Urban distribution centres in historical cities from the perspective of residents, retailers and carriers

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Urban distribution centre in historical cities from the perspective of residents, retailers and carriers Nayara Louise Alves de Carvalhoa, Priscilla Cristina Cabral Ribeirob, Carolina García-Martosc, Camino González Fernándezc, José Geraldo Vidal Vieirad,∗ a

Graudate Program of Production Engineering - CCGT, Federal University of Sao Carlos, Joao Leme dos Santos, KM 110. Itinga, Sorocaba, São Paulo, 18072-780, Brazil Department of Production Engineering, Fluminense Federal University, Passo da Pátria Street, 156, Office 306, Block D. São Domingos, Niterói, RJ, 24210-24, Brazil c Universidad Politécnica de Madrid, Escuela Técnica Superior de Ingenieros Industriales, C/ José Gutiérrez Abascal, 2, 28006, Madrid, Spain d Department of Production Engineering - CCGT, Federal University of Sao Carlos, Joao Leme dos Santos, KM 110. Itinga, Sorocaba, São Paulo, 18072-780, Brazil b

ARTICLE INFO

ABSTRACT

Keywords: Urban distribution centre Urban freight transport agents Multivariate statistical analysis Corporate social responsibility

The heavy flow of vehicles in historical cities leads to negative impacts for city logistics and for the preservation of its heritage. The use of an urban distribution centre (UDC) is a solution to minimise these impacts. This paper compares the operational, economic, social, cultural, and environmental aspects that influence the implementation of a UDC in a Brazilian historical city, considering the viewpoints of the agents: residents, retailers and carriers. Having a more complete picture of these aspects by the agents, this paper also sheds light on corporate social responsibility (CSR) in urban freight transport (UFT). A survey was developed with each agent. Factor analysis is used to find the factors for implementation of a UDC and the Structural Equivalence by Orthogonal Procrustes Rotation is used to compare the factors. The findings reveal different points of view for these agents. Residents attached greater importance to factors related to habitability and sustainability in the city. Retailers focused on economic environmental issues, while carriers emphasised operational and environmental aspects.

JEL classification: R41 R00 R13 R42

1. Introduction Brazilian historical cities declared as world heritage sites by the United Nations Educational, Scientific and Cultural Organisation (UNESCO) are a challenge for city logistics (Oliveira et al., 2019), mainly the city centre, where there are groupings of historical buildings, a range of small retailers, narrow streets, and a high concentration of pedestrians and tourists (IPHAN, 2014a, 2014b). Many of these cities have cobblestone streets, rough relief, and slippery, irregular sidewalks built of soapstone (Nobre, 2002). These distinctive characteristics heighten the difficulty in delivering freight loads in these historical centres, especially on rainy days. According to Unesco (2017), Brazil has fourteen cultural heritage sites in ten States. Heritage areas mainly consist of private properties, although some include publicly owned lands (Vincent & Comay, 2014). Considering cultural heritage sites as part of the Culture Economy (Fingueruti, Blumenschein, Souto, Leal, & Mohélsky & Pantoja, 2015), in 2010, the cultural sector represented 4% of the Brazilian GDP, 0.86% of Jobs in the Cultural Economy sector, and 27.3% of public funds

(Valiati & Fialho, 2017, p. 214). The annual culture sector public spending has grown twice as much as the total national budget from 2003 to 2013 (Fingueruti et al., 2015). In 2013, the Federal government launched the Growth Acceleration for Historical Cities Program, with roughly US$ 395 million for 425 restorations of buildings and public spaces in 44 cities in 20 Brazilian states (IPHAN, 2018). Ouro Preto, the city chosen to be investigated, is the biggest set of architecture baroque, a unique characteristic in Brazil (IPHAN, 2014a, 2014b). Ouro Preto city was declared a National Monument in 1933, protected by IPHAN in 1938, and it was the first Brazilian city included in the World Heritage List by UNESCO in 1980 (Oliveira, 2016), and it has (around) a thousand buildings from the colonial period (IPHAN, 2008). Adopting rules for access to the city centre (Allen, Browne, Woodburn & Leonardi, 2012; Lin, Chen, & Kawamura, 2016; Quak, 2008) is essential for organising the urban space and supplying local commerce. In the case of historical cities, such rules are key to preserving the world heritage regarding the accessibility of cargo vehicles like a time-window and general vehicle restrictions (Carvalho, Ribeiro, Oliveira, Silva, & Vieira, 2019).

Corresponding author. E-mail addresses: [email protected] (N.L.A. de Carvalho), [email protected] (P.C.C. Ribeiro), [email protected] (C. García-Martos), [email protected] (C.G. Fernández), [email protected], [email protected] (J.G.V. Vieira). ∗

https://doi.org/10.1016/j.retrec.2019.100744 Received 16 November 2018; Received in revised form 26 August 2019; Accepted 2 September 2019 0739-8859/ © 2019 Elsevier Ltd. All rights reserved.

Please cite this article as: Nayara Louise Alves de Carvalho, et al., Research in Transportation Economics, https://doi.org/10.1016/j.retrec.2019.100744

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According to the Institute of Historical and Artistic Heritage (IPHAN) (2011), the organisation responsible for protecting and safeguarding cultural heritage in Brazil, the trade in historical centres is maintained as traditional and popular. These tradesmen are independent retailers that do not have optimised deliveries (Van Duin, Van Dam, Wiegmans, & Tavasszy, 2016). As a result, there is a range of small retailers that demand a large number of vehicles for frequent deliveries. These cargo vehicles do not respect the rules to preserve the world heritage, trans-shipping in forbidden places, such as at the entrance into cities and highways, and ignoring the time window. In addition, the city does not have enough protection for its heritage sites, and as a consequence, some of them have experienced fires and a lack of maintenance, as what happened on March 30th, 2019, when a door at the ‘Nossa Senhora Rosário dos Pretos' burnt down in the historical centre (Bom dia Minas, 2019). Salvador, Bahia, another city where its historical centre is a heritage site in Brazil, also shows problems with discontinuities (Nobre, 2002), lack of transparency of public investments in restoring the buildings, squares and churches, and occupation of some buildings in historical centres by drugdealers since the 1970s, and especially from the 1990s–2000s (Reis, 2004). In addition, the preservation of this cultural/historical heritage gives local tourism the opportunity to create new jobs and income for the local population, alleviating poverty. Although advantages in investing in the maintenance of historical heritage sites in Brazil have been recognised, there are five states that do not have departments to control the use of land in these sites (Oliveira, 2016). Other Brazilian historical cities also experience these issues because of the lack of interest; some of them have spent years without having been renovated (Bispo & Giannecchini, 2015). Given the special characteristics of historical cities, the implementation of an urban distribution centre (UDC) is an alternative for efficient urban freight transport (UFT) in terms of sustainability and preservation of historical heritage. The objective is to consolidate urban delivery service (Browne, Sweet, Woodburn, & Allen, 2005; Taniguchi & Thompson, 2015, pp. 1–12) and have space for temporary storage where retailers can withdraw or request the delivery of goods during the day. Pulawska and Starowicz (2014) explained the need for greater awareness of the historical and artistic heritage, citing a UDC as a solution for city logistics problems. In Europe, the ENCLOSE Project sensitised to the challenges of energy efficient and sustainable urban logistics in small and medium-sized historical cities (CHPMD) also addressed the use of a UDC. Although several case studies indicate that UDCs are beneficial to the functioning of urban transport systems, implementing them is a complex initiative because it is not economically or financially sustainable (Nocera & Cavallaro, 2017), and involves the coordination of different and conflicting agents (Zhou & Wang, 2014) and multiple aspects regarding logistics operations and land use control in historical cities (Björklund, Abrahamsson, & Johansson, 2017). This paper compares the operational, economic, social, cultural, and environmental aspects that influence the implementation of a UDC in a Brazilian historical city, considering the viewpoints of residents, retailers and carriers. This research also sheds light on management practices regarding corporate social responsibility (CSR) (Knorringa & Nadvi, 2016) into UFT. The research was developed in the historical centre of Ouro Preto, which presents common characteristics of other Latin American and some European cities that are part of the World Heritage List; therefore, this research can be generalised to those cities. The contribution of this research is to provide a theoretical framework regarding the main factors that should be considered in the implementation of a UDC in historical cities from the perspective of residents, retailers and carriers by comparing these different viewpoints. No study was found regarding the factors that influence the implementation of the UDC and that can contribute to the preservation of

the historical patrimony. Furthermore, there is no study from the perspective of the agent (residents, retailers and carriers) that take into account the discussion of management practices regarding CSR in UFT. The structure of this paper is as follows: Section 2 describes the agents who may be interested in implementing a UDC and their relationships. Section 3 summarises the use of the UDC in historical cities based on the main aspects that can influence the implementation of a UDC. In section 4, we introduce the corporate social responsibility in urban freight transport. In Section 5, we describe the materials and methods. Section 6 presents the results, and Section 7 discusses the results based on the theoretical framework. Finally, in Section 8, we provide the overall conclusions of the study. 2. Relationship between urban freight transport agents There are three different groups of agents involved in UFT decisionmaking: public authorities, professionals and residents (Quak, 2008; Taniguchi, Thompson, & Yamada, 2003; Yanqiang, 2014; Le Pira et al., 2017). Public authorities are represented by local, regional and national governments. The key concerns of these agents are to maintain an attractive urban area and to increase the quality of life, whilst attempting to attract businesses and visitors to the area (Ballantyne, Lindholm, & Whiteing, 2013). Professionals are involved in the movement of urban goods because of their profession. The most important actors in this group are shippers, carriers, receivers and terminal operators (Quak, 2008; Yanqiang, 2014). Residents are affected by the urban movement of goods, though they are not directly involved (Quak, 2008), and they are distinguished by residents and tourists. Ballantyne et al. (2013) differentiate two groups for the city logistics agents: ‘stakeholders’ and ‘actors’. Fig. 1 shows the interrelationships between all agents involved in the UFT, distinguishing them as ‘stakeholders’ and ‘actors’. ‘Stakeholders’ are all agents that have an interest in the UFT system (individuals, groups of people, organisations, companies, etc.) and others who work in urban logistics in search of economic, environmental, social and cultural improvements. Vehicle manufacturers have an indirect impact on urban freight transport in the design and technological innovation of freight vehicles: they are interested in building (and marketing) vehicles that suit urban freight transport operations (Ballantyne et al., 2013, p. 99); associations and commercial organisations have an interest in stimulating the economic and social development of a community. In the case of historical cities, institutions that seek to preserve world heritage and encourage the imposition of laws on cargo transport, such as UNESCO and IPHAN, are also part of the group of stakeholders. ‘Actors’ are shippers, carriers, receivers (as an integral part of the professionals), public authorities and others that are impacted. Shippers and receivers (i.e., retailers) act as a starting point/destination or collection/delivery point when dealing with both urban freight and reverse logistics flow. The carrier is responsible for the transportation of cargo and the terminal operator manages the urban logistics activities, such as responsibility for the activities performed in the UDC. Although all agents share common goals related to freight transport in urban areas, each one has different roles, problems and objectives (Taniguchi et al., 2003, p. 491), and with this range of different points of view and conflicting interests, it is a complex problem to find acceptable solutions for all of them (Taniguchi et al., 2003). These agents act autonomously without any centralised control (Anand, Van duin, & Tavasszy, 2012). Retailers order small but frequent deliveries to reduce their inventory cost, which creates disruption to other freight vehicles. Public authorities impose rules such as weight restrictions to relieve urban traffic. Despite their limited decision-making power, governments tend to pay more attention to those impacted (their voters, residents) than to

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Fig. 1. Inter-relationship among UFT agents. Data source: Adapted from Ballantyne et al. (2013) and Yanqiang (2014).

the professionals (retailers, carriers, etc.) (Ogden, 1992). Within the commercial zones of urban areas, retailers want to receive their commodities at a time convenient for them. However, this sometimes conflicts with residents who want quiet and safe conditions on local roads (Taniguchi et al. (2003). On the other hand, tourists and visitors compared to the city's residents, care less about air quality and pollutant emissions (MDS Transmodal Limited, 2012).

- it provides the opportunity for professionals to gain qualifications (Henriot, Patier, Bossin, & Gérardin, 2008), such as driver training, identified by the European Commission (2000) as one of the five key areas of urban transport strategy, which are expected to achieve environmental and competitiveness gains for all agents involved - it allows the actual or potential use of non-road modes for UDC deliveries, as well as the use of smaller vehicles (Browne et al., 2005; Browne, Woodburn, & Allen, 2007).

3. Urban distribution centres in historical cities

Related to the economic aspect, a UDC contributes to local prosperity by job creation (e.g., for drivers and operational and administrative employees of the UDC) and incentive for competitiveness in retail, increasing the competitiveness of an urban economy because of a more efficient freight distribution system (Russo & Comi, 2010). Local prosperity also has a social aspect, as well as the ability to reduce insecurity (the number of accidents caused by the uncontrolled acts of loading and unloading prohibited in the city centre, large vehicle traffic and recklessness of the drivers) (Agrebi, Abed, & Omri, 2015; Anderson, Allen, & Browne, 2005; Awasthi & Chauhan, 2012; Gonzalez-Feliu & Morana, 2010; Kin et al., 2016). A UDC can also be viewed from the cultural aspect, protecting these historical centres (Recommendation of the 19th General Conference of the United Nations in Nairobi, 1976; Machu Picchu, 1977; Washington, 1986). A UDC contributes to reducing the shaking of heritage architecture and decreases the impacts (noise, shocks, & vibrations) caused by vehicles on the surface of walls (filiform cracks, cracked walks, and broken pipes), mainly from heavier vehicles (Azevedo & Patrício, 2001, pp. 1–9; Browne et al., 2005; Resende, 2011). Finally, damage to buildings by collision is a criterion related to every accident caused by vehicles, which collide with buildings in historical cities. During a

An urban distribution centre (UDC) is a logistics solution to try to minimise the negative effects from freight transport into the city. Conceptually, it is a freight strategy intended to reduce trips made by trucks into urban centres, and therefore reduce the vehicle miles travelled (VMT), energy consumption and emissions (Lin et al., 2016). The negative effects are operational, economic, social, cultural, and environmental. Regarding the operational aspect, a UDC has some advantages, which include the following: - it facilitates freeing public space (Awasthi & Chauhan, 2012, p. 579), increases the ability to find parking spaces due to facilitated operations with freight vehicles in loading/unloading areas within the cities and delivery bays (Zunder & Marinov, 2011), and reduces the number of big cargo vehicles in city centres (Brasileiro, Ascenção, & Rosin, 2015); - it reduces congestion caused by trucks blocking a street, problems with parking because of freight transportation, and others (Gonzalez-Feliu, 2008; Gonzalez-Feliu & Morana, 2010; Kin, Verlinde, Van Lier, & Macharis, 2016)

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previous field survey, the author found damage caused by cargo vehicles on license plates that were partially destroyed or overturned by cargo vehicles on the narrowest streets in the city centre. Regarding the environmental aspect, a UDC can reduce atmospheric/air pollution, visual intrusion and noise nuisance levels (Quak, 2008; Rao, Goh, Zhao, & Zheng, 2015). The first concerns the weathering of rocks on historical monuments; emissions cause the degradation of rocky materials of the monuments (Reys, Lama, & Dehira, 2008), and the black smoke from vehicles’ exhaust, especially from trucks, accumulates on the facades of the buildings. Visual intrusion is caused by the permanence and movement of cargo vehicles (Zarinato, 2008) breaking perspectives, hiding part of the landscape and causing functional changes in the interaction of the individual with the environment (IPHAN, 2014a, 2014b; Zarinato, 2008). According to Quak (2008), the environmental aspect can be caused by blockage during shopping because of loading activities or double parked vehicles. The noise nuisance level (Anderson et al., 2005) is related to the vibrations and sounds caused by the movement of vehicles (Quak, 2008; Rao et al., 2015), and can produce physiological, psychological and social problems. Factors can modify the perception of the noise in each situation (Gonzalez-Feliu, 2008, p. 22; Gonzalez-Feliu & Morana, 2010). A UDC can help noise reduction by using silent vehicles for freight (Gonzalez-Feliu & Morana, 2010). According to Allen, Thorne, and Browne (2007), Ville, GonzalezFeliu, and Dablanc (2010), and Allen, Browne, Woodburn, and Leonardi (2012), UDCs enable the use of alternative powered vehicles. These vehicles run on natural gas or electricity (Allen et al., 2007; Browne, Allen, & Leonardi, 2011; Giuliano, O'Brien, Dablanc, & Holliday, 2013; Ville et al., 2010) and electrically assisted cargo tricycles (Browne et al., 2011). Compliance with legislation means using a UDC as a way to comply with environmental legislation at municipal, regional and federal levels (Agrebi et al., 2015; Rao et al., 2015). This is a way to consider all city and regional space plans and resources, including the determination of low emission zones (LEZs). Table A1 (see appendix A) presents the authors of all studies cited above and defines the common implementation criteria of a UDC for different agents.

further analysis. For instance, how to consider a UDC in a place where the law related to land use control is scarce or the stakeholders neglect or have no knowledge of the local regulations? It is also hard to understand the implementation of a UDC when we consider different perspectives of stakeholders in light of CSR because they have different interests. As suggested by Van Marrewijk (2003), a successful CSR strategy has shown that the stakeholders should be engaged in the specific CSR issues, for example, environmental aspects or economic aspects, and so on. The CSR strategy has presented many practices that show that businesses have social, environmental and economic impacts, considering stakeholders (government, clients or owners) and general regulations. However, at an operational level, operations are changing more rapidly (Dahlsrud, 2008); local regulations and the use of new technologies have challenged decision makers, changing how social, environmental and economic impacts should be optimised. Turoń and Czech (2016) summarise some typical practices in sustainable transport that have been adopted by European companies: reduction of CO2 emissions, eco-driving training for drivers, alternative fuel vehicles, sustainable car fleet management, using vehicles with alternative powertrains (electric, hybrid), using alternative types of vehicles when possible e.g. electric cargo bikes while restrictions are imposed on city traffic. Dyczkowska (2015) reports that, in Europe, the TransportShipping-Logistics (TSL) industry has been concerned with environmental protection when they develop their logistics activities; they also take the responsibility for the negative effects produced by their business. However, Vieira, Mendes, and Suyama (2016) have found that in Brazil, carriers appear unwilling to adopt sustainable practices. Carriers are less concerned about the impact caused by the disposal of spare parts and gas emissions. About 66.67% of the carriers do not have a carbon dioxide emission reduction target, 58.33% have no carbon dioxide measurement, 58.33% do not have a target for waste reduction, and 77.08% do not recycle. In addition, carriers have revealed low levels of agreement for preventive actions regarding impact reduction, such as “regular brake and suspension system maintenance”, “proper disposal of accessories” and “proper disposal of lubricating oil” (Van Marrewijk, 2003). 5. Materials and methods The methodology of this study consists of a descriptive survey distributed to the three city logistics agents related to the UFT in the historical centre of Ouro Preto: residents, retailers and carriers. The survey was designed with respect to the guidelines and recommendations in Forza (2002). The choice of the city of Ouro Preto is because it is one of the most important and symbolic cities in Brazilian culture. We chose to study the historical centre of the city for two reasons. First, according to the data of the Municipal Finance Department, it is the neighbourhood with the highest concentration of commercial companies in the city, accounting for 15% of 3239 stores. The second reason is that it has established rules for UFT (creation of special protection zones and rules for limiting weight, size and time of urban freight and operation of cargo vehicles). However, it lacks land use control and updated laws to protect the historical heritage. Law number 29, of December 28, 2006, established, by means of a decree, the special protection zone of the historical centre of Ouro Preto. In 2008, two decrees (numbers 1.153 and 1.154, from May 30th) avoid circulation of heavier vehicles in the historical centre (i.e. the vehicles cannot exceed 8.0 m in length; 3.5 m high, including cargo; 2.6 m wide and; total gross weight exceeding 7 tonnes). The law also establishes a restrictive time for this in some streets (i.e. 6a.m.–9a.m.; 7p.m–10p.m. on weekdays. In September of the same year, another decree (number 1.380) defined rules for registering companies that trans-ship from one city to Ouro Preto. However, up to 2017 there was no company accredited.

4. Corporate social responsibility in urban freight transport The negative effects faced by the agents in UFT can also be analysed in light of the corporate social responsibility (CSR) due to it including economic responsibilities (being profitable), philanthropic responsibilities (being a good corporate citizen), legality (obeying the law) and ethical responsibilities (being ethical) (Nikolaou, Konstantinos and Allan, 2013). However, the definition of CSR is rather confusing in the literature. Dahlsrud (2008) has compiled many definitions and coded them into the following dimensions: environmental (natural environment), social (relationship between business and society) economic (socio-economic or financial, and business operational aspects), stakeholder and willingness (actions not prescribed by law). All of them should be analysed altogether, and the most common aspects are: social, environmental and economic - voluntary by definition - in interactions with stakeholders (Van Marrewijk, 2003). Regardless of any definition, CSR means “the responsibility by enterprises for their impacts on society” (European Commission, 2011) or how the enterprises communicate/follow policies and practices that reflect their business responsibility for some of the wider societal good (Matten & Moon, 2008). This research does not aim to define or to apply CSR in UFT as a whole; however, some discussion regarding CSR may be useful for

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We used the measure D2 de Mahalanobis to detect atypical values of multivariate data (Zijlstra, Van Der Ark, & Sijtsma, 2013). Thus, 31 atypical observations were detected, so the final collected sample was 311 residents, of which 142 were male (46%) and 169 female (54%). To guarantee representativeness of the sample, it was compared to the proportions of the population (men, women and their age groups) presented in the IBGE demographic census (2010). Fig. 2 shows that, except for the range of 25–34 years old where more people were interviewed in relation to the population, the difference between sample and population is less than 6%. We surveyed a sample of 122 retailers from different sectors (foodstuffs, textiles and clothing, pharmacies, etc.). No typical observations were found. Most of the retailers' representatives (67%) have strategic positions (partner owners, managers or directors) and have an average of 13 years of experience. Therefore, they have extensive knowledge about the UFT in the historical centre of Ouro Preto. From carriers, 46 questionnaires were collected from drivers with an average of 10 years’ experience in the profession. The Mahalanobis test did not detect any atypical observations. Of the total, 63% of the drivers were employed by carriers, and 37% were autonomous.

Recently, decree number 5183 created in 2018 allowed circulation of heavier vehicles in the historical centre, instead of the previous decree number 1.337 in the same year, which did not permit this circulation, establishing some limits of the number of passengers for buses and vans. In November 2018, the Public Ministry of Minas Gerais State suspended the decree; and since then nothing has been decided. 5.1. Questionnaire design The questionnaire was structured for each agent, based on literature review of criteria that can influence the implementation of a UDC (see Appendix A, Table A1). Pilot tests were performed to ensure that the survey instrument and its procedures were adequate. The final versions of the questionnaires (retailers and carriers) were applied face to face. Collection from residents was done in two ways: face to face and using an online questionnaire by “goggle docs - Online platform”. These agents were invited to express their agreement with the statements using a Likert scale of 1–5 (‘I fully agree’ to ‘I strongly disagree’). 5.2. Sample and procedures The population of residents (70,281) was on the database developed by IBGE (2015). The population of retailers was extracted from the database of the Municipality database and considered only companies focused on commerce/retail, except those that work with a high added value service, such as retailing of jewellery articles. This refinement generated a population of 196 retailers. The population of carriers is unknown. For residents and retailers, the sample was calculated based on a finite and known population as presented by Cochran (1985). We considered the known confidence level equal to 95% and a sample error margin of 6%. Thus, the calculated target sample of residents and retailers are 266 and 113, respectively. In the case of the carriers, the sample is not defined because the data collection was carried out by accessibility, when the researcher only obtained the elements with greater ease of access, admitting that they can effectively represent the population adequately. Data collection was carried out between July and August 2016. We collected 342 questionnaires from residents over 18 years old.

5.3. Data analysis We used the multivariate factor analysis (FA) technique to find the factors that influence the implementation of a UDC to supply the retailers positioned in the historical centre of Ouro Preto. The function of FA is to generate linear combinations (Hair, Black, Babin, & Anderson, 2005) called factorial loads. The higher the factor load, the more the variable contributes to this factor (Harman, 1976). Based on Hair et al. (2005), we performed four tests to ensure the application of FA and they were above their respective cut-offs: correlation matrix analysis (> 0.3); Kaiser-Meyer-Olklin (KMO) sample adequacy measure (> 0.5); Barlett sphericity test (BTS) significant at 1%; and measures of sampling adequacy (MSA) by anti- Image (> 0.5). To determine the number of factors, we used three extraction methods: screeplot, eigenvalue and amount of variance explained (Hair et al., 2005). To obtain a better interpretation of the factors and eliminate possible ambiguities, the varimax orthogonal rotation was

Fig. 2. Proportion of residents based on gender and age group. Legend: M (Male); F (Female).

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selected. We also analysed the communalities above 0.5 (Hair et al., 2005). Cronbach's alpha was used to re-specify the factorial model and to validate the factorial matrix (> 0.5) (George & Mallery, 2003). To compare the same option from the resident, retailer and carrier viewpoints, we used the Structural Equivalence by Orthogonal Procrustes Rotation, proposed by Ronald and Fontaine (2012, pp. 179–215), which is possible only with the same number of variables and factor dimensions. In each of the cultural groups (in this case represented by the three agents: residents, retailers, and carriers), a factor structure is generated with the same number of factors as in the reference group, which should be chosen arbitrarily. Procrustes rotation is made towards the factor structure of the reference cultural group. Once the solutions have been rotated, the congruence between the factor loadings for pairs of cultural groups can be computed. Ronald and Fontaine (2012, pp. 179–215) proposed four congruence measures: the linearity, the proportionality (Tucker's phip), the additivity, and the identity coefficient. The difference between these measures is that they are affected by the addition of factorial loads and/or the multiplication of factorial loads. The IBM SPSS Statistics Base, version 21.0, was used to conduct the factor analysis and comparisons.

size’ (V4). Automobiles always result in low levels of vibration, while heavy traffic and its vibrations result in risks to the structure of buildings in historical cities. Trucks provide ‘visual intrusion’ (V10) (Quak, 2008), which degrades the urban landscape (Zarinato, 2008; IPHAN, 2014a,b). Using smaller load vehicles (V4) for deliveries can contribute to better local urban logistics. We call this factor “effects of cargo transport on the urban landscape”. F2Re contains the variables related to driving condition: ‘noise nuisance level’ (V11), air pollution level’ (V9) and ‘congestion’ (V2). According to Daniela, Paolo, Gianfranco, Graham, and Miriam (2014), freight transport is responsible for increasing congestion, pollution and reduction in the quality of life of people who live in and visits cities. In Paris, one way to contain the negative impacts of freight transport was to create driver training schemes (V9) to help improve driving and productivity in loading and unloading operations (Anderson et al., 2005). Thus, this factor can be interpreted as the “behaviour and skills of the driver”. F3Re consists of the variables ‘use of alternative powered vehicle’ (V12) and ‘air pollution level’ (V9), and it is interpreted as a “measure of air quality”. According to Demir, Bektas, and Laporte (2014), it can be assumed that CO2 emissions are directly related to fuel consumption. Therefore, the use of alternative powered vehicles such as electric vehicles could be an important solution to reduce these emissions (Lebeau, Macharis, Mierlo, & Maes, 2013). F4Re is formed by the variables ‘insecurity’ (V6), ‘parking spaces' (V1) and ‘local prosperity’ (V5). Local prosperity is related to job creation and competitiveness in the retail trade. With a greater number of parking spaces, it is easier and quicker to supply retailers because there is a reduction in the aversion of drivers who deliver goods in the city, which helps increase competitiveness. Especially in historical city centres, larger vehicles can block narrow roads while unloading, as can double parked vans (Russo & Comi, 2010; Zunder & Marinov, 2011), contributing to the generation of accidents. Therefore, this is a factor of “local prosperity”. The second group of factors is represented by retailers. We excluded the variables ‘air pollution level’ (V9) and ‘compliance with legislation’ (V13) due to the low value of the communalities. F1Rt is represented by the variables ‘depletion of building by collision’ (V8), ‘shaking of the architectural heritage’ (V7) and ‘noise nuisance level’ (V11). The ‘depletion of building by collision’ is related to any accident caused by vehicles that collide against the architecture, while mechanical vibrations contribute to the appearance of cracks or the increase of existing cracks in the walls of the historical buildings (Azevedo & Patrício, 2001, pp. 1–9). The ‘noise nuisance level’ reflects a consequence of mechanical vibrations, not only in buildings, but in people (Quak, 2008). Thus, F1Rt is interpreted as a factor of “effects of cargo transport on the conservation of historical buildings”. F2Rt is formed by ‘use of alternative powered vehicles' (V12), ‘visual intrusion level’ (V10) and ‘local prosperity’ (V5). The ‘use of alternative powered vehicles' (V12) impacts the level of service when the customer requires that their suppliers have actions towards sustainability or have related certifications. The ‘visual intrusion level’ (V10) is a reflection of the vehicle's stopping or staying in an inadequate place (Zarinato, 2008). Having a UDC may minimise this issue. ‘Local prosperity’ (V5) includes job creation and contribution to the competitiveness of retailers through a more efficient distribution system (Russo & Comi, 2010). This factor is defined as “economic-environmental improvements”. F3Rt contains ‘insecurity’ (V6) and ‘congestion’ (V2), which are identified by some authors (Kin et al., 2016; Quak, 2008) as negative consequences of the transport of cargo that may be attenuated by the use of UDC. The morphology of city centres, especially those inherited from the Middle Ages, contain narrow streets without parking lots or

6. Results 6.1. Descriptive statistics of data Table A1 (appendix A) shows the descriptive analysis for the sample. For residents, the variables with the highest agreement were ‘compliance with legislation’ (V13); ‘vehicle size’ (V4) and ‘shaking of the architectural heritage’ (V7). All these variables are related to the rules such as weight and size restriction applicable to the city centre. For retailers, ‘vehicle size’ (V4) and ‘parking spaces’ (V1) were the variables with the highest level of agreement, both related to operational aspects of the UFT. On the other hand, most retailers disagreed that the UFT is responsible for generating noise in the historical city centre. The ‘congestion’ (V2) presented completely opposite modes, emphasising a variable that divided opinions among retailers. As was the case with retailers, carriers agreed on the need for ‘parking spaces’ (V1) and delineation of ‘vehicle size’ (V4) in the city centre. However, many of them were against the existence of negative impacts caused by transport, such as ‘insecurity’ (V6), ‘congestion’ (V2), and ‘noise nuisance level’ (V11). In addition, most of them are against maintaining the current law (V13) that restricts weight, size and time window for distribution of goods in the historical city centres. 6.2. Relevant factors for the implementation of a UDC We performed a factorial analysis to reduce the variables and find the most relevant factors for implementing a UDC (see Appendix A, Table A2). It presents the four generated factors for each agent, as well as the communalities, KMO, explained variance and the Cronbach's alpha for each set of variables regarding residents, retailers and carriers. To interpret the factors, their factor loadings are analysed (see Appendix A, Fig. A1). The first group of factors regards the residents. We eliminated the variable ‘compliance with legislation’ (V13) because of its low commonality. However, although ‘vehicle size’ (V4) and ‘insecurity’ (V6) had low commonality, these variables were maintained because they contributed theoretically to the composition of the factors. In addition, only four factors had a low Cronbach's alpha due to relatively low interitem correlations (Cortina, 1993), but its composition has support in the theory. F1Re consists of ‘depletion of buildings by collision’ (V8), ‘shaking of the architectural heritage’ (V7), ‘visual intrusion’ (V10), and ‘vehicle

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alleys. This feature added to the accentuated topography, making it even more difficult to transport cargo. As a result, a large number of larger vehicles (trucks) in the centre increases insecurity (especially when very narrow streets limit the driver's visibility) and creates congestion. Therefore, this factor is interpreted as a “negative perception of cargo transport”. F4Rt integrates the variables ‘parking spaces' (V1), ‘vehicles size’ (V4) and ‘professional qualification’ (V3). When a smaller number of vehicles enter the city and considering ‘smaller vehicle sizes' (V4), it is expected that there will be more available ‘parking spaces' (V1), since trucks occupy more places than smaller cars (Brasileiro et al., 2015). There is more fluidity in the freight transport, and vehicles do not need to park too far from customers. There are also operational gains related to the best ‘professional qualification’ (V3) that handle retailers' burdens, as well as efficiency and productivity gains (Henriot et al., 2008). Therefore, F4v * is a “productivity factor”. The third agents are carriers. The variables ‘air pollution level’ (V9), ‘compliance with legislation’ (V13) and ‘local prosperity’ (V5) were excluded due to the low value of the communalities. Only F4t presented a low Cronbach's alpha due to the relatively low inter-item correlations (Cortina, 1993). F1Ca includes the following variables: ‘shaking of the architectural heritage’ (V7), ‘depletion of buildings by collision’ (V8), ‘visual intrusion level’ (V10) and ‘insecurity (V6). The first two variables, as mentioned for F1Re, were cited by the 19th General Conference of the United Nations (1976) as a means of protecting historical sites. According to Allen et al. (2003), the number of kilometres and the total travel time of the cargo vehicle indicates the amount of ‘visual intrusion’ (V10) and ‘insecurity’ (V6) in a certain area. Thus, the less time the vehicle remains in the historical centre, the less the impact will be. This factor is interpreted as the “effects of cargo transportation on the conservation of historical buildings and road safety”. F2Ca was formed by ‘use of alternative powered vehicles' (V12) and ‘noise nuisance level’ (V11). Gonzalez-Feliu and Morana (2010) explain that from the use of UDC, social and environmental advantages may include noise reductions through the use of quieter vehicles. As an example, alternative propulsion vehicles such as electric and hybrid are very quiet, especially when travelling at low speeds (Verheijen & Jabben, 2010). Faced with this, this factor can be interpreted as “environmental improvements”. F3Ca contains the variables ‘parking spaces' (V1) and ‘vehicles size’ (V4) with the highest loads. As explained in F4r, the increase in the number of parking spaces facilitates the retailers' supply. Most carriers stated the lack of parking spaces, and the lack of signal loading and unloading and even movement in the centre. Moreover, 30% of carrierss prefer to risk being fined (parking the vehicle in a prohibited or permitted only for passenger cars) and only 9% said they returned to the place of origin of the trip. The size of the vehicles is related to the number of parking spaces because the smaller the vehicle, the less space is occupied, and it is easier to find free places (Brasileiro et al., 2015). However, the majority of daily and weekly deliveries are made by trucks weighing 3–5 tons. This is a factor of “ease in freight transport”. F4Ca contains the variables ‘professional qualification’ (V3) and ‘congestion’ (V2) with the highest loads. As explained for F2Re, one of the ways to avoid congestion is training on driving and loading/unloading operations for drivers, as was the case in Paris (Anderson et al., 2005). Thus, this factor can be interpreted as the “behaviour and skills of the driver”.

Table 1 Measures of congruence between factors. Compared factors

Linearity

Proportionality/Tucker

Additivity

Identity

F1Re-F1Rt F2Re-F3Rt F3Re-F2Rt F4Re-F4Rt F1Re-F1Ca F2Re-F4Ca F3Re-F2Ca F4Re-F3Ca F1Ca-F1Rt F2Ca-F2Rt F3Ca-F4Rt F4Ca-F3Rt

0.88 0.73 0.61 0.36 0.81 0.85 0.46 0.10 0.77 0.35 0.81 0.71

0.93 0.85 0.80 0.56 0.91 0.88 0.70 0.39 0.86 0.62 0.88 0.81

0.88 0.72 0.61 0.36 0.81 0.85 0.46 0.10 0.77 0.35 0.81 0.71

0.93 0.85 0.80 0.56 0.91 0.88 0.70 0.39 0.86 0.61 0.88 0.81

Note: We underline the factors' coefficients that showed similarity with some factor.

the perception of the three agents (residents, retailers and carriers), the first factors generated in the three cases in the FA are considered the most important, since they comprise the highest percentage of the initial variance of the sample. In all three cases, the ‘depletion of building by collision’ and ‘shaking of the architectural heritage’ were the variables highlighted with the highest loads in the first factor, which confirms the strong correlation between them and the recommendations of the 19th General Conference of the United Nations (1976) about the protection of historical sites. In addition to the ‘depletion of building by collision’ and ‘shaking of the architectural heritage’, retailers only included ‘noise nuisance level’ in the first factor because many of them are installed in historical buildings and thus have a greater perception about the effects of noise on people and the workplace. The carriers also included in this factor the ‘visual intrusion level’ and ‘insecurity’ generated by the transportation of cargo, mixing variables that have a direct impact on buildings with a negative impact on people. As noted, each agent has different perspectives of the same aspects. However, when the factors reveal similarity with each other, a viewpoint of an agent can be similar to another. Comparing the factors among agents, congruence coefficients (linearity, proportionality, additivity and identity) are used for the factor loadings for pairs of factors of the three agents (see Table 1) using the Structural Equivalence by Orthogonal Procrustes Rotation (Ronald & Fontaine, 2012, pp. 179–215). To compare the factors, the residents' group was used as a reference in comparison with the groups of retailers and carriers; in the comparison between retailers and carriers, carriers are used as a reference. The excluded variables (according to the FA of each agent) were computed with zero loads. The congruence coefficients may be at most 1. A value in the range of 0.85–0.94 corresponds to a fair similarity, while a value larger than 0.95 implies that the two factors showed acceptable similarity (Lorenzo-Seva & Ten Berge, 2006). High values between coefficients indicate that the structure of the factor is similar. If low values are found or large differences exist for the various indices, the similarity or replicability of the factor structure may be questioned (Ronald & Fontaine, 2012, pp. 179–215). In comparison between residents and retailers, the similarity between the factors F1Re and F1Rt is verified in all coefficients, especially because of the high loads of the cultural aspect: ‘shaking of the architectural heritage’ and ‘depletion of buildings by collision’. When comparing residents and carriers, all coefficients were similar for F2Re and F4Ca due to the presence of the operational aspect of the variables ‘congestion’ and ‘professional qualification’, both with high loads.

7. Discussion Regarding the relevant variables in the implementation of a UDC in

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Fig. 3. Inter-relationships among factors generated by agents and their aspects. Note The variables V2 and V11 (for residents) and V10 (for retailers) were positioned and the first factor of respectively agent. Aspects: Cultural (C); Environmental (E); Economic (Ec); Operational (O); Social (S).

However, despite the similarity, the F2Re factor is considered to be relatively more important for the residents than the F4Ca factor for the carriers (conclusion drawn from the variance explanation percentage). In comparison of carriers and retailers, there is no factor that presented similarity for all the coefficients. It should be noted that although the tucker and identity coefficients indicate the existence of a correlation between the factors F2Re and F3Rt, F1Re and F1Ca, F1Ca and F1Rt, and F3Ca and F4Rt, these similarities should be questioned due to the different values found in the coefficients as stated by Ronald and Fontaine (2012, pp. 179–215). There is no common factor among the three agents. Based on the results of similarity between the factors, Fig. 3 presents the results of comparison in the form of sets of the principal factors formed by the three agents, highlights the variables with high cargo and aspects found in each factor. Residents expressed attention to cultural, operational, environmental and social aspects, giving importance to the preservation of the city's patrimony, the way of driving and improvements in air quality and local economy. Residents want an attractive urban area and reinforce their concern for the sustainability and liveability of the city, free from noise and visual intrusion caused by freight vehicles (Ballantyne et al., 2013; Quak, 2008; Yanqiang, 2014). Then they are more concerned with CSR. Retailers also focused on the effects of freight transport on historical buildings and road safety but were also concerned with aspects of environmental economic improvement, perceptions of the negative effects of freight transport and productivity. Retailers focus more on the profitability of the business (Anand et al., 2012). As most retailers are very small local firms, they may focus more

on financial issues, and therefore social and environmental responsibility is not a priority (Van Marrewijk, 2003). Finally, carriers emphasised the importance of heritage preservation, environmental improvements, ease of UFT, and driver behaviour and skills. This result shows their concern on operational terms since they are the ones who actually deliver goods into the urban area (Ballantyne et al., 2013). However, a huge percentage of carriers (30%) prefer being fined. In addition, these trucks use motorised vehicles, mainly trucks to carry out the most frequent deliveries (daily/weekly). Therefore, carriers do not seem to be aware of the CSR, they are not fully aware of the environmental impacts (Vieira et al., 2016) and seem to have little knowledge of the legal aspects (local laws) regarding traffic restrictions. In addition, carriers appear to be also far from ethical responsibilities and do not voluntarily communicate their actions (Nikolaou, Konstantinos and Allan, 2013). 8. Conclusions The objective of the research was to compare the operational, economic, social, cultural, and environmental aspects that influence the implementation of a UDC in a Brazilian historical city, considering the viewpoints of residents, retailers and carriers. This research also grouped the criteria into appropriate factors, which represent the aspects evaluated by each agent. In general, the results show that agents present different points of view. The existence of many different factors shows how complex it is to satisfy the needs of different agents (MDS Transmodal Limited, 2012; Muñuzuri, Larrañeta, Onieva, & Cortés,

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2005) because each agent has particular objectives of UFT, which makes it difficult to establish a solution common to all of them, also in the light of CSR (Van Marrewijk, 2003). Residents attached greater importance to factors related to habitability and sustainability in the city. Retailers focused on economic aspects while carriers emphasised operational and some environmental aspects. A way needs to be found to acquire operational (carriers and retailers), economics (retailers) and environmental (all agents) efficiency. A possible way of doing this can be initiated with studies based on the variables and common factors found in this research, which go beyond economic and operational factors and include concern for the environment and social well-being, as supported by CSR strategies (Van Marrewijk, 2003; Dahlsrud, 2008; Matten & Moon, 2008). The carriers should use environmentally friendly vehicles (electric and less gas emission consumption) or non-motorised vehicles (Turoń & Czech, 2016) to avoid the depletion of buildings and shaking of the architectural heritage. It will also improve the visual intrusion level as reported by the retailers. Therefore, a project that contains more than just technological and logistical aspects can increase the chances of successful UDC deployment in historical cities, mainly in Brazil where the use of those alternative vehicles is still at the beginning. In light of the CSR, some initiatives such as these may affect the core business (carriers, for instance) and lead the companies to achieve their sustainability goal, for instance by balancing residents’ requirements, land use policies and other local policies (municipality), and profit in their business practices (Wesselink, Blok, van Leur, Lans, & Dentoni, 2015). Even though retailers and carriers are in the group called “professionals” because they act directly in freight transport (Quak, 2008; Taniguchi et al., 2003; Yanqiang, 2014), they did not present any similar factor considering all variables into their factors. These results provide implications for the public authorities that fail in urban planning because they do not consider the viewpoint of all of the groups involved and focus only on basic regulatory rules or urban mobility or companies (Ballantyne et al., 2013), also for business practitioners who pay attention only to operational and economic aspects. However, there is a consensus among all the agents that the most important factor was related to the preservation of historical buildings. This concern shows how important the system is with respect to the corporate responsibility to protect the city heritage. The Brazilian government faces problems in terms of investing in renovations, creating laws for the long term, planning and structuring proposals for the private sector to invest in maintenance and preservation initiatives for historical sites. Maybe there is an inefficiency in managing plans, as well as consolidating practices that are contrary to international experience as they deconstruct the universal outstanding values that motivated the will to preserve buildings of the past (Brasileiro & Dangelo, 2017). The laws in Ouro Preto are necessary, or maybe not sufficient to preserve the heritage, due to the lack of land use controls for protecting historical areas. For instance, the current law focuses on limiting the times or areas limitation for heavy vehicles. There is poor or not enough signalling for freight vehicles and not enough bays for parking or loading/unloading for freight vehicles. So far, the city has not registered any company within the program created to control access to the areas of circulation in special zones or time window. Using non-motorised or light vehicles, and off-peak deliveries could be

combined with UDC solution (Gatta, Marcucci, Site, Le Pira, & Carrocci, 2019). The criteria for implementing a UDC, suggested by this research, may encourage policymakers with regards to preserving its cultural heritage and provide the community with opportunities to increase the local prosperity. This result also points to the need to integrate urban land use and heritage policies in historical cities. That is, there is clearly a need for urban logistics planners and policymakers to take a special look at the preservation of the historical centre, considering the conflicting interests of the different agents (Muñuzuri et al., 2005; Zhou & Wang, 2014). The starting point would be to establish appropriate laws for UFT regarding preservation of heritage encompassing the municipality, local society and companies. The responsibility policies, programs, and practices should be enacted by the local society involving all stakeholders (Matten & Moon, 2008; Nocera & Cavallaro, 2017). For the area of research, this study also contributes to a new look at other aspects to be considered in the implementation of a UDC, such as the effect that cargo transport can cause on the urban landscape and the preservation of the historical buildings. The UDC literature highlights economic and political aspects (Danielis, Rotaris, & Marcucci, 2010; Nordtømme, Bjerkan, & Sund, 2015.; Paddeu, Parkhurst, Fancello, Fadda, & Ricci, 2018), but have still neglected evaluating environment and social aspects inside CSR, mainly studies regarding historical cities. It is hoped that the presented results can be used as a basis for future discussions concerning the design of urban logistics planning not only in the historical centre of Ouro Preto, but also in other historical cities such as Salvador, Diamantina and Olinda (Brazil), Porto (Portugal), and others. The results can be used together with a financial feasibility study to search for the direct implementation of UDCs or pilot projects. As a result, cities will have their historical centre preserved and adapted to the current needs of retailers without changing characteristic values. Although our research provides suitable statistical results and methods and achieves proposed objectives, we must recognise some limitations, both related to the sampling. The first limitation is concerning the number of variables used in the analysis. We grouped variables (factors) encompassing a limited number of variables. Maybe some important researched variables could add relevant information regarding the implementation of UDC according to some actors. However, the good results come from the same variables (almost all of them) perceived by all actors, how they experience the logistic solution differently. The second limitation refers to the low number of questionnaires applied to the carriers, which forced the exclusion of a greater number of variables in FA. The lack of knowledge of the population of carriers does not allow a statement that the data of this agent represents a true sample of the city. Future researchers could investigate how companies explicitly incorporate and communicate their CSR and social responsibility strategy in depth, mainly small companies that act locally. Brazilian emerging market enterprises (EMNEs), which operate in an international market, may be able to inspire local companies because these multinational companies adopt sustainable practices that help them incorporate CSR. Acknowledgements None.

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Appendix A Table A1

Descriptive analysis Source: Adapted from Carvalho et al. (2019). Code

V1 V2 V3 V4 V5 V6

V7 V8 V9 V10 V11 V12 V13

Variable/ Criteria

Aspect

Parking spaces Congestion Professional qualification Vehicle size Local prosperity Insecurity

Shaking of the architectural heritage Depletion of buildings by collision Air pollution level Visual intrusion level Noise nuisance level Use of alternative powered vehicle Compliance with legislation

Residents

Retailers

Carriers

Main authors

Mode

1Q

Median

3Q

Mode

1Q

Median

3Q

Mode

1Q

Median

3Q

O

1

1.00

1.00

2.00

1

1.00

1.00

2.00

1

1.00

1.00

1.00

O

1

1.00

1.00

2.00

1a

1.00

2.00

5.00

5

2.00

4.00

5.00

O

1

1.00

1.00

2.00

1

1.00

1.00

3.00

1

1.00

2.00

5.00

O Ec

1 1

1.00 1.00

1.00 2.00

1.00 2.00

1 1

1.00 1.00

1.00 1.00

1.00 2.00

1 1

1.00 1.00

1.00 1.00

1.00 2.00

S

1

1.00

2.00

2.00

1

1.00

2.00

5.00

5

1.00

4.00

5.00

C

1

1.00

1.00

1.00

1

1.00

2.00

2.00

2

1.75

2.00

5.00

C

1

1.00

1.00

2.00

1

1.00

1.00

3.25

1

1.00

2.00

5.00

-

E

1

1.00

1.00

2.00

1

1.00

1.00

2.00

1

1.00

2.00

4.00

E

1

1.00

1.00

2.00

1

1.00

2.00

4.00

5

1.00

2.00

5.00

E

1

1.00

1.00

2.00

1

1.00

3.00

4.00

5

2.00

4.00

5.00

E

1

1.00

1.00

2.00

1

1.00

2.00

3.00

1

1.00

2.00

4.25

E

1

1.00

1.00

1.00

1

1.00

1.00

4.00

5

2.00

4.00

5.00

Quak (2008), Reys et al., (2008), Rao et al. (2015) Iphan (2014), Quak (2008), Reys et al. (2008), Zarinato (2008), Rao et al. (2015) Anderson et al. (2005), Gonzalez-Feliu (2008), Quak (2008), Gonzalez-Feliu and Morana (2010), Rao et al. (2015) Allen et al. (2007), Ville et al. (2010), Browne et al. (2011), Allen et al. (2012), Giuliano et al. (2013) Agrebi et al. (2015), Rao et al. (2015)

Zunder and Marinov (2011), Awasthi and Chauhan (2012), Brasileiro et al. (2015) Gonzalez-Feliu (2008), Kin et al. (2016), Gonzalez-Feliu and Morana (2010) European Comission (2000), Henriot et al. (2008) Browne et al. (2005), Browne et al. (2007 Russo and Comi (2010) Anderson et al. (2005), Gonzalez-Feliu and Morana (2010), Awasthi and Chauhan (2012), Agrebi et al. (2015), Kin et al. (2016) Azevedo and Patrício (2001), Resende et al. (2011)

1) Research question: The following items are related to the implementation of a UDC in Ouro Preto. Please indicate your agreement level in each one:1 – Strongly Agree; 2 – Somewhat agree; 3 – Neither agree nor disagree; 4 – Somewhat disagree; 5 – Strongly disagree. Note: 1Q and 3Q are first and third quartile, respectively Note 2: E (Environmental); Ec (Economic); S (Social); O (Operational); C (Cultural)

Table A2

Extracted Factors for agents Extracted Factors for Residents Variables

Factor F1Re

V8 V7 V10 V4 V11 V3 V2 V12 V9 V6 V1 V5

Communalities F2Re

F3Re

F4Re

.864 .788 .667 .656 .247 .059 .210 .252 .144 .363 .095 -.147

.134 .050 .243 .155 .710 .660 .633 .093 .228 .354 .173 -.034

.042 .159 .177 .097 .146 .219 -.029 .790 .730 .238 -.226 .454

.133 .209 -.082 -.168 -.256 .176 .331 .060 -.060 .358 .713 .702

Explained cumulative variance (%)

21.649

35.502

48.919

60.915

Cronbach’s alpha (0-1)

0.779

0.537

0.563

0.440

.784 .692 .543 .492 .652 .518 .556 .700 .610 .442 .599 .722

KMO = 0.796

Extracted Factors for Retailers

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Table A2 (continued) Extracted Factors for Residents Variables

Factor F1Re

Variables

F2Re

F3Re

F4Re

Factor F1Rt

V8 V7 V11 V12 V10 V5 V6 V2 V1 V4 V3

Communalities

Communalities F2Rt

F3Rt

F4Rt

.874 .840 .559 .148 .448 -.249 .023 .335 -.061 .335 .163

.067 .160 .052 .834 .636 .573 .257 -.021 -.057 .286 .397

.119 .092 .453 -.003 .205 .356 .782 .743 .098 -.182 .393

-.081 .251 .118 .054 .041 .230 .036 .021 .856 .614 .561

Explained cumulative variance (%)

21.123

37.232

53.210

67.443

Cronbach's alpha (0-1)

0.770

0.594

0.620

0.560

.790 .803 .534 .721 .649 .570 .680 .665 .749 .604 .653

KMO = 0.743

Extracted Factors for Carriers Variables

Factor F1Ca

V7 V8 V6 V10 V11 V12 V1 V4 V2 V3

Communalities F2Ca

F3Ca

F4Ca

.866 .769 .672 .657 .170 .273 -.065 .286 .576 .110

.237 .414 .029 .266 .820 .802 .074 .267 -.077 .191

-.026 -.004 .253 .036 .115 .169 .860 .759 .078 .040

.023 -.079 .200 .114 .171 .025 .274 -.281 .502 .841

Explained cumulative variance (%)

27.581

44.917

59.224

71.248

Cronbach’s alpha (0-1)

0.806

0.709

0.541

0.401

11

.807 .770 .557 .517 .744 .746 .825 .807 .596 .757

KMO = 0.735

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Fig. A1. Factor loadings of the four generated factors for each agent.

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