In formulating the theoretical model, we refer to the basic structure presented in Figure 1 that we explained in the previous section. We used the TOE framework to identify the variables that act as the determinants for rural smartness. On the other hand, we used the concept of service ecosystem and the microeconomic foundation of prosperity to identify the variables that mediate the impact of rural smartness on economic welfare improvement. Next to these foundational theories, we also use relevant articles based on a systematic literature study by Mukti et al. (2021) to define indicators of the variables included in the model.
Figure 2 shows the proposed theoretical model of rural smartness. In summary, this model hypothesizes that: (1) there are three interrelated variables that act as the determinants for rural smartness: technological readiness, organizational readiness, and environmental readiness, and (2) there are two variables that mediate the impact of rural smartness on the perceived economic welfare improvement: innovativeness and competitiveness.
The theoretical model includes two types of variables, namely, latent variables and emergent variables. Latent variables are the variables that cannot be measured directly but instead inferred through their indicators. Latent variables typically represent abstract concepts, such as attitude, traits, or behavior (Benitez et al., 2020; Henseler et al., 2016). Variables in the model operationalized as latent variables were innovativeness, competitiveness, and perceived economic welfare improvement. These variables are represented in an oval shape. On the other hand, emergent variables refer to the variables that emerge from a combination of their indicators. Emergent variables fit best to model man/firm-made artefacts, such as technologies, systems, processes, strategies, or management instruments (Benitez et al., 2020; Henseler et al., 2016). Variables in the model operationalized as emergent variables were organizational readiness, technological readiness, environmental readiness, and rural smartness. These variables are depicted using a hexagon shape. In the next sub-sections, we explain each of these variables, define their measurement indicators, and provide theoretical argumentation for the hypotheses in the model.
Determinants of rural smartness
As explained in the Theoretical background section, we used the TOE framework as the basis to define the independent variables that can be seen as the determinants of rural smartness. Consistent with the TOE, the variables are technological readiness (technology context), organizational readiness (organization context), and environmental readiness (environment context). Table 1 presents their formal definition and their indicators. The indicators (and the instrument development process) are the result of the SLR included in Mukti et al. (2021), which identified the challenges occurring during the adoption and diffusion of smartness in rural areas from the perspective of the TOE. We argue that by being ready to overcome these challenges, we can increase the likelihood of realizing rural smartness. In the following sub-sections, we explain the formulation of the research hypotheses that interrelate these variables.
Role of organizational readiness
Previous studies found that the organizational entity that plays an important role in the initiatives toward rural smartness is the government (Jung et al., 2014; Mishbah et al., 2018; Zavratnik et al., 2018). This finding implies that organizational readiness in the context of rural smartness is actually synonymous with the readiness of the government. To understand the role of the government, we need to look at the characteristics of rural areas, at least from three perspectives: geographic, economic, and human resources.
First, geographically, rural areas are typically remote locations with limited connectivity to economic centers that concentrate in urban areas. Given this geographical situation, the logistics and transportation costs to and from urban areas are high and lead to stagnation of economic growth in rural areas (Cunha et al., 2020; Wiggins & Proctor, 2001). Second, the rural economy dependencies are very much dependent on the agricultural sector. However, agricultural activities are less profitable compared to non-agricultural activities. This situation causes workers in rural areas to migrate and seek employment in the non-agricultural sector in urban areas, which deprives rural areas of the young population and workplaces (Cunha et al., 2020; Imai et al., 2017). Third, from a human resource perspective, an empirical study found that 80% of the extremely poor and 75% of the moderately poor are people living in rural areas (Castañeda et al., 2018), implying that rural citizens have a much lower purchasing power when compared to urban citizens. Furthermore, rural citizens typically have a low educational level. Although most rural citizens finished the high-school education level, only a small fraction of them continue with higher education (Imai & Malaeb, 2018). This situation makes human resources in rural areas less competitive, low-skilled and cheap (Zhang, 2016).
Given the current conditions of rural areas described above, it is difficult to rely on the private sector to realize rural smartness. The low purchasing power, the low education level of human resources, and the high logistics and transportation costs make the investment in rural areas not economically attractive for the private sector. Therefore, the initiation of programs for rural smartness must be the responsibility of the government (Jung et al., 2014; Mishbah et al., 2018; Wiggins & Proctor, 2001; Zavratnik et al., 2018), as explained below.
As a public entity, the government has the obligation to improve the economic situation of people living in rural areas. One of the regional governments’ primary tasks is to allocate the necessary budget to develop the infrastructures in the respective rural areas, either logistics infrastructures (e.g., roads and bridges) or IT infrastructure (e.g., internet access and reliable electricity), in such a way that it improves the connectedness between the different stakeholders of the rural business ecosystem (Rodríguez-Pose & Hardy, 2015; Zavratnik et al., 2018). Furthermore, the government can initiate a collaboration with the private sector, for example through a public-private partnership scheme, to provide IT infrastructure and service for rural areas. In this way, the private sector can be encouraged to get involved actively in rural development (Gulati, 2007; Zavratnik et al., 2018). The government also has the authority to initiate educational policies and programs with the goal of accelerating the diffusion of productive utilization of IT by rural citizens. These educational policies and programs encompass not only technical digital literacy but also creative literacy and entrepreneurship skills, in such a way that they can empower rural citizens to have a better livelihood (Nedungadi et al., 2018). Finally, the government as the policy maker has the capability to ensure the coherence of IT services provisioning in rural areas, in line with the strategic directions and necessary regulations for rural development (Naldi et al., 2015; Talbot, 2016).
The explanation of the roles of the government described above suggests that organizational readiness not only has a direct positive effect on the realization of rural smartness, but also contributes to the realization of technological, and environmental readiness.
H1: Organizational readiness contributes positively to technological readiness.
H2: Organizational readiness contributes positively to environmental readiness.
H3: Organizational readiness contributes positively to the realization of rural smartness.
Role of technological readiness
In the context of the theoretical model (see Table 1), we refer to technological readiness as the technological elements required for rural smartness. These elements are especially concerned with the readiness of internet access, including its services and associated supporting infrastructures (online services, stable electricity, and IT devices). In particular, these technological elements are provided, either independently by the government (therefore, IT strategic guideline is included in the technological readiness), or independently by the third party. Support from the third party to the government, as the responsible organization, in realizing rural smartness is part of the environmental readiness (Bhattacharya & Wamba, 2018; Dewi et al., 2018; Ramdani et al., 2009) that will further be explained in the next section.
As explained earlier, important geographic characteristics of rural areas, are remoteness and poor organization of transportation and logistics. The immediate consequence of this is low accessibility to the resources and markets which force business ecosystems in rural areas to operate mostly locally and in silos (Cunha et al., 2020; Philip & Williams, 2019). This situation implies that rural areas do not have much potential of their own to accelerate their economic growth (Naldi et al., 2015).
On the other hand, studies found that internet access enables businesses in rural areas to mitigate the issue with geographic isolation (Freeman et al., 2016; Philip & Williams, 2019). Having access to online services such as websites, social media, and e-commerce, enables them to connect to a broader market, and pool of suppliers and resources, regardless of their location. This helps businesses in rural areas to improve their efficiency in production and marketing activities and triggers the growth of their business (Philip & Williams, 2019; Prieger, 2013). Therefore, access to the internet and online services is instrumental for achieving connectedness between stakeholders in a rural business ecosystem, which is the foundation for rural smartness.
Furthermore, internet access also has particular benefits for rural communities. First, it enables rural citizens to have access to online learning opportunities and learning communities, ranging from informal information portals and community networking to formal online education and training courses (Mason & Rennie, 2004). Second, access to the internet encourages rural citizens to participate actively in rural development initiatives. Citizens in rural areas can use the internet to find information and to discuss important issues in their community. This awareness can motivate them to initiate voluntarily activities to improve the situation in their village (Stern et al., 2011).
Based on the above arguments, we expect the technological readiness contributes positively to the realization of rural smartness, as well as, to environmental readiness.
Role of environmental readiness
Environmental readiness (see Table 1) mainly covers three aspects related to rural smartness: the citizens, the third parties, and the regulatory environment. Next, we explain the importance of these three aspects for the realization of rural smartness.
The goal of IT implementation in the context of rural smartness is to improve the quality of living and the economic welfare of rural citizens. However, the benefits of IT implementation are lost when the IT is not actually used as intended (Davis, 1993). A systematic literature study found there are several factors that hinder the actual use of IT by rural citizens (Mukti et al., 2021). First, rural citizens have low digital literacy, namely a lack of knowledge to properly use the IT devices and services (Dowell, 2019; Nedungadi et al., 2018). Second, rural citizens have a low purchasing power. The average wage in rural areas is much lower compared to the wage in urban areas, and a significant percentage of rural citizens are living below the poverty line (Castañeda et al., 2018; Imai & Malaeb, 2018), which makes the affordability of IT devices/services extremely low. Third, from a cultural perspective, citizens in rural areas tend to be traditionalists and exhibit rather strong resistance to change and innovation. For them, a computer, a smartphone and the internet represent the products of and a threat to their community (Correa & Pavez, 2016; Ray, 2018). These challenges make citizens in rural areas have a low motivation to embrace IT as a part of their economic activities and way of working and living. Therefore, to increase the likelihood of rural smartness, readiness in the citizens' aspect is needed.
However, readiness in the aspect of citizens per se is not sufficient to realize rural smartness. This is because, from a higher perspective, rural area is being viewed as an ecosystem that comprised of different interrelated stakeholders. According to the quadruple helix model, besides the citizens' aspects, involvement of the third parties (e.g., university and industry) and the supportive regulatory environment are also considered as the crucial elements that enable regional connectedness and participatory ecosystem, which are the important characteristics of rural smartness (Carayannis et al., 2018; Van Waart et al., 2016). The R&D third parties (e.g., universities) play a significant role in knowledge creation and diffusion that triggers innovation in the ecosystem, whereas the non-R&D third parties (e.g., industries) play an important role to provide necessary services for the ecosystem (Borghys et al., 2020; Carayannis et al., 2018). On the other hand, the supportive regulatory environment plays an essential role to push forward the adoption of IT innovation in the ecosystem. For example, a regulation on data interoperability can increase the confidence of IT service providers to interchange the data with the other stakeholders in the ecosystem, in such a way, can accelerate the value creation process and at the same time protect the rights of the involved stakeholders (Weber & Podnar Zarko, 2019).
The importance of the citizens, the third party and the regulatory environment for the realization of rural smartness described above, motivates us to posit that environmental readiness can be a strong determinant of rural smartness.
Impact of rural smartness
Based on the model’s basic structure explained in the Theoretical background section, rural smartness is hypothesized to have an impact on the variable in the desired value block through its positive influences on the variables within the process improvement block. The variable in the desired value block should be a dependent variable that measures the economic welfare improvement. However, it is extremely difficult to isolate and measure the improvement as a result of rural smartness of economic welfare, since many other variables beyond the context of this research model may influence its value (Wu & Wang, 2006). This difficulty has been acknowledged in several other studies that measured the impact of IT innovations. To address this difficulty, previous studies in the literature measured the impact based on perceptions of those who are affected by the IT innovations, for example, perceived usefulness (Davis, 1989), perceived benefits (Karlinsky-Shichor & Zviran, 2015), and perceived economic wellbeing (Sinha & Verma, 2020). We follow the same line of thinking and define the dependent variable in our theoretical model as perceived economic welfare improvement, which reflects the degree to which rural citizens believe the realization of rural smartness will result in economic welfare improvement.
On the other hand, based on the concepts of BCI and the microeconomic foundation of prosperity explained in the Theoretical background section, we identified that there are two variables in the process improvement block of the model’s basic structure, namely innovativeness and competitiveness. These variables act as the variables that mediate the effect of rural smartness on the perceived economic welfare improvement.
Table 2 presents the definition and indicators of the variables related to the impact of rural smartness. These indicators are derived from our previous SLR regarding the economic impacts of smartness adoption (Mukti et al., 2021). The formulation of research hypotheses that interrelate these variables are explained in the following sub-sections.
Immediate impacts of rural smartness
As explained in the Theoretical background section, according to the concept of service ecosystem by Lusch and Nambisan (2015), rural areas that have realized rural smartness can leverage resource liquefaction and enhance the resource density within their ecosystem. In the rural context, liquefaction of resources means that the information about resources owned by businesses in rural areas, either tangible resources (e.g., goods and natural resources) or intangible resources (e.g., skills and culture) are converted into a digital form. This digital transformation process empowers businesses in rural areas to be able to exchange information about their resources without needing to have physical interactions. Therefore, rural businesses are no longer isolated. Instead, they operate within a collaboration network that constitutes a fertile ground for them to innovate by combining the available resources (e.g., new product or new service) (Lusch & Nambisan, 2015; Talbot, 2016). Consequently, the development of the innovations inspires rural citizens to become entrepreneurs, which in time can stimulate growth in rural economic activities (Yadav & Goyal, 2015).
From another point of view, the liquefaction and the high density of resources can help rural businesses to strengthen their competitiveness. Within the collaboration network, the rural businesses can establish, for example, cooperative arrangements for sales or promotion, in such a way that they are able to reach the customers, not as independent entities, but based on a cooperative approach such that they have access to a broader market (Cunha et al., 2020). Furthermore, with the help of the digitization of resources and the easiness to exchange their resources within the collaboration network, rural businesses can operate efficiently and be more productive with their available resources (Oluwatayo, 2014; Talbot, 2016).
Based on the above arguments, that explained how businesses in rural areas can benefit from the liquefaction and the high density of resources, we hypothesize that rural smartness contributes positively to the innovativeness and the competitiveness of rural businesses.
Role of innovativeness and competitiveness
In the rural context, small and medium enterprises (SMEs) are the main actors that drive the economy (Arifin et al., 2020; Talbot, 2016). However, due to their geographical nature, these rural SMEs typically operate in isolation: having limited access to market, resources, and funding; thus their numbers is limited and stagnant (Eniola & Entebang, 2015; Muñoz & Kimmitt, 2019). This is why the business environment in rural areas need to become more interconnected, in order to trigger innovation (i.e., creation of new products, new services, and new businesses). These innovations, in turn, can contribute directly to the economic welfare improvement (e.g., through the creation of job opportunities) or indirectly through the competitiveness improvement (e.g., access to a wider market, higher productivity, and a more resource-efficient production) (Cunha et al., 2020; Naldi et al., 2015; Talbot, 2016). The above argument is aligned with the microeconomic foundation of prosperity by Porter et al. (2007) that is explained in the Theoretical background section, where the ability to innovate through a collaborative environment is the dominant source of competitiveness that leads to prosperity.
Based on these arguments we posit that innovativeness contributes positively to competitiveness, and both variables (innovativeness and competitiveness) are predictors of the perceived economic welfare improvement.
H9: Innovativeness contributes positively to competitiveness.
H10: Innovativeness contributes positively to the perceived economic welfare improvement.
H11: Competitiveness contributes positively to the perceived economic welfare improvement.