Defining Newtown user satisfaction in a shopping mall

Abstract

Purpose

The purpose of this paper is to examine the user satisfaction dimensions at the Newtown Junction shopping mall to improve its performance.

Design/methodology/approach

Users of the Newtown Junction shopping mall were surveyed and the results were analysed using mean scores, principal components and regression analysis.

Findings

The study identified user satisfaction dimensions as “facilities management”, “design using Newtown principles”, “cultural transmission”, “utility functionality”, “accessibility”, “human factors” and “hotel access”. The dimensions extracted using principal component analysis were better predictors of performance than those of the literature.

Research limitations/implications

The study sample is from the Newtown Junction Mall in the Newtown precinct, Johannesburg, South Africa. The results may not be generalisable to all Newtown shopping malls.

Practical implications

The results will be useful for improving the marketing and operations of shopping malls in similar Newtown in South Africa. A Newtown shopping mall is more attractive to users who want to learn about African culture actively. In addition, the mall’s design and access to other parts of its mixed-used development, which are major complementary places of interest in the precinct, make it attractive to shoppers and tourists.

Originality/value

There are limited studies defining Newtown dimensions in a shopping mall.

Citation

Adewunmi, Y.A., Ramushu, B. and Nelson, M. (2024), "Defining Newtown user satisfaction in a shopping mall", Journal of Corporate Real Estate, Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/JCRE-09-2023-0040

1. Introduction

The Newtown precinct and design movement have their roots in social principles of the proletariat to specific events in a structured and clean environment (Preston, 2006). A Newtown is a “town that emerged and built from free land or on a settlement smaller in size that followed an established plan and supervised by professionals” (Panait, 2013). It has a policy-driven Greenfield development approach (Xu, 2022). “The dimensions of Newtown are spatial, social and economic”, similar to any village or town (De Klerk, 2007, p. 8) and shows a practical belief in the social upliftment of people through improved living and working environments. South Africa has many Newtowns, influenced by the international Newtown movement (Brockett, 1996). Most of these are products of mining industry activities and large industries. Newtown attract global attention because of their economic growth and formal urban design. They should be infused with concepts such as sustainability, inclusion, resilience, local culture and stakeholder participation, including its shopping mall centres (Provoost, 2014). The Newtown Junction precinct in Newtown, Johannesburg, was created to promote a dynamic culture for anti-apartheid goals (Minty, 2018).

South Africa has the sixth-highest number of shopping malls worldwide. The average size of shopping malls has gradually increased since the 1990s as developers want larger spaces to increase their sphere of influence. These developments resulting partly from globalisation, have attracted many international brands to the country, creating an opportunity for increased retail space (Masojada, 2021). As companies evolve with focus on the in-store product mix and disciplines in the retail industry (Masojada, 2021), the attractiveness of these spaces within different contexts becomes valuable.

User satisfaction is a complex and subjective concept. There are varied opinions and definitions of user satisfaction and different measurement criteria; thus, concisely defining user satisfaction and its variables is difficult (Huber et al., 2014). This research adopted the ISO (2018) 10,004 definition of user satisfaction, which is the perception of the degree to which the customer’s expectations have been fulfilled.

Newtown Junction Mall, Johannesburg, had complaints from tenants regarding a lack of consultation with stakeholders regarding engagement and problems with differences in the organisational cultures of tenants and those managing the mall. Therefore, retail operators and stakeholders are unable to understand the needs of shopping mall users (Minty, 2018). Previous research in retailing and user satisfaction examined the dimensions of user satisfaction. These dimensions are physical appearance, air quality, toilets, internet, support services, parking, information desk and design (Olushola, 2018; Ong et al., 2022; Jung and Abdelaziz Mahmoud, 2023 and Büyükşahin, 2023). Dimensions include sound, temperature, lighting and distance (Du et al., 2020). Tannor et al. (2022) focused on the management dimensions of outsourced facilities in conventional shopping malls.

From the Newtown perspective, studies on user satisfaction, such as Mbhiza's (2013), are based on the precinct and the perspective of tourists. Motivations to visit the precinct include education, socialising, safety and security, accessibility entertainment and relaxation. A study by Tsang et al. (2014) was on tourists and found personal development, learning development, prestige, safety, enjoyment, relationship and novelty were dimensions of user satisfaction in a shopping mall. Users' perceptions of the physical attributes of the mall affect social relations (Farahani et al., 2022). Cheung (2023) studied symbolic meanings and shopping malls and proposed that studies consider other stakeholders and the management of shopping malls. This study aims to fill the gap by examining the dimensions of Newtown user satisfaction from the perspectives of shoppers and their management. The Newtown Junction Mall is located in the Newtown precinct, a mixed-use development in Newtown, Johannesburg, South Africa.

2. Dimensions of user satisfaction in shopping malls

2.1 User satisfaction studies in shopping malls

Due to changing user requirements, shopping malls have grown in number and size, with increasingly convenient locations for service businesses and tenants that provide entertainment. With a shift to the experience economy, trends have moved from functionality to creating user experience (Cillo, 2016). They may include extra space for businesses. These mixed-use retail buildings serve as significant locations for events, for young people and the elderly (Ahmed et al., 2007).

Previous studies examined user satisfaction in shopping malls (e.g., the UK, USA, Europe, South Africa, Nigeria and Ghana). A review of the criteria used in determining user satisfaction in shopping malls (Table 1) had few studies focusing on measuring user satisfaction from the Newtown perspective.

The consolidated criteria for performance in a Newtown shopping mall include: “design”; “public spaces”; “facilities”; “socialising”; “culture and heritage”; “environment”; “accessibility”; “entertainment”; “inclusive shopping”; “communication”; and “friendliness of staff” (Table 1). These principles are found in other malls but the combination may differ in these malls. The principles apply to Newtown Junction in South Africa and form the basis of the analysis. This study aimed to identify the criteria that are the best predictors of performance in a Newtown shopping mall.

3. Theoretical framework and literature review

3.1 Theoretical framework

Oliver (1980) described the disconfirmation theory happening when customers compare a new service experience with a standard they have established. The theory assumes that customers make purchases based on their expectations, attitudes and intentions, later, during or after consumption; perception of performance happens when customers evaluate the experience.

The process can be completed when “users compare the actual performance of a service with an expectation that can be regarded as pre-experience” (Mill, 2002). The resulting outcome is confirmation, satisfaction or dissatisfaction. This theory comprises four dimensions: expectations, perceived performance, disconfirmation and satisfaction (Mill, 2002).

To measure customer satisfaction, disconfirmation is difficult to implement (Cronin and Taylor, 1992) due to the difficulty in defining “expectations”, continual customer expectation adjustment and the complete removal of the gap between expectations and customer familiarity with the service. Empirical investigations of the assessment of factors identified the best construct for explaining differences in customer satisfaction is perceived performance (Nair, 2018; Oeser et al., 2019). The setting and their individual and collective experiences determine how experiences vary. In the context of FM in buildings, Ikediashi et al. (2015) defined user satisfaction as “the product of an evaluative process measures what is received by users against what they expected”. This research assumes that changes in consumer satisfaction with shopping malls are based on individual satisfaction, which may result in a distinctive aggregate satisfaction (Anselmsson, 2006). Therefore, this study defined satisfaction as the performance of services to dynamic and diverse users in Newtown Junction shopping mall.

3.2 Newtown Developments in South Africa

In response to the 1990s migration of “big business” to Sandton, North Johannesburg, the Newtown Cultural Precinct was one of the government's primary attempts (Shand, 2011) to improve Johannesburg's inner city, led by a decline in urban management and land use regulations. The government adopted a culture-led urban regeneration strategy via the public sector’s massive capital expansion to encourage sustainable urban redevelopment and stop the stream of wealth from leaving the city core. In rebuilding Johannesburg's inner city, distinct change processes focused on Newtown Junction, namely, urban culture, business, the urban real estate cycle and politics. The Market Theatre opened in 1976 and is responsible for Newtown Junction as a cultural district. The following key performance indicators (Newtown Principles) were used to measure Newtown Junction's performance:

• heritage and architecture;

• infrastructure;

• sufficient quantity of viable cultural organisations training and production;

• clustering;

• visitors;

• day- and night-time offering/opening;

• marketing;

• public space;

• funding and sustainability; and

• economic regeneration.

3.3 User satisfaction dimensions in Newtown shopping malls

Newtown shopping mall’s user satisfaction dimensions were derived from consolidated themes emerging from the literature. This study determined the users' experience by their satisfaction with different mall attributes as follows:

“Perception of customers”: Users' perceptions about the quality of their environment may differ from those of the shopping mall and vary from one user to another, subject to age and gender (Baker and Wakefield, 2012). User satisfaction is linked to patronage in retail spaces (Nair, 2018), with previous research on Newtown's retailing focusing on tourists' motivations (Mbhiza, 2013), namely, education, socialising, safety, accessibility, entertainment and relaxation.

“Design of the mall structure”: This should include commercial and public spaces, structures and spatial practices. Shopping malls are relational spaces designed to meet users' demands for new experiences (Hagberg and Styhre, 2013). Design is an essential factor in attracting visitors to the mall (Ortegón-Cortázar and Royo-Vela, 2017). Rashid et al. (2022) found a link between design and user satisfaction in malls in Pakistan. Chen et al. (2023) covered forms and types of designs of American-style malls in China. A study by Pikó (2017) discussed the design of a Newtown shopping mall in the Milton Keynes Shopping Building, UK.

“Social”: Newtown has objectives to encourage a social life with night and day offerings, promoting cultural activities in the mall to encourage people visit the mall and the precinct (Ngwenya, 2018). Malls are places where shoppers interact (Kim and Kim, 2012). Mbhiza (2013) discussed socialising in a Newtown precinct but not within a mall. Social factors could enable customers influence an individual’s attitude towards the retail environment (Kwon and Brinthaupt, 2015).

“Cultural” refers to a society's personality, beliefs and values. The objective is to use culture to regenerate the precinct (Ngwenya, 2018). South Africa's culture is unique and diverse (Breytenbach, 2014). In a shopping mall, users from different ethnic backgrounds can display different shopping motivations (Laroche et al., 2000). The Newtown is a core of cultural organisations (Shand, 2011). Cultural artists in the precinct visit spaces to improve their skills in music, dance, crafts, clothes and fine arts, which have the potential to be in demand in the international marketplace. Tourists are also given cultural training to develop a new identity for South Africa (Preston, 2006).

There are limited studies on the role of shopping malls in cultural transmission, i.e. passing information about culture to people through social platforms such as teaching and imitation, an important part of the culture (Mesoudi and Whiten, 2008). Piko's (2017) study was on the sensory experiences of history. It was not actively learning about culture where learning occurs (Tsang et al., 2014). Artistic elements affect shoppers’ value of the mall (Vukadin et al., 2018). Culture could be from masculinity, avoidance of uncertainty and long-term orientation and it influences retail promotions (Khare et al., 2019). Social, political and technological factors influence customer experiences in retail (Grewal and Roggeveen, 2020).

“Facilities” are needed at shopping malls to attract retailers and ensure users’ satisfaction (Hui et al., 2013). The Newtown precinct has infrastructure that encourages socialising, which can be enhanced through facilities management (FM) (Ngwenya, 2018; Tandon et al., 2016). FM will help the precinct achieve its objectives (Sari, 2018) and managing the infrastructure. Facilities dimension can be measured using satisfaction classifications: tenant management, FM, atmospherics and entertainment (Tandon et al., 2016).

Tanner et al.'s (2022) research on conventional malls used the service quality technique to examine user satisfaction with aspects of FM services, though it is not clear how FM affects mall user satisfaction. Limited literature exist on the management of facilities in Newtown malls. The main differentiator between malls in urban centres and Newtown is that low-income earners initially use malls in Newtown. It may not have top-brand stores but as changes occur in the space of Newtown, it can attract high-income earners and top brands (Rogerson, 2006). Aspects of infrastructure such as security (Ncwane, 2023), environment (Chen and Haron, 2023) and IT (Wang et al., 2016) emerged from studies on Newtown in general, not shopping malls.

“Physical environment” includes the ““appearance”; “layout”; “interior architecture”; “décor”; “lighting”; “music”; “aromas”; and “cleanliness” of the mall (Wakefield and Baker, 1998). It is a determinant of users’ perception. Ginzarly and Teller (2018) assert that the landscape has historical relevance, though its emphasis on external surroundings, did not affect customer behaviour (Hyllegard et al., 2016). The external environment influences user satisfaction regarding psychological health and aesthetics (Ortegón-Cortázar and Royo-Vela, 2017).

“Inclusion” involves spaces arranged to foster community creation (Staeheli and Mitchell, 2006). Malls can be used to promote a sense of community to revitalise spaces in Newtown (Staeheli and Mitchell, 2006 and Mawer and Kiddle, 2021). Edwards et al. (2018) focused on vulnerable groups of shoppers and affirmed that the retail space should cater to all shoppers’ categories.

“Accessibility” is one of the characteristics of a Newtown (Branch, 1983). It refers to the location of the shopping malls and other facilities (Hassanain et al., 2016). Accessibility to transport influences the hierarchy of shopping malls as more people have access to automobiles (Handy, 1993), negatively influencing sustainability due to car emissions (Funsho Idowu et al., 2022). There are links between accessibility and user satisfaction in shopping (Amin et al., 2021; Ong et al., 2022; Jung and Abdelaziz Mahmoud, 2023). Yin et al. (2024) found that accessibility is important in Newtown. Although the Newtown Junction could be linked by the M1 from the Mandela Bridge, the enhancement of access by public transport and taxis is inadequate (Ngwenya, 2018). Also, walking is accessibility (Tao et al., 2023). Limited studies considered accessibility in terms of nearness to places of interest, especially within Newtown shopping malls in Africa.

4. Methodology

4.1 Research approach

Using Saunders et al. (2009) research onion to guide the research methodology, the research philosophy was pragmatism (knowledge based on experience and research starts with a problem), approach was inductive and interpretivist. The strategy was a single case study and a mixed method of research techniques (Kaushik and Walsh, 2019). The cross-sectional case study enabled a challenge to existing relationships in theory to describe the context of Newtown user satisfaction in-depth (Gustafsson, 2017). To do this, a convenience sampling approach (Van Kerrebroeck et al., 2017) of mall users was used. User characteristics and preferences regarding the shopping mall were extracted from the literature review on shopping malls and Newtown. The mall manager was interviewed to provide context for the findings.

4.2 Research techniques

4.2.1 Measurement scale.

It is better to develop scale items when investigating satisfaction; hence, all shopping mall preferences were measured using a five-point Likert scale, from 1 = very dissatisfied to 5 = very satisfied (Parasuraman et al., 1991). The Likert scale assists with obtaining better insights into a set of questions (Batterton and Hale, 2017).

4.2.2 Data collection and analysis.

The questionnaire two sections focused on the users' demographic background and user satisfaction. The second section comprised 25 items on the predetermined satisfaction attributes in Newtown shopping mall (Table 2). These were further grouped into eight satisfaction factors from a thematic analysis of the literature (Table 2). All questions were carefully worded in English and the questionnaire was initially pre-tested on a sample of 40 users. Cronbach’s alpha test for reliability of variance was used to determine the reliability of the questionnaire, with the scores ranking ranging from 0.6 to 0.8. The results suggested that the evaluation instrument (questionnaire) was reliable and had internal consistency in the variables chosen, as the reliability figure obtained exceeded the 0.7 value required in the statistical analysis (Field, 2009). In April 2018, questionnaires were distributed and collected within the mall. Data was analysed using principal component analysis and linear regression.

4.2.3 Population and sampling.

Mall management estimated the number of mall users, the study population, to be 19,000 people per week. A random sample size of 377 was obtained from a sample table for a population of 19,000 users (Krejcie and Morgan, 1970; Akour et al., 2022), out of which 133 were returned, giving a total response rate of 35%. Hendra and Hill (2019) found no significant difference between survey response rates and non-response bias. According to Mustafa (2017), a response rate of not less than 30% was considered adequate and not susceptible to bias. In addition, a sample size of between 100 and 200 is sufficient as long as the communalities are high, factors are properly determined and convergence is obtained (Banerji and Mishra, 2018).

5. Case study

5.1 Survey context

The Newtown Junction shopping mall was part of the city’s plan for urban regeneration (Branch, 1983), with the precinct, the city's cultural heart, having a landscaped public piazza, open event space and pedestrian routes. The site is next to other buildings of cultural significance, including the Market Theatre, Museum Africa, Mary Fitzgerald Square, the M1 highway overpass and the Nelson Mandela Bridge. It has buildings such as the Potato Sheds, Edwardian railway sidings, and smaller heritage buildings such as the Majestic complex, an Edwardian toilet block and Kippie’s Jazz Club, all with historical significance. Newtown Junction was selected as the case study because it was developed on inclusion and anti-apartheid principles (Brockett, 1996). The mall has a spacious layout with several street entrances and car parking, a total area of 38,000 m², with 30,000 m² dedicated to office space. Tenants include Nedbank, a hotel, Planet Fitness gym and over 100 businesses (Figure 1 and Plates 1–2). It incorporates thermal energy storage to facilitate air cooling, with the building awarded a four-star Green rating by the Green Building Council of South Africa (Dhk, 2019).

5.2 Demographic details of participants

The following details were collected from participants for analysis: race, gender, marital status, education, age, frequency of visits and access to the mall (Figure 2). These helped develop user profiles to be measured against satisfaction.

Users’ characteristics were compared with some of the characteristics of the population and shoppers in the area. This showed their diversity (Evanschitzky et al., 2008; Tannor et al., 2022). For example, the results found that the retailers' offerings are more attractive to the young and black segments of the catchment area, supporting Rogerson's (2006) findings on the population in the spatial location of Newtown malls.

5.3 Dimensions of user satisfaction in the Newtown shopping mall, Johannesburg

The user satisfaction dimensions were ascertained through factor analysis. The following statistics were cross-checked using correlation analysis, a variable-wise measure of sampling adequacy, the KMO test of sampling adequacy and Bartlett's test of sphericity (Singh and Prashar, 2014). A significant correlation between many of the variables showed there is an underlying structure in the data. This was supported by the anti-image correlation matrix with diagonal values more than 0.5, revealing sufficient variable-wise measure sampling adequacy.

Reliability for each factor was tested using Cronbach’s alpha (Table 2) with values for all the factors over 0.7, meaning the output is reliable (Singh and Prashar, 2014). The value of the KMO test of sampling adequacy was 0.8, better than the accepted score of 0.5. The calculated value of 1,534.3 at 325 degrees of freedom and a 5% level of significance in Bartlett's test of sphericity revealed that it was suitable for factor analysis.

The principal component analysis reduced 25 variables into seven factors (Table 3). To find a name for each factor, the nature and meaning of all the attributes in each component were examined (Singh and Prashar, 2014).

5.3.1 Factor 1: facilities management.

This factor explained 12.2% of the total variance, comprising five mall attributes: “hours of operation”, “emergency services”, “cleaning”, “Wi-Fi” and “parking”. These variables were correlated with the extracted factor loadings, ranging from 0.5 to 0.79, a grand mean score of 3.96. These attributes were types of facilities and services and aspects of FM (Hui et al., 2013; Tannor et al., 2022). Newtown’s goal is to promote a healthy nightlife (Ngwenya, 2018) but mall users were averagely satisfied with the hours of operation. From the interview, the mall needs improvements regarding marketing, emergency procedures, poor signage, weak Wi-Fi connection caused by the location of the mast and functionality of the information desk. The interview also showed that the form of management of the mall favoured the traditional approach, as it takes time for owners to embrace innovation.

5.3.2 Factor 2: design using Newtown principles.

This factor explained 24.1% of the total variance and included four mall attributes: “physical appearance of the mall”, “façade”, “mall layout” and “circulation spaces”. These variables were correlated with the extracted factor loadings, ranging from 0.6 to 0.87, a grand mean score of 4.16. These attributes were in the design category. The design preserved the important historical features using materials and details similar to the original industrial setting, like steel and bricks. Modern glass pieces in large sizes were used to balance out these elements. Although the survey showed that users were satisfied with the mall's design, the interview identified satisfaction to a broader population than current users is achievable through its architectural design. The design did not embrace artistic, cultural and heritage attributes essential to the vision of the Newtown precinct (Shand, 2011). The selection of the building materials was instead in response to legislative requirements.

5.3.3 Factor 3: culture and heritage transmission.

The third factor explained 35.43% of total variance and includes five mall attributes: “workshop cultural shops and potato sheds”, “Market Theatre”, “open spaces”, “art gallery” and “socialising in the mall”. These variables were correlated with the extracted factor loadings, ranging from 0. 51 to 0.79, the grand mean score being 3.98. These attributes were social factors and satisfaction with heritage organisations with room for improvement in these areas.

5.3.4 Factor 4: utility functionality.

This factor explained 46.45% of total variance with four mall attributes: “lifts and escalators”, “toilets”, “landscaping of the mall” and “information desk”. These variables were correlated with the extracted factor loadings, ranging from 0.5 to 0.77. The grand mean score for this factor was 4.07. These attributes were facilities and the mall environment (utilities).

5.3.5 Factor 5: accessibility.

Accessibility explained 54.31% of the total variance with two attributes: “access to residential homes” and “access to public transport”. These variables were highly correlated with the extracted factor loadings, ranging from 0.73 to 0.82, a grand mean score of 3.98. The interview identified that the building is accessible to private and public transportation. There is also no direct access to Gautrain – trains and the airport. The underground parking is planned and safe, with limited entry points and exit points. Pedestrian accessibility can be challenging due to crime (Ngwenya, 2018).

5.3.6 Factor 6: human factors.

This explained 61.326% of total variance with two attributes: “friendliness of mall staff” and “similarity to other users of the mall”. These variables were highly correlated with the extracted factor loadings, ranging from 0.66 to 0.72, a grand mean score of 3.88.

5.3.7 Factor 7: access to hotels.

The seventh factor explained 65.78% of the total variance with one attribute, “access to hotels”. This variable was highly correlated with the extracted factor loading of 0.86, with a grand mean score of 3.96. The interview showed the mall is part of a mixed-use development with a hotel and offices. This hotel is the major hotel in the Newtown neighbourhood, where people attended meetings and attended events in the precinct. Guests (local and international) also patronise the mall during their stay in the hotel.

5.4 Regression analysis of overall user satisfaction with other dimensions

A linear regression test was used to ascertain the relative effects of the dimensions on overall user satisfaction extracted from factor analysis compared with dimensions extracted from the literature on user satisfaction (Tables 4 and 5).

Table 4 summarises the results for the predictor variables used in the model. The F-statistic was 12.79, with a p-value less than 0.00. The adjusted R square was 41.7%, and the Durbin–Watson value was 1.95 with a p-value of 0.000. A non-significant Durbin–Watson p-value indicates a lack of autocorrelation, implying independence of errors. A significant p-value for the Breusch Pagan test (0.015) suggests heteroscedasticity. The variance inflation factor for each predictor was below five, suggesting low multicollinearity among the predictor variables. The results in Table 4 imply that design using Newtown principles (p = 0.048), utility functionality (p = 0.001) and accessibility (p = 0.000) are dimensions of user satisfaction that have a relative effect on user satisfaction.

Table 5 summarises the results for the predictor variables used in the model. The F-statistic was 11.42, with a p-value of 0.000. The adjusted R square was 38.7%, and the Durbin–Watson value was 1.7, a p-value of 0.06. A non-significant Durbin–Watson p-value indicates a lack of autocorrelation, which implies independence of errors. A non-significant p-value for the non-constant variance test (0.21) and for the Breusch–Pagan test (0.68) suggests that the variance of the error terms is constant (homoscedasticity). The variance inflation factor for each predictor was below five, suggesting low multicollinearity among the predictor variables.

The results (Table 5) imply that design (p = 0.008), accessibility (p = 0.006) and environment (p = 0.0005) are Newtown dimensions from the literature that have a relative effect on user satisfaction.

The dimensions extracted through principal component analysis are partly similar to those extracted from the literature and the principal component analysis dimensions had a greater impact than those extracted from the literature from the adjusted R square value, suggesting they better defined user satisfaction in the Newtown Junction mall.

6. Theoretical contribution

The study focused on the Newtown user satisfaction dimensions in a retail setting. Some of the themes that emerged from the literature on user satisfaction in conventional shopping malls include physical attractiveness, air quality, restroom facilities, internet access, support services, parking, sound, temperature, design lighting, distance, information desk, branding, comfort, aesthetics, convenience, mall environment, value, accessibility and support services (Olushola, 2018; Du et al., 2020; Ong et al., 2022; Jung and Abdelaziz Mahmoud, 2023, Adeola et al., 2023; Büyükşahin, 2023). Du et al. (2020) examined the relationship between indoor air quality and green buildings. Factors such as the availability of pedestrian space, green landscape, accessibility to the surrounding environment, quality of parking services and safe access significantly impacted user satisfaction (Jung et al., 2022).

In addition, themes that emerged from studies on the Newtown precinct in general included opportunities for education, social interaction, safety and security, accessibility, entertainment and leisure (Tsang et al., 2014; Mbhiza, 2013). Emerging themes from research on Newtown shopping malls were personal growth, learning development, prestige, safety, satisfaction, interaction and novelty, which were the key factors contributing to user satisfaction at a mall (Tsang et al., 2014). FM was also a key dimension, as mall management helps in shaping user satisfaction and achieving the goals of the Newtown precinct. FM in Newtown Mall included customer service and improving the operational hours, by providing various offerings and services during the day and night. Another aspect to consider was the architectural design of the mall using Newtown principles.

This study identified “cultural transmission”, “human factors” and “access to hotels” as unique sources of user satisfaction in a Newtown Junction mall. The mall had spaces where people learned about the culture. “Human factors”, according to Kim and Kim (2012), include influences of shoppers and salespersons on the mall environment. This study further examined the influence of other mall staff, such as “facilities staff”, important for managing the mall to enhance user satisfaction. “Hotel guests have defined hotel accessibility” in general as access to places of interest such as tourist attractions, entertainment centres and the neighbourhood (Yang et al., 2018). “Hotel accessibility” in the Newtown precinct, however, is the access of mall users to places of temporary residence or meeting places close to or part of the mall.

7. Managerial implications

Newtowns should prioritise the “design of the mall” and the “facilities” and market their uniqueness. Chebat and Morrin (2007) found that mall decor, in terms of colour, influences users’ perceptions of the mall. Other design aspects of culture were outside the scope of their study. Younger, black and middle-class users were found to be the main users of Newton Junction mall, in line with the area’s demography of mostly black residents. This is to be expected in a Newtown Mall (Rogerson, 2006). Marketing strategies should be developed to attract other population segments. Products and services that can attract a more diverse population should be part of the mall's product offerings. “Cultural transmission” can attract more tourists to the mall and international users interested in African culture (Ngwenya, 2018). It is also essential to ascertain the performance of all mall staff through customer surveys.

The utility functionality, part of the FM function (Tannor et al., 2022), significantly affects user satisfaction. Though utility performance was good, there was room for improvement. Management should improve on socialising and entertainment offerings, consider creative ways to determine the possible entertainment options, and match them with different segments of the population that visit the mall or are potential visitors. Complementary services such as Wi-Fi, information desk and getting information through short surveys on visitors’ phones were examples of improvements. The environmental performance of the mall could be improved by greening (Du et al., 2020).

External factors also influence the performance of malls and impact on user satisfaction. For example, the mall’s hours of operation and timing of entertainment offerings can be extended when the security infrastructure in the neighbourhood is improved. Calvo-Porral and Lévy-Mangín (2018) believed that accessibility is closely related to a shopping mall’s location and convenience. Accessibility to public transport, such as access to Gautrain trains, can be improved to attract diverse users including tourists. Accessibility can be improved if security is improved through the collective efforts of the government, the mall operators and the community (Ngwenya, 2018). Mall operators and hotel owners should use collaborative marketing strategies to market their products and services and attract more people to the precinct, enhancing hotel accessibility. Future Newtown shopping mall developments can use complementary developments to attract users.

8. Conclusion

The research focussed on variables specific to the context of the Newtown Junction shopping environment and found the mall's user satisfaction dimensions to be: “facilities”, “design”, “cultural transmission”, “accessibility”, “human factors” and “access to hotel”, indicating that these are unique dimensions of user satisfaction within a Newtown retail mall. “Human factors” were inclusive of all mall employees. The factors from the principal component analysis showed a greater impact than factors from literature. This implies that developers and managers need to focus on the former to improve user satisfaction in this mall. More emphasis should be placed on the utility functionality and accessibility of the shopping mall to a wider range of shoppers and transportation.

The user satisfaction measures in retail settings can be imperfect and complex making it difficult to measure user satisfaction because of the diverse activities and responses of users who exhibit different behaviours at different times (Evanschitzky et al., 2008). The research had a limited sample, as the case study was restricted to a particular Newtown mall. Future studies can cover more than one mall and a larger sample (Evanschitzky et al., 2008). Also, each dimension of user satisfaction can be studied. Future studies could focus on longitudinal studies in Newtown-style retail settings or community participation in the security of Newtown Shopping malls. Although the research was conducted in Johannesburg, future research can be conducted on Newtown-style shopping malls in other cities and countries. Results may also be generalised to other Newtown shopping malls built on inclusion and anti-apartheid principles.

Studies can also compare Newtown shopping mall dimensions with traditional bazaars or souks, which are economic, cultural, religious, social and sometimes political centres for communities.

Figures

Figure 1.

Layout of the Newtown Junction mall (Centre Management, Newtown Mall)

Figure 2.

Demographic details of participants

Plate 1.

Newtown Junction Shopping mall

Plate 2.

Newtown Junction mixed use development

Table 1.

Literature themes on user experience criteria for shopping centres

Authors	Physical appearance	Façade	General layout	Circulation spaces	Wayfinding	Sound	Signage	Air quality	Temperature	Lighting	Lifts	Toilet	Landscape	Information desk	Internet/ICT	Price	Brands	Operation hours	Emergency services	Support services	Socializing	Marketing	Healthy living	Disabled facilities	Friendliness of staff	Family needs	Entertainment	Parking	Accessibility	Distance	Sustainability
Wakefield and Baker (1998)	X		X
Hui et al. (2013)												X								X		X			X
Dubihlela and Dubihlela (2014)	X		X	X																							X		X
Breytenbach (2014)
Kwon and Brinthaupt (2015)																					X
Tandon et al. (2016)			X	X		X								X						X
Toe (2016)
El-Adly and Eid (2016)	X							X
Calvo-Porral and Lévy-Mangín (2018)								X						X
Olushola (2018)	X							X	X			X			X					X								X
Lucia-Palacios et al. (2020)																X	X			X	X				x X
Du et al. (2020)						X		X	X	X																					X
Amin et al. (2021)																							X		X				X		X
Tannor et al. (2022)													X	X						X								X
Mayhoub and Rabboh (2022)		X
Ong et al. (2022)	X													X			X	X		X	X		X		X	X			X
Jung and Abdelaziz Mahmoud (2023)	X																				X								X
Adeola et al. (2023)	X		X													X	X	X			X				X		X	X
Büyükşahin (2023)	X		X	X

Source: Authors’ creation

Table 2.

Newtown factors

Factor no.	Factor title	The mean score of variables concerned with mean scores	Average mean scores	Cronbach alpha
F1	Facilities management	Hours of Operation (F) (3.74)	3.96	0.709
		Emergency services (F) (3.9)
		Cleaning (F) (4.19)
		Wi-Fi (F) (3.8)
		Parking (A) (4.19)
F2	Design	Physical appearance of the mall (D) (4.41)	4.16	0.730
		Façade of the mall (D) (4.03)
		Mall layout (D) (4.08)
		Circulation spaces (D) (4.11)
F3	Cultural transmission	Workshop cultural shops and Potato shed (C) (3.96)	3.98	0.706
		Market theatre (C) (3.96)
		Open spaces (P) (4.02)
		Art gallery (C) (3.87)
		Socialising (S) (4.09)
F4	Utilities functionality and facilities management	Lifts and escalators (F) (4.17)	4.07	0.708
		Toilets (F) (4.11)
		Landscape (E) (4.17)
		Information desk (F) (3.83)
F5	Accessibility	Access to residential home (A) (3.94)	3.98	0.740
		Access to public transport (A) (4.02)
F6	Human factors	Friendliness of all mall staff (F) (3.89)	3.88	0.717
		Similarity to other users (I) (3.86)
F7	Access to hotel	Access to the hotel (A) (3.96)	3.96	0.749

Notes:

1. Variables from literature: Design D; Social S; presence of cultural organizations C; Facilities F, environment E; Public spaces P; Inclusion I; and Accessibility A.

2. Unloaded factors of the PCA: satisfaction with potato shed and security

Source: Authors’ own creation

Table 3.

Total variance

Component	Initial eigenvalues			Extraction sums of squared loadings			Rotation sums of squared loadings
	Total	% of variance	Cumulative %	Total	% of variance	Cumulative %	Total	% of variance	Cumulative %
1	7.505	28.864	28.864	7.505	28.864	28.864	3.174	12.206	12.206
2	2.744	10.553	39.417	2.744	10.553	39.417	3.092	11.891	24.097
3	1.806	6.947	46.364	1.806	6.947	46.364	2.945	11.328	35.425
4	1.545	5.941	52.305	1.545	5.941	52.305	2.867	11.026	46.451
5	1.336	5.140	57.445	1.336	5.140	57.445	2.043	7.859	54.311
6	1.130	4.347	61.793	1.130	4.347	61.793	1.824	7.016	61.326
7	1.037	3.987	65.780	1.037	3.987	65.780	1.158	4.453	65.780
8	0.945	3.635	69.415
9	0.801	3.080	72.495
10	0.780	2.998	75.493
11	0.727	2.798	78.291
12	0.657	2.525	80.816
13	0.588	2.261	83.077
14	0.547	2.103	85.180
15	0.532	2.046	87.226
16	0.485	1.867	89.093
17	0.455	1.751	90.844
18	0.404	1.555	92.400
19	0.397	1.525	93.925

Source: Authors’ creation

Table 4.

Predictor variables from the survey

	Estimate	t-value	p-value
Constant	0.430	0.286	0.775
Facilities management	0.021	−0.001	0.999
Design	0.026	1.999	0.048
Cultural transmission	0.021	0.918	0.360
Utilities functionality and facilities management	0.029	3.436	0.001
Accessibility	0.040	3.609	0.000
Human factors	0.053	1.500	0.136
Access to hotel	0.044	1.528	0.129
Unloaded factor	0.062	−0.100	0.921

Note:

Authors’ creation

Table 5.

Predictor variables from the literature

	Estimate	t-value	p-value
Intercept	0.280	0.631	0.529
Design	0.240	2.696	0.008
Social	0.001	0.007	0.994
Cultural	0.041	0.321	0.749
Facilities	0.120	0.872	0.384
Environment	0.283	3.566	0.0005
Public spaces	0.077	0.988	0.325
Inclusion	−0.049	−0.556	0.579
Accessibility	0.212	2.78	0.006

Source: Authors’ creation