REGIONAL DEVELOPMENT AND INSTITUTIONAL ENVIRONMENT: REGIONAL EXPANSION OF FRANCHISE CHAINS IN BRAZIL

ABSTRACT

Purpose:

This paper aims to analyze the attractiveness of the markets in the inland of Brazil to franchise chains based on the characteristics of institutional environment, referring to the socioeconomic, geographical, and human resources dimensions.

Originality/value:

Interiorization is a theme that has been hardly explored in franchise chains’ growth strategies. This paper contributes to this debate through the institutional theoretical perspective, contributing to the clarification and ordering of the decision-making factors for the regional expansion of franchises. For regional development, it calls for municipal management to direct actions aimed at socioeconomic development and human resources.

Design/methodology/approach:

The quantitative method using secondary data - from Brazilian Association of Franchising (Associação Brasileira de Franchising [ABF]), Brazilian Association of Shopping Centers (Associação Brasileira de Shopping Centers [Abrasce]), Brazilian Institute of Geography and Statistics (Instituto Brasileiro de Geografia e Estatística [IBGE]) and Google Maps - was employed in this study for the analysis of franchise location and for municipalities. The sample comprised 458 municipalities with a populaion of above 50 thousand inhabitants. The statistical techniques used were factor analysis and multiple regression analysis.

Findings:

The results show that the socioeconomic and human resources factors of the municipalities are essential for the attractiveness of franchises chains to the inland of the country. In turn, the geographical distance of the inland municipality in relation to the state capital did not present adherence to the model as an explanation for the attraction of franchises.

KEYWORDS:
Franchise chains; Institutional environment; Regional development; Interiorization; Entrepreneurship

RESUMO

Objetivo:

O artigo tem como objetivo analisar a atratividade dos mercados do interior do Brasil para as redes de franquias, considerando as características do ambiente institucional referente às dimensões socio­econômica, geográfica e de recursos humanos.

Originalidade/valor:

A interiorização é um tema pouco explorado nas estratégias de crescimento das redes de franquias. Por meio da perspectiva teórica institucional, o artigo contribui para esse debate ao esclarecer e ordenar os fatores de tomada de decisão para a expansão regional das redes de franquias. Da mesma forma, contribui para o desenvolvimento regional ao instigar a gestão municipal para o direcionamento de ações voltadas para desenvolvimento socioeconômico e de recursos humanos.

Design/metodologia/abordagem:

Trata-se de um estudo quantitativo, com dados secundários - da Associação Brasileira de Franchising (ABF), Associação Brasileira de Shopping Centers (Abrasce), Instituto Brasileiro de Geografia e Estatística (IBGE) e do site Google Maps - tanto para a análise da localização das unidades franqueadas como dos municípios. Para a amostra foram selecionados 458 municípios com população acima de 50 mil habitantes. Utilizou-se a técnica estatística de análise fatorial e de análise de regressão múltipla.

Resultados:

Os resultados mostram que os fatores socioeconômico e de recursos humanos dos municípios são primordiais para a atratividade das redes de franquias no interior do país. Por sua vez, a distância geográfica do município do interior em relação à capital do estado não apresentou aderência ao modelo explicativo para a atração das redes de franquias.

PALAVRAS-CHAVE:
Redes de franquias; Ambiente institucional; Desenvolvimento regional; Interiorização; Empreendedorismo

1. INTRODUCTION

Brazil has 4,619 municipalities located in the interior, which can be described as cities that are neither state capitals nor part of metropolitan regions. This corresponds to 49% of the Brazilian population (94.3 million inhabitants) and represents a family income of BRL 827 billion annually (Data Popular, 2014). According to Associação Brasileira de Franchising (2017), in 5,570 Brazilian municipalities, 2,321 have franchise chains units, which correspond to more than 40% of cities with franchise chains. Among the franchise chains associated with Brazilian Association of Franchising (Associação Brasileira de Franchising [ABF]), 25% are in cities in the interior of the country, whereas the remaining 75% are in capitals and metropolitan regions. These demographic and financial indicators show the consumption potential of regional markets, which can be exploited by franchise chains.

From the perspective of retail ventures, the selection of the location is decisive for its success, and because of this, the concern primarily focuses on places with relevant population concentration (Barringer & Greening, 1998). This is considered a crucial process when it comes to the expansion of franchise chains. From the 1980s to the 2000s, franchise chains expansion in Brazil concentrated in larger cities, mainly in capitals and regional hubs. Although the expansion strategy for locations with a high population was a priority, some limitations for franchise chains, such as stagnation of the consumer market, high competition, cannibalization between units in the same franchise chain, and high real estate costs may be identified (Moita & Guerra, 2012). In contrast, smaller cities create opportunities for new ventures and reduce models of franchise chains because of its increased purchasing power and lower level of competition (Moita & Guerra, 2012; Cunha et al., 2015; Bitti, Aquino, & Amato, 2010; Portal do Franchising, 2015).

This situation originated the phenomenon of interiorization, charac­terized by the expansion of franchise chains throughout the country. There are limited studies that portray this theme, but all converge to the understanding that expansion is a market growth strategy and has a limitation in the capacity of regional markets to receive a new venture (Jackson, 2008; Minadeo & Camargos, 2009; Moita & Guerra, 2012; Silva et al., 2016). Despite this, the process of selecting these markets is not clear. To fill this gap in the literature, this research aims to address the phenomenon of the franchise chain interiorization. This approach will be based on institutional theory, as studies suggest that institutions can be important precursors to entrepreneurial activities. An institutional perspective helps to structure the exploration of how corporate factors influence business activity and shape entrepreneurial behavior throughout the business process (Valdez & Richardson, 2013). Formal institutional aspects have an impact on regulations and law enforcement, whereas informal aspects have an impact on how society enables businesses to thrive locally (Silva et al., 2016; Félix & Farah, 2013; Khoury & Prasad, 2015; Melo, Borini, & Ogasavara, 2019).

This research has argued that franchise chains prefer regional markets with a favorable institutional structure for business, which is represented by socioeconomic, human, and geographical elements. Therefore, this article aims to analyze the attractiveness of markets in the interior of Brazil for franchise chains by considering the socioeconomic, geographical, and human resources dimensions of the institutional environment. To achieve this objective, a quantitative descriptive research was conducted using secondary data, with a sample of 458 Brazilian municipalities with more than 50 thousand inhabitants. For the analyses, multivariate quantitative techniques of factor analysis were used, followed by a multiple linear regression analysis.

The expected academic contribution of the study is the identification of the characteristics of the institutional environment that propelled the expansion of franchise chains in its domestic market, corresponding to the regional markets in Brazil. This identification presents contributions to studies on the institutional environment for entrepreneurship (Bruton, Ahlstrom, & Li, 2010; Khoury & Prasad, 2015), expansion of franchise chains (Jackson, 2008; Minadeo & Camargos 2009; Moita & Guerra, 2012; Silva et al., 2016), and geographic expansion to regional markets (Barringer & Greening, 1998; Amin, 1999; Chung, Chen, & Hsieh, 2007; Cordeiro et al., 2017).

The present article is structured as follows: the literature review section discusses the theories used referring to franchise chains and institutional environment, followed by the development of hypotheses and the methodology section. The analysis of results will be discussed and, lastly, final considerations that include academic and managerial contributions will be presented.

2. LITERATURE REVIEW

2.1 Institutional theory and entrepreneurship

Institutions can be defined as the set of rules and norms that shape the way individuals interact in a society. These rules have several characteristics, encompassing both formal rules (constitutions, laws, economic rules, property rights, and contracts) and informal rules (values, norms, sanctions, taboos, customs, traditions, and codes of conduct) that shape political, economic, and social issues (North, 1991). Therefore, legislation, contracts, organizations (state, companies, civil society organizations etc.), sanctions, property rights, and cultural norms of behavior would be some of the components that form the institutional environments that reference how economies develop. Hence, institutions help explain the roots of uneven economic development between countries and regions (Lopes, 2013). In this sense, institutionalism can offer an incentive structure to the economy. Additionally, as the institutional structure evolves, it can shape the direction of economic change toward growth, stagnation, or decline.

By informing the “rules of the game” within society, formal institutions define the parameters of the market, resources, and protection of property rights, whereas informal institutions define relational conventions, habits, and customs that allow behavior within business processes (Biggart & Beamish, 2003; Bathelt & Gluckler, 2014). Formal institutions are found in political rules, legal decisions, regulatory regime, and economic issues and determine the nature of property rights, access to finance, skills and knowledge development, and employment relationships (Hessels & Terjesen, 2010; Schwens, Eiche, & Kabst, 2011). In many developing countries, informal and formal institutions coexist to compensate for the lack of formal institutions and maintain reasonable stability (Khoury & Prasad, 2015). This notion of informal relations also represents the way in which entrepreneurs survive in a dynamic context, as in the case of economies in transition and, especially, in emerging countries (Steer & Sen, 2010).

Informal institutional constraints, such as limitations in the interaction between cultures in which gender, ethnicity, family history, or religion governs social exchange systems, occur in relational interactions within and between groups of individuals. Such informal institutional systems can be, according to their own rules, the existing restrictions on institutions (Khoury & Prasad, 2015). These conditions represent the starting point for the entrepreneur, who must reconcile the characteristics, flaws, and obstacles within the institutional environment to take advantage of opportunities (Peredo & McLean, 2013; Khoury, Cuervo-Cazurra, & Dau, 2014).

Research on entrepreneurship within the scope of the institutional environment has focused on how external environmental factors, in combination with personality and gender factors, influence business activities (Bruton et al., 2010; Welter & Smallbone, 2010). The most analyzed factors are socioeconomic, geographic, and human resources.

The analysis of socioeconomic factors includes demographic and economic factors. Demographic factors involve investigating the size of the population, which is considered an essential aspect for the dimensioning of the market, and the economic factors help to identify the population’s consumption power, which constitutes a relevant indicator of market potential (Baumol, Litan, & Schramm, 2007).

Geographic factors are part of the intrinsic variables of a region and can impact transport costs, rent values, and labor qualification. This dimension describes how spatial structure can impact economic analysis, producing imperfect competition between regions (Castiglione et al., 2012).

Finally, the analysis of human resources aspects involves the values, aspirations, and qualifications of professionals, whether employees or owners. It is exclusively about the human part because these factors and elements guide the determinant actions of individuals or groups and generate personal and professional progress (Faller & Almeida, 2014).

2.2 Regional development

The regional development process comprises not only economic growth but also social, cultural, environmental, and political factors. This process includes changes in the composition of society and socioeconomic indicators, such as poverty, unemployment, and inequality (Xavier, Inácio, Wittmann, & Kern, 2013). The main objective of the regional development is to make peripheral and remote regions sustainable and self-sufficient (Muller, 2016). There is a consensus on the existence of a relationship between entrepreneurship and regional development, as the entrepreneur is responsible for introducing new technologies and resources, stimulating employment, and bringing economic growth (Muller, 2016).

In the last decades, the regional development perspective has increased its presence in the academic sphere, since it represents a way of providing competitiveness for a region in the context of globalized markets. The articles specifically address the role of small businesses in peripheral regions, analyzing three issues: 1. economic: relationship between companies; 2. social: characteristics of the social structure; and 3. territorial: local territorial organization (Xavier et al., 2013).

Furthermore, the determination of regional conditions associated with places with great entrepreneurial activity is a relevant and debated topic in the academy. This line of research analyzes how the regional structure and the institutional context can influence entrepreneurial activity (Muller, 2016). Studies have identified the impact of the unemployment rate on the attractiveness of entrepreneurial activity, but they are not conclusive as to whether the effect is positive or negative. Another indicator pointed out is the employment structure, as areas with a high proportion of educated and specialized workforce have higher rates of starting a business. Regions dominated by small companies, too, have higher rates of new companies than those dominated by large companies. Additionally, there is the impact of local policies that encourage entrepreneurship, access to financial capital, and the presence of local networks (Muller, 2016; Dan & Goia, 2018).

Franchise chains have been noted as the key companies for the economy. They have been a driving force for business activities and for the growth of small companies. As small businesses usually lack basic management skills, they are more vulnerable to financial risks and uncertainties, especially when they are not part of a franchise chain. Consequently, franchise chains are a gateway to entrepreneurship, facilitating business success because of the cooperation of the franchisor (Lee et al., 2015).

2.3 Franchise chains and regional development

Franchise chains can be defined as a networked system that allows the owner of a company (franchisor) to grow and expand their business by selling units to a third party (franchisee). In addition to the acquisition of the unit, the franchisee will be acquiring the know-how, brand, products, and services developed by the franchisor (Melo et al., 2015). The franchisor, in return, will receive monetary contributions from the franchisee, such as the initial investment and royalties that will maintain the franchise chain, in addition to serving as the payment for tangible and intangible resources (Melo et al., 2015). This business model allows for cost-sharing and rapid market penetration, making it a relevant expansion option for small companies that have scarce or limited resources, whether financial, employee-related, managerial, or informational (Melo et al., 2015).

Brazilian franchise chains are more concentrated in large urban centers and cities with populations of over 500 thousand inhabitants. Smaller cities, in contrast, have small local merchants who are not competitive with franchise chains. The demand for new brands in these cities and the cannibalization in large cities has guided franchise chains to expand toward the interior of the country (Moita & Guerra, 2012).

The strategic search of new markets in the municipalities by franchise chains shows that the high capillarity rates achieved in capitals and large urban centers limit growth and cause cannibalization (Silva et al., 2016). The large number of points of sale causes spatial competition between geographically close points, which is represented by a new unit that captures similar sales from already-established points. Thus, the expansion strategy, depending on the choice of location, is affected by cannibalization, which can influence the choice of a new location (Silva et al., 2016). To avoid cannibalization, franchise chains have to expand into the interior of the country, in cities that have a potential consumer market, infrastructure resources, distribution logistics, and regional attractiveness (Minadeo & Camargos, 2009).

3. HYPOTHESES

Three research hypotheses were developed to relate the attractiveness of the institutional environment with the geographic expansion of the franchise chains to the markets of the interior of the country. These hypotheses comprise the socioeconomic, geographical, and human resources dimensions as these represent factors of the institutional environment that provide greater attractiveness to business in the municipalities (Silva, Monte-Mór, & Barbieri, 2012). Figure 3.1 summarizes the research framework.

Figure 3.1
RESEARCH FRAMEWORK

3.1 Socioeconomic dimension

The characteristics of a society are affected by its socioeconomic dynamics, depending on how the population changes, not only in absolute size, but also in other aspects, such as age structure, spatial distribution, income distribution, household structure, level of education, and employability (Silva et al., 2012). This dimension influences the business environment to the extent that gaining its knowledge enables better financial and marketing management, resulting in better decisions about the business model, product offered, pricing, location, and communication (Cordeiro et al., 2017).

Among the aspects indicated, two stood out: education and income. These aspects directly influence the development and creation of a favorable institutional environment for local businesses, such as influencing consumers’ attitudes toward products and brands, and they can be used to segment markets. In addition, specifically related to income, it can be highlighted that, for socioeconomic development, it is essential that the population is employed, as this will result in the consequent reduction of poverty and better social conditions and purchasing power.

In Brazil, income inequality is a major factor that makes poverty alleviation difficult, as the effect of economic growth on poverty reduction is less in Brazil than in other countries with similar per capita income (Cabral & Araujo, 2015). Additionally, in the case of small Brazilian municipalities, they must find ways to develop economically to reduce the exodus toward large centers. Franchise chains, specifically, are attracted to organized point of sale structures, such as shopping centers. These ventures appear as new consumption spaces that create and recreate new ways to attract consumers. Thus, franchise chains start to grow more with the proliferation of shopping centers and malls, adapting to the lifestyle of cities (Carlos, 2001; Silva & Gonçalves, 2013; Lee et al., 2015).

Regarding the characteristics of the population profile, municipalities with a large population concentration attract franchise chains. Although these locations have greater income inequality, when added together, a large portion of the population considered to be of low income represents a great business potential (Prahalad, 2006, 2012; Cruz, 2014; Dias & Hemais, 2015). Based on the preceding insights, the following hypothesis was constructed:

• H1: The higher the indexes of the socioeconomic dimension of the municipalities, the more attractive the municipality is for franchise chains.

3.2 Human resources dimension

Human resources represent the workforce of a population, considering only the portion that can effectively generate economic development. Without adequate human resources, sustainable development is not possible. The potential of a region’s human resources is not measured by the number of people, but by its level of qualification, defined as the ability to turn resources into productivity. For this to occur, an institutional environment that favors the understanding and application of the acquired knowledge is also assumed (Kamakura & Mazzon, 2016).

The most cited variable in the literature that can impact the level of qualification of human resources is education, as investments in education can improve the performance of human capital and the productivity of workers (Eberhardt & Lima, 2012; Fonseca, Beltrão, & Prado, 2013; Paschoalino, Caldarelli, & Camara, 2016). The theory of human capital developed by Theodore Schultz in 1960 emphasizes the importance of human capital in increasing the levels of productivity. This is because individuals with greater skills and knowledge become more productive, generating a higher level of production and enabling technological innovation. Human capital encompasses the skills and knowledge that, together with personal characteristics and expended efforts, increase the productive possibilities of personal, social, and economic well-being (Fontenele, Moura, & Leocadio, 2011). This transformation of knowledge into human capital means not only transforming the professional side, but also transforming knowledge with respect to ethics, solidarity, entrepreneurship, and social relations as important parts of professional qualification (Botomé & Zanelli, 2011).

Because of a lack of incentives to attract companies that generate employment and income in small- and medium-sized cities, qualified people tend to move to other regions in search for better job opportunities. This results in difficulties in finding qualified resources. These cities must seek alternatives for sustainable development. In addition to avoiding economic stagnation and population emptying, sustainable development can attract new ventures, which may see the scarcity of qualified resources as an impediment (Félix & Farah, 2013).

A key factor for franchise chains is qualified labor, as the productivity of workers is higher. Additionally, the increase in workers’ productivity will make them acquire greater purchasing power. With greater income in the region, new products and services can be offered, creating new ventures and employing more workers. This will create a virtuous circle in the municipalities and improve the region’s economic and social development and consumption potential (Haddad, 2009; Eberhardt & Lima, 2012; Fonseca et al., 2013). Thus, the following hypothesis was formulated:

• H2: The higher the human resource dimension indexes of the municipalities, the more attractive the municipality is for franchise chains.

3.3 Geographical dimension

Geographical distance is considered a relevant variable, as it implies a reduction in commercial relations with an increase in distance. The distance is related to the costs of transportation, communication, and reduced control over investment operations by the respective investors. Distance is considered an obstacle by many researchers, as it increases the costs and risks of doing business in a new market. Therefore, distance is not only a geographical separation, but also a cultural, administrative, political, and economic limiter that changes the attractiveness of the regional market (Rodrigues, Bezerra, & Cavalcante, 2015).

A company can operate in one or more geographical areas, but it should pay attention to local variations and peculiarities, regional structure, population characteristics, and market behavior (Cordeiro et al., 2017). In franchise chains, specifically, the risk of opportunistic behavior and breaking standards by franchisees means that the expansion needs to consider the application of control and monitoring mechanisms. The distant location of capitals and large centers can help in the development of business because of the distance from competition, but it tends to increase the logistical cost and the expenses with monitoring and communication (Moita & Guerra, 2012; Rodrigues et al., 2015). Therefore, regarding operations and logistics related to the distance of the municipalities from the state capitals and the benefits provided by their structures, the following hypothesis is proposed:

• H3: The shorter the distance between the municipality and the state capital, the more attractive the municipality is for franchise chains.

4. METHODOLOGY

The quantitative method of a descriptive character was used in this research (Creswell, 2010). The intention was to describe and explore the characteristics of the studied phenomenon that, in this case, concern the process of expanding franchise chains to the interior of the country.

4.1 Data collection

The research aimed to analyze the attractiveness of markets in the interior of Brazil for franchise chains considering the characteristics of the institutional environment, referring to the socioeconomic, geographical, and human resources dimensions. For this, secondary data were used in relation to the location of both the franchise chains and those of Brazilian municipalities. Only municipalities with more than 50 thousand inhabitants were selected, because according to Brazilian Institute of Geography and Statistics (Instituto Brasileiro de Geografia e Estatística [IBGE]) (2014), municipalities with fewer inhabitants have restrictions on the development of retail. Additionally, 91.6% of franchise units are in municipalities with more than 50 thousand inhabitants (ABF, 2017), which is relevant to the sample selection. Also, the Federal District, the state capitals, and metropolitan regions considered by IBGE (2014) were excluded because the purpose of this research lies in understanding the attractiveness of franchise chains in inland markets. Consequently, 458 municipalities were selected for the sample.

The data on the location of the franchise units were collected through the Relatório de desempenho do franchising do ano de 2015 (ABF, 2016). Information regarding the number of franchise units in each Brazilian municipality can be extracted from the report. Conversely, institutional data from Brazilian municipalities (socioeconomic and human resources dimensions) were collected through the Atlas do desenvolvimento humano (Programa das Nações Unidas para o Desenvolvimento [Pnud], 2013). Figure 4.1.1 shows the list of the 15 main municipalities in this study.

Figure 4.1.1
MAIN CITIES IN THE INTERIOR

City	State	Franchise units	Population	Percent
Ribeirão Preto	SP	588	666.323	0.7%
São José dos Campos	SP	579	688.597	0.7%
Sorocaba	SP	509	644.919	0.6%
São José do Rio Preto	SP	467	442.548	0.6%
Uberlândia	MG	456	662.362	0.6%
Maringá	PR	377	397.437	0.5%
Jundiaí	SP	373	401.896	0.5%
Bauru	SP	318	366.992	0.4%
Piracicaba	SP	309	391.449	0.4%
Juiz de Fora	MG	272	555.284	0.3%
Caxias do Sul	RS	249	474.853	0.3%
Imperatriz	MA	218	253.123	0.3%
Blumenau	SC	214	338.876	0.3%
Cascavel	PR	212	312.778	0.3%
Taubaté	SP	212	302.331	0.3%

Source:

The dependent variable used was the number of franchise units in the municipality, whereas the independent variables are the socioeconomic, human resources, and geographical dimensions. The analysis of the socioeconomic dimension included the following: 1. employed persons; 2. proportion of poor people; and 3. the number of shopping malls in the municipalities. The human resources dimension comprises the following: 1. the percentage of employed persons with a complete degree; 2. the percentage of employed persons in the service sector; 3. the percentage of employed persons in the trade sector; and 4. the percentage of self-employed workers. Moreover, the data referring to the geographical dimension correspond to the distance from the municipalities of the state capital. Figure 4.1.2 presents the variables in detail.

Figure 4.1.2
DESCRIPTION OF VARIABLES

Dimension	Variable	Description	Authors	Source
Socioeconomic dimension	Employed persons	This corresponds to the number of workers in the municipality. Empirical market-based studies reveal critical links between the level of employment, wages, and consumption of the population.	Carpenter and Moore (2006) and Shugan (2007)	Atlas do desenvolvimento humano (Pnud, 2013)
	Proportion of poor people	It is the proportion of the poor population, considering residents with monthly household income below 1/2 minimum wage per capita, in relation to the total population of the municipality. This variable gained more relevance after the recent wave of consumption in the national market reached the poorest sections of the Brazilian population. Therefore, because of the need to know and differentiate the municipalities, this variable started to receive attention from companies interested in the most diverse segments and social classes.	Prahalad (2006), Pereira, Maia, Joseph, Freitas, and Oyamada (2010), Montenegro and Contel (2017), Cabral and Araujo (2012), Dias and Chiavegatto (2013), Souza, Souza, and Pinto (2014)	Atlas do desenvolvimento humano (Pnud, 2013)
	The number of shopping malls in the municipalities	This corresponds to the number of malls in the municipality, in units. The location, quantity, and format of stores are essential to combine retail opportunities with serving individuals in a community. The changes that have taken place in urban society are related to the expansion and modernization of tertiary activities, in which case shopping centers stand out. These have become important retail centers, acting in the way of life in cities, as well as boosting regional development and serving as an economic indicator of a given location.	Meneely, Burns, and Strugnell (2009) and Ortigoza (2010)	Abrasce
Geographical dimension	Distance from capitals	Distance from municipalities to the capitals of their states, measured in kms.	Jackson (2001), Buzzacchi and Valletti (2006) and Lobo and Matos (2011)	Google Maps
Human resources dimension	The percentage of employed persons with a complete degree	This corresponds to the percentage of workers in the municipality with complete higher education. Some authors affirm that education is a variable related to income, by showing that areas with higher income have higher education and vice versa. Additionally, the increase in the educational level of people equals wages between regions. This is because people tend to migrate to regions that pay better wages, although the capital may migrate to regions that offer cheaper qualified labor. The result, therefore, would be a better income distribution.	Carpenter and Moore (2006), Yang and Li (2008) and Mendes et al. (2016)	Atlas do desenvolvimento humano (Pnud, 2013)
	The percentage of employed persons in the service sector	This pertains to the percentage of workers in the municipality working in the service sector. The index shows the ratio between the number of persons over 18 years of age who are employed in the service sector and the total number of employed persons. With this, it is possible to identify the area of activity and the segment of workers, the degree of qualification, and the percentage of people working, in addition for this percentage to be an economic indicator.	Carvalho and Schoiozer (2012) and Pnud (2013)	Atlas do desenvolvimento humano (Pnud, 2013)
	The percentage of employed persons in the trade sector	This corresponds to the percentage of workers in the municipality who work in commerce. This index shows the ratio between the number of people over 18 years of age who are employed in the trade sector and the total number of employed persons. The index is important for understanding the profile of workers and the segment in which the municipalities operate, the type of qualification, the level of employability in the city, and the degree of heating up of the economy.	Carvalho and Schoiozer (2012) and Pnud (2013)	Atlas do desenvolvimento humano (Pnud, 2013)
	The percentage of self-employed workers	This is the percentage of self-employed workers. Many municipalities, with many responsibilities to fulfill and few opportunities to attract large companies, need alternative ways to guarantee socioeconomic development. More important than the installation of industries is the possibility for each municipality to develop certain talents and capabilities of its population to encourage innovation and entrepreneurship.	Jackson (2001) and Yang and Li (2008)	Atlas do desenvolvimento humano (Pnud, 2013)

Source:

Figure 4.1.3 presents the variables with their corresponding codes that will be used from this point onwards.

Figure 4.1.3
CODIFICATIONS OF VARIABLES

Code	Variable
P_SUPER	The percentage of employed persons with a complete degree
P_COM	The percentage of employed persons in the trade sector
P_SERV	The percentage of employed persons in the service sector
POP	Proportion of poor people
Shopping	The number of shopping malls in the municipalities
KM Capital	Distance from capitals
Occupied total	Employed persons
CPR	The percentage of self-employed workers

Source:

Both the variables presented and the results were treated with multivariate statistical techniques of factor analysis and regression.

5. RESULTS ANALYSIS

Initially, it was necessary to verify whether it was possible to reduce the variables in socioeconomic, human, and geographical dimensions. For this purpose, a factor analysis was performed using the principal component method with the objective of analyzing which variables have greater explanatory power for the proposed model, synthesizing the data and validating the relationships (Corrar, Paulo, & Dias, 2012; Flach, Castro, & Mattos, 2017). Bartlett’s sphericity test showed the adequacy of the factor analysis for the data in question, as the p-value was less than the 5% significance level. Additionally, all communalities were greater than 0.500 (Johnson & Wichern, 1992). The Varimax orthogonal rotation method was selected as it is most used to produce non-correlated factors and in situations involving human behaviors (Henson & Roberts, 2006; Johnson & Wichern, 1992). Figure 5.1 presents the results and shows the rotated factors and the factorial loads distributed for each of them as well as the explained variance of each factor and the total (77.75%).

Figure 5.1
ROTATED COMPONENTS/FACTORS MATRIX

Matriz de componente rotativa
	Factors
	1 - Socioeconomic	2 - Human resources	3 - Geographical
Occupied total	0.94	0.26	-0.06
POP	0.94	0.18	0.06
Shopping	0.92	0.13	-0.07
P_SERV	0.22	0.87	0.00
P_SUPER	0.39	0.76	-0.15
P_COM	0.09	0.64	0.45
CPR	-0.05	-0.64	0.50
KM Capital	-0.05	-0.03	0.80
Variância explicada fator	35.14%	28.58%	14%
Variância explicada total	77.75%

Source:

Three factors were obtained: factor 1 (socioeconomic), factor 2 (human resources), and factor 3 (geographical). Factor 1 explains approximately 35% of the total variance being formed by the proportion of poor people, total number of employed persons, and number of shopping centers in the municipality. The percentage of people employed in services and commerce, percentage of people with higher education employed, and percentage of self-employed workers are the variables that form approximately 28.5% of the total variance in factor 2. Finally, factor 3 explains approximately 14% of the total variance, expressing how far the municipality is in relation to the capital of its state of the federation.

After obtaining the three dimensions, multiple regression analysis was performed to verify the associations proposed in the hypotheses. The regression model is shown in Figure 5.2, with an explanatory power of approximately 91%. The results indicate that the socioeconomic and human resources dimensions are significant for the regression model (p < 0.01) and are positively associated with the model. Accordingly, the higher the indexes associated with the socioeconomic and human resources dimension, the greater the number of franchise chains in the municipality. In the analysis of standardized coefficients, the socioeconomic dimension presented a Beta of 0.919, that is, a stronger or more important predictor for the number of franchise chains than the human resources dimension, which presented a Beta of 0.259 only. The geographic dimension, in contrast, did not show a significant association.

Figure 5.2
REGRESSION MODEL

	Dependent variable Franchise units	Standardize d beta	t	Sig	VIF
Independent variable	Constant		45.678	0.000
	Socioeconomic	0.919	66.014	0.000	1.000
	Human resources	0.259	18.641	0.000	1.000
	Geographical	-0.019	-1.338	0.181	1.000
	R2 adjusted	0.911
	Durbin-Watson	1.883
	F	1,569.02

Source:

Three hypotheses were developed in this research. Hypothesis H1, which deals with the indexes linked to the socioeconomic dimension of the municipalities, was confirmed as the factor that represents that the socioeconomic dimension is significantly and positively related to the dependent variable. This hypothesis can be explained by the fact that the higher the professional occupation index of the population, the higher the per capita income of the municipality tends to be, thus generating greater consumption and making the municipality more attractive for franchise chains. Income generation provides a virtuous cycle to the municipality, increasing tax collection and improving the lives of the population and the companies installed there.

Along with hypothesis H1, hypothesis H2 was also confirmed as the factor that represents that the dimension of human resources is significantly and positively related to the dependent variable. This dimension goes back to the presence and quality of labor in sectors linked to the activity of franchise chains. Having qualified and specialized labor can be a great differential to attract new business models for the municipalities, mainly in municipalities that are geographically distant from the headquarters of the companies; therefore, the expenses with training and agency costs tend to be lower, facilitating business administration. Qualified labor expectedly increases the productivity of workers, which tends to promote individual income and consumption patterns. A virtuous cycle is created because of greater consumption. Companies tend to intensify their production and employ a larger share of workers as well as an increase in new ventures. This generates greater tax revenue for the region, which may increase its spending on social improvements.

In contrast, the result of the factor that represents the geographical dimension was not significant; hence, the hypothesis formulated for the geographical dimension, hypothesis H3, was not confirmed. This result is in line with previous studies (Moita & Guerra, 2012; Rodrigues et al., 2015). Based on this result, it is understood that, despite the proximity to the capitals being a logistical facilitator for the units in the interior, this is not a condition for the franchise chains’ decision in selecting markets for expansion. This may occur because of other reference locations for supply, such as regional centers or, in the case of border regions between states, the capitals of other states. Additionally, with the advancement of technology, various forms of communication and monitoring have emerged, even with physical distance, which may have further reduced the effect of this dimension.

Hence, the only confirmed hypotheses were H1 and H2, which managed to explain the model in 91.1%. H3 did not show adherence to the model. Figure 5.3 presents the synthesis of the results.

Figure 5.3
SUMMARY OF THE RESULT

Hypothesis	Dimensions	Results
H1: The higher the indexes of the socioeconomic dimension of the municipalities, the more attractive the municipality is for franchise chains.	Socioeconomic	Confirmed
H2: The higher the human resource dimension indexes, the more attractive the municipality is for franchise chains.	Human resources	Confirmed
H3: The shorter the distance between the municipality and the state capital, the more attractive the municipality is for franchise chains.	Geographic	Not confirmed

Source:

6. FINAL CONSIDERATIONS

This research sought to determine and analyze which characteristics of the institutional environment contribute to a greater presence of franchise chains in markets in the interior of Brazil. To achieve this, with data from 458 Brazilian municipalities, eight variables were analyzed. These were reduced to three dimensions, namely, socioeconomic, human resources, and geographical. The results of this research point out that the positive characteristics related to the socioeconomic and human resources dimensions have an impact on the attractiveness of the municipalities for expanding franchise chains. This is in line with some authors’ points on the importance of creating new consumption spaces, such as shopping centers and malls (Carlos, 2001; Silva & Gonçalves, 2013; Lee et al., 2015), and on the importance of education and qualification of the workforce (Eberhardt & Lima, 2012; Fonseca et al., 2013; Paschoalino et al., 2016) in the attractiveness of a market for entrepreneurship. However, one dimension did not show adherence to the model in the study. The characteristics of the geographic dimension are not relevant to the attractiveness of municipalities for expanding franchise chains, which is different from what was pointed out by other authors (Moita & Guerra, 2012; Rodrigues et al., 2015).

The academic contributions of this study refer to the identification of the characteristics of the institutional environment that propelled the expansion of franchise chains in cities in the interior of Brazil. These results show that the attractiveness to the interior markets is because of the formal institutions as understood by the socioeconomic dimension, which is relevant for the identification of the consuming public and the commercial establishment of the franchise chains (Baumol et al., 2007), and the dimension of human resources, determinant for the supply from employees to franchised units (Faller & Almeida, 2014).

Consequently, contributions are made to studies on the institutional environment for entrepreneurship (Bruton et al., 2010; Khoury & Prasad, 2015), expansion of franchise chains (Jackson, 2008; Minadeo & Camargos, 2009; Moita & Guerra, 2012; Silva et al., 2016), and geographic expansion to regional markets (Barringer & Greening, 1998; Amin, 1999; Chung et al., 2007; Cordeiro et al., 2017).

Regarding managerial contributions, this research may collaborate with managers of expanding franchise chains in prospecting markets in the interior. The results make it clear that, in the decision-making process, the issue of geographic distance in relation to the state capital is not a determining factor for the analysis. In contrast, the analysis must first consider the socioeconomic situation. Municipalities with a larger population and number of employed persons, as well as with a greater number of shopping centers, tend to be more attractive for the establishment of franchised units. Secondly, the decision must also be based on human resources. Municipalities with better-trained workforce are more attractive to franchise chains. However, we emphasize that, because of the results, the hierarchical order of the franchisor’s decision-making process must first be socioeconomic factors and then human resources.

The result of the present study also presents managerial contributions to the public managers of the municipalities, in particular the secretaries of economic, social, and education development. Promoting municipal employability and better education for citizens, not only guarantees the discretionary fulfillment expected from the public entity, but is also an important mechanism for attracting new businesses for the creation of a virtuous cycle of regional development. Therefore, public management based on socioeconomic and human resources development, in addition to attracting business, guarantees an increase in the social impact of public management. The limitations of this study are in the profile of the cities studied, which are cities that are state capitals and that belong to metropolitan regions were disregarded, municipalities with less than 50 thousand inhabitants were not considered, and only the distance from the interior city to the capitals was considered as a reference pole.

Suggestions for future studies comprises analyzing the following: 1. the impact of the geographical dimension in relation to the regional hubs closest to the municipalities or regions of greatest influence; 2. the adherence of franchise chain formats that require less investment, such as microfranchises, in cities with less than 50 thousand inhabitants; 3. the stratification and formation of city clusters according to population size; and 4. the verification of these models in companies that do not adopt the franchise chain model.

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Publication Dates

• Publication in this collection
  04 Sept 2020
• Date of issue
  2020

History

• Received
  06 May 2019
• Accepted
  28 Apr 2020