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Social Media Marketing Attributes, Sandton’s Rental Market Brand Image, and the Millennials’ Rental Preference: An Empirical Study

Social Media Marketing Attributes, Sandton’s Rental Market Brand Image, and the Millennials’... A good image of millennials’ residential rental space is an important issue. This image can be impacted by the available telecommunication technology. Social media marketing can, therefore, be an important marketing tool to achieve it. Many studies have shown that a good brand image positively impacts brand preference. This study quantitatively investigated the impact of social media attributes of trendiness, entertainment, customization, information, interaction on Sandton’s rental market’s brand image, and the relationship between this image and millennials’ rental preference. Data were collected from millennials who have lived, live or intend to live in Sandton. Structural equation modeling was employed for data analysis. The findings of the study are that entertainment, customization, and information positively impact Sandton’s image and that trendiness and interactions do not. Also, the image of Sandton’s rental market has a positive influence on the millennials’ preferences as to rental housing. The outcomes will find application for both academics and management practice as will be shown below. Key words: Millennials, Social media marketing attributes, Sandton rental housing brand image, Sandton rental housing brand preference. JEL Classification: M31; M37; O18; O35. Citation: Nhlabathi, M., Mgiba, F.M., & Ligaraba, N. (2022). Social media marketing attributes, sandton’s rental market brand image, and the millennials’ rental preference: an empirical study. Real Estate Management and Valuation, 30(1), 34-52. DOI: https://doi.org/10.2478/remav-2022-0004 1. Introduction The world is characterized by rising housing costs (Galesetr & Gyourko, 2018), which in turn limits homeownership among people (Sissons & Houston, 2019). The situation is further complicated by the REAL ESTATE MANAGEMENT AND VALUATION, eISSN: 2300-5289 vol. 30, no.1, 2022 www.degruyter.com/view/j/remav volatility of housing markets (Chang, 2020; Wang et al., 2020). These issues change the accessibility of housing for new entrants, and therefore have implications for the residential real estate markets. The impacts are even more severe for the millennials (Mulyano et al., 2020) because this group’s attitude towards housing is affected by special drivers (Mishra et al., 2020). Before further elaborating on millennials and their relationship with the residential housing markets, it is prudent to describe this group of people. Different periods of birth are attributed to millennials. For example, they are seen as people that were born between 1999 and 2002 (Blair, 2017). Deka (2018), on the other hand, defines them as persons born in the 1980s and 1990s. It is generally accepted, however, that these people were born during a time of rapid internet and technology growth (Blair 2017). It is the first generation to grow up surrounded by digital media, people who consider computers and mobile phones to be essential tools for many activities (SanMiguel et al. 2018), who are accustomed to buying and socializing online (SanMiguel et al., 2018). Due to their easy access to technology, a case can be made for the use of technology by housing brands to target this segment (Öztürk & Batum, 2019). They also have unique characteristics in terms of easy access to social media and the usage thereof (Vitelar, 2019), their liking of interactive brand communications (Atthwal & Istanbulluoglu, 2019), their brand preferences on many products and services (Longo & Saxena, 2020; Ali &Alyani, 2019), bias towards customized products and services, and their fondness of products and services that are trendy (Hassanzadeh & Namdar, 2018; Pandey et al., 2018). These are some of the constructs that define millennials. A legitimate question would be whether these special traits can also be profitably harnessed by the rental housing industry, especially for a developing country like South Africa? If yes, can a permutation of these constructs lead to brand preference and possible e-word of mouth marketing opportunities? According to Circella et al. (2017), there is still a lack of comprehensive data on the factors affecting millennials’ choices of residential location. Their housing unit preferences present enormous scope for further academic exploration. In general, people’s preference indicators for residential areas are location, accessibility, price, physical attributes, facilities, design aesthetics, and developer reputation (Mulyano et al., 2020). However, these people have different lifestyles (Circella et al., 2017), are more prone to rent a property than to buy it (Godelnik, 2017), and are more likely to relocate to high-wage and high-productivity areas (Blake, 2019; Glaeser & Gyourko, 2018; Li, 2020). Their unique consumption behavior is the most probable cause behind the increased rental demand throughout the world. In the light of these trends, this group deserves special academic scrutiny. Further, Sandton, as a sought-after place to rent property, provides an attractive setting for this study. Sandton is the richest square mile of land on the African continent (Laughton et al., 2015). It is the home to the Johannesburg Stock Exchange (largest stock market in Africa), head office to most of Africa’s largest banks and corporates (Africa’s wealth report 2021). It is a modern city gleaming with high-rise architecture, retail outlets, modern hospitals, and clean residential areas (Kelleher, 2018). As a city, it attracts representatives of world capital and skill (Lahire, 2008). Sandton epitomizes consumption, affluence and power. Its’ network of malls, restaurants, nightclubs, and hotels offers the possibility of conspicuous consumption. Sandton also contains one of Africa’s most advanced transport systems, exemplified by the Gautrain (Arnold et al., 2017). Its’ nature and character can be a magnet that attracts upwardly mobile millennials. There is, generally, a decline in homeownership amongst working-class people (Aramburu, 2015). Across the world, 1.2 billion people live in rented accommodation (Gilbert, 2016). Millennials form a big chunk of that figure, as will be shown below. In some countries, their share of the population ranges between 25% and 27%. Their motivation towards choices of rented dwellings becomes an attractive academic pursuit. When people choose rental housing units, dwelling-related factors, such as unit size, or the number of rooms and bathrooms have an impact on their decisions. However, Kam et al., (2018) state that neighborhood attributes have a greater impact on people’s housing selections. With the increased mobility of millennials to urban areas (Nethercote, 2020), do these factors still hold true, even for this market, or are there other factors that only apply to them? As shown above, for the millennials, the internet and social network sites have become important communication media (Taylor & Keeter, 2010). Further, rental housing transactions are moving online as the internet offers divergent possibilities (Boeing, 2020). The birth of Social media marketing has ushered in many possibilities. According to Schmidtke et al. (2021), SMM interventions produce positive outcomes for business. Can the advent of social media marketing (SMM) be harnessed to effectively target the millennials in the rental housing market? There is generally a dearth of literature that devotes attention to this specific REAL ESTATE MANAGEMENT AND VALUATION, eISSN: 2300-5289 vol. 30, no. 1, 2022 www.degruyter.com/view/j/remav generation’s motivations when deciding on rental housing neighborhoods. This study was conceptualized in response to this gap. The purpose of the study was to investigate the possible effects of social media marketing on millennials’ rental housing brand image and preferences with specific reference to Sandton in Johannesburg. The study variables are social media marketing SMM attributes (entertainment, interactions, information, customization, and trendiness), brand image and brand preference. For other contexts, SMM is an important platform for promoting a brand image, thus influencing brand preference, especially for the tech-savvy Millennials market (Lissitsa & Kol, 2016). The relationships between these attributes, brand image, and brand preference with regards to the Sandton rental market and millennial consumers are hypothesized below. The study uses a well- established theory of planned behavior (TPB) to develop a conceptual model that will advance the understanding of the interaction of millennials, social media, and the rental housing industry. The conceptual model extends the application of this grounding theory to include the rental market for an African city. This will open up more avenues for future research on the millennials’ consumption behavior in the fourth industrial revolution era. This study also has management implications. Presently, there is a move of millennials to urban areas which offer better socio-economic opportunities (Galimullin, 2019). There is, also, an increase of institutional investors into these urban rental markets (Nethercote, 2020). A better understanding of this market, especially for a developing country, would help managers to better respond to this target group’s rental housing needs. This would improve the effectiveness of their planning and decrease the number of unrented properties. The remainder of the article is organized in the following way. The first part deals with a literature review. This is followed by research methodology, data analysis, and a discussion of the results. The study concludes by stating some limitations and gives directions for future research. 3. Literature review The literature review subsection covers the grounding theory, concept development, conceptual model, and hypotheses development. 3.1. Grounding theory This study is grounded on the theory of planned behavior (TPB). According to TPB, perceived brand awareness, affordability, consumer attitude, usefulness, and availability influence brand preference (Singh & Kathuria, 2016). The TPB proposes that volitional human behavior is a function of the intention to perform the behavior and perceived behavioral control (PBC). The intention is hypothesized to be a function of attitudes towards the behavior, subjective norm, and perceived behavioral control. Attitudes, subjective norms, and PBC are assumed to be based on the strength and evaluation of accessible behavioral, normative, and control beliefs (Sniehotta et al., 2014). The theory is well-placed to explain behavioral intentions, and persuasive use of technology (Teo et al., 2016). It has been successfully applied to other social media’s influence on purchase intentions (Harun & Husin, 2019). Also, the subjects for the present study are millennials, whose behavior is greatly impacted by social media technology. The rationale for the choice of the grounding theory will be shown along with the discussion of the results. 3.2. Construct development, conceptual model, and hypotheses development The constructs of interest for the present study are social media marketing attributes as described above, namely: entertainment, information, interactive, trendiness, customization, and the well- known concepts of brand image and brand preference as applied to rental housing choices for South African millennials. This study hypothesizes positive relationships between these SMM attributes and millennials’ Sandton brand image, and between Sandton brand image and the millennials’ Sandtonbrand preference. 3.2.1. Social media marketing (SMM) Millennials’ purchasing behavior can be affected by social media marketing (Harun &Husin, 2019). Social media has become the method of statement in the 21st century, enabling people to express their beliefs, ideas, and manners in a new way. According to Singh and Kaur (2021), SMM targets these subjective aspects. Schivinski et al. (2020) further confirm that SMM has the potential to positively influence customer perceptions, brand image, and their future engagements with any brand. Perhaps these positive aspects of SMM can be partly explained by its ability to create a platform for online REAL ESTATE MANAGEMENT AND VALUATION, eISSN: 2300-5289 vol. 30, no.1, 2022 www.degruyter.com/view/j/remav community collaboration, social commerce, sharing, and collaborative lifestyles (Garrett et al., 2017).Social media comes in many forms and the eight most popular are: Blogs, Microblogs, Social Networks, Media-Sharing Sites, Social Bookmarking and selection Sites, analysis Sites, and forums (Saravanakumar & SuganthaLakshmi, 2012). Social media has given birth to Social media marketing (SMM) (Yadav & Rahman, 2017), which has become an important platform to reach a wider consumer market by enabling brand-consumer interaction (Constantinides, 2014). Social media marketing can be a medium through which consumers and businesses can communicate within a limited time, allowing all parties to use, experience, and gain benefits (Dwivedi et al., 2015). Apart from that, social media marketing uses social media technologies, channels, and software to create, communicate, deliver, and exchange offerings that are valuable for organizations (Harun & Husin, 2019).Some of the benefits of SMM are the following: increased market exposure, increased customer traffic, new business partnerships, and reduced marketing expenditure (Constantinides, 2014). It has been further noted that organizations involved in SMM experience growth in both revenue margins (Constantinides, 2014). Social media marketing activities have five attributes, namely: entertainment, interaction, trendiness, information, and customization (Kim & Ko, 2012; Seo & Park, 2017). These attributes form the basis for the present study and are thus further discussed below. For brands that target the highly tech-savvy Millennials, the SMM platform presents an ideal platform (Lissitsa & Kol, 2016). Indeed, many industries are already exploiting this opportunity. Examples are luxury brands (Kim & Ko, 2012; Phan et al., 2011), airlines (Seo & Park, 2017), e-commerce practitioners (Yadav & Rahman, 2017), insurance (Sano, 2015), and area branding (de Noronha et al., 2017). These applications justify the extension of the application of SMM attributes to study the rental housing markets. The above- mentioned attributes are discussed separately, and their relevance to the present study is highlighted. 3.2.2. Entertainment in Sandton Entertainment is the capacity to fulfill an individual’s needs for escapism, diversion, aesthetic enjoyment, or emotional enjoyment (Harshini, 2015). It is connected to enjoyment, relaxation, and pastime (Muntinga et al., 2011). Something is entertaining when it is pleasurable and motivating (Shao, 2009), produces positive emotions (Seo & Park, 2017), and is joyful, exciting, and cool (Muntinga et al., 2011). Consequences of entertainment include engagement with online content, positive emotions, and intended continuous usage of the platforms (Seo & Park, 2017). Social media users have different motivations for using social media platforms, including finding pleasure and entertainment from using such platforms (Godey et al., 2016; Manthiou et al., 2013). Users derive pleasure from engaging with peers for commercial and non-commercial purposes (Hayes & King, 2014; Shareef et al., 2017). The more pleasant such platforms are to use (including escapism and relaxation aspects), the more consumers (Millennials) will take in the brand-related content (Muntinga et al., 2011). Sandton is home to many shopping malls, casinos, major sporting facilities, etc. Its rental market can project itself as a beautiful place (Harshini, 2015), pleasurable to live in (Sao 2009) and with an advanced technology infrastructure to attract the millennial audience. The proximity to places of entertainment could also be emphasized. 3.2.3. Trendiness of Sandton Trendiness implies being fashionable (Moresjo & Xin, 2020), being popular, and being a symbol of status (Marone, 2017). It refers to the currency of the object or topic under discussion. Trendiness is closely related to the word of mouth commendation (Sari & Yulianti, 2019). In the social media marketing context, this will mean electronic word of mouth. With the increasing popularity of social media, customers demand immediate access to brand information and frequently utilize the information available on various social media to make purchase decisions (Vollmer & Precourt, 2008). Within this environment, trendiness entails the provision of inspiring brand-related information and online product reviews amongst virtual brand communities (Muntinga et al., 2011). For the Sandton brand, online communication of information about the availability of good quality food such as sushi and the access to the high-end popular millennial restaurants would portray it as a symbol of status. As a rental market, Sandton can also position itself as a trendy place, an ideal destination for innovation, and techno-savvy individuals (Van Esch & Mente, 2018). Trendiness can also mean the extent to which the luxury brand disseminates the latest and trendiest information about the brand. The millennials consider social media to be a REAL ESTATE MANAGEMENT AND VALUATION, eISSN: 2300-5289 vol. 30, no. 1, 2022 www.degruyter.com/view/j/remav trustworthy, trendy source for important up-to-date brand information (Liua et al., 2019). To further boost its image as a trendy rental housing market, landlords can ensure that advertisements about available rental stock frequently update information, unlike printed communication. The advertisements can include hot topics and accurate and trendy content. Customers tend to trust and prefer brands that provide updated content (Naman et al., 2011). 3.2.4. Interaction in Sandton The participatory nature of social media readily enables collaboration and sharing of contents, including information, video, and pictures (Hennig-Thurau et al., 2010). Interactiveness refers to the ability to allow for the sharing and exchanging of information with others. The interactivity of social media posting is important because it promotes customer reactions, such as liking and commenting on the firm's post (Liu et al., 2021). According to Kim and Ko (2012), social media platforms are aimed at facilitating interactions between users (i.e., inter-consumer interaction, consumer-brand, etc.), among other things. Enormous possibilities exist for Sandton to promote itself as a rental market of choice. The place can communicate messages of its suburbs that allow for social interactions. As an illustration, Sandton has excellent neighborhoods, online connectivity, social amenities, and a good road network for ease of movement (Abass et al., 2020). 3.2.5. Customization of Sandton rental market The era of social media has offered brands the ability to customize information targeted at individual customers (Seo & Park, 2017). Customization refers to the modification of a product or service to fulfill the needs or preferences of a customer or a small group of consumers (Godey et al., 2016). For social media, Zhu and Chen (2015) defined customization as tailored brand-specific messages, targeted at an individual or a niche market. Social media marketing has a greater ability to get very close to customers and to enable brands to customize their communication with customers (Seo & Park, 2017).There are endless opportunities for Sandton city to be the rental place of choice for millennials. Businesses can brand it as a evolving neighborhood of smart rental housing market (Tomal, 2020), acity in which housing transaction platforms are online, and as a city that is future-ready in terms of the fourth industrial revolution (Lojanica & Colic-Damajanovic, 2018). 3.2.6. Information access in Sandton Consumers learn and develop understanding by analyzing marketing messages (Shareef et al., 2017). Information contained in brand-related posts can influence consumer awareness, result in positive perceptions and preference for a brand (Hayes & King, 2014). Social media users participate in social media activities for various reasons, including seeking useful information for decision-making purposes (Chang et al., 2015). Customers seek brand-related information on social media (e.g., Sandton brand), which influences their brand perceptions (Muntinga et al., 2011). Such information could include the best area to rent an apartment based on specific requirements by the tenant. The quality of information on social media platforms is determined by, among other factors, its persuasive power to positively influence recipient perceptions and change their attitudes (Chang et al., 2015). Sandton, as a brand, can utilize several approaches when targeting millennials. Firstly, the media of choice should be telecommunication social media (Kusyanti et al., 2018). Businesses can use persuasive influencer user-generated information advertisements (Shareef et al., 2018) and graphic information of the city. 3.3. Sandton brand Image Brand image is a key pillar of brand equity which influences consumer perceptions, attitudes, and preferences towards a brand (Chovanova et al., 2015);it is the perceptions a consumer has about a brand, which includes feelings for the brand as well as other related factors (Keller, 1993). Brand image and brand associations are interchangeable concepts because they both refer to a consumers’ memory about a brand which influences their perceptions and, ultimately, attitudes towards that brand (Romaniuk & Nenycz-Thiel, 2013). A strong brand image enhances consumer brand equity and the willingness to pay a premium price for luxury brands (Liu et al., 2017). As a rental housing destination, there are several things that Sandton can engage in. It can promote itself as an environmentally friendly city that is ideal for the life experiences of upwardly mobile millennials (Aitken & Campelo, 2011). This can be partly achieved by communicating its brand positioning REAL ESTATE MANAGEMENT AND VALUATION, eISSN: 2300-5289 vol. 30, no.1, 2022 www.degruyter.com/view/j/remav messages to attract mobile talent, residents, tourists, and investment (Cleave et al., 2017). This would amount to re-imaging the place to differentiate itself and create a favorable image which will positively affect how millennials perceive it (Blakely & Leigh, 2013). Lastly, Sandton can use its image as a brand that portrays personal characteristics that are used by millennials (Kara et al., 2020).  3.4. Sandton brand Preference Usually, a consumer chooses one brand over its competitors because of the perceived brand strength in the consumer’s mind (Godey et al., 2016). It is reasonable to conclude that the final purchase decision is preceded by brand preference. Brand preference is a personal feeling and interest towards a brand (Chang et al., 2015). Positive brand perception is one of the factors which positively influence consumer attitudes and, ultimately, preference for a brand (Aghekyan-Simonian et al., 2012). For millennials who monitor trends in the market, finding useful information on rental housing on social media would improve their perceptions of the brand. For the rental market, marketing communication should be geared toward producing a positive predisposition which would result in millennials consistently preferring it over other neighboring suburbs or cities (Duffett et al., 2019). Several options are available for the Sandton rental housing market. It can communicate messages that consistently project an image of a place that people like to live in (Duffet et al., 2019). It can be promoted as a destination of choice that other millennials would always choose over others (Adnyana & Respati, 2019). One of the attributes to promote would be Sandton’s location efficiencies (Gabeet et al., 2021). 3.5. Research model and hypotheses development The study proposes the conceptual model shown in Figure 1. The model proposes that, for millennials, the SMM attributes have a positive impact on Sandton rental brand image, which, in turn, impacts their preference for the city. Hypotheses development for the present study follows. Intervening Variable Outcomes Predictors Entertainment H1 Trendiness H2 Interaction Brand Brand H3 Preference Image H6 H4 Information H5 Customization Fig.1. Proposed conceptual model. Source: Authors’ study. 3.5.1. Entertainment and Sandton brand image Social media platforms provide fun, joy, and entertainment (Shareef et al., 2018). The entertainment element of SMM is an important factor in influencing the perceived brand image (Kang, 2005; Seo & Park, 2017). Consumers who perceive a brand’s social media presence as fun, exciting and cool will have positive perceptions of its image (Muntinga et al., 2011; Taylor et al., 2011). Media users engage on social media platforms to seek excitement from usage as well as communicating with other users REAL ESTATE MANAGEMENT AND VALUATION, eISSN: 2300-5289 vol. 30, no. 1, 2022 www.degruyter.com/view/j/remav (Hayes & King, 2014; Pietro & Pantano, 2012). Thus, drawing from the above literature, the study proposes that: H1: Availability of entertainment positively influences attitude towards Sandton brand image. 3.5.2. Trendiness and Sandton brand image Customer feedback on social media is an important factor influencing product or service performance (Ramananthan et al., 2015). An active social media presence positively affects brand image (Godey et al., 2016). Consumers tend to show confidence towards and preference for brands that provide trendy information (Naman et al., 2011). Providing trendy content helps brands develop and strengthen their image (Vollmer & Precourt, 2008). Based on these arguments, it can be hypothesized that: H2: The trendiness of SMM content on Sandton positively influences Sandton’s brand image. 3.5.3. Interaction and Sandton brand image Social media are online platforms, applications and media aimed at facilitating interactions (Kim & Ko, 2012). They enable easier and more efficient ways to perform marketing activities, thus impacting a brand’s reputation (Kim & Ko, 2012). Social media users develop positive perceptions towards a brand, which offers them the opportunity to engage with the brand products or services (Bilgin, 2018). It can therefore be concluded that the link between social media interaction and brand image is positive. Indeed, social media are very effective in facilitating the interaction between business and customers, and in creating a positive brand image (Fortezza & Pencarelli, 2015). Social media strengthens brand image through its interactive nature of communication (Godey et al., 2016). The implications for Sandton city rental property owners are that they need to create valuable content that the millennials find entertaining or useful via social media in order to create a positive brand image (Quesenberry, 2020).   Based on the above argument, the study proposes hypothesis H3. H3:SMM interaction positively affects Sandton’s brand image for the millennial consumer. 3.5.4. Information and Sandton brand image Consumers utilize social media platforms to seek brand-related content information (Lin & Lu, 2011; Dholakia et al., 2004). Social media informative brand posts positively affect consumer attitudes towards a brand (de Vries et al., 2012) because social media users tend to develop positive attitudes towards informative brand content (Taylor et al., 2011). When consumers receive relevant and useful information regarding a brand’s products and services, positive consumer perceptions are likely to develop or be strengthened (Zhou et al., 2019). When consumers get useful information on social media platforms, they develop a stronger brand preference towards such a brand. Positive brand perceptions can lead to increased brand preference and positive WOM. The above arguments led to the hypothesis below: H4: Informative SMM content positively influences Sandton’s brand image. 3.5.5. Customization and Sandton brand image Customized information is the second most popular element of SMM, as consumers prefer receiving information that suits their needs (Seo & Park, 2017). Brands can use customized content and direct contact with individual consumers to emphasize their brand differentiation among rivals, thus strengthening their consumer-based perceived brand image (Ding & Keh, 2016). Developing and strengthening a distinct identity is good for a brands’ competitive edge in the market (Seo & Park, 2017). Based on the above argument, the hypothesis below was derived. H5: SMM customization positively affects Sandton’s brand image. 3.5.6. Sandton’s brand image and brand Preference This influence of brand image on perceptions and ultimately customer behavior has received attention from many researchers (Lien et al., 2015). It is now safe to state that the perceived value of a brand is determined by its brand image, and this influences consumers’ preference for that brand (Chow et al., REAL ESTATE MANAGEMENT AND VALUATION, eISSN: 2300-5289 vol. 30, no.1, 2022 www.degruyter.com/view/j/remav 2017). A positive brand image influences consumer attitudes positively, causing a positive impact on consumer behavior (Aghekyan-Simonian et al., 2012). Brand image helps brands distinguish themselves among rivals and these distinguishing features can be used as a basis for customer brand preferences. A positive brand image influences consumer attitudes and behavior positively, as well as leading to brand preference (Aghekyan-Simonian et al., 2012). Social media platforms are important channels for developing and enhancing consumer-based brand image (Yadav & Ragman, 2017; Godey et al., 2016). SMM can impact brand image and this might positively influence their brand preference. Further, area branding and marketing influence consumer perceptions and ultimately brand preference towards an area, either for rental or homeownership (Zenker et al., 2017).The above argument leads to the hypothesis below. H6:Sandton’s brand image positively influences millennial’s brand preference. 4. Data and methods This subsection describes the target population and sampling, the measurement instrument, data gathering, ethics, data analysis, and results. 4.1. Target population and sampling The research targeted the millennials who have lived, live, or consider living in or within a 15- kilometer radius from Sandton City, as they are assumed to be extensive social media users and acceptors of social meanings given by influencers (Mgiba & Nyamande, 2020). This is in line with other studies that concentrated on either influencer marketing or the use of social media (Yadav & Rahman, 2018). Most of the participants came from the Sandton CBD area, Bryanston, Fourways, Craighall, Hurlingham, Illovo, Morningside, Rivonia, Sandhurst and Sunninghill. Considering the nature of the target market and the difficulty of obtaining a sampling frame, this study employed non- probability convenience sampling (Malhotra et al., 2017). Data collection achieved a sample size of 408 responses, which is well within the required range of a 95% confidence level, 50% population variability, and the sample size requirement for the Structural equation modeling analysis technique (Bartlett et al., 2001) 4.2. Measurement instrument A multi-item scale was used to measure the constructs used in this study, as adopted from previous studies (Seo & Park, 2017; Yadav & Rahman, 2017). Each construct had 8 items, with a 7-point Likert scale used (i.e. from 1 = Strongly Agree to 7 = Strongly Disagree). The measurement instrument was assessed and approved for content validity by senior lecturers within the department of Marketing Department of a Johannesburg-based university. A pilot project involving 30 participants was conducted before the final version of the instrument was distributed for data collection. 4.3. Data gathering A research company was used for data collection and analysis. Participants were sent the survey link through email, social media platforms, and other web-based platforms (e.g., LinkedIn) with the survey questionnaire to collect data. This approach was followed because of its advantages over the telephone, post, personal, and paper-based surveys (Malhotra et al., 2017; Wiid & Diggines, 2015). All ethics protocols were observed and potential respondents voluntarily offered their responses. Ethical clearance for this study was approved by the above-mentioned Johannesburg-based University ethics committee. The ethics protocol number is H20/03/18. 4.4. Empirical results The analysis stage follows the scholarly recommended approach of doing the descriptive part before analyzing both proposed relationships. SPSS was used for the descriptive part of the data analysis. For the second part, the Structural equation modeling procedure was applied to perform hypotheses testing using Amos 25 statistical package. For the results of the descriptive statistics, see Table 1 below. Reading from Table 2, a total of one hundred and eighty-seven (46%) males made up the sample compared to two hundred and seventeen (54%) females. Three hundred and twelve (76%) of the sampled respondents were aged 21-30 years, with the 21-25 years making for a larger portion (44%). REAL ESTATE MANAGEMENT AND VALUATION, eISSN: 2300-5289 vol. 30, no. 1, 2022 www.degruyter.com/view/j/remav Most of the respondents (83%) said they were single, followed by those who were married (16%). The divorced and widowed categories made up the remaining 1% of the sample. About 32% of the respondent had completed high school (Grade 12), followed by 30% with a bachelor’s degree, and 24% who completed a post-high school certificate or national diploma. The remaining qualifications made up 14% of the sample. The occupation status of the respondents was split as follows: employed full-time (34%), unemployed (21%), part-time employed (15%), students (19%), and self-employed (12%; n=48). Table 1 Descriptive statistics % (n) Gender Male 46% (n=187) Female 54% (n=217) 21-25 years 44% (n=181) 26-30 years 32% (n=131) Age 31-35 years 15% (n=62) 36-40 years 8% (n=34) Single 83% (320) Married 16% (61) Marital Status Divorced 1% (n=xxx) Widowed 0% Primary School 2% (n=6) Some High School 5% (n=18) Matric/Grade 12 Completed 32% (n=125) Level of Education Post High School 24% (n=94) Cert/Diploma 30% (n=119) Bachelor’s Degree 8% (n=33) Postgraduate Full Time Student 19% (n=74) Employed Full Time 34% (n=137) Occupation Employed Part Time 15% (n=59) Self-employed 12% (48) Unemployed 21% (n=82) Less than R10 000 52,4 R10 000-R14 999 13,5 R15 000-R19 999 5,5 Gross monthlyincome R20 000-R24 999 7,8 R25 000-R29 999 7,5 More than R30 000 13,3 Source: Analysis results. 4.4.1. Measurement model accuracy analysis The accuracy of the measurement model was assessed by checking the reliability and validity of the model. Reliability For the reliability of the model, composite reliability (CR), the average value extracted (AVE), and Chronbach-alpha values were used. To confirm Reliability, the CR should be greater than 0.7, the AVE should be greater than 0.5 , and the Chronbach alpha should be greater than 0.7 (Nasution et al., 2020; Hair et al., 2020). For the study values, see Table 2 below. REAL ESTATE MANAGEMENT AND VALUATION, eISSN: 2300-5289 vol. 30, no.1, 2022 www.degruyter.com/view/j/remav Table 2 Statistical evidence of reliability and convergent validity Constructs Items Factor P- Cronbach's Composite Average Final number loadings value Alpha Reliability variance of items and extracted (initials) (AVE) SE1 0.816 *** SE2 0.831 *** SE3 0.872 *** SMM – SE4 0.853 *** 0.946 0.946 0.686 Entertainment SE5 0.799 *** SE6 0.801 *** SE7 0.840 *** SE8 0.812 *** ST2 0.808 *** ST3 0.871 *** ST4 0.840 *** SMM – 0.940 0.937 0.714 6(8) Trendiness ST5 0.826 *** ST6 0.847 *** ST7 0.876 *** SInt3 0.807 *** SInt4 0.834 *** SMM – SInt5 0.852 *** 0.917 0.915 0.682 5(8) Interaction SInt6 0.824 *** SInt7 0.812 *** SInf1 0.759 *** SInf2 0.798 *** SInf3 0.831 *** SInf4 0.790 *** SMM – 0.930 0.929 0.620 8(8) Information SInf5 0.803 *** SInf6 0.804 *** SInf7 0.768 *** SInf8 0.742 *** SC1 0.794 *** SC2 0.817 *** SC3 0.821 *** SMM – SC4 0.854 *** 0.941 0.941 0.665 8(8) Customization SC5 0.856 *** SC6 0.812 *** SC7 0.740 *** SC8 0.825 *** BI1 0.759 *** BI2 0.801 *** BI3 0.810 *** Brand Image BI4 0.813 *** 0.928 0.929 0.650 7(8) BI5 0.821 *** BI6 0.805 *** BI7 0.833 *** BPr3 0.784 *** BPr4 0.813 *** BPr5 0.816 *** Brand 0.929 0.926 0.676 6(8) Preference BPr6 0.865 *** BPr7 0.822 *** BPr8 0.831 *** Source: Analysis results. REAL ESTATE MANAGEMENT AND VALUATION, eISSN: 2300-5289 vol. 30, no. 1, 2022 www.degruyter.com/view/j/remav Validity Measuring the validity of the instrument is another requirement for measurement model analysis (Mohajan, 2017). The validity of the model deals with the extent to which the instrument measures what it intends to measure (Mohajan, 2017). For this study, AVE and the correlation matrix were used. The correlation matrix results are displayed in Table 3 below. Discriminant validity was confirmed because the values obtained on the inter-construct correlation matrix are below 0.90 (Henseler et al., 2015). Table 3 Correlation matrix BI BPref SMME SMMT SMMC SMMInf SMMI Brand Image 0.806 Brand Preference 0.835 0.822 SMM Entertainment 0.678 0.605 0.828 SMM Trendiness 0.692 0.611 0.834 0.845 SMM Customization 0.814 0.762 0.749 0.780 0.816 Electronic WOM 0.684 0.623 0.876 0.773 0.740 SMM Information 0.826 0.762 0.741 0.837 0.917 0.787 SMM Interaction 0.712 0.650 0.787 0.819 0.804 0.855 0.826 Source: Analysis results. 4.4.2. The Goodness of fit testing results Following Wang, Wang, and Lee (2018) and Hayes et al., (2017) recommendation, before testing the hypotheses, the structural model was inspected for model fitness to check for the plausibility of the postulated relationships in the model. Common guidelines for acceptable model fit are Chi- squared/degrees of freedom below 3, RMSEA of 0.05-0.06, CFI over 0.95, TLI over 0.9 (Scherer et al. 2019). Table 4 below gives the indices, cut-off values, results and decisions. Table 4 Model fitness test statistics Fit Indicator Threshold adapted from Initial Final Hair et al. (2014: 579-580) measurement measurement model model 2.011 CMIN/DF (Chi- Below 3 (good) 2.464 square/degree of From 3 to 5 (acceptable) freedom) Over 5 (bad) 0.050 RMSEA (Root Below 0.05 (good) 0.060 Mean Square Error From 0.06 to 0.1 of Approximation) (acceptable) Over 0.1 (bad) CFI (Comparative Below 0.90 (bad) 0.841 0.915 Fit Index) Over 0.90 (good) TLI (Tucker Lewis Below 0.80 (bad) 0.835 0.909 Index) From 0.80 to 0.90 (acceptable) Over 0.90 (good) Source: Own study. 4.4.3. Hypotheses testing results The results of the hypotheses testing are presented in Table 5 below. REAL ESTATE MANAGEMENT AND VALUATION, eISSN: 2300-5289 vol. 30, no.1, 2022 www.degruyter.com/view/j/remav Table 5 Standardized Regression Weights and hypothesis conclusion Dependent Independent variables β values P-value Decision variables H1 is accepted. Brand Image <-- SMM Entertainment 0.302 0.000 H2 is rejected. Brand Image <-- SMM Trendiness -0.13 0.042 H3 is rejected. Brand Image <-- SMM Interaction -0.031 0.597 H4 is accepted. Brand Image <-- SMM Information 0.26 0.009 H5 is accepted. Brand Image <-- SMM Customization 0.27 0.000 Brand H6 is accepted. <-- Brand Image 0.939 0.000 Preference Source: Analysis results. 5. Results, discussion and conclusions The entry point for this paper was that all the SMM attributes positively affect the millennials’ choice of Sandton’s rental houses. The outcomes of the study confirmed some hypotheses and rejected others. Those that were confirmed are customization and brand image, entertainment and brand image, information and brand image, brand image and brand preference. The customization and brand image outcome confirmed a list of many others in industries unrelated to the rental market, examples of which are the studies done by Chobhan et al., (2020), Yoo and Park (2016), and by Bilgin (2018). The entertainment and brand image outcome is also in line with studies such as Ganji et al. (2021), and Stylidis and Cherifi (2018). The hypothesized relationship between information and Sandton brand image was also confirmed. This also served as confirmation of other studies on how millennials view and esteem telecommunication information availability. Examples are Guo and Peela (2020), Natalia et al., (2021), and Boeing, Besbris et al., (2019). However, the hypotheses that were related to the trendiness of Sandton and that of the interactions within the city were not confirmed. These outcomes are not in line with other findings. For instance, studies by Ngesan et al., (2018), and Correia et al., (2019) confirmed a positive relationship between the trendiness of a brand and its image. Finally, the interaction and brand image outcome came as a surprise. One of the explanations behind this may be that both trendiness and interactions should be viewed in the light of the new reality of virtual experience. Interaction today is different from actual physical interaction. The results of this study have both academic and managerial implications. For academics, it was shown that SMM plays an important role in influencing millennial consumers’ attitudes and behavior towards rental housing brands. This was achieved by using the theory of planned behavior (TPB) as a lens. The outcomes extend the application of the grounding theory to include generational groups and their housing rental property requirements. Further, the proposed model can form a strong base for future academic investigation for generational market targets in other industries. The framework can also be used to predict millennials’ and other generations’ attitudes and behaviors within the residential housing contexts in other African states. For management practitioners, this study will assist them in deciding on what aspects of SMM to emphasize. Three of the SMM constructs (entertainment, information, and customization) showed a positive influence on brand image. Residential real estate owners and managers should focus on these attributes in their advertisement messages through social media. Understating SMM as one of the drivers of rental preferences within the Millennials’ market will help practitioners develop strategies that will appeal to the market and produce positive results for residential housing brands. The limitations of this study could be used as a base for future studies. Only the Millennials in the Sandton rental housing market were studied. The study, therefore, excluded other generational segments in this industry. The findings are, therefore, only relevant to the millennial segment. The sample for the study consisted of millennials who were intercepted around Johannesburg. This also further limits the generalizability of the findings to South Africa or Africa as a whole. It is therefore recommended that the study be replicated with a wider representative sample to enhance its application to millennials in all South African and African cities. REAL ESTATE MANAGEMENT AND VALUATION, eISSN: 2300-5289 vol. 30, no. 1, 2022 www.degruyter.com/view/j/remav Further, the number of respondents was only 408. Caution should therefore be exercised when interpreting the results of this study. Lastly, the study also focused on the high-end rental housing market in Johannesburg, South Africa (Sandton). Lower-income markets were, therefore, also excluded. The findings of the study, therefore, do not apply to this market segment. This study was aimed at examining how SMM attributes (interaction, information, customization, trendiness, entertainment) impact millennials’ rental housing choices for Sandton in South Africa. Related literature was used to hypothesize the relationships between these SMM attributes and Sandton brand image, and between Sandton brand image and the millennials’ preference for the city. A quantitative approach was used to collect and analyze data for the study. The results confirmed four of the hypothesized relationships and rejected two. These results emphasize that not all SMM attributes can be used to attract millennials to the Sandton rental market. The findings will assist property managers and investors in making informed decisions on their social marketing strategies. This knowledge becomes a useful tool for future promotions and advertisement campaigns directed at millennial customers. The other findings were that Sandton’s image as a brand is a major attraction for millennials. It is the reason why millenials decide to rent residential properties in Sandton. The study concludes that future investment in promoting the Sandton brand image via SMM efforts is justified. 9. References Aaker, D. A. (2009). Managing brand equity. Simon and Schuster. Abass, Z. I., Andrews, F., & Tucker, I. (2020). Socializing in the suburbs: Relationships between neighbourhood design and social interaction in low-density housing contexts. Journal of Urban Design, 25, 108–133. https://doi.org/10.1080/13574809.2019.1592663 Adnyana, I., Made, P., Respati, N N R., (2019), The Role of Brand Preference in Mediating the Relationship Between Brand Equity and Purchase Intention (PeranPreferensiMerekdalamMemediasiHubungan Antara EkuitasMerekdenganNiatBeli). Udayana university e-journal, Vol. 8, no.1, pp. 7519–7547. Aghekyan-Simonian, M., Forsythe, S., Suk Kwon, W., & Chattaraman, V. (2012). The role of product brand image and online store image on perceived risks and online purchase intentions for apparel. Journal of Retailing and Consumer Services, 19(3), 325–331. https://doi.org/10.1016/j.jretconser.2012.03.006 Ahmad, F. S., Quoquab, F., & Bahrun, R. Mansor M. N. Md. (2014). Branding Leadership in Malaysian SMEs. Procedia-Social and Behavioral Sciences, 130, 2014. https://doi.org/10.1016/j.sbspro.2014.04.007 Aitken, R., & Campelo A., (2011). The Four R’s of Place Branding. Journal of marketing management, 27(9/10), 913–933. Ajzen, I. (1985). From intentions to actions: A theory of planned behaviour. In Action control (pp. 11–39). Springer. https://doi.org/10.1007/978-3-642-69746-3_2 Ajzen, I. (2002). Perceived behavioural control, self‐efficacy, locus of control, and the theory of planned behaviour. Journal of Applied Social Psychology, 32(4), 665–683. https://doi.org/10.1111/j.1559-1816.2002.tb00236.x Ajzen, I., & Fishbein, M. (1980). Understanding attitudes and predicting social behaviour. Prentice- Hall. Gilbert, A. (2016). Rental housing: The international experience. Habitat International, 54, 173–181. https://doi.org/10.1016/j.habitatint.2015.11.025 Ali, A., & Alyani, N. I. (2019). Factors affecting China smartphone brand preference among millennials. https://ir.uitm.edu.my/id/eprint/25862/ Aramburu, M. (2015). Rental as a taste of freedom: The Decline of Home Ownership amongst Working-class Youth in Spain during Times of Crisis. International Journal of Urban and Regional Research, 39(6), 1172–1193. https://doi.org/10.1111/1468-2427.12218 Athwal, N. K., Istanbulluoglu, D., & Mccormack, S. (2018). The allure of luxury brands’ social media activities: A uses and gratifications perspective. Information Technology & People, 32(1), 1–36. https://doi.org/10.1108/ITP-01-2018-0017 Bang, H. K., Ellinger, A. E., Hadjimarcou, J., & Traichal, P. A. (2000). Consumer concern, knowledge, belief, and attitude toward renewable energy: An application of the reasoned action theory. Psychology and Marketing, 17(6), 449–468. https://doi.org/10.1002/(SICI)1520- 6793(200006)17:63.0.CO;2-8 REAL ESTATE MANAGEMENT AND VALUATION, eISSN: 2300-5289 vol. 30, no.1, 2022 www.degruyter.com/view/j/remav Bartlett, J. E., Kotrlik, J. W., & Higgins, C. C. (2001). Organizational research: Determining appropriate sample size in survey research. Information Technology, Learning and Performance Journal, 19(1), 43– Bhattacherjee, A., & Premkumar, G. (2004). Understanding changes in belief and attitude toward information technology usage: A theoretical model and longitudinal test. Management Information Systems Quarterly, 28, 229–254. https://doi.org/10.2307/25148634 Bhattacherjee, A., & Sanford, C. (2006). Influence processes for information technology acceptance: An elaboration likelihood model. Management Information Systems Quarterly, 30, 805–825. https://doi.org/10.2307/25148755 Bilgin, Y. (2018). The effect of social media marketing activities on brand awareness, brand image and brand loyalty. Business & Management Studies: An International Journal, 6(1), 128–148. https://doi.org/10.15295/bmij.v6i1.229 Blair, O. (2017). What Comes After Millenials? Meet the Generation Known as Linkster. independent.co.uk Blake, T. (2019). Commuting Costs and Geographic Sorting in the Housing Market. Real Estate Economics, 47(4), 1089–1118. https://doi.org/10.1111/1540-6229.12159 Blakely, E. J., & Leigh, N. G. (2013). Planning local economic development: Theory and practice. 5th edition. Boeing G. (2020) Online Rental Housing Market Representation and the Digital Reproduction of Urban Inequality. Environment and Planning A: Economy and Space. https://doi.org/10.1177/0308518X19869678. Chang, K. L. (2020). Are cyclical patterns of international housing markets interdependent? Economic Modelling, 88, 14–24. https://doi.org/10.1016/j.econmod.2019.09.002 Chang, Y. T., Yu, H., & Lu, H. P. (2015). Persuasive messages, popularity cohesion, and message diffusion in social media marketing. Journal of Business Research, 68(4), 777–782. https://doi.org/10.1016/j.jbusres.2014.11.027 Chatzigeorgiou, C. (2017). Modelling the impact of social media influencers on behavioural intentions of millennials: The case of tourism in rural areas in Greece. Journal of Tourism. Heritage & Services Marketing, 3(2), 25–29. Chen, J., Hui, E. C. M., Seiler, M. J., & Zhang, H. (2018). Household tenure choice and housing price volatility under a binding home-purchase limit policy constraint. Journal of Housing Economics, 41, 124–134. https://doi.org/10.1016/j.jhe.2018.06.004 Cheung, M. L., Pires, G., & Rosenberger, P. J. (2020). The influence of perceived social media marketing elements on consumer–brand engagement and brand knowledge. Asia Pacific Journal of Marketing and Logistics, 32(3), 695–720. https://doi.org/10.1108/APJML-04-2019-0262 Chovanová, H. H., Korshunov, A. I., & Babčanová, D. (2015). Impact of brand on consumer behavior. Procedia Economics and Finance, 34, 615–621. https://doi.org/10.1016/S2212-5671(15)01676-7 Chow, H. W., Ling, G. J., Yen, I. Y., & Hwang, K. P. (2017). Building brand equity through industrial tourism. Asia Pacific Management Review, 22(2), 70–79. https://doi.org/10.1016/j.apmrv.2016.09.001 Circella, G., Alemi, F., Tiedeman, K., Handy, S., & Mokhtarian, P. (2017). What Affects Millennials’ Mobility? PART II: The Impact of Residential Location, Individual Preferences and Lifestyles on Young Adults’ Travel Behavior in California. Project Report, National Center for Sustainable Transportation. University of California, Davis, March 2017; Available at https://ncst.ucdavis.edu/wp Cleave E., Arku G., Sadler R., & Kyeremeh E., (2017). Place Marketing, Place Branding, and Social Media: Perspectives of Municipal Practitioners. Growth and change. A journal of urban and regional policy, 48(4), 1012-1033. Constantinides, E. (2014). Foundations of social media marketing. Procedia: Social and Behavioral Sciences, 148, 40–57. https://doi.org/10.1016/j.sbspro.2014.07.016 Cretu, A. E., & Brodie, R. J. (2007). The influence of brand image and company reputation where manufacturers market to small firms: A customer value perspective. Industrial Marketing Management, 36(2), 230–240. https://doi.org/10.1016/j.indmarman.2005.08.013 Davis, F. D. (1985). A technology acceptance model for empirically testing new end-user information systems: Theory and results. Doctoral dissertation, Sloan School of Management, Massachusetts Institute of Technology. De Noronha, I., Coca-Stefaniak, J A., & Morrison, A M. (2017). Confused branding? An exploratory study of place branding practices among place management professionals. Cities, 66, 91-98. REAL ESTATE MANAGEMENT AND VALUATION, eISSN: 2300-5289 vol. 30, no. 1, 2022 www.degruyter.com/view/j/remav Deka, D. (2018). Are millennials moving to more urbanized and transit-oriented counties? Journal of Transport and Land Use, 11(1), 443–461. https://doi.org/10.5198/jtlu.2018.1345 Dholakia, U. M., Bagozzi, R. P., & Pearo, L. K. (2004). A social influence model of consumer participation in network-and small-group-based virtual communities. International Journal of Research in Marketing, 21(3), 241–263. https://doi.org/10.1016/j.ijresmar.2003.12.004 Di Pietro L., & Pantano E. (2012). An empirical investigation of social network influence on consumer purchasing decision: the case of Facebook. J. Direct Data Dig. Mark. Pract, 14, 18–29. https://doi.org/10.1057/dddmp.2012.10 Duffett, R., Petrosanu, D. M., Negricea, L. C., & Edu, T. (2019). Effect of YouTube Marketing Communication on Converting Brand Liking into Preference among Millennials Regarding Brands in General and Sustainable Offers in Particular. Evidence from South Africa and Romania. Sustainability (Basel), 11(3), 604. https://doi.org/10.3390/su11030604 Dwivedi, Y. K., Kapoor, K. K., & Chen, H. (2015). Social Media Marketing and Advertising. The Marketing Review, 15(3), 289–309. https://doi.org/10.1362/146934715X14441363377999 Galimullin, E. Z. (2019). Migration attitudes and mechanisms for attracting young people to the Russian Arctic. Arctic and North., 36, 78–88. https://doi.org/10.17238/issn2221-2698.2019.36.96 Foroudi, P. (2019). Influence of brand signature, brand awareness, brand attitude, brand reputation on hotel industry’s brand performance. International Journal of Hospitality Management, 76, 271–285. https://doi.org/10.1016/j.ijhm.2018.05.016 Fortezza, F., & Pencarelli, T. (2015). Potentialities of Web 2.0 and new challenges for destinations: Insights from Italy. Anatolia: An International Journal of Tourism and Hospitality, 26(4), 563–573. https://doi.org/10.1080/13032917.2015.1040813 Gabe, J., Robinson, S., & Sanderford, A. (2021). Willingness to pay for attributes of location efficiency. The Journal of Real Estate Finance and Economics, 2021, 1–35. https://doi.org/10.1007/s11146-021- 09847-z Glaeser, E., & Gyourko, J. (2018). The Economic Implications of Housing Supply. The Journal of Economic Perspectives, 32(1), 3–30. https://doi.org/10.1257/jep.32.1.3 Garrett, A., Straker, K., & Wrigley, C. (2017). Digital channels for building collaborative consumption communities. Journal of Research in Interactive Marketing, 11(2), 160–184. https://doi.org/10.1108/JRIM-08-2016-0086 Godelnik, R. (2017). Millennials and the sharing economy: Lessons from a ‘buy nothing new, share everything month’ project. Environmental Innovation and Societal Transitions, 23, 40–52. https://doi.org/10.1016/j.eist.2017.02.002 Godey, B., Manthiou, A., Pederzoli, D., Rokka, J., Aiello, G., Donvito, R., & Singh, R. (2016). Social media marketing efforts of luxury brands: Influence on brand equity and consumer behavior. Journal of Business Research, 69(12), 5833–5841. https://doi.org/10.1016/j.jbusres.2016.04.181 Hair, J. F., Jr., Howard, M. C., & Nitzl, C. (2020). Assessing measurement model quality in PLS-SEM using confirmatory composite analysis. Journal of Business Research, 109, 101–110. https://doi.org/10.1016/j.jbusres.2019.11.069 Han, H., Hsu, L. T. J., & Sheu, C. (2010). Application of the theory of planned behaviour to green hotel choice: Testing the effect of environmentally friendly activities. Tourism Management, 31(3), 325– 334. https://doi.org/10.1016/j.tourman.2009.03.013 Han, H., & Kim, Y. (2010). An investigation of green hotel customers’ decision formation: Developing an extended model of the theory of planned behavior. International Journal of Hospitality Management, 29(4), 659–668. https://doi.org/10.1016/j.ijhm.2010.01.001 Han, S. H., Nguyen, B., & Lee, T. J. (2015). Consumer-based chain restaurant brand equity, brand reputation, and brand trust. International Journal of Hospitality Management, 50, 84–93. https://doi.org/10.1016/j.ijhm.2015.06.010 Harshini, C. S. C. S. (2015). Influence of social media ads on consumer’s purchase intention. Government R C College. Recognized Research Centre, 2(10), 110–115. Harun, A., & Husin, W. H. R. (2019). Social Media Marketing amongst Millennial’s in Malaysia: Issues and Challenges. Journal of Social Transformation and Regional Development, 1(2), 1–7. Hassanzadeh A., & Namdar T. (2018). Millennials brand loyalty in the fashion industry & the role of brand identity. Test Engineering and Management, 82, 4234-4240. REAL ESTATE MANAGEMENT AND VALUATION, eISSN: 2300-5289 vol. 30, no.1, 2022 www.degruyter.com/view/j/remav Hayes, A. F., Montoya, A. K., & Rockwood, N. J. (2017). The analysis of mechanisms and their contingencies: PROCESS versus structural equation modelling. Australasian Marketing Journal, 25(1), 76–81. https://doi.org/10.1016/j.ausmj.2017.02.001 Hayes, S. J. L., & King, K. W. (2014). The social exchange of viral ads: Referral and co-referral of ads among college students. Journal of Interactive Advertising, 14(2), 98–109. https://doi.org/10.1080/15252019.2014.942473 Hennig-Thurau, T., Malthouse, E. C., Friege, C., Gensler, S., Lobschat, L., Rangaswamy, A., & Skiera, B. S. (2010). The Impact of New Media on Customer Relationships. Journal of Service Research, 13(3), 311–330. https://doi.org/10.1177/1094670510375460 Henseler, J., Ringle, C. M., & Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modeling. Journal of the Academy of Marketing Science, 43(1), 115– 135. https://doi.org/10.1007/s11747-014-0403-8 Heo, C. Y., & Hyun, S. S. (2015). Do luxury room amenities affect guests’ willingness to pay? International Journal of Hospitality Management, 46, 161–168. https://doi.org/10.1016/j.ijhm.2014.10.002 Kam, K. J., Lim, A. S. H., Al-obaidi, K. M., & Lim, T. S. (2018). Evaluating Housing Needs and Preferences of Generation Y in Malaysia. Planning Practice and Research, 33, 172–185. Advance online publication. https://doi.org/10.1080/02697459.2018.1427413 Kang, M. J. (2005). A Study on the Effect of Features of Brand Community Using One-person Media on Consumers. Master’s dissertation.Seoul National University. Kara, S., Gunasti, K., & Ross, W. T., Jr. (2020). My brand identity lies in the brand name: Personified suggestive brand names. Journal of Brand Management, 27, 607–621. https://doi.org/10.1057/s41262-020-00201-x Keller, K. L. (2003). Understanding brands, branding and brand equity. Interactive Marketing, 5(1), 7– 20. https://doi.org/10.1057/palgrave.im.4340213 Keller, K. L. (1993). Conceptualizing, Measuring, and Managing Customer-Based Brand Equity. Journal of Marketing, 57(1), 1–22. https://doi.org/10.1177/002224299305700101 Kim, A. J., & Ko, E. (2012). Do social media marketing activities enhance customer equity? An empirical study of luxury fashion brand. Journal of Business Research, 65(10), 1480–1486. https://doi.org/10.1016/j.jbusres.2011.10.014 Kim, S. S., & Son, J. Y. (2009). Out of dedication or constraint? A dual model of post-adoption phenomena and its empirical test in the context of online services. Management Information Systems Quarterly, 33, 49–70. https://doi.org/10.2307/20650278 Kusyanti, A., Puspa, H., Rahma, D., & April, Y. (2018). Teen’s Social Media Adoption: An Empirical Investigation in Indonesia. International Journal of Advanced Computer Science and Applications, 9(2), 380–384. https://doi.org/10.14569/IJACSA.2018.090252 Lee, Y. H., Hsieh, Y. C., & Hsu, C. N. (2011). Adding innovation diffusion theory to the technology acceptance model: Supporting employees’ intentions to use e-learning systems. Journal of Educational Technology & Society, 14(4), 124–137. Li, T. (2020). The Value of Access to Rail Transit in a Congested City: Evidence from Housing Prices in Beijing. Real Estate Economics, 48(2), 556–598. https://doi.org/10.1111/1540-6229.12222 Lien, C. H., Wen, M. J., Huang, L. C., & Wu, K. L. (2015). Online hotel booking: The effects of brand image, price, trust and value on purchase intentions. Asia Pacific Management Review, 20(4), 210– 218. https://doi.org/10.1016/j.apmrv.2015.03.005 Lissitsa, S., & Kol, O. (2016). Generation X vs. Generation Y–A decade of online shopping. Journal of Retailing and Consumer Services, 31, 304–312. https://doi.org/10.1016/j.jretconser.2016.04.015 Liu, M. T., Wong, I. A., Tseng, T. H., Chang, A. W. Y., & Phau, I. (2017). Applying consumer-based brand equity in luxury hotel branding. Journal of Business Research, 81, 192–202. https://doi.org/10.1016/j.jbusres.2017.06.014 Liu, X., Shin, H., & Burns, A. C. (2021). Examining the impact of luxury brand’s social media marketing on customer engagement: Using big data analytics and natural language processing. Journal of Business Research, 125, 815–826. https://doi.org/10.1016/j.jbusres.2019.04.042 Lojanica, V., Colic-Damjanovic, V. M., & Jankovic, N. (2018). Housing of the Future: Housing Design of the Fourth Industrial Revolution. 5th International Symposium on Environment-Friendly Energies and Applications (EFEA), 1-4. https://doi.org/10.1109/EFEA.2018.8617094 REAL ESTATE MANAGEMENT AND VALUATION, eISSN: 2300-5289 vol. 30, no. 1, 2022 www.degruyter.com/view/j/remav Longo, I., & Saxena, D. (2020). Self-brand Connection in the Digital Age: A Qualitative Exploration of Brand Usage on Instagram for Identity Creation among Millennials. In Proceedings of the 20th Portuguese Association for Information Systems Conference, UniversidadePortucalense, Porto, Portugal. Malhotra, N. K., Nunan, D., & Birks, D. F. (2017). Marketing research: An applied approach. Pearson Education Limited. Manthiou, A., Chiang, L. T. A. N. G. L. R., & the Liang (Rebecca) Tang. (2013). Identifying and responding to customer needs on Facebook fan pages. [IJTHI]. International Journal of Technology and Human Interaction, 9(3), 36–52. https://doi.org/10.4018/jthi.2013070103 Mgiba, F. M., & Nyamande, N. (2020). Persuasive Influencers and the Millennials: How their relationships affect brand, value, and relationship equities, and customers’ intention to purchase. Journal of Contemporary Management, 17(2), 492. https://doi.org/10.35683/jcm19115.88 Mohajan, H K., (2017). Two Criteria for Good Measurements in Research: Validity and Reliability. Annals of SpiruHaret University: Economic series, 17(3), 58-82. https://doi.org/10.26458/1746 Moresjo, S., & Xin, Y. (2020). Does CSR really influence Millennials’ purchase decisions? A qualitative study on attitudes toward the fast fashion industry. Masters degree thesis: Jonkoping University. Mulyano Y., Rahadi R A., & Amaliah U. (2020). Millennials Housing Preferences Model in Jakarta. European Journal of Business and Management Research, 5(1). Muntinga, D., Moorman, M., & Smit, E. (2011). Introducing COBRAs: Exploring motivations for brand-related social media use. International Journal of Advertising, 30(1), 13–46. https://doi.org/10.2501/IJA-30-1-013-046 Nam, K., & Yeo, J. (2011). Study on consumers’ acceptance proceed of mobile advertising. J. Consum. Stud., 22(4), 1–28. Nasution, M. I., Fahmi, M., Jufrizen., Muslih., & Prayogi, M. A. (2020). The Quality of Small and Medium Enterprises Performance Using the Structural Equation Model-Part Least Square (SEM- PLS). Journal of Physics: Conference Series. Journal of Physics: Conference Series, 1477, 052052. https://doi.org/10.1088/1742-6596/1477/5/052052 Nethercote, M. (2020). Build-to-Rent and the financialization of rental housing: Future research directions. Housing Studies, 35, 839–874. Advance online publication. https://doi.org/10.1080/02673037.2019.1636938 Noble s., Haytko D., Phillips J., (2009), What drives college-age Generation Y consumers? Journal of business research, Vol, 62, no. 6, pp. 617-628. Öztürk, M., & Batum, T. P. (2019). How Housing Brands Use Social Media In Their Marketing Communications? A Content Analysis. YönetimBilimleriDergisi, 17(33), 111–135. Pandey, A., Sahu, R., & Dash, M. K. (2018). Social media marketing impact on the purchase intention of millennials. International Journal of Business Information Systems, 28(2), 147–162. https://doi.org/10.1504/IJBIS.2018.091861 Park, N., Kee, K. F., & Valenzuela, S. (2009). Being immersed in social networking environment: Facebook groups, uses and gratifications, and social outcomes. Cyberpsychology & Behavior, 12(6), 729–733. https://doi.org/10.1089/cpb.2009.0003 PMID:19619037 Phan, M., Thomas, R., & Heine, K. (2011). Social media and luxury brand management: The case of Burberry. Journal of Global Fashion Marketing, 2(4), 213–222. https://doi.org/10.1080/20932685.2011.10593099 Qu, H., Kim, L. H., & Im, H. H. (2011). A model of destination branding: Integrating the concepts of the branding and destination image. Tourism Management, 32(3), 465–476. https://doi.org/10.1016/j.tourman.2010.03.014 Quesenberry, K. A. (2020). Social media strategy: Marketing, advertising, and public relations in the consumer revolution (2nd ed.). Bowman & Littlefield. Rahman, Z., & Yadav, M. (2018). The influence of social media marketing activities on customer loyalty: A study of e-commerce industry. Benchmarking, 25(9), 3882–3905. https://doi.org/10.1108/BIJ-05-2017-0092 Ramanathan, U., Subramanian, N., & Parrott, G. (2017). Role of social media in retail network operations and marketing to enhance customer satisfaction. International Journal of Operations & Production Management, 37(1), 105–123. https://doi.org/10.1108/IJOPM-03-2015-0153 Román, S., & Sánchez-siles, L. M. (2018). Parents’ choice criteria for infant food brands: A scale development and validation. Food Quality and Preference, 64, 1–10. https://doi.org/10.1016/j.foodqual.2017.10.008 REAL ESTATE MANAGEMENT AND VALUATION, eISSN: 2300-5289 vol. 30, no.1, 2022 www.degruyter.com/view/j/remav Romaniuk, J., & Nenycz-thiel, M. (2013). Behavioral brand loyalty and consumer brand associations. Journal of Business Research, 66(1), 67–72. https://doi.org/10.1016/j.jbusres.2011.07.024 Ryan, J., & Casidy, R. (2018). The role of brand reputation in organic food consumption: A behavioral reasoning perspective. Journal of Retailing and Consumer Services, 41, 239–247. https://doi.org/10.1016/j.jretconser.2018.01.002 Sääksjärvi, M., & Samiee, S. (2007). Nonprice antecedents of consumer preference for cyber and extension brands. Journal of Interactive Marketing, 21(1), 22–35. https://doi.org/10.1002/dir.20072 Sanmiguel, P., Guercini, S., & Sádaba, T. (2018). The impact of attitudes towards influencers amongst millennial fashion buyers. Studies in Communication Sciences, 18(2), 439–460. Saravanakumar, M., & Suganthalakshmi, T. (2012). Social media marketing. Life Science Journal, 9(4), 4444–4451. Sari, D. M F P., & Yulianti, M. N. D. R. (2019). Celebrity Endorsement, Electronic Word of Mouth and Brand Trust on Buying Habits: Fashion Women Online Shop Products in Instagram. International Journal of Social Science and Humanity, 3(1), 82–90. Scherer, R., Siddiq, F., & Tondeur, J. (2019). The technology acceptance model (TAM): A meta-analytic structural equation modeling approach to explaining teachers’ adoption of digital technology in education. Computers & Education, 128, 13–35. https://doi.org/10.1016/j.compedu.2018.09.009 Schivinski, B., Langaro, D., Fernandes, T., & Guzmán, F. (2020). Social media brand engagement in the context of collaborative consumption: The case of AIRBNB. Journal of Brand Management, 27, 645– 661. https://doi.org/10.1057/s41262-020-00207-5 Schmidtke, D., Rundle-Thiele, S., Kubcaki, K., & Burns, G. L. (2021). Co-designing social marketing programs with “bottom of the pyramid” citizens. International Journal of Market Research, 63(1), 86– 105. https://doi.org/10.1177/1470785320968029 Seo, E. J., & Park, J. W. (2018). A study on the effects of social media marketing activities on brand equity and customer response in the airline industry. Journal of Air Transport Management, 66, 36–41. https://doi.org/10.1016/j.jairtraman.2017.09.014 Shao, G. (2009). Understanding the appeal of user‐generated media: A uses and gratification perspective. Internet Research, 19(1), 7–25. https://doi.org/10.1108/10662240910927795 Shareef, M. A., Mukerji, B., Dwivedi, Y. K., Rana, N. P., & Islam, R. (2017). Social media marketing: Comparative effect of advertisement sources. Journal of Retailing and Consumer Services, 46(C), 58– Singh, A., & Kathuria, L. M. (2016). Understanding drivers of branded food choice among low-income consumers. Food Quality and Preference, 52, 52–61. https://doi.org/10.1016/j.foodqual.2016.03.013 Singh, J., & Kaur, R. (2021). Influencing the Intention to Adopt Anti-Littering Behavior: An Approach With Modified TPB Model. Social Marketing Quarterly, 27(2), 117–132. https://doi.org/10.1177/15245004211013333 Sissons, P., & Houston, D. (2019). Changes in transitions from private renting to homeownership in the context of rapidly rising house prices. Housing Studies, 34(1), 49–65. https://doi.org/10.1080/02673037.2018.1432754 Sniehotta, F.F., Presseau, J., & Araújo-Soares, V. (2014). Time to retire the theory of planned behaviour. Health Psychology Review, 8(1), 1-7. https://doi.org/10.1080/17437199.2013.869710 Sniehotta, F. F., Presseau, J., & Araújo-Soares, V. (2014). Time to retire the theory of planned behaviour. Health Psychology Review, 8(1), 1–7. https://doi.org/10.1080/17437199.2013.869710 PMID:25053004 Taylor, D. G., Lewin, J. E., & Strutton, D. (2011). Friends, Fans, and Followers: Do ads work on social networks? Journal of Advertising Research, 51(1), 258–275. https://doi.org/10.2501/JAR-51-1-258-275 Taylor, P., & Keeter, S. (2010). Millennials: Confident. Connected. Open to Change. Retrieved from http://www.pewsocialtrends.org/files/2010/10/millennials-confident-connected-open-to- change.pdf Teo, T., Zhou, M., & Noyes, J. (2016). Teachers and technology: Development of an extended theory of planned behaviour. Educational Technology Research and Development, 64(6), 1033–1052. https://doi.org/10.1007/s11423-016-9446-5 Van Esch, P., Mente, M. (2018). Marketing video-enabled social media as part of your e-recruitment strategy: Stop trying to be trendy. Journal of Retailing and Consumer Services, 44, 266-273. REAL ESTATE MANAGEMENT AND VALUATION, eISSN: 2300-5289 vol. 30, no. 1, 2022 www.degruyter.com/view/j/remav Vitelar, A. (2019). Like Me: Generation Z and the Use of Social Media for Personal Branding. Management Dynamics in the Knowledge Economy, 7(2), 257–268. Vollmer, C., & Precourt, G. (2008). Always on: Advertising, marketing and media in an era of consumer control. McGraw-Hill. Wang, H., Yu, F., & Zhou, Y. (2020). Property Investment and Rental Rate under Housing Price Uncertainty: A Real Options Approach. Real Estate Economics, 48(2), 633–665. https://doi.org/10.1111/1540-6229.12235 Wang, S., Wang, W., & Lee, S. (2018). Interactive roles of social identity and evaluative attitudes in sports events participation. Journal of Convention & Event Tourism, 19(4-5), 327-346. https://doi.org/10.1080/15470148.2018.1488640 Watzlawick, P., Bavelas, J. B., & Jackson, D. D. (2011). Pragmatics of human communication: A study of interactional patterns, pathologies and paradoxes. WW Norton & Company. Wiid, J., & Diggines, C. (2015). Marketing research (3rd ed.). Juta and Company. Wilcox, K., Kim, H. M., & Sen, S. (2009). Why do consumers buy counterfeit luxury brands? JMR, Journal of Marketing Research, 46(2), 247–259. https://doi.org/10.1509/jmkr.46.2.247 Yadav, M., & Rahman, Z. (2017). Social media marketing: Literature review and future research directions. International Journal of Business Information Systems, 25(2), 213–240. https://doi.org/10.1504/IJBIS.2017.083687 Yang, W., Zhang, L., & Mattila, A. S. (2016). Luxe for less: How do consumers react to luxury hotel price promotions? The moderating role of consumers’ need for status. Cornell Hospitality Quarterly, 57(1), 82–92. https://doi.org/10.1177/1938965515580133 Zenker, S., Braun, E., & Petersen, S. (2017). Branding the destination versus the place: The effects of brand complexity and identification for residents and visitors. Tourism Management, 58, 15–27. https://doi.org/10.1016/j.tourman.2016.10.008 Zhou, F., Mou, J., Su, Q., & Wu, Y. C. J. (2019). How does consumers’ Perception of Sports Stars’ Personal Brand Promote Consumers’ brand love? A mediation model of global brand equity. Journal of Retailing and Consumer Services, 54, 1–10. Zhou, T., Lu, Y., & Wang, B. (2009). The relative importance of website design quality and service quality in determining consumers’ online repurchase behaviour. Information Systems Management, 26(4), 327–337. https://doi.org/10.1080/10580530903245663 Zhu, Y. Q., & Chen, H. G. (2015). Social media and human need satisfaction: Implications for social media marketing. Business Horizons, 58(3), 335–345. https://doi.org/10.1016/j.bushor.2015.01.006 REAL ESTATE MANAGEMENT AND VALUATION, eISSN: 2300-5289 vol. 30, no.1, 2022 http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Real Estate Management and Valuation de Gruyter

Social Media Marketing Attributes, Sandton’s Rental Market Brand Image, and the Millennials’ Rental Preference: An Empirical Study

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de Gruyter
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© 2022 Mthobisi Nhlabathi et al., published by Sciendo
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1733-2478
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2300-5289
DOI
10.2478/remav-2022-0004
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Abstract

A good image of millennials’ residential rental space is an important issue. This image can be impacted by the available telecommunication technology. Social media marketing can, therefore, be an important marketing tool to achieve it. Many studies have shown that a good brand image positively impacts brand preference. This study quantitatively investigated the impact of social media attributes of trendiness, entertainment, customization, information, interaction on Sandton’s rental market’s brand image, and the relationship between this image and millennials’ rental preference. Data were collected from millennials who have lived, live or intend to live in Sandton. Structural equation modeling was employed for data analysis. The findings of the study are that entertainment, customization, and information positively impact Sandton’s image and that trendiness and interactions do not. Also, the image of Sandton’s rental market has a positive influence on the millennials’ preferences as to rental housing. The outcomes will find application for both academics and management practice as will be shown below. Key words: Millennials, Social media marketing attributes, Sandton rental housing brand image, Sandton rental housing brand preference. JEL Classification: M31; M37; O18; O35. Citation: Nhlabathi, M., Mgiba, F.M., & Ligaraba, N. (2022). Social media marketing attributes, sandton’s rental market brand image, and the millennials’ rental preference: an empirical study. Real Estate Management and Valuation, 30(1), 34-52. DOI: https://doi.org/10.2478/remav-2022-0004 1. Introduction The world is characterized by rising housing costs (Galesetr & Gyourko, 2018), which in turn limits homeownership among people (Sissons & Houston, 2019). The situation is further complicated by the REAL ESTATE MANAGEMENT AND VALUATION, eISSN: 2300-5289 vol. 30, no.1, 2022 www.degruyter.com/view/j/remav volatility of housing markets (Chang, 2020; Wang et al., 2020). These issues change the accessibility of housing for new entrants, and therefore have implications for the residential real estate markets. The impacts are even more severe for the millennials (Mulyano et al., 2020) because this group’s attitude towards housing is affected by special drivers (Mishra et al., 2020). Before further elaborating on millennials and their relationship with the residential housing markets, it is prudent to describe this group of people. Different periods of birth are attributed to millennials. For example, they are seen as people that were born between 1999 and 2002 (Blair, 2017). Deka (2018), on the other hand, defines them as persons born in the 1980s and 1990s. It is generally accepted, however, that these people were born during a time of rapid internet and technology growth (Blair 2017). It is the first generation to grow up surrounded by digital media, people who consider computers and mobile phones to be essential tools for many activities (SanMiguel et al. 2018), who are accustomed to buying and socializing online (SanMiguel et al., 2018). Due to their easy access to technology, a case can be made for the use of technology by housing brands to target this segment (Öztürk & Batum, 2019). They also have unique characteristics in terms of easy access to social media and the usage thereof (Vitelar, 2019), their liking of interactive brand communications (Atthwal & Istanbulluoglu, 2019), their brand preferences on many products and services (Longo & Saxena, 2020; Ali &Alyani, 2019), bias towards customized products and services, and their fondness of products and services that are trendy (Hassanzadeh & Namdar, 2018; Pandey et al., 2018). These are some of the constructs that define millennials. A legitimate question would be whether these special traits can also be profitably harnessed by the rental housing industry, especially for a developing country like South Africa? If yes, can a permutation of these constructs lead to brand preference and possible e-word of mouth marketing opportunities? According to Circella et al. (2017), there is still a lack of comprehensive data on the factors affecting millennials’ choices of residential location. Their housing unit preferences present enormous scope for further academic exploration. In general, people’s preference indicators for residential areas are location, accessibility, price, physical attributes, facilities, design aesthetics, and developer reputation (Mulyano et al., 2020). However, these people have different lifestyles (Circella et al., 2017), are more prone to rent a property than to buy it (Godelnik, 2017), and are more likely to relocate to high-wage and high-productivity areas (Blake, 2019; Glaeser & Gyourko, 2018; Li, 2020). Their unique consumption behavior is the most probable cause behind the increased rental demand throughout the world. In the light of these trends, this group deserves special academic scrutiny. Further, Sandton, as a sought-after place to rent property, provides an attractive setting for this study. Sandton is the richest square mile of land on the African continent (Laughton et al., 2015). It is the home to the Johannesburg Stock Exchange (largest stock market in Africa), head office to most of Africa’s largest banks and corporates (Africa’s wealth report 2021). It is a modern city gleaming with high-rise architecture, retail outlets, modern hospitals, and clean residential areas (Kelleher, 2018). As a city, it attracts representatives of world capital and skill (Lahire, 2008). Sandton epitomizes consumption, affluence and power. Its’ network of malls, restaurants, nightclubs, and hotels offers the possibility of conspicuous consumption. Sandton also contains one of Africa’s most advanced transport systems, exemplified by the Gautrain (Arnold et al., 2017). Its’ nature and character can be a magnet that attracts upwardly mobile millennials. There is, generally, a decline in homeownership amongst working-class people (Aramburu, 2015). Across the world, 1.2 billion people live in rented accommodation (Gilbert, 2016). Millennials form a big chunk of that figure, as will be shown below. In some countries, their share of the population ranges between 25% and 27%. Their motivation towards choices of rented dwellings becomes an attractive academic pursuit. When people choose rental housing units, dwelling-related factors, such as unit size, or the number of rooms and bathrooms have an impact on their decisions. However, Kam et al., (2018) state that neighborhood attributes have a greater impact on people’s housing selections. With the increased mobility of millennials to urban areas (Nethercote, 2020), do these factors still hold true, even for this market, or are there other factors that only apply to them? As shown above, for the millennials, the internet and social network sites have become important communication media (Taylor & Keeter, 2010). Further, rental housing transactions are moving online as the internet offers divergent possibilities (Boeing, 2020). The birth of Social media marketing has ushered in many possibilities. According to Schmidtke et al. (2021), SMM interventions produce positive outcomes for business. Can the advent of social media marketing (SMM) be harnessed to effectively target the millennials in the rental housing market? There is generally a dearth of literature that devotes attention to this specific REAL ESTATE MANAGEMENT AND VALUATION, eISSN: 2300-5289 vol. 30, no. 1, 2022 www.degruyter.com/view/j/remav generation’s motivations when deciding on rental housing neighborhoods. This study was conceptualized in response to this gap. The purpose of the study was to investigate the possible effects of social media marketing on millennials’ rental housing brand image and preferences with specific reference to Sandton in Johannesburg. The study variables are social media marketing SMM attributes (entertainment, interactions, information, customization, and trendiness), brand image and brand preference. For other contexts, SMM is an important platform for promoting a brand image, thus influencing brand preference, especially for the tech-savvy Millennials market (Lissitsa & Kol, 2016). The relationships between these attributes, brand image, and brand preference with regards to the Sandton rental market and millennial consumers are hypothesized below. The study uses a well- established theory of planned behavior (TPB) to develop a conceptual model that will advance the understanding of the interaction of millennials, social media, and the rental housing industry. The conceptual model extends the application of this grounding theory to include the rental market for an African city. This will open up more avenues for future research on the millennials’ consumption behavior in the fourth industrial revolution era. This study also has management implications. Presently, there is a move of millennials to urban areas which offer better socio-economic opportunities (Galimullin, 2019). There is, also, an increase of institutional investors into these urban rental markets (Nethercote, 2020). A better understanding of this market, especially for a developing country, would help managers to better respond to this target group’s rental housing needs. This would improve the effectiveness of their planning and decrease the number of unrented properties. The remainder of the article is organized in the following way. The first part deals with a literature review. This is followed by research methodology, data analysis, and a discussion of the results. The study concludes by stating some limitations and gives directions for future research. 3. Literature review The literature review subsection covers the grounding theory, concept development, conceptual model, and hypotheses development. 3.1. Grounding theory This study is grounded on the theory of planned behavior (TPB). According to TPB, perceived brand awareness, affordability, consumer attitude, usefulness, and availability influence brand preference (Singh & Kathuria, 2016). The TPB proposes that volitional human behavior is a function of the intention to perform the behavior and perceived behavioral control (PBC). The intention is hypothesized to be a function of attitudes towards the behavior, subjective norm, and perceived behavioral control. Attitudes, subjective norms, and PBC are assumed to be based on the strength and evaluation of accessible behavioral, normative, and control beliefs (Sniehotta et al., 2014). The theory is well-placed to explain behavioral intentions, and persuasive use of technology (Teo et al., 2016). It has been successfully applied to other social media’s influence on purchase intentions (Harun & Husin, 2019). Also, the subjects for the present study are millennials, whose behavior is greatly impacted by social media technology. The rationale for the choice of the grounding theory will be shown along with the discussion of the results. 3.2. Construct development, conceptual model, and hypotheses development The constructs of interest for the present study are social media marketing attributes as described above, namely: entertainment, information, interactive, trendiness, customization, and the well- known concepts of brand image and brand preference as applied to rental housing choices for South African millennials. This study hypothesizes positive relationships between these SMM attributes and millennials’ Sandton brand image, and between Sandton brand image and the millennials’ Sandtonbrand preference. 3.2.1. Social media marketing (SMM) Millennials’ purchasing behavior can be affected by social media marketing (Harun &Husin, 2019). Social media has become the method of statement in the 21st century, enabling people to express their beliefs, ideas, and manners in a new way. According to Singh and Kaur (2021), SMM targets these subjective aspects. Schivinski et al. (2020) further confirm that SMM has the potential to positively influence customer perceptions, brand image, and their future engagements with any brand. Perhaps these positive aspects of SMM can be partly explained by its ability to create a platform for online REAL ESTATE MANAGEMENT AND VALUATION, eISSN: 2300-5289 vol. 30, no.1, 2022 www.degruyter.com/view/j/remav community collaboration, social commerce, sharing, and collaborative lifestyles (Garrett et al., 2017).Social media comes in many forms and the eight most popular are: Blogs, Microblogs, Social Networks, Media-Sharing Sites, Social Bookmarking and selection Sites, analysis Sites, and forums (Saravanakumar & SuganthaLakshmi, 2012). Social media has given birth to Social media marketing (SMM) (Yadav & Rahman, 2017), which has become an important platform to reach a wider consumer market by enabling brand-consumer interaction (Constantinides, 2014). Social media marketing can be a medium through which consumers and businesses can communicate within a limited time, allowing all parties to use, experience, and gain benefits (Dwivedi et al., 2015). Apart from that, social media marketing uses social media technologies, channels, and software to create, communicate, deliver, and exchange offerings that are valuable for organizations (Harun & Husin, 2019).Some of the benefits of SMM are the following: increased market exposure, increased customer traffic, new business partnerships, and reduced marketing expenditure (Constantinides, 2014). It has been further noted that organizations involved in SMM experience growth in both revenue margins (Constantinides, 2014). Social media marketing activities have five attributes, namely: entertainment, interaction, trendiness, information, and customization (Kim & Ko, 2012; Seo & Park, 2017). These attributes form the basis for the present study and are thus further discussed below. For brands that target the highly tech-savvy Millennials, the SMM platform presents an ideal platform (Lissitsa & Kol, 2016). Indeed, many industries are already exploiting this opportunity. Examples are luxury brands (Kim & Ko, 2012; Phan et al., 2011), airlines (Seo & Park, 2017), e-commerce practitioners (Yadav & Rahman, 2017), insurance (Sano, 2015), and area branding (de Noronha et al., 2017). These applications justify the extension of the application of SMM attributes to study the rental housing markets. The above- mentioned attributes are discussed separately, and their relevance to the present study is highlighted. 3.2.2. Entertainment in Sandton Entertainment is the capacity to fulfill an individual’s needs for escapism, diversion, aesthetic enjoyment, or emotional enjoyment (Harshini, 2015). It is connected to enjoyment, relaxation, and pastime (Muntinga et al., 2011). Something is entertaining when it is pleasurable and motivating (Shao, 2009), produces positive emotions (Seo & Park, 2017), and is joyful, exciting, and cool (Muntinga et al., 2011). Consequences of entertainment include engagement with online content, positive emotions, and intended continuous usage of the platforms (Seo & Park, 2017). Social media users have different motivations for using social media platforms, including finding pleasure and entertainment from using such platforms (Godey et al., 2016; Manthiou et al., 2013). Users derive pleasure from engaging with peers for commercial and non-commercial purposes (Hayes & King, 2014; Shareef et al., 2017). The more pleasant such platforms are to use (including escapism and relaxation aspects), the more consumers (Millennials) will take in the brand-related content (Muntinga et al., 2011). Sandton is home to many shopping malls, casinos, major sporting facilities, etc. Its rental market can project itself as a beautiful place (Harshini, 2015), pleasurable to live in (Sao 2009) and with an advanced technology infrastructure to attract the millennial audience. The proximity to places of entertainment could also be emphasized. 3.2.3. Trendiness of Sandton Trendiness implies being fashionable (Moresjo & Xin, 2020), being popular, and being a symbol of status (Marone, 2017). It refers to the currency of the object or topic under discussion. Trendiness is closely related to the word of mouth commendation (Sari & Yulianti, 2019). In the social media marketing context, this will mean electronic word of mouth. With the increasing popularity of social media, customers demand immediate access to brand information and frequently utilize the information available on various social media to make purchase decisions (Vollmer & Precourt, 2008). Within this environment, trendiness entails the provision of inspiring brand-related information and online product reviews amongst virtual brand communities (Muntinga et al., 2011). For the Sandton brand, online communication of information about the availability of good quality food such as sushi and the access to the high-end popular millennial restaurants would portray it as a symbol of status. As a rental market, Sandton can also position itself as a trendy place, an ideal destination for innovation, and techno-savvy individuals (Van Esch & Mente, 2018). Trendiness can also mean the extent to which the luxury brand disseminates the latest and trendiest information about the brand. The millennials consider social media to be a REAL ESTATE MANAGEMENT AND VALUATION, eISSN: 2300-5289 vol. 30, no. 1, 2022 www.degruyter.com/view/j/remav trustworthy, trendy source for important up-to-date brand information (Liua et al., 2019). To further boost its image as a trendy rental housing market, landlords can ensure that advertisements about available rental stock frequently update information, unlike printed communication. The advertisements can include hot topics and accurate and trendy content. Customers tend to trust and prefer brands that provide updated content (Naman et al., 2011). 3.2.4. Interaction in Sandton The participatory nature of social media readily enables collaboration and sharing of contents, including information, video, and pictures (Hennig-Thurau et al., 2010). Interactiveness refers to the ability to allow for the sharing and exchanging of information with others. The interactivity of social media posting is important because it promotes customer reactions, such as liking and commenting on the firm's post (Liu et al., 2021). According to Kim and Ko (2012), social media platforms are aimed at facilitating interactions between users (i.e., inter-consumer interaction, consumer-brand, etc.), among other things. Enormous possibilities exist for Sandton to promote itself as a rental market of choice. The place can communicate messages of its suburbs that allow for social interactions. As an illustration, Sandton has excellent neighborhoods, online connectivity, social amenities, and a good road network for ease of movement (Abass et al., 2020). 3.2.5. Customization of Sandton rental market The era of social media has offered brands the ability to customize information targeted at individual customers (Seo & Park, 2017). Customization refers to the modification of a product or service to fulfill the needs or preferences of a customer or a small group of consumers (Godey et al., 2016). For social media, Zhu and Chen (2015) defined customization as tailored brand-specific messages, targeted at an individual or a niche market. Social media marketing has a greater ability to get very close to customers and to enable brands to customize their communication with customers (Seo & Park, 2017).There are endless opportunities for Sandton city to be the rental place of choice for millennials. Businesses can brand it as a evolving neighborhood of smart rental housing market (Tomal, 2020), acity in which housing transaction platforms are online, and as a city that is future-ready in terms of the fourth industrial revolution (Lojanica & Colic-Damajanovic, 2018). 3.2.6. Information access in Sandton Consumers learn and develop understanding by analyzing marketing messages (Shareef et al., 2017). Information contained in brand-related posts can influence consumer awareness, result in positive perceptions and preference for a brand (Hayes & King, 2014). Social media users participate in social media activities for various reasons, including seeking useful information for decision-making purposes (Chang et al., 2015). Customers seek brand-related information on social media (e.g., Sandton brand), which influences their brand perceptions (Muntinga et al., 2011). Such information could include the best area to rent an apartment based on specific requirements by the tenant. The quality of information on social media platforms is determined by, among other factors, its persuasive power to positively influence recipient perceptions and change their attitudes (Chang et al., 2015). Sandton, as a brand, can utilize several approaches when targeting millennials. Firstly, the media of choice should be telecommunication social media (Kusyanti et al., 2018). Businesses can use persuasive influencer user-generated information advertisements (Shareef et al., 2018) and graphic information of the city. 3.3. Sandton brand Image Brand image is a key pillar of brand equity which influences consumer perceptions, attitudes, and preferences towards a brand (Chovanova et al., 2015);it is the perceptions a consumer has about a brand, which includes feelings for the brand as well as other related factors (Keller, 1993). Brand image and brand associations are interchangeable concepts because they both refer to a consumers’ memory about a brand which influences their perceptions and, ultimately, attitudes towards that brand (Romaniuk & Nenycz-Thiel, 2013). A strong brand image enhances consumer brand equity and the willingness to pay a premium price for luxury brands (Liu et al., 2017). As a rental housing destination, there are several things that Sandton can engage in. It can promote itself as an environmentally friendly city that is ideal for the life experiences of upwardly mobile millennials (Aitken & Campelo, 2011). This can be partly achieved by communicating its brand positioning REAL ESTATE MANAGEMENT AND VALUATION, eISSN: 2300-5289 vol. 30, no.1, 2022 www.degruyter.com/view/j/remav messages to attract mobile talent, residents, tourists, and investment (Cleave et al., 2017). This would amount to re-imaging the place to differentiate itself and create a favorable image which will positively affect how millennials perceive it (Blakely & Leigh, 2013). Lastly, Sandton can use its image as a brand that portrays personal characteristics that are used by millennials (Kara et al., 2020).  3.4. Sandton brand Preference Usually, a consumer chooses one brand over its competitors because of the perceived brand strength in the consumer’s mind (Godey et al., 2016). It is reasonable to conclude that the final purchase decision is preceded by brand preference. Brand preference is a personal feeling and interest towards a brand (Chang et al., 2015). Positive brand perception is one of the factors which positively influence consumer attitudes and, ultimately, preference for a brand (Aghekyan-Simonian et al., 2012). For millennials who monitor trends in the market, finding useful information on rental housing on social media would improve their perceptions of the brand. For the rental market, marketing communication should be geared toward producing a positive predisposition which would result in millennials consistently preferring it over other neighboring suburbs or cities (Duffett et al., 2019). Several options are available for the Sandton rental housing market. It can communicate messages that consistently project an image of a place that people like to live in (Duffet et al., 2019). It can be promoted as a destination of choice that other millennials would always choose over others (Adnyana & Respati, 2019). One of the attributes to promote would be Sandton’s location efficiencies (Gabeet et al., 2021). 3.5. Research model and hypotheses development The study proposes the conceptual model shown in Figure 1. The model proposes that, for millennials, the SMM attributes have a positive impact on Sandton rental brand image, which, in turn, impacts their preference for the city. Hypotheses development for the present study follows. Intervening Variable Outcomes Predictors Entertainment H1 Trendiness H2 Interaction Brand Brand H3 Preference Image H6 H4 Information H5 Customization Fig.1. Proposed conceptual model. Source: Authors’ study. 3.5.1. Entertainment and Sandton brand image Social media platforms provide fun, joy, and entertainment (Shareef et al., 2018). The entertainment element of SMM is an important factor in influencing the perceived brand image (Kang, 2005; Seo & Park, 2017). Consumers who perceive a brand’s social media presence as fun, exciting and cool will have positive perceptions of its image (Muntinga et al., 2011; Taylor et al., 2011). Media users engage on social media platforms to seek excitement from usage as well as communicating with other users REAL ESTATE MANAGEMENT AND VALUATION, eISSN: 2300-5289 vol. 30, no. 1, 2022 www.degruyter.com/view/j/remav (Hayes & King, 2014; Pietro & Pantano, 2012). Thus, drawing from the above literature, the study proposes that: H1: Availability of entertainment positively influences attitude towards Sandton brand image. 3.5.2. Trendiness and Sandton brand image Customer feedback on social media is an important factor influencing product or service performance (Ramananthan et al., 2015). An active social media presence positively affects brand image (Godey et al., 2016). Consumers tend to show confidence towards and preference for brands that provide trendy information (Naman et al., 2011). Providing trendy content helps brands develop and strengthen their image (Vollmer & Precourt, 2008). Based on these arguments, it can be hypothesized that: H2: The trendiness of SMM content on Sandton positively influences Sandton’s brand image. 3.5.3. Interaction and Sandton brand image Social media are online platforms, applications and media aimed at facilitating interactions (Kim & Ko, 2012). They enable easier and more efficient ways to perform marketing activities, thus impacting a brand’s reputation (Kim & Ko, 2012). Social media users develop positive perceptions towards a brand, which offers them the opportunity to engage with the brand products or services (Bilgin, 2018). It can therefore be concluded that the link between social media interaction and brand image is positive. Indeed, social media are very effective in facilitating the interaction between business and customers, and in creating a positive brand image (Fortezza & Pencarelli, 2015). Social media strengthens brand image through its interactive nature of communication (Godey et al., 2016). The implications for Sandton city rental property owners are that they need to create valuable content that the millennials find entertaining or useful via social media in order to create a positive brand image (Quesenberry, 2020).   Based on the above argument, the study proposes hypothesis H3. H3:SMM interaction positively affects Sandton’s brand image for the millennial consumer. 3.5.4. Information and Sandton brand image Consumers utilize social media platforms to seek brand-related content information (Lin & Lu, 2011; Dholakia et al., 2004). Social media informative brand posts positively affect consumer attitudes towards a brand (de Vries et al., 2012) because social media users tend to develop positive attitudes towards informative brand content (Taylor et al., 2011). When consumers receive relevant and useful information regarding a brand’s products and services, positive consumer perceptions are likely to develop or be strengthened (Zhou et al., 2019). When consumers get useful information on social media platforms, they develop a stronger brand preference towards such a brand. Positive brand perceptions can lead to increased brand preference and positive WOM. The above arguments led to the hypothesis below: H4: Informative SMM content positively influences Sandton’s brand image. 3.5.5. Customization and Sandton brand image Customized information is the second most popular element of SMM, as consumers prefer receiving information that suits their needs (Seo & Park, 2017). Brands can use customized content and direct contact with individual consumers to emphasize their brand differentiation among rivals, thus strengthening their consumer-based perceived brand image (Ding & Keh, 2016). Developing and strengthening a distinct identity is good for a brands’ competitive edge in the market (Seo & Park, 2017). Based on the above argument, the hypothesis below was derived. H5: SMM customization positively affects Sandton’s brand image. 3.5.6. Sandton’s brand image and brand Preference This influence of brand image on perceptions and ultimately customer behavior has received attention from many researchers (Lien et al., 2015). It is now safe to state that the perceived value of a brand is determined by its brand image, and this influences consumers’ preference for that brand (Chow et al., REAL ESTATE MANAGEMENT AND VALUATION, eISSN: 2300-5289 vol. 30, no.1, 2022 www.degruyter.com/view/j/remav 2017). A positive brand image influences consumer attitudes positively, causing a positive impact on consumer behavior (Aghekyan-Simonian et al., 2012). Brand image helps brands distinguish themselves among rivals and these distinguishing features can be used as a basis for customer brand preferences. A positive brand image influences consumer attitudes and behavior positively, as well as leading to brand preference (Aghekyan-Simonian et al., 2012). Social media platforms are important channels for developing and enhancing consumer-based brand image (Yadav & Ragman, 2017; Godey et al., 2016). SMM can impact brand image and this might positively influence their brand preference. Further, area branding and marketing influence consumer perceptions and ultimately brand preference towards an area, either for rental or homeownership (Zenker et al., 2017).The above argument leads to the hypothesis below. H6:Sandton’s brand image positively influences millennial’s brand preference. 4. Data and methods This subsection describes the target population and sampling, the measurement instrument, data gathering, ethics, data analysis, and results. 4.1. Target population and sampling The research targeted the millennials who have lived, live, or consider living in or within a 15- kilometer radius from Sandton City, as they are assumed to be extensive social media users and acceptors of social meanings given by influencers (Mgiba & Nyamande, 2020). This is in line with other studies that concentrated on either influencer marketing or the use of social media (Yadav & Rahman, 2018). Most of the participants came from the Sandton CBD area, Bryanston, Fourways, Craighall, Hurlingham, Illovo, Morningside, Rivonia, Sandhurst and Sunninghill. Considering the nature of the target market and the difficulty of obtaining a sampling frame, this study employed non- probability convenience sampling (Malhotra et al., 2017). Data collection achieved a sample size of 408 responses, which is well within the required range of a 95% confidence level, 50% population variability, and the sample size requirement for the Structural equation modeling analysis technique (Bartlett et al., 2001) 4.2. Measurement instrument A multi-item scale was used to measure the constructs used in this study, as adopted from previous studies (Seo & Park, 2017; Yadav & Rahman, 2017). Each construct had 8 items, with a 7-point Likert scale used (i.e. from 1 = Strongly Agree to 7 = Strongly Disagree). The measurement instrument was assessed and approved for content validity by senior lecturers within the department of Marketing Department of a Johannesburg-based university. A pilot project involving 30 participants was conducted before the final version of the instrument was distributed for data collection. 4.3. Data gathering A research company was used for data collection and analysis. Participants were sent the survey link through email, social media platforms, and other web-based platforms (e.g., LinkedIn) with the survey questionnaire to collect data. This approach was followed because of its advantages over the telephone, post, personal, and paper-based surveys (Malhotra et al., 2017; Wiid & Diggines, 2015). All ethics protocols were observed and potential respondents voluntarily offered their responses. Ethical clearance for this study was approved by the above-mentioned Johannesburg-based University ethics committee. The ethics protocol number is H20/03/18. 4.4. Empirical results The analysis stage follows the scholarly recommended approach of doing the descriptive part before analyzing both proposed relationships. SPSS was used for the descriptive part of the data analysis. For the second part, the Structural equation modeling procedure was applied to perform hypotheses testing using Amos 25 statistical package. For the results of the descriptive statistics, see Table 1 below. Reading from Table 2, a total of one hundred and eighty-seven (46%) males made up the sample compared to two hundred and seventeen (54%) females. Three hundred and twelve (76%) of the sampled respondents were aged 21-30 years, with the 21-25 years making for a larger portion (44%). REAL ESTATE MANAGEMENT AND VALUATION, eISSN: 2300-5289 vol. 30, no. 1, 2022 www.degruyter.com/view/j/remav Most of the respondents (83%) said they were single, followed by those who were married (16%). The divorced and widowed categories made up the remaining 1% of the sample. About 32% of the respondent had completed high school (Grade 12), followed by 30% with a bachelor’s degree, and 24% who completed a post-high school certificate or national diploma. The remaining qualifications made up 14% of the sample. The occupation status of the respondents was split as follows: employed full-time (34%), unemployed (21%), part-time employed (15%), students (19%), and self-employed (12%; n=48). Table 1 Descriptive statistics % (n) Gender Male 46% (n=187) Female 54% (n=217) 21-25 years 44% (n=181) 26-30 years 32% (n=131) Age 31-35 years 15% (n=62) 36-40 years 8% (n=34) Single 83% (320) Married 16% (61) Marital Status Divorced 1% (n=xxx) Widowed 0% Primary School 2% (n=6) Some High School 5% (n=18) Matric/Grade 12 Completed 32% (n=125) Level of Education Post High School 24% (n=94) Cert/Diploma 30% (n=119) Bachelor’s Degree 8% (n=33) Postgraduate Full Time Student 19% (n=74) Employed Full Time 34% (n=137) Occupation Employed Part Time 15% (n=59) Self-employed 12% (48) Unemployed 21% (n=82) Less than R10 000 52,4 R10 000-R14 999 13,5 R15 000-R19 999 5,5 Gross monthlyincome R20 000-R24 999 7,8 R25 000-R29 999 7,5 More than R30 000 13,3 Source: Analysis results. 4.4.1. Measurement model accuracy analysis The accuracy of the measurement model was assessed by checking the reliability and validity of the model. Reliability For the reliability of the model, composite reliability (CR), the average value extracted (AVE), and Chronbach-alpha values were used. To confirm Reliability, the CR should be greater than 0.7, the AVE should be greater than 0.5 , and the Chronbach alpha should be greater than 0.7 (Nasution et al., 2020; Hair et al., 2020). For the study values, see Table 2 below. REAL ESTATE MANAGEMENT AND VALUATION, eISSN: 2300-5289 vol. 30, no.1, 2022 www.degruyter.com/view/j/remav Table 2 Statistical evidence of reliability and convergent validity Constructs Items Factor P- Cronbach's Composite Average Final number loadings value Alpha Reliability variance of items and extracted (initials) (AVE) SE1 0.816 *** SE2 0.831 *** SE3 0.872 *** SMM – SE4 0.853 *** 0.946 0.946 0.686 Entertainment SE5 0.799 *** SE6 0.801 *** SE7 0.840 *** SE8 0.812 *** ST2 0.808 *** ST3 0.871 *** ST4 0.840 *** SMM – 0.940 0.937 0.714 6(8) Trendiness ST5 0.826 *** ST6 0.847 *** ST7 0.876 *** SInt3 0.807 *** SInt4 0.834 *** SMM – SInt5 0.852 *** 0.917 0.915 0.682 5(8) Interaction SInt6 0.824 *** SInt7 0.812 *** SInf1 0.759 *** SInf2 0.798 *** SInf3 0.831 *** SInf4 0.790 *** SMM – 0.930 0.929 0.620 8(8) Information SInf5 0.803 *** SInf6 0.804 *** SInf7 0.768 *** SInf8 0.742 *** SC1 0.794 *** SC2 0.817 *** SC3 0.821 *** SMM – SC4 0.854 *** 0.941 0.941 0.665 8(8) Customization SC5 0.856 *** SC6 0.812 *** SC7 0.740 *** SC8 0.825 *** BI1 0.759 *** BI2 0.801 *** BI3 0.810 *** Brand Image BI4 0.813 *** 0.928 0.929 0.650 7(8) BI5 0.821 *** BI6 0.805 *** BI7 0.833 *** BPr3 0.784 *** BPr4 0.813 *** BPr5 0.816 *** Brand 0.929 0.926 0.676 6(8) Preference BPr6 0.865 *** BPr7 0.822 *** BPr8 0.831 *** Source: Analysis results. REAL ESTATE MANAGEMENT AND VALUATION, eISSN: 2300-5289 vol. 30, no. 1, 2022 www.degruyter.com/view/j/remav Validity Measuring the validity of the instrument is another requirement for measurement model analysis (Mohajan, 2017). The validity of the model deals with the extent to which the instrument measures what it intends to measure (Mohajan, 2017). For this study, AVE and the correlation matrix were used. The correlation matrix results are displayed in Table 3 below. Discriminant validity was confirmed because the values obtained on the inter-construct correlation matrix are below 0.90 (Henseler et al., 2015). Table 3 Correlation matrix BI BPref SMME SMMT SMMC SMMInf SMMI Brand Image 0.806 Brand Preference 0.835 0.822 SMM Entertainment 0.678 0.605 0.828 SMM Trendiness 0.692 0.611 0.834 0.845 SMM Customization 0.814 0.762 0.749 0.780 0.816 Electronic WOM 0.684 0.623 0.876 0.773 0.740 SMM Information 0.826 0.762 0.741 0.837 0.917 0.787 SMM Interaction 0.712 0.650 0.787 0.819 0.804 0.855 0.826 Source: Analysis results. 4.4.2. The Goodness of fit testing results Following Wang, Wang, and Lee (2018) and Hayes et al., (2017) recommendation, before testing the hypotheses, the structural model was inspected for model fitness to check for the plausibility of the postulated relationships in the model. Common guidelines for acceptable model fit are Chi- squared/degrees of freedom below 3, RMSEA of 0.05-0.06, CFI over 0.95, TLI over 0.9 (Scherer et al. 2019). Table 4 below gives the indices, cut-off values, results and decisions. Table 4 Model fitness test statistics Fit Indicator Threshold adapted from Initial Final Hair et al. (2014: 579-580) measurement measurement model model 2.011 CMIN/DF (Chi- Below 3 (good) 2.464 square/degree of From 3 to 5 (acceptable) freedom) Over 5 (bad) 0.050 RMSEA (Root Below 0.05 (good) 0.060 Mean Square Error From 0.06 to 0.1 of Approximation) (acceptable) Over 0.1 (bad) CFI (Comparative Below 0.90 (bad) 0.841 0.915 Fit Index) Over 0.90 (good) TLI (Tucker Lewis Below 0.80 (bad) 0.835 0.909 Index) From 0.80 to 0.90 (acceptable) Over 0.90 (good) Source: Own study. 4.4.3. Hypotheses testing results The results of the hypotheses testing are presented in Table 5 below. REAL ESTATE MANAGEMENT AND VALUATION, eISSN: 2300-5289 vol. 30, no.1, 2022 www.degruyter.com/view/j/remav Table 5 Standardized Regression Weights and hypothesis conclusion Dependent Independent variables β values P-value Decision variables H1 is accepted. Brand Image <-- SMM Entertainment 0.302 0.000 H2 is rejected. Brand Image <-- SMM Trendiness -0.13 0.042 H3 is rejected. Brand Image <-- SMM Interaction -0.031 0.597 H4 is accepted. Brand Image <-- SMM Information 0.26 0.009 H5 is accepted. Brand Image <-- SMM Customization 0.27 0.000 Brand H6 is accepted. <-- Brand Image 0.939 0.000 Preference Source: Analysis results. 5. Results, discussion and conclusions The entry point for this paper was that all the SMM attributes positively affect the millennials’ choice of Sandton’s rental houses. The outcomes of the study confirmed some hypotheses and rejected others. Those that were confirmed are customization and brand image, entertainment and brand image, information and brand image, brand image and brand preference. The customization and brand image outcome confirmed a list of many others in industries unrelated to the rental market, examples of which are the studies done by Chobhan et al., (2020), Yoo and Park (2016), and by Bilgin (2018). The entertainment and brand image outcome is also in line with studies such as Ganji et al. (2021), and Stylidis and Cherifi (2018). The hypothesized relationship between information and Sandton brand image was also confirmed. This also served as confirmation of other studies on how millennials view and esteem telecommunication information availability. Examples are Guo and Peela (2020), Natalia et al., (2021), and Boeing, Besbris et al., (2019). However, the hypotheses that were related to the trendiness of Sandton and that of the interactions within the city were not confirmed. These outcomes are not in line with other findings. For instance, studies by Ngesan et al., (2018), and Correia et al., (2019) confirmed a positive relationship between the trendiness of a brand and its image. Finally, the interaction and brand image outcome came as a surprise. One of the explanations behind this may be that both trendiness and interactions should be viewed in the light of the new reality of virtual experience. Interaction today is different from actual physical interaction. The results of this study have both academic and managerial implications. For academics, it was shown that SMM plays an important role in influencing millennial consumers’ attitudes and behavior towards rental housing brands. This was achieved by using the theory of planned behavior (TPB) as a lens. The outcomes extend the application of the grounding theory to include generational groups and their housing rental property requirements. Further, the proposed model can form a strong base for future academic investigation for generational market targets in other industries. The framework can also be used to predict millennials’ and other generations’ attitudes and behaviors within the residential housing contexts in other African states. For management practitioners, this study will assist them in deciding on what aspects of SMM to emphasize. Three of the SMM constructs (entertainment, information, and customization) showed a positive influence on brand image. Residential real estate owners and managers should focus on these attributes in their advertisement messages through social media. Understating SMM as one of the drivers of rental preferences within the Millennials’ market will help practitioners develop strategies that will appeal to the market and produce positive results for residential housing brands. The limitations of this study could be used as a base for future studies. Only the Millennials in the Sandton rental housing market were studied. The study, therefore, excluded other generational segments in this industry. The findings are, therefore, only relevant to the millennial segment. The sample for the study consisted of millennials who were intercepted around Johannesburg. This also further limits the generalizability of the findings to South Africa or Africa as a whole. It is therefore recommended that the study be replicated with a wider representative sample to enhance its application to millennials in all South African and African cities. REAL ESTATE MANAGEMENT AND VALUATION, eISSN: 2300-5289 vol. 30, no. 1, 2022 www.degruyter.com/view/j/remav Further, the number of respondents was only 408. Caution should therefore be exercised when interpreting the results of this study. Lastly, the study also focused on the high-end rental housing market in Johannesburg, South Africa (Sandton). Lower-income markets were, therefore, also excluded. The findings of the study, therefore, do not apply to this market segment. This study was aimed at examining how SMM attributes (interaction, information, customization, trendiness, entertainment) impact millennials’ rental housing choices for Sandton in South Africa. Related literature was used to hypothesize the relationships between these SMM attributes and Sandton brand image, and between Sandton brand image and the millennials’ preference for the city. A quantitative approach was used to collect and analyze data for the study. The results confirmed four of the hypothesized relationships and rejected two. These results emphasize that not all SMM attributes can be used to attract millennials to the Sandton rental market. The findings will assist property managers and investors in making informed decisions on their social marketing strategies. This knowledge becomes a useful tool for future promotions and advertisement campaigns directed at millennial customers. The other findings were that Sandton’s image as a brand is a major attraction for millennials. It is the reason why millenials decide to rent residential properties in Sandton. The study concludes that future investment in promoting the Sandton brand image via SMM efforts is justified. 9. References Aaker, D. A. (2009). Managing brand equity. Simon and Schuster. Abass, Z. I., Andrews, F., & Tucker, I. (2020). Socializing in the suburbs: Relationships between neighbourhood design and social interaction in low-density housing contexts. Journal of Urban Design, 25, 108–133. https://doi.org/10.1080/13574809.2019.1592663 Adnyana, I., Made, P., Respati, N N R., (2019), The Role of Brand Preference in Mediating the Relationship Between Brand Equity and Purchase Intention (PeranPreferensiMerekdalamMemediasiHubungan Antara EkuitasMerekdenganNiatBeli). Udayana university e-journal, Vol. 8, no.1, pp. 7519–7547. Aghekyan-Simonian, M., Forsythe, S., Suk Kwon, W., & Chattaraman, V. (2012). The role of product brand image and online store image on perceived risks and online purchase intentions for apparel. Journal of Retailing and Consumer Services, 19(3), 325–331. https://doi.org/10.1016/j.jretconser.2012.03.006 Ahmad, F. S., Quoquab, F., & Bahrun, R. Mansor M. N. Md. (2014). Branding Leadership in Malaysian SMEs. Procedia-Social and Behavioral Sciences, 130, 2014. https://doi.org/10.1016/j.sbspro.2014.04.007 Aitken, R., & Campelo A., (2011). The Four R’s of Place Branding. Journal of marketing management, 27(9/10), 913–933. Ajzen, I. (1985). From intentions to actions: A theory of planned behaviour. In Action control (pp. 11–39). Springer. https://doi.org/10.1007/978-3-642-69746-3_2 Ajzen, I. (2002). Perceived behavioural control, self‐efficacy, locus of control, and the theory of planned behaviour. Journal of Applied Social Psychology, 32(4), 665–683. https://doi.org/10.1111/j.1559-1816.2002.tb00236.x Ajzen, I., & Fishbein, M. (1980). Understanding attitudes and predicting social behaviour. Prentice- Hall. Gilbert, A. (2016). Rental housing: The international experience. Habitat International, 54, 173–181. https://doi.org/10.1016/j.habitatint.2015.11.025 Ali, A., & Alyani, N. I. (2019). Factors affecting China smartphone brand preference among millennials. https://ir.uitm.edu.my/id/eprint/25862/ Aramburu, M. (2015). Rental as a taste of freedom: The Decline of Home Ownership amongst Working-class Youth in Spain during Times of Crisis. International Journal of Urban and Regional Research, 39(6), 1172–1193. https://doi.org/10.1111/1468-2427.12218 Athwal, N. K., Istanbulluoglu, D., & Mccormack, S. (2018). The allure of luxury brands’ social media activities: A uses and gratifications perspective. Information Technology & People, 32(1), 1–36. https://doi.org/10.1108/ITP-01-2018-0017 Bang, H. K., Ellinger, A. E., Hadjimarcou, J., & Traichal, P. A. (2000). Consumer concern, knowledge, belief, and attitude toward renewable energy: An application of the reasoned action theory. Psychology and Marketing, 17(6), 449–468. https://doi.org/10.1002/(SICI)1520- 6793(200006)17:63.0.CO;2-8 REAL ESTATE MANAGEMENT AND VALUATION, eISSN: 2300-5289 vol. 30, no.1, 2022 www.degruyter.com/view/j/remav Bartlett, J. E., Kotrlik, J. W., & Higgins, C. C. (2001). Organizational research: Determining appropriate sample size in survey research. Information Technology, Learning and Performance Journal, 19(1), 43– Bhattacherjee, A., & Premkumar, G. (2004). Understanding changes in belief and attitude toward information technology usage: A theoretical model and longitudinal test. Management Information Systems Quarterly, 28, 229–254. https://doi.org/10.2307/25148634 Bhattacherjee, A., & Sanford, C. (2006). Influence processes for information technology acceptance: An elaboration likelihood model. Management Information Systems Quarterly, 30, 805–825. https://doi.org/10.2307/25148755 Bilgin, Y. (2018). The effect of social media marketing activities on brand awareness, brand image and brand loyalty. Business & Management Studies: An International Journal, 6(1), 128–148. https://doi.org/10.15295/bmij.v6i1.229 Blair, O. (2017). What Comes After Millenials? Meet the Generation Known as Linkster. independent.co.uk Blake, T. (2019). Commuting Costs and Geographic Sorting in the Housing Market. Real Estate Economics, 47(4), 1089–1118. https://doi.org/10.1111/1540-6229.12159 Blakely, E. J., & Leigh, N. G. (2013). Planning local economic development: Theory and practice. 5th edition. Boeing G. (2020) Online Rental Housing Market Representation and the Digital Reproduction of Urban Inequality. Environment and Planning A: Economy and Space. https://doi.org/10.1177/0308518X19869678. Chang, K. L. (2020). Are cyclical patterns of international housing markets interdependent? Economic Modelling, 88, 14–24. https://doi.org/10.1016/j.econmod.2019.09.002 Chang, Y. T., Yu, H., & Lu, H. P. (2015). Persuasive messages, popularity cohesion, and message diffusion in social media marketing. Journal of Business Research, 68(4), 777–782. https://doi.org/10.1016/j.jbusres.2014.11.027 Chatzigeorgiou, C. (2017). Modelling the impact of social media influencers on behavioural intentions of millennials: The case of tourism in rural areas in Greece. Journal of Tourism. Heritage & Services Marketing, 3(2), 25–29. Chen, J., Hui, E. C. M., Seiler, M. J., & Zhang, H. (2018). Household tenure choice and housing price volatility under a binding home-purchase limit policy constraint. Journal of Housing Economics, 41, 124–134. https://doi.org/10.1016/j.jhe.2018.06.004 Cheung, M. L., Pires, G., & Rosenberger, P. J. (2020). The influence of perceived social media marketing elements on consumer–brand engagement and brand knowledge. Asia Pacific Journal of Marketing and Logistics, 32(3), 695–720. https://doi.org/10.1108/APJML-04-2019-0262 Chovanová, H. H., Korshunov, A. I., & Babčanová, D. (2015). Impact of brand on consumer behavior. Procedia Economics and Finance, 34, 615–621. https://doi.org/10.1016/S2212-5671(15)01676-7 Chow, H. W., Ling, G. J., Yen, I. Y., & Hwang, K. P. (2017). Building brand equity through industrial tourism. Asia Pacific Management Review, 22(2), 70–79. https://doi.org/10.1016/j.apmrv.2016.09.001 Circella, G., Alemi, F., Tiedeman, K., Handy, S., & Mokhtarian, P. (2017). What Affects Millennials’ Mobility? PART II: The Impact of Residential Location, Individual Preferences and Lifestyles on Young Adults’ Travel Behavior in California. Project Report, National Center for Sustainable Transportation. University of California, Davis, March 2017; Available at https://ncst.ucdavis.edu/wp Cleave E., Arku G., Sadler R., & Kyeremeh E., (2017). Place Marketing, Place Branding, and Social Media: Perspectives of Municipal Practitioners. Growth and change. A journal of urban and regional policy, 48(4), 1012-1033. Constantinides, E. (2014). Foundations of social media marketing. Procedia: Social and Behavioral Sciences, 148, 40–57. https://doi.org/10.1016/j.sbspro.2014.07.016 Cretu, A. E., & Brodie, R. J. (2007). The influence of brand image and company reputation where manufacturers market to small firms: A customer value perspective. Industrial Marketing Management, 36(2), 230–240. https://doi.org/10.1016/j.indmarman.2005.08.013 Davis, F. D. (1985). A technology acceptance model for empirically testing new end-user information systems: Theory and results. Doctoral dissertation, Sloan School of Management, Massachusetts Institute of Technology. De Noronha, I., Coca-Stefaniak, J A., & Morrison, A M. (2017). Confused branding? An exploratory study of place branding practices among place management professionals. Cities, 66, 91-98. REAL ESTATE MANAGEMENT AND VALUATION, eISSN: 2300-5289 vol. 30, no. 1, 2022 www.degruyter.com/view/j/remav Deka, D. (2018). Are millennials moving to more urbanized and transit-oriented counties? Journal of Transport and Land Use, 11(1), 443–461. https://doi.org/10.5198/jtlu.2018.1345 Dholakia, U. M., Bagozzi, R. P., & Pearo, L. K. (2004). A social influence model of consumer participation in network-and small-group-based virtual communities. International Journal of Research in Marketing, 21(3), 241–263. https://doi.org/10.1016/j.ijresmar.2003.12.004 Di Pietro L., & Pantano E. (2012). An empirical investigation of social network influence on consumer purchasing decision: the case of Facebook. J. Direct Data Dig. Mark. Pract, 14, 18–29. https://doi.org/10.1057/dddmp.2012.10 Duffett, R., Petrosanu, D. M., Negricea, L. C., & Edu, T. (2019). Effect of YouTube Marketing Communication on Converting Brand Liking into Preference among Millennials Regarding Brands in General and Sustainable Offers in Particular. Evidence from South Africa and Romania. Sustainability (Basel), 11(3), 604. https://doi.org/10.3390/su11030604 Dwivedi, Y. K., Kapoor, K. K., & Chen, H. (2015). Social Media Marketing and Advertising. The Marketing Review, 15(3), 289–309. https://doi.org/10.1362/146934715X14441363377999 Galimullin, E. Z. (2019). Migration attitudes and mechanisms for attracting young people to the Russian Arctic. Arctic and North., 36, 78–88. https://doi.org/10.17238/issn2221-2698.2019.36.96 Foroudi, P. (2019). Influence of brand signature, brand awareness, brand attitude, brand reputation on hotel industry’s brand performance. International Journal of Hospitality Management, 76, 271–285. https://doi.org/10.1016/j.ijhm.2018.05.016 Fortezza, F., & Pencarelli, T. (2015). Potentialities of Web 2.0 and new challenges for destinations: Insights from Italy. Anatolia: An International Journal of Tourism and Hospitality, 26(4), 563–573. https://doi.org/10.1080/13032917.2015.1040813 Gabe, J., Robinson, S., & Sanderford, A. (2021). Willingness to pay for attributes of location efficiency. The Journal of Real Estate Finance and Economics, 2021, 1–35. https://doi.org/10.1007/s11146-021- 09847-z Glaeser, E., & Gyourko, J. (2018). The Economic Implications of Housing Supply. The Journal of Economic Perspectives, 32(1), 3–30. https://doi.org/10.1257/jep.32.1.3 Garrett, A., Straker, K., & Wrigley, C. (2017). Digital channels for building collaborative consumption communities. Journal of Research in Interactive Marketing, 11(2), 160–184. https://doi.org/10.1108/JRIM-08-2016-0086 Godelnik, R. (2017). Millennials and the sharing economy: Lessons from a ‘buy nothing new, share everything month’ project. Environmental Innovation and Societal Transitions, 23, 40–52. https://doi.org/10.1016/j.eist.2017.02.002 Godey, B., Manthiou, A., Pederzoli, D., Rokka, J., Aiello, G., Donvito, R., & Singh, R. (2016). Social media marketing efforts of luxury brands: Influence on brand equity and consumer behavior. Journal of Business Research, 69(12), 5833–5841. https://doi.org/10.1016/j.jbusres.2016.04.181 Hair, J. F., Jr., Howard, M. C., & Nitzl, C. (2020). Assessing measurement model quality in PLS-SEM using confirmatory composite analysis. Journal of Business Research, 109, 101–110. https://doi.org/10.1016/j.jbusres.2019.11.069 Han, H., Hsu, L. T. J., & Sheu, C. (2010). Application of the theory of planned behaviour to green hotel choice: Testing the effect of environmentally friendly activities. Tourism Management, 31(3), 325– 334. https://doi.org/10.1016/j.tourman.2009.03.013 Han, H., & Kim, Y. (2010). An investigation of green hotel customers’ decision formation: Developing an extended model of the theory of planned behavior. International Journal of Hospitality Management, 29(4), 659–668. https://doi.org/10.1016/j.ijhm.2010.01.001 Han, S. H., Nguyen, B., & Lee, T. J. (2015). Consumer-based chain restaurant brand equity, brand reputation, and brand trust. International Journal of Hospitality Management, 50, 84–93. https://doi.org/10.1016/j.ijhm.2015.06.010 Harshini, C. S. C. S. (2015). Influence of social media ads on consumer’s purchase intention. Government R C College. Recognized Research Centre, 2(10), 110–115. Harun, A., & Husin, W. H. R. (2019). Social Media Marketing amongst Millennial’s in Malaysia: Issues and Challenges. Journal of Social Transformation and Regional Development, 1(2), 1–7. Hassanzadeh A., & Namdar T. (2018). Millennials brand loyalty in the fashion industry & the role of brand identity. Test Engineering and Management, 82, 4234-4240. REAL ESTATE MANAGEMENT AND VALUATION, eISSN: 2300-5289 vol. 30, no.1, 2022 www.degruyter.com/view/j/remav Hayes, A. F., Montoya, A. K., & Rockwood, N. J. (2017). The analysis of mechanisms and their contingencies: PROCESS versus structural equation modelling. Australasian Marketing Journal, 25(1), 76–81. https://doi.org/10.1016/j.ausmj.2017.02.001 Hayes, S. J. L., & King, K. W. (2014). The social exchange of viral ads: Referral and co-referral of ads among college students. Journal of Interactive Advertising, 14(2), 98–109. https://doi.org/10.1080/15252019.2014.942473 Hennig-Thurau, T., Malthouse, E. C., Friege, C., Gensler, S., Lobschat, L., Rangaswamy, A., & Skiera, B. S. (2010). The Impact of New Media on Customer Relationships. Journal of Service Research, 13(3), 311–330. https://doi.org/10.1177/1094670510375460 Henseler, J., Ringle, C. M., & Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modeling. Journal of the Academy of Marketing Science, 43(1), 115– 135. https://doi.org/10.1007/s11747-014-0403-8 Heo, C. Y., & Hyun, S. S. (2015). Do luxury room amenities affect guests’ willingness to pay? International Journal of Hospitality Management, 46, 161–168. https://doi.org/10.1016/j.ijhm.2014.10.002 Kam, K. J., Lim, A. S. H., Al-obaidi, K. M., & Lim, T. S. (2018). Evaluating Housing Needs and Preferences of Generation Y in Malaysia. Planning Practice and Research, 33, 172–185. Advance online publication. https://doi.org/10.1080/02697459.2018.1427413 Kang, M. J. (2005). A Study on the Effect of Features of Brand Community Using One-person Media on Consumers. Master’s dissertation.Seoul National University. Kara, S., Gunasti, K., & Ross, W. T., Jr. (2020). My brand identity lies in the brand name: Personified suggestive brand names. Journal of Brand Management, 27, 607–621. https://doi.org/10.1057/s41262-020-00201-x Keller, K. L. (2003). Understanding brands, branding and brand equity. Interactive Marketing, 5(1), 7– 20. https://doi.org/10.1057/palgrave.im.4340213 Keller, K. L. (1993). Conceptualizing, Measuring, and Managing Customer-Based Brand Equity. Journal of Marketing, 57(1), 1–22. https://doi.org/10.1177/002224299305700101 Kim, A. J., & Ko, E. (2012). Do social media marketing activities enhance customer equity? An empirical study of luxury fashion brand. Journal of Business Research, 65(10), 1480–1486. https://doi.org/10.1016/j.jbusres.2011.10.014 Kim, S. S., & Son, J. Y. (2009). Out of dedication or constraint? A dual model of post-adoption phenomena and its empirical test in the context of online services. Management Information Systems Quarterly, 33, 49–70. https://doi.org/10.2307/20650278 Kusyanti, A., Puspa, H., Rahma, D., & April, Y. (2018). Teen’s Social Media Adoption: An Empirical Investigation in Indonesia. International Journal of Advanced Computer Science and Applications, 9(2), 380–384. https://doi.org/10.14569/IJACSA.2018.090252 Lee, Y. H., Hsieh, Y. C., & Hsu, C. N. (2011). Adding innovation diffusion theory to the technology acceptance model: Supporting employees’ intentions to use e-learning systems. Journal of Educational Technology & Society, 14(4), 124–137. Li, T. (2020). The Value of Access to Rail Transit in a Congested City: Evidence from Housing Prices in Beijing. Real Estate Economics, 48(2), 556–598. https://doi.org/10.1111/1540-6229.12222 Lien, C. H., Wen, M. J., Huang, L. C., & Wu, K. L. (2015). Online hotel booking: The effects of brand image, price, trust and value on purchase intentions. Asia Pacific Management Review, 20(4), 210– 218. https://doi.org/10.1016/j.apmrv.2015.03.005 Lissitsa, S., & Kol, O. (2016). Generation X vs. Generation Y–A decade of online shopping. Journal of Retailing and Consumer Services, 31, 304–312. https://doi.org/10.1016/j.jretconser.2016.04.015 Liu, M. T., Wong, I. A., Tseng, T. H., Chang, A. W. Y., & Phau, I. (2017). Applying consumer-based brand equity in luxury hotel branding. Journal of Business Research, 81, 192–202. https://doi.org/10.1016/j.jbusres.2017.06.014 Liu, X., Shin, H., & Burns, A. C. (2021). Examining the impact of luxury brand’s social media marketing on customer engagement: Using big data analytics and natural language processing. Journal of Business Research, 125, 815–826. https://doi.org/10.1016/j.jbusres.2019.04.042 Lojanica, V., Colic-Damjanovic, V. M., & Jankovic, N. (2018). Housing of the Future: Housing Design of the Fourth Industrial Revolution. 5th International Symposium on Environment-Friendly Energies and Applications (EFEA), 1-4. https://doi.org/10.1109/EFEA.2018.8617094 REAL ESTATE MANAGEMENT AND VALUATION, eISSN: 2300-5289 vol. 30, no. 1, 2022 www.degruyter.com/view/j/remav Longo, I., & Saxena, D. (2020). Self-brand Connection in the Digital Age: A Qualitative Exploration of Brand Usage on Instagram for Identity Creation among Millennials. In Proceedings of the 20th Portuguese Association for Information Systems Conference, UniversidadePortucalense, Porto, Portugal. Malhotra, N. K., Nunan, D., & Birks, D. F. (2017). Marketing research: An applied approach. Pearson Education Limited. Manthiou, A., Chiang, L. T. A. N. G. L. R., & the Liang (Rebecca) Tang. (2013). Identifying and responding to customer needs on Facebook fan pages. [IJTHI]. International Journal of Technology and Human Interaction, 9(3), 36–52. https://doi.org/10.4018/jthi.2013070103 Mgiba, F. M., & Nyamande, N. (2020). Persuasive Influencers and the Millennials: How their relationships affect brand, value, and relationship equities, and customers’ intention to purchase. Journal of Contemporary Management, 17(2), 492. https://doi.org/10.35683/jcm19115.88 Mohajan, H K., (2017). Two Criteria for Good Measurements in Research: Validity and Reliability. Annals of SpiruHaret University: Economic series, 17(3), 58-82. https://doi.org/10.26458/1746 Moresjo, S., & Xin, Y. (2020). Does CSR really influence Millennials’ purchase decisions? A qualitative study on attitudes toward the fast fashion industry. Masters degree thesis: Jonkoping University. Mulyano Y., Rahadi R A., & Amaliah U. (2020). Millennials Housing Preferences Model in Jakarta. European Journal of Business and Management Research, 5(1). Muntinga, D., Moorman, M., & Smit, E. (2011). Introducing COBRAs: Exploring motivations for brand-related social media use. International Journal of Advertising, 30(1), 13–46. https://doi.org/10.2501/IJA-30-1-013-046 Nam, K., & Yeo, J. (2011). Study on consumers’ acceptance proceed of mobile advertising. J. Consum. Stud., 22(4), 1–28. Nasution, M. I., Fahmi, M., Jufrizen., Muslih., & Prayogi, M. A. (2020). The Quality of Small and Medium Enterprises Performance Using the Structural Equation Model-Part Least Square (SEM- PLS). Journal of Physics: Conference Series. Journal of Physics: Conference Series, 1477, 052052. https://doi.org/10.1088/1742-6596/1477/5/052052 Nethercote, M. (2020). Build-to-Rent and the financialization of rental housing: Future research directions. Housing Studies, 35, 839–874. Advance online publication. https://doi.org/10.1080/02673037.2019.1636938 Noble s., Haytko D., Phillips J., (2009), What drives college-age Generation Y consumers? Journal of business research, Vol, 62, no. 6, pp. 617-628. Öztürk, M., & Batum, T. P. (2019). How Housing Brands Use Social Media In Their Marketing Communications? A Content Analysis. YönetimBilimleriDergisi, 17(33), 111–135. Pandey, A., Sahu, R., & Dash, M. K. (2018). Social media marketing impact on the purchase intention of millennials. International Journal of Business Information Systems, 28(2), 147–162. https://doi.org/10.1504/IJBIS.2018.091861 Park, N., Kee, K. F., & Valenzuela, S. (2009). Being immersed in social networking environment: Facebook groups, uses and gratifications, and social outcomes. Cyberpsychology & Behavior, 12(6), 729–733. https://doi.org/10.1089/cpb.2009.0003 PMID:19619037 Phan, M., Thomas, R., & Heine, K. (2011). Social media and luxury brand management: The case of Burberry. Journal of Global Fashion Marketing, 2(4), 213–222. https://doi.org/10.1080/20932685.2011.10593099 Qu, H., Kim, L. H., & Im, H. H. (2011). A model of destination branding: Integrating the concepts of the branding and destination image. Tourism Management, 32(3), 465–476. https://doi.org/10.1016/j.tourman.2010.03.014 Quesenberry, K. A. (2020). Social media strategy: Marketing, advertising, and public relations in the consumer revolution (2nd ed.). Bowman & Littlefield. Rahman, Z., & Yadav, M. (2018). The influence of social media marketing activities on customer loyalty: A study of e-commerce industry. Benchmarking, 25(9), 3882–3905. https://doi.org/10.1108/BIJ-05-2017-0092 Ramanathan, U., Subramanian, N., & Parrott, G. (2017). Role of social media in retail network operations and marketing to enhance customer satisfaction. International Journal of Operations & Production Management, 37(1), 105–123. https://doi.org/10.1108/IJOPM-03-2015-0153 Román, S., & Sánchez-siles, L. M. (2018). Parents’ choice criteria for infant food brands: A scale development and validation. Food Quality and Preference, 64, 1–10. https://doi.org/10.1016/j.foodqual.2017.10.008 REAL ESTATE MANAGEMENT AND VALUATION, eISSN: 2300-5289 vol. 30, no.1, 2022 www.degruyter.com/view/j/remav Romaniuk, J., & Nenycz-thiel, M. (2013). Behavioral brand loyalty and consumer brand associations. Journal of Business Research, 66(1), 67–72. https://doi.org/10.1016/j.jbusres.2011.07.024 Ryan, J., & Casidy, R. (2018). The role of brand reputation in organic food consumption: A behavioral reasoning perspective. Journal of Retailing and Consumer Services, 41, 239–247. https://doi.org/10.1016/j.jretconser.2018.01.002 Sääksjärvi, M., & Samiee, S. (2007). Nonprice antecedents of consumer preference for cyber and extension brands. Journal of Interactive Marketing, 21(1), 22–35. https://doi.org/10.1002/dir.20072 Sanmiguel, P., Guercini, S., & Sádaba, T. (2018). The impact of attitudes towards influencers amongst millennial fashion buyers. Studies in Communication Sciences, 18(2), 439–460. Saravanakumar, M., & Suganthalakshmi, T. (2012). Social media marketing. Life Science Journal, 9(4), 4444–4451. Sari, D. M F P., & Yulianti, M. N. D. R. (2019). Celebrity Endorsement, Electronic Word of Mouth and Brand Trust on Buying Habits: Fashion Women Online Shop Products in Instagram. International Journal of Social Science and Humanity, 3(1), 82–90. Scherer, R., Siddiq, F., & Tondeur, J. (2019). The technology acceptance model (TAM): A meta-analytic structural equation modeling approach to explaining teachers’ adoption of digital technology in education. Computers & Education, 128, 13–35. https://doi.org/10.1016/j.compedu.2018.09.009 Schivinski, B., Langaro, D., Fernandes, T., & Guzmán, F. (2020). Social media brand engagement in the context of collaborative consumption: The case of AIRBNB. Journal of Brand Management, 27, 645– 661. https://doi.org/10.1057/s41262-020-00207-5 Schmidtke, D., Rundle-Thiele, S., Kubcaki, K., & Burns, G. L. (2021). Co-designing social marketing programs with “bottom of the pyramid” citizens. International Journal of Market Research, 63(1), 86– 105. https://doi.org/10.1177/1470785320968029 Seo, E. J., & Park, J. W. (2018). A study on the effects of social media marketing activities on brand equity and customer response in the airline industry. Journal of Air Transport Management, 66, 36–41. https://doi.org/10.1016/j.jairtraman.2017.09.014 Shao, G. (2009). Understanding the appeal of user‐generated media: A uses and gratification perspective. Internet Research, 19(1), 7–25. https://doi.org/10.1108/10662240910927795 Shareef, M. A., Mukerji, B., Dwivedi, Y. K., Rana, N. P., & Islam, R. (2017). Social media marketing: Comparative effect of advertisement sources. Journal of Retailing and Consumer Services, 46(C), 58– Singh, A., & Kathuria, L. M. (2016). Understanding drivers of branded food choice among low-income consumers. Food Quality and Preference, 52, 52–61. https://doi.org/10.1016/j.foodqual.2016.03.013 Singh, J., & Kaur, R. (2021). Influencing the Intention to Adopt Anti-Littering Behavior: An Approach With Modified TPB Model. Social Marketing Quarterly, 27(2), 117–132. https://doi.org/10.1177/15245004211013333 Sissons, P., & Houston, D. (2019). Changes in transitions from private renting to homeownership in the context of rapidly rising house prices. Housing Studies, 34(1), 49–65. https://doi.org/10.1080/02673037.2018.1432754 Sniehotta, F.F., Presseau, J., & Araújo-Soares, V. (2014). Time to retire the theory of planned behaviour. Health Psychology Review, 8(1), 1-7. https://doi.org/10.1080/17437199.2013.869710 Sniehotta, F. F., Presseau, J., & Araújo-Soares, V. (2014). Time to retire the theory of planned behaviour. Health Psychology Review, 8(1), 1–7. https://doi.org/10.1080/17437199.2013.869710 PMID:25053004 Taylor, D. G., Lewin, J. E., & Strutton, D. (2011). Friends, Fans, and Followers: Do ads work on social networks? Journal of Advertising Research, 51(1), 258–275. https://doi.org/10.2501/JAR-51-1-258-275 Taylor, P., & Keeter, S. (2010). Millennials: Confident. Connected. Open to Change. Retrieved from http://www.pewsocialtrends.org/files/2010/10/millennials-confident-connected-open-to- change.pdf Teo, T., Zhou, M., & Noyes, J. (2016). Teachers and technology: Development of an extended theory of planned behaviour. Educational Technology Research and Development, 64(6), 1033–1052. https://doi.org/10.1007/s11423-016-9446-5 Van Esch, P., Mente, M. (2018). Marketing video-enabled social media as part of your e-recruitment strategy: Stop trying to be trendy. Journal of Retailing and Consumer Services, 44, 266-273. REAL ESTATE MANAGEMENT AND VALUATION, eISSN: 2300-5289 vol. 30, no. 1, 2022 www.degruyter.com/view/j/remav Vitelar, A. (2019). Like Me: Generation Z and the Use of Social Media for Personal Branding. Management Dynamics in the Knowledge Economy, 7(2), 257–268. Vollmer, C., & Precourt, G. (2008). Always on: Advertising, marketing and media in an era of consumer control. McGraw-Hill. Wang, H., Yu, F., & Zhou, Y. (2020). Property Investment and Rental Rate under Housing Price Uncertainty: A Real Options Approach. Real Estate Economics, 48(2), 633–665. https://doi.org/10.1111/1540-6229.12235 Wang, S., Wang, W., & Lee, S. (2018). Interactive roles of social identity and evaluative attitudes in sports events participation. Journal of Convention & Event Tourism, 19(4-5), 327-346. https://doi.org/10.1080/15470148.2018.1488640 Watzlawick, P., Bavelas, J. B., & Jackson, D. D. (2011). Pragmatics of human communication: A study of interactional patterns, pathologies and paradoxes. WW Norton & Company. Wiid, J., & Diggines, C. (2015). Marketing research (3rd ed.). Juta and Company. Wilcox, K., Kim, H. M., & Sen, S. (2009). Why do consumers buy counterfeit luxury brands? JMR, Journal of Marketing Research, 46(2), 247–259. https://doi.org/10.1509/jmkr.46.2.247 Yadav, M., & Rahman, Z. (2017). Social media marketing: Literature review and future research directions. International Journal of Business Information Systems, 25(2), 213–240. https://doi.org/10.1504/IJBIS.2017.083687 Yang, W., Zhang, L., & Mattila, A. S. (2016). Luxe for less: How do consumers react to luxury hotel price promotions? The moderating role of consumers’ need for status. Cornell Hospitality Quarterly, 57(1), 82–92. https://doi.org/10.1177/1938965515580133 Zenker, S., Braun, E., & Petersen, S. (2017). Branding the destination versus the place: The effects of brand complexity and identification for residents and visitors. Tourism Management, 58, 15–27. https://doi.org/10.1016/j.tourman.2016.10.008 Zhou, F., Mou, J., Su, Q., & Wu, Y. C. J. (2019). How does consumers’ Perception of Sports Stars’ Personal Brand Promote Consumers’ brand love? A mediation model of global brand equity. Journal of Retailing and Consumer Services, 54, 1–10. Zhou, T., Lu, Y., & Wang, B. (2009). The relative importance of website design quality and service quality in determining consumers’ online repurchase behaviour. Information Systems Management, 26(4), 327–337. https://doi.org/10.1080/10580530903245663 Zhu, Y. Q., & Chen, H. G. (2015). Social media and human need satisfaction: Implications for social media marketing. Business Horizons, 58(3), 335–345. https://doi.org/10.1016/j.bushor.2015.01.006 REAL ESTATE MANAGEMENT AND VALUATION, eISSN: 2300-5289 vol. 30, no.1, 2022

Journal

Real Estate Management and Valuationde Gruyter

Published: Mar 1, 2022

Keywords: Millennials; Social media marketing attributes; Sandton rental housing brand image; Sandton rental housing brand preference; M31; M37; O18; O35

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