapidly in developing countries than in developed countries and significantly bridge the digital divide between them. The diffusion of frugal smartphones is investigated as a case of the diffusion of frugal digital ICTs, which provides empirical evidence for the theoretical model presented herein. © 2018 Publishing Services by Elsevier B.V. on behalf of KeAi Communications Co., Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/ licenses/by-nc-nd/4.0/).

Keywords: Frugal innovation Diffusion of innovation Information communication technology Digital divide Smartphone

Introduction Frugal innovation is low priced but can meet the specific needs of target consumers (Bhatti, 2012). This is different from high-end innovation, which is invented and diffused mostly in developed countries characterized by abundant resources, sufficient affordability, and mature infrastructure (Schanz, Husig, Dowling, & Gerybadze, 2011). Frugal innovation is usually invented and diffused in developing countries, where resources are strictly limited, consumers have low purchasing power, and there is insufficient infrastructure. Scholars have shown increasing interest in frugal innovations in recent years as these innovations can satisfy the demands of the majority of the population living in developing countries, developing conceptual frameworks of frugal innovation and conducting case studies. However, compared with the vast body of research on the diffusion of high-end innovations, research on the diffusion of frugal innovations is scarce (Hossain, Simula, & Halme, 2016). This study explores the diffusion characteristics of a specific frugal innovation: frugal information communication technologies (ICTs). ICTs are defined as “the combination of informatics technology with other, related technologies, specifically communication technology” (UNESCO, 2002, p. 13). OECD (2002) defined the ICT sector as “a combination of manufacturing and services industries that capture, transmit and display data and information electronically” (p. 81), which includes nondigital ICTs such as antenna radios and TVs and digital ICTs such as computers and mobile phones. ICTs play significant roles in contemporary society. They are widely used in the manufacturing and service sectors and have become central to information management integration, which is opening up new opportunities for business management (Maraghini, 2010). They are also major platforms through which people communicate with each other as well as obtain and distribute information and knowledge on the Internet. Owing to their significant impact on contemporary society, the United Nations (2009) advocated access to ICTs as a basic human right. In addition, ICTs play a crucial role in achieving the

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Please cite this article in press as: Zhang, X., Frugal innovation and the digital divide: Developing an extended model of the diffusion of innovations, International Journal of Innovation Studies (2018), https://doi.org/10.1016/j.ijis.2018.06.001

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Millennium Development Goals such as promoting higher education, improving healthcare services, and facilitating occupational advancement (United Nations Development Programme, 2008). Many ICTs meet the two essential criteria of frugal innovations: low prices that are affordable to low-income people and basic functions that address people's communication needs. Mobile phones are major ICTs (ITU, 2017; OECD, 2002) through which people access mobile broadband Internet. There are multiple frugal smartphone brands such as Xiaomi that are mainly produced in China at low cost but satisfy people's various needs for mobile broadband services. Mobile phones have diffused rapidly in recent decades. There were 4.08 billion mobile phone users globally in 2012. This number grew to 4.33 billion in 2013 and to 4.55 billion in 2014. The number of smartphone users worldwide reached 1.75 billion in 2014 (Emarketer, 2014). In the United States, more than 72% of the population own smartphones (Pew Research Center, 2016). Like the diffusion of other ICTs, the diffusion of mobile phones exhibits different patterns across countries. The gap between the users and non-users of mobile phones is termed the mobile divide, which is one of the significant aspects of the digital divide (Jung, Chan-Olmsted, & Kim, 2013; Loo & Ngan, 2012; Mir & Dangerfield, 2013). Mobile technology has the potential to bridge the digital divide globally (e.g., Loo & Ngan, 2012; Mir & Dangerfield, 2013; Srinuan, Srinuan, & Bohlin, 2012). As mobile broadband penetration exceeds fixed broadband penetration in many countries (ITU, 2017), mobile media are becoming the major Internet access platforms for the majority of people in the world. Moreover, mobile technology has the potential to achieve multiple development goals such as economic growth, political participation, and education (e.g., Bomhold, 2013; Loo & Ngan, 2012; Martin, 2014; Prieger, 2013). Multiple studies have used diffusion of innovation (DOI) theory to explore the diffusion of mobile phones (e.g., Kalba, 2008; Leung & Wei, 1999; Mallat, 2007; Zhang, 2017). Nevertheless, they do not differentiate frugal phones and high-end phones, which aim at different markets and exhibit different diffusion patterns. While DOI explains general diffusion patterns, it does not expound how the different technical/engineering modes (e.g., frugal phones and high-end phones) of an innovation (e.g., the Internet) diffuse differently in various societies or their joint effects on the diffusion process of that innovation. To bridge this gap in the literature, this study develops an extended DOI model for the Internet diffusion by integrating DOI theory and consumption analysis. This model expounds the different characteristics of the diffusion of frugal ICTs in developed and developing countries and examines their impacts on the diffusion of the Internet in these countries. Based on this model, this study describes the diffusion of frugal and high-end smartphones in the world and their impacts on the digital divide. Two countries, China and the United States, are used as cases to compare the different patterns of the diffusion of frugal and high-end smartphones.

Literature review DOI theory and the digital divide DOI theory was initially proposed by Rogers (1962) and systematically expounded in Rogers (2003). An innovation is defined as “an idea, practice, or object that is perceived as new by an individual or other unit of adoption” (Rogers, 2003, p. 11). This theory explores the complex process of the DOI and provides a classical framework of the characteristics of innovations including their relative advantage, compatibility, complexity, trialability, and observability. Rogers applied this framework to explain why some innovations have higher rates of adoption, while others have lower rates. This framework also includes such factors as communication channels and the characteristics of the social system to analyze the innovation diffusion process. DOI theory also categorizes innovation adopters into innovators (the first 2.5% of adopters), early adopters (the next 13.5% of adopters), the early majority (the next 34% of adopters), the later majority (the next 34% of adopters), and laggards (the last 16% of adopters). DOI theory defines the adoption rate of an innovation as “the relative speed with which an innovation is adopted by members of a social system” (Rogers, 2003, p. 23). It presumes that if the cumulative number of adopters is plotted over time, an s-shaped curve would describe the trajectory of the innovation diffusion process. At the beginning, only a few people adopt the innovation and thus the curve is relatively flat. Gradually, as more people adopt it, the curve becomes steeper. Subsequently, fewer and fewer people are left who have not adopted the innovation and the curve becomes relatively flat again. When this curve reaches its asymptote, the diffusion process is finished. The s-shaped curves are not uniform. Rogers (2003) noted that “there is a variation in the slope of the ‘s’ from innovation to innovation” (p. 23). Some slopes of the s-shaped curves are steep, while others are flat. Curves of the same innovation also exhibit different patterns in different social systems. An s-shaped curve can be generated by using a simple logistic function. However, this uniform function does not reflect the different patterns of the innovation diffusion process. Hence, scholars have developed alternative models to specify these different innovation diffusion processes. In particular, Coleman (1964) proposed the internal-influence model and externalinfluence model. In the former, the adoption rate depends on the interactions between adopters and non-adopters. The adoption rate of this model is described by the following equation:

dA ¼ aAt ðN  At Þ dt

(1)

where A is the number of adopters, N is the population size, a is the coefficient of internal influence, and t is time. Please cite this article in press as: Zhang, X., Frugal innovation and the digital divide: Developing an extended model of the diffusion of innovations, International Journal of Innovation Studies (2018), https://doi.org/10.1016/j.ijis.2018.06.001

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As initial adopters (innovators) comprise only a small proportion of the population, the interactions between them and non-adopters are at a low level and the early adoption rate is slow. Jackson (2008) noted that an s-shaped curve is generated by this model. Rogers (2003) explained the factors that determine the coefficient of internal influence, including the attributes of an innovation and interpersonal communication. In the external-influence model, the adoption rate depends on the factors of the social system (Barnett, 2011). The adoption rate of this model is described by the following equation:

dA ¼ bðN  At Þ dt

(2)

where b is the coefficient of external influence. In this model, external forces have a strong influence on the adoption rate and the diffusion curve begins convexly with a high diffusion rate. This model will generate a curve that resembles an “r” shape (Henrich, 1999) that has a much steeper slope than the normal s-shaped curve. The outside social system factors, especially the mass media, government, and change agents, are the external forces. Moreover, Danowski, Gluesing, and Riopelle (2009) argued that the heavy use of ICTs facilitates the DOI more rapidly in the early stage, making the DOI curves more like r-shapes. In addition to ICTs, they suggested other factors that may drive r-shaped diffusion patterns including the visibility of the number of adopters, ambiguity about an innovation's attributes, herd effects, information cascading, reduced interpersonal communication, and mandated adoption. Based on these two models, a mixed-influence model was proposed by Barnett (2011). The adoption rate of this model is described by the following equation:

dA ¼ ðaAt þ bÞðN  At Þ dt

(3)

In this model, known as the fundamental diffusion model (Mahajan & Peterson, 1985), the coefficients of the internalinfluence model a and external-influence model b determine the shape of the diffusion curve. Furthermore, DOI has been advanced by a theoretical construct termed critical mass defined as the point “at which enough individuals in a system have adopted an innovation so that the innovation's further rate of adoption becomes self-sustaining” (Rogers, 2003, p. 363). Critical mass also influences the shape of the diffusion curve (Valente, 1995). An r-shaped curve has a higher adoption rate than an s-shaped curve in the early stage. Thus, an innovation with an r-shaped curve would reach critical mass faster than one with an s-shaped curve. Therefore, whether an innovation has an r-shaped curve or a normal sshaped curve is a crucial question for studying its diffusion process. Valente (1995) proposed threshold theory to explain the underlying factors behind these two types of curves. He argued that the patterns of diffusion curves are determined by the threshold density functions, with the threshold defined as the point at which the perceived benefits of adoption exceed the perceived costs. The threshold is determined by the proportion of people who adopt an innovation in the social system. When the proportion of adopters is large, an individual would more likely perceive the benefits of the adoption exceed the costs. Then, he/she would more likely adopt the innovation (Granovetter, 1978). Moreover, the threshold density function determines the diffusion curve of an innovation. A symmetrical threshold density function yields an s-shaped diffusion curve, a left-skewed density function generates a flatter diffusion curve, and a right-skewed density function generates a steeper r-shaped diffusion curve (Valente, 1995). Valente (1996) further argued that adoption thresholds are significantly influenced by personal networks, which are the set of direct ties an individual has within a social system (Wellman, 1988). Exposure, defined as “the proportion of adopters in an individual's personal network at a given time” (Valente, 1996, p. 73), is more closely related to adoption thresholds than the proportion of adopters in society. According to this argument, both the internal-influence model and external-influence model are associated with adoption thresholds. The internal influence comes from the interactions between adopters and non-adopters. As an individual has tighter ties with the people in his/her personal networks, adopters in the networks would have more influence on him/her than adopters outside the networks. The external influence comes from social structures that affect people's personal networks. People with the same demographic and socioeconomic statuses (i.e., age, ethnicity, income, and occupation) are more likely to form personal networks than people with different statuses. In the information society, the Internet is crucial for social and economic development (ITU & UNCTAD, 2007). However, the diffusion of the Internet across countries is uneven. The concept of the digital divide has been developed to describe this phenomenon. Originally, the digital divide was defined as the gap between those who have access to the Internet and those who do not (NTIA, 1999), the so-called first-level digital divide. A large number of empirical studies have been conducted on the first-level digital divide, finding that income has a significant correlation with Internet penetration level (e.g., Ahn & Lee, pez, 2009; Bohlin, Gruber, & Koutroumpis, 2010; Chinn & Fairlie, 2007; Funchs, 1999; Bagchi, 2005; Billon, Marco, & Lera-Lo 2009; Guillen & Suarez, 2005). While most previous studies have focused on the number of Internet users and Internet hosts as proxies of the penetration level of the Internet, some have explored the patterns of Internet diffusion curves and adoption rates from a longitudinal perspective. For example, Andres, Cuberes, Diouf, and Serebrisky (2010) explored the different patterns of Internet diffusion curves in high- and low-income countries over time. They argued that low-income countries have much steeper diffusion Please cite this article in press as: Zhang, X., Frugal innovation and the digital divide: Developing an extended model of the diffusion of innovations, International Journal of Innovation Studies (2018), https://doi.org/10.1016/j.ijis.2018.06.001

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curves than high-income countries and that the diffusion curves of low-income countries lag behind (lie to the right of) those of high-income countries. Consumption theory and the purchase of ICTs According to DOI theory, economic factors, along with other factors, influence the adoption of innovations. Specifically, price drops enhance the rate of adoption and earlier adopters have a higher social status than later adopters (Rogers, 2003). Further, since most innovative products or services are sold in the marketplace, the innovation diffusion process is a “commercialization” process (Rogers, 2003). However, although DOI takes economic factors into account, it does not integrate economic theories into its theoretical framework. Thus, consumption analysis can be employed as a theoretical approach to explore the Internet diffusion. Consumption theory holds that consumers make rational purchase decisions to maximize their utility, which is defined as “how consumers rank different goods and services” (Samuelson & Nordhaus, 2004, p. 84). Utility is associated with preferences, which represent “a variety of cultural and historical influences” (Samuelson & Nordhaus, 2004, p. 48). Different preferences render different utility functions (Krugman & Wells, 2005). As consumers' purchase decisions are constrained by their income budgets, the consumption equilibrium is the point at which an individual attains the maximum utility within his/her budget. At each level of income, there is an equilibrium point for a consumer. An income consumption curve (widely referred to as an Engel curve) therefore represents the relationship between the equilibrium quantity of a good purchased and income level. A variety of ICTs at different prices are available in markets. According to consumption theory, when people decide to purchase ICTs, their budget constrains their purchasing behaviors. Consumption theory also provides a two-good framework within which to analyze people's purchase behaviors, which is helpful to explore the relationships among income budget, ICT consumption, and non-ICT good consumption. Frugal innovations and frugal ICTs Frugal innovation can be considered to be a specific type of innovation that responds to limitations in resources and attempts to produce outcomes that address a specific need of the target populace (Bhatti, 2012). Hence, frugal innovations fit the needs of the vast majority of the population in developing countries, where there are significant societal resource constraints, target customers often have limited means, and social infrastructure is incomplete or poorly functioning. The term “frugal innovation” was first used by Wooldridge (2010), and it quickly gained popularity in academia and industry because of its significance for the huge population in the developing world. Bhatti and Ventresca (2013) conceptualized frugal innovation as aiming at “leveraging limited resources or lackluster institutions, and achieving the ends that serve more people who have less” (p. 16). Hossain et al. (2016) argued that frugal innovation must be “significantly cheaper than competitive offerings and good enough to meet the basic needs of customers who would otherwise remain un(der)served” (p. 133). Like its counterpart, frugal innovation also involves products, services, and/or processes and it satisfies two criteria for innovation: novelty and improvement. On the contrary, it carries several unique characteristics different from high-end innovation. Frugal innovation attempts to minimize the use of resources and significantly reduce the production cost to be affordable to low-income populations. Some frugal innovations can even outperform high-end innovations when they use frontier science and technology (Bound & Thornton, 2012). Many of the ICTs developed in developing countries satisfy the criteria of frugal innovation. For example, in the early 2010s, Shanzhai mobile phones made in China were produced at very low cost and sold at very low prices (10e20% of other brands), leading them to be widely purchased in China and elsewhere. The Financial Times estimated that the sale of Shanzhai phones accounted for about 20% of the global 2G mobile phone market in 2010 (“Bandit phone king”, 2010). Since the end of 2012, Shanzhai has changed its marketing strategy. Some Shanzhai mobile phone manufacturers have set up their own brandname phones such as Xiaomi. Since its inception in 2010, Xiaomi has become a leading “clone” brand of Apple's iPhone. With similar features and functions, Xiaomi smartphones are sold at less than half the price of iPhones. Indeed, 71 million Xiaomi smartphones were sold in 2015 in the global market (Cendrowski, 2016a). However, in the first quarter of 2016, another two Chinese smartphone brands, Oppo and Vivo, exceeded Xiaomi in global phone sales and became the no. 4 and no. 5 phone sellers in the world (Fried, 2016). Developing an extended DOI model for the internet diffusion The purchase of ICTs: an economic analysis Let us assume the following scenario. People have two kinds of goods, ICTs and other goods (e.g., food, house), and they have different income budgets. We also assume that they have the same preferences (the same patterns of indifference curves) for ICTs and other goods and that the same ICT has the same price. Fig. 1 shows this scenario, where the y-axis represents ICTs and the x-axis represents other goods. The y-axis represents a continuum from non-digital ICTs such as antenna radios and TVs to digital ICTs such as computers and smartphones. There is a threshold level below (above) which people only purchase non-digital ICTs (digital ICTs). Digital ICTs consist of a variety of different priced technologies. Thus, there is another threshold level below (above) which people only purchase frugal digital ICTs (high-end digital ICTs). The Please cite this article in press as: Zhang, X., Frugal innovation and the digital divide: Developing an extended model of the diffusion of innovations, International Journal of Innovation Studies (2018), https://doi.org/10.1016/j.ijis.2018.06.001

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Fig. 1. Consumers' choices of ICT goods and other goods.

threshold level of frugal digital ICTs is above that of non-digital ICTs because the former enables users to access the Internet and thus have higher utility than non-digital ICTs. Assume we have three individuals in this scenario: individual A has the lowest income budget, individual B has the middle-income budget, and individual C has the highest income budget. They make purchase decisions at the equilibrium points, which are the tangent points of the indifference curves and budget lines: EA, EB, and Ec. EA is below the threshold level of frugal digital ICTs. EB is above the threshold level of frugal digital ICTs, but below the threshold level of high-end digital ICTs. Ec is above the threshold level of high-end digital ICTs. These equilibrium points suggest that individual A purchases nondigital ICTs, individual B purchases frugal digital ICTs, and individual C purchases high-end digital ICTs. That is, individual A is an adopter of non-digital ICTs, individual B is an adopter of frugal digital ICTs, and individual C is an adopter of high-end digital ICTs. The prices of ICTs vary. The prices of digital ICTs drop rapidly because the number of transistors in a dense integrated circuit doubles approximately every two years (the so-called Moore's law) and owing to the low labor cost in developing countries. The prices of non-digital ICTs also drop because of the competition and substitution of digital ICTs. For the same ICT, its price is high in the early stage and falls over time. In this scenario, the price change is represented by the movement of the income budget line. For example, the income budget line of individual B moves from BB0 to B’B’’. Consequently, the equilibrium moves from EB to E’B, which is above the threshold level of high-end digital ICTs. Hence, the middle-income individual (individual B) decides to purchase high-end digital ICTs (Fig. 1). Frugal digital ICTs and the internet diffusion As frugal digital ICTs such as frugal smartphones can satisfy people's need to use the Internet, they are the major Internet access device for low-income people. In China, 91.5% of people use smartphones to access the Internet, 10% use laptops, and 19.5% use desktop computers (Wang, 2015). Obviously, frugal digital ICTs facilitate the adoption of the Internet as more people can afford these low-priced products. If only high-end digital ICTs were available, most people in the world would not have Internet access. As discussed above, the prices of high-end digital ICTs drop over time. Fig. 1 shows that individual B with the middleincome budget becomes a consumer of high-end digital ICTs when their prices drop. Usually, early adopters of high-end digital ICTs are wealthy. Over time, middle-income earners become adopters of high-end digital ICTs. Then, the early majority and late majority mainly consist of middle-income people. Low-income people are non-adopters. Frugal digital ICTs have a different pattern of diffusion. Early adopters of frugal digital ICTs are more likely to be middle-income people, as wealthy people already adopt high-end digital ICTs. The early majority and late majority of frugal digital ICTs should mainly consist of low-income people because they can purchase frugal digital ICTs when prices become affordable. As people can access the Internet through either high-end or frugal digital ICTs, the diffusion of the Internet should be the combination of the diffusions of high-end digital ICTs and frugal digital ICTs. Fig. 2 shows the diffusion curves of high-end digital ICTs, frugal digital ICTs, and the Internet in developed countries. Because frugal digital ICTs are usually followers of Please cite this article in press as: Zhang, X., Frugal innovation and the digital divide: Developing an extended model of the diffusion of innovations, International Journal of Innovation Studies (2018), https://doi.org/10.1016/j.ijis.2018.06.001

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Fig. 2. Diffusion curves of frugal ICTs, high-end ICTs, and the Internet (developed countries).

high-end digital ICTs, they lag behind high-end digital ICTs for a certain period. Thus, their diffusion curve is to the right of that of high-end digital ICTs. After frugal digital ICTs enter markets, people without sufficient purchasing power for high-end digital ICTs buy them and use them to access the Internet. Then, the penetration of the Internet increases because of the adoption of frugal digital ICTs and the diffusion curve of the Internet is above the diffusion curve of high-end digital ICTs. Average GNI per capita in high-income countries was $41,245 (current USD) in 2016 (World Bank, n.d.). These countries are among the developed countries defined by the United Nations (2014). The majority of people in these countries have highincome budgets that enable them to purchase high-end digital ICTs. Nevertheless, even in high-income countries, many people still live under the poverty line. For example, 43.1 million (12.7%) Americans live in poverty (“What is the current poverty rate”, n.d.). Most poor people cannot afford high-end digital ICTs. They also desire Internet access and purchase frugal digital ICTs when they become available in the markets. As the majority of people in high-income countries can afford high-end digital ICTs, high-end ICTs have higher diffusion and penetration rates than frugal digital ICTs, as shown in Fig. 2. In the extended DOI model, the Internet diffusion is the combination of the adoption of high-end digital ICTs and frugal digital ICTs. Thus, the adoption of frugal digital ICTs makes the Internet diffusion curve steeper, driving it from an s-shaped curve toward an r-shaped curve. The patterns of the diffusion of high-end digital ICTs, frugal digital ICTs, and the Internet in developing countries should differ from those of developed countries. In developing countries, most people have low-income budgets and cannot afford high-end digital ICTs. Of course, there are some wealthy people in these countries who purchase high-end digital ICTs and constitute early adopters of the Internet. When frugal digital ICTs enter these countries, they diffuse more rapidly than highend digital ICTs as the majority of people can afford them. Although the diffusion of frugal digital ICTs lags behind that of highend digital ICTs, their diffusion curve rises rapidly and goes above that of high-end digital ICTs. Average GNI per capita in low-income countries was $618 (current USD) in 2016 (World Bank, n.d.). These countries are among the developing countries defined by the United Nations (2014). The majority of people in these countries have lowincome budgets and cannot afford high-end digital ICTs. Nevertheless, even in these low-income countries, there are still many wealthy people. For example, in Zimbabwe, a country with an average GNI per capita of $890 (current USD) in 2016 (World Bank, n.d.), the wealth of top 10 richest people is above $500 million (Elena, 2018). These wealthy people can clearly afford high-end digital ICTs. However, as the majority of people in low-income countries cannot afford high-end digital ICTs, frugal digital ICTs have higher diffusion and penetration rates than high-end digital ICTs, as shown in Fig. 3. Likewise, the diffusion of frugal digital ICTs drives the Internet diffusion curve from an s-shaped curve toward an r-shaped curve. Hence, the diffusion of frugal digital ICTs in these countries changes the diffusion curve of the Internet to a larger extent than it does in developed countries. The literature suggests that the external-influence model generates an r-shaped diffusion curve, whereas the internalinfluence model generates an s-shaped diffusion curve. Thus, the former is a better fit for the Internet diffusion driven by frugal digital ICTs than the latter. The external-influence model emphasizes the factors of the social system that determine the DOI. The extended DOI model thus focuses on the influence of the income budget of a representative consumer on his/her consumption choice between frugal digital ICTs and high-end digital ICTs. The income budget of a representative consumer is determined by the economic development and wealth distribution of society and thus should be a factor of the social system in the external-influence model.

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Fig. 3. Diffusion curves of frugal ICTs, high-end ICTs, and the Internet (developing countries).

Categories of Internet adopters: combining high-end and frugal digital ICT adopters The categories of Internet adopters should be different combinations of the categories of high-end and frugal digital ICT adopters. As shown in Fig. 4, early adopters of the Internet are early adopters of high-end digital ICTs since frugal digital ICTs enter markets sometime later. The early majority of Internet adopters consist of the early majority of high-end digital ICT adopters and a certain proportion of the early majority of frugal digital ICT adopters. This proportion depends on the time lag of frugal digital ICTs and purchasing power of frugal digital ICT consumers: the longer the time lag is, the smaller this proportion is; the lower the purchasing power people have, the smaller this proportion is. The late majority of Internet adopters consist of the late majority of high-end digital ICT adopters and a certain proportion of the laggards of high-end digital ICT adopters. This proportion depends on the purchasing power of high-end digital ICT consumers. The lower purchasing power people have, the smaller this proportion is. The late majority of Internet adopters also consist of a certain proportion of early adopters of frugal digital ICTs, a certain proportion of the early majority of frugal digital ICTs, and a certain proportion of the late majority of frugal digital ICTs. These proportions are dependent on the time lag of frugal digital ICTs and purchasing power of their consumers. The longer the time lag is, the larger the proportion of early adopters of frugal ICTs is and the smaller the proportions of the early majority and late majority of frugal digital ICTs are. The lower purchasing power people have, the larger the proportion of early adopters of frugal digital ICTs is and the smaller the proportions of the early majority and late majority of frugal digital ICTs are. The laggards of Internet adopters consist of a certain proportion of the laggards of high-end digital ICTs. This proportion is dependent on the purchasing power of high-end digital ICT consumers. The lower purchasing power they have, the larger this proportion is. The laggards of Internet adopters also consist of a certain proportion of the early majority, a certain proportion of the late majority, and the laggards of frugal ICTs. These proportions depend on the time lag of frugal digital ICTs and purchasing power of their consumers. The longer the time lag is, the larger the proportions of the early majority and late majority of frugal digital ICTs are. The lower the purchasing power people have, the larger the proportions of the early

Fig. 4. Categories of Internet adopters with the combination of high-end ICTs and frugal ICTs.

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majority and late majority of frugal digital ICTs are. Of course, this is a general pattern of the mixtures of Internet adopters. A society may have a specific pattern that exhibits more complex and different mixtures from this general pattern. Frugal innovation and the digital divide: the case of smartphones Diffusion of mobile phones globally The low cost of the equipment and prepaid technology allow millions of people in the world, especially in developing countries, to purchase mobile phones and their services (Kalba, 2008). Many scholars explore the rapid diffusion of mobile phones in developing countries. For example, Loo and Ngan (2012) and Lim, Nam, Kim, Euehun, and Lee (2015) demonstrated that China has implemented successful strategies to diffuse mobile phones and has now become the largest mobile phone market in the world. Srinuan et al. (2012) investigated how mobile phones had been rapidly adopted in Thailand. Their study showed that the adoption rate of mobile phones in Thailand exceeded 100% in 2010 compared with 33% in 2003. Similar studies have also been conducted in India, Vietnam, and Peru (Gupta & Jain, 2012; Hwang, Cho, & Long, 2009; Yamakawa, Rees, Salas, & Alva, 2013), finding that mobile phones have bridged the digital divide between developed and developing countries (e.g., Kalba, 2008; Loo & Ngan, 2012; Mir & Dangerfield, 2013; Pearce & Rice, 2013; Prieger, 2013; Srinuan et al., 2012). Moreover, scholars find that the average income of a country has a positive correlation with its mobile phone penetration (e.g., Chu, Wu, Kao, & Yen, 2009; Kalba, 2008; Lee & Cho, 2007; Lee & Kim, 2014). Smartphones fulfill users' various needs for voice services, a digital camera, GPS navigation, multimedia players, games, news, search engines, web browsers, and mobile payment/banking. The first smartphone was brought into market by Apple in 2007. As promised by Steve Jobs, Apple's former chief executive, smartphones have begun to change everything (“Planet of the phones,” 2015). They have the processing power of yesterday's supercomputers. However, compared with desktops and laptops, smartphones have the advantage of ubiquity: they can be used anywhere and at any time. They also have many apps available for free, which enable users to surf websites, use emails, carry out online banking/shopping, and use social networking. Because of these advantages, they have become the fastest-selling gadget in history, outselling personal computers by four-to-one. Half of the adult population in the world owns a smartphone and this number will rise to 80% in 2020 (“Planet of the phones,” 2015). The rapid diffusion of smartphones has changed the pattern of the Internet diffusion drastically as they have become the vehicle for billions of people to use the Internet. Frugal smartphones play a significant role in this change. When smartphones first entered markets, their price (close to $1000) made them unaffordable for most people globally. The adoption rate of smartphones would be very low if only high-end smartphones such as the iPhone were available. Frugal smartphones have made this innovation affordable for most people, the cheapest of which are now sold for less than $40. In the second quarter of 2016, two high-end brands, Samsung and iPhone, held the largest market shares of the world market (22.8% and 11.7%, respectively). Three Chinese brands, Huawei, Oppo, and Vivo, captured market shares of 9.3%, 6.6%, and 5.9%, respectively. Other brands, including Xiaomi, accounted for 40.2% of the world market (“Smartphone vendor market share,” 2016). Smartphone ownership rates in developing countries have been rising at an extraordinary rate, climbing from a median of 21% in 2013 to 37% in 2015 (Pew Research Center, 2016). The rapid diffusion of frugal smartphones helps bridge the digital divide between developed and developing countries. The Internet penetration of developing countries was 54% in 2015, while that of 11 developed countries was 87% (Pew Research Center, 2016). Comparing the diffusion processes of smartphones between the United States and China The first smartphone was invented in the United States. Most people in the United States have sufficient purchasing power to own high-end smartphones. Indeed, 72% of the US population own smartphones (Pew Research Center, 2016). The most expensive brand (iPhone) holds the largest share (43.9%) of the US market. The second is Samsung with a market share of 28.4%. hence, these two high-end smartphones jointly occupy 72.3% of the US smartphone market. Nevertheless, low-priced smartphones also attract US consumers. The top three low-priced smartphones are LG with a market share of 9.6%, Motorola (5.3%), and HTC (3.4%). Although Chinese brands have not captured significant shares in the United States, their sales have increased very fast. For example, ZTE boasted that its US smartphone shipments were growing at 30%, reaching 15 million phones in 2015 (Cendrowski, 2016b). Huawei's sales grew by 10e15% in 2015 (Dano, 2016). Internet penetration in the United States was 84.2% in 2013, which exceeded the endpoint of the later majority (84%), meaning that since 2013 all new Internet users have been laggards. Internet penetration rose further to 88.2% in 2015. The average growth rate of Internet users from 2010 to 2015 was 5.2% (United States Internet users, n.d.). Low-priced smartphones began to enter the US market only a few years ago. Therefore, most adopters of low-priced smartphones are laggards of the Internet. With over 750 million Internet users, China has the largest Internet population in the world. Its penetration level was 51.3% in 2015, much lower than that of the United States, but still above the endpoint of the early majority (50%). That is, since 2015, new Internet users have been the late majority. The average growth rate of Internet users from 2010 to 2015 was 11.9%, much higher than that of the United States (“China Internet users,” n.d.), suggesting that the digital divide between the United States and China has rapidly reduced in recent years. Please cite this article in press as: Zhang, X., Frugal innovation and the digital divide: Developing an extended model of the diffusion of innovations, International Journal of Innovation Studies (2018), https://doi.org/10.1016/j.ijis.2018.06.001

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The rapid diffusion of the Internet in China should mostly be attributed to the fast diffusion of frugal smartphones. Smartphones started to be sold in the Chinese market in 2010. Most early smartphones sold in China were high-end brands such as iPhone and Samsung. After frugal smartphones entered the market, the adoption rate of smartphones in China increased rapidly. The penetration rate of smartphones rose from 10% to 68% during 2011e2015. China had over 900 million smartphone users by 2015, becoming the largest smartphone market in the world (Perez, 2015). In the first quarter of 2016, iPhone's market share in China was only 11%. Chinese brands occupied the majority of the market: Huawei 15.8%, Oppo 12.6%, Xiaomi 12.2%, and Vivo 11.9% (China Internet Watch, 2016; “China Internet users,” n.d.). Hence, the diffusion of frugal smartphones has been much faster than that of high-end smartphones in China. Since the Internet penetration rate of China was only 42.3% in 2012 (“China Internet users,” n.d.), which is below the endpoint of the early majority (50%), frugal smartphone users should constitute a small proportion of the early majority, but a large proportion of the late majority of Internet users. Although the data reported here are only descriptive, they reveal the different patterns of the Internet diffusion between the United States and China. The United States is the largest economy in the world, with a GDP per capita of $57,638 (current USD) in 2016. China is the second largest economy, with a GDP per capita of $8123 (current USD) in 2016 (World Bank, n.d.). The huge difference in GDP per capita between the two countries results in a huge difference in the purchasing power of their consumers. This difference determines the diverse diffusion patterns of the frugal and high-end smartphones of the two countries. The extended DOI model developed in this study should help explain these patterns. The consumption analysis suggests that a representative consumer with a middle-income budget purchases frugal digital ICTs but cannot afford high-end ICTs. This representative consumer represents the majority of consumers in China. Moreover, a representative consumer with a high-income budget purchases high-end ICTs. This representative consumer represents the majority of consumers in the United States. The extended DOI model argues that frugal ICTs diffuse faster than high-end ICTs in developing countries. The diffusion processes of frugal and high-end smartphones in China thus mirror this pattern. The model also argues that highend ICTs diffuse faster than frugal ICTs in developed countries, which is also mirrored by the diffusion processes of frugal and high-end smartphones in the United States. Moreover, the extended DOI model argues that Internet penetration rises faster when frugal digital ICTs are adopted. In developing countries, the proportion of frugal digital ICT adopters exceeds that of high-end digital ICT adopters at some point. This happened in China as frugal smartphones exceeded high-end smartphones to become the major platform for people to use the Internet. In developed countries, the proportion of high-end digital ICTs is larger than that of frugal digital ICTs. This happened in the United States and high-end smartphones still dominate the US market. Owing to the faster diffusion rate of frugal smartphones in China, the digital divide between China and the United States has been significantly bridged. Conclusion and discussion Frugal innovations have different characteristics from high-end innovations. While they serve low-income consumers, high-end innovations serve high-income consumers. Therefore, frugal innovations have different diffusion patterns from those of high-end innovations. Based on DOI theory and an economic analysis, this study develops an extended DOI model to analyze the impacts of the diffusion of frugal digital ICTs on the diffusion of the Internet. As people in developing countries have much lower purchasing power than those in developed countries, frugal digital ICTs diffuse much faster than high-end ICTs. The rapid diffusion of frugal digital ICTs in developing countries has significantly reduced the digital divide between them and developed countries. This study uses frugal smartphones as a case to provide empirical evidence for the extended DOI model. Although many empirical studies demonstrate the significant correlation between income and mobile phone penetration (e.g., Castells, Mdernandez-Ardevol, & Liu, 2007; Gruber & Verhoven, 2001; Kalba, 2008), consumption analysis has not been applied as much as DOI theory to study mobile phone diffusion. Consumption analysis is more generic to all kinds of consumption behaviors, while DOI is specific for innovation adoption. Attempts to combine these two theories are limited. For example, Zhang (2013) developed an Internet consumption model based on DOI and consumption theory. The extended DOI model developed in this study has several theoretical implications. First, the consumption analysis posits two thresholds for digital ICT consumption: one for frugal ICTs and one for high-end ICTs. The concept of thresholds comes from the DOI literature (e.g., Valente, 1995, 1996). This study differentiates these two types of thresholds and uses them in the consumption equilibrium analysis. This analysis concludes that a representative consumer with a middle-income budget purchases frugal digital ICTs and a representative consumer with a high-income budget purchases high-end ICTs. This economic analysis thus adds a new angle to study the diffusion of frugal and high-end ICTs. Neither the internalinfluence model nor the external-influence model differentiates these two types of innovations with similar functions but different prices. They also do not take the consumption equilibrium into account in which the income budget is a crucial determinant. Thus, these two models are insufficient to explain the rapid diffusion of frugal ICTs in developing countries. By contrast, the extended DOI model explains this phenomenon from an economic perspective. The extended DOI model also proposes a new Internet diffusion curve combining the diffusion curves of frugal and highend digital ICTs. This is based on the fact that frugal digital ICTs such as frugal smartphones can also enable people to use the Internet. Since mobile broadband penetration exceeds fixed broadband penetration in the majority of countries, the diffusion of frugal digital ICTs becomes a significant component of the diffusion of the Internet. Please cite this article in press as: Zhang, X., Frugal innovation and the digital divide: Developing an extended model of the diffusion of innovations, International Journal of Innovation Studies (2018), https://doi.org/10.1016/j.ijis.2018.06.001

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The extended DOI model further posits that the diffusion rate of frugal digital ICTs is faster than that of high-end digital ICTs in developing countries, whereas the opposite pattern exists in developed countries. Thus, frugal digital ICTs contribute more to the Internet diffusion in developing countries than in developed countries. Owing to the contribution of frugal digital ICTs, the diffusion curve of the Internet is driven from an s-shaped curve toward an r-shaped curve in developing countries. This change is reducing the digital divide between developing and developed countries. Mathematical models of the DOI suggest that the diffusion curve is determined by the coefficients of the models. In particular, the diffusion curve is determined by the coefficient (aÞ of the internal-influence model, which is determined by the attributes of innovations and interpersonal communication, and by the coefficient (bÞ of the external-influence model, which is determined by the mass media, government, and change agents (Danowski et al., 2009). The economic analysis of the extended DOI model suggests that the income budget of a representative consumer affects the coefficient of the diffusion model. As average income in a society, an approximate measure of the income budget of a representative consumer, is determined by the economic development and structure of that society, economic factors should influence the coefficient (bÞ of the external-influence model. The extended DOI model also suggests that economic factors have more influence on the coefficients (bÞ of frugal ICTs as well as the Internet in developing countries than on those in developed countries. The literature indicates that the threshold function determines the shape of the diffusion curve of an innovation and that exposure, namely the proportion of adopters in an individual's personal network, has a larger influence on his/her threshold function than that in society. Adjunct with these arguments, the consumption analysis of this study explains why frugal digital ICTs diffuse faster in developing countries. The majority of people in developing countries are at a low-income level and thus they can only afford frugal digital ICTs rather than high-end digital ICTs. The number of these people in developing countries is much larger than that in developed countries. The social networks of these low-income people in developing countries are much larger than those in developed countries. Thus, the adoption of frugal digital ICTs by individuals influences more people in developing countries than in developed countries. This kind of network effect drives the rapid diffusion of frugal digital ICTs in developing countries. Limitations of this study Frugal innovations include both products and services. This study focuses on ICT products. Frugal services also contribute to the rapid diffusion of frugal ICTs. For example, the prepaid model of smartphone services makes it affordable to many lowincome people and this promotes the adoption of smartphones. To provide more support for the extended DOI model, empirical studies should be conducted not only on frugal ICT devices but also on frugal ICT services. Moreover, this study analyzes the diffusion of frugal digital ICTs in different markets (developed countries vs. developing countries). It would also be worthwhile to analyze the diffusion of frugal digital ICTs among groups of people in one market (e.g., country, state, city). Income disparity exists in every market and thus frugal digital ICTs should have different adoption rates among groups of people in one market. In addition, the diffusion of frugal digital ICTs would reduce the digital divide among them. The empirical analysis of this study is descriptive because of the limitation of the operationalization of frugal ICTs and scarce data. Although frugal innovation is an insightful concept, it faces challenges when operationalized. For smartphones, it is hard to define which brand is a frugal smartphone and which brand is a high-end smartphone. This study uses iPhone and Samsung as high-end smartphones. This approach is debatable, as other brands such as Huawei also have high-end smartphones. In addition, the lack of smartphone diffusion data in China, the United States, and other countries hampers the statistical analysis. Besides smartphones, other frugal digital ICTs (e.g., frugal tablets) have also diffused rapidly in recent years. 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