ISSN: 1550-7521
ISSN: 1550-7521
K. Mercy Makhitha1*, Ms. Kate Ngobeni2
1Professor Department of Marketing and Retail Management, University of South Africa, South Africa
2Lecturer Department of Marketing and Retail Management, College of Economic and Management Sciences, University of South Africa, South Africa
Received: 01-Feb-2023, Manuscript No. gmj-23-88428; Editor assigned: 03-Feb2023, PreQc No. 88428 (PQ); Reviewed: 17-Feb-2023, QC No.Q-88428; Revised:21-Feb-2023, Manuscript No. gmj-23-88428 (R); Published: 28-Feb-2023, DOI: 10.36648/1550-7521.21.60.353
Citation: Makhitha KM, Ngobeni K (2023) Factors Influencing the Online Clothing Shopping Intention of Emerging Township Consumers in South Africa: The Mediation Effect of Attitude. Global Media Journal, 21:60.
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Over the past two decades, online shopping has grown in prominence. Despite its popularity, however, the adoption by emerging South African consumers of online shopping lags behind that of other regions in the world. Very little research has been conducted in the area of online shopping adoption in developing countries, including South Africa, and in particular research into the underlying factors that potentially influence online shopping adoption, particularly among emerging township consumers, who make up the largest consumer group in South Africa, is scant. To reduce this particular knowledge gap, the study was conducted with the aim of determining the underlying factors that influence the adoption by emerging township consumers of online shopping in South Africa. To achieve this objective, respondents in Soweto, South Africa, were invited to participate in an online survey; the convenience non-probability sampling method was adopted, and 300 respondents were sampled for data. The findings revealed convenience to have the greatest influence on consumer attitude in the context of online purchasing. None of the factors had an influence on shopper intention to shop online. The intention of consumers was also influenced by their attitude toward online purchasing. Consumer attitudes mediate the relationship between convenience and online shopping intention as well as usefulness and online shopping intention. The findings are valuable for online retailers seeking to direct their offerings towards township market consumers and could be incorporated into their online retail and marketing strategies.
Over the past two decades, online shopping has grown in prominence. Despite its popularity, however, the adoption by emerging South African consumers of online shopping lags behind that of other regions in the world. Very little research has been conducted in the area of online shopping adoption in developing countries, including South Africa, and in particular research into the underlying factors that potentially influence online shopping adoption, particularly among emerging township consumers, who make up the largest consumer group in South Africa, is scant. To reduce this particular knowledge gap, the study was conducted with the aim of determining the underlying factors that influence the adoption by emerging township consumers of online shopping in South Africa. To achieve this objective, respondents in Soweto, South Africa, were invited to participate in an online survey; the convenience non-probability sampling method was adopted, and 300 respondents were sampled for data. The findings revealed convenience to have the greatest influence on consumer attitude in the context of online purchasing. None of the factors had an influence on shopper intention to shop online. The intention of consumers was also influenced by their attitude toward online purchasing. Consumer attitudes mediate the relationship between convenience and online shopping intention as well as usefulness and online shopping intention. The findings are valuable for online retailers seeking to direct their offerings towards township market consumers and could be incorporated into their online retail and marketing strategies.
Perceived Ease of Use; Perceived Usefulness; Convenience; Word of Mouth; Attitude; Intention; TAM
The advancement of the internet has further broadened the already widespread nature of online shopping adoption in the modern economy. Online shopping, defined as the purchasing of products and services over the internet Malapane [1], has been recognised as an important global concept [2] and has grown substantially over the years. Online shopping allows consumers to purchase products and services at any time and from any location [3], and it is perceived as providing more benefits to consumers than traditional retail stores, notably in terms of convenience [4- 6]. Despite advances in technology, infrastructure and internet penetration [7] online shopping in South Africa, particularly among emerging consumers, trails behind other regions of the world. There is a lack of published empirical research on online shopping adoption in developing countries such as South Africa, particularly among emerging consumers, and as a result scholars have recommended that researchers work to better understand technology adoption as well as the key determinants of online shopping adoption in developing countries [8, 9] especially in South Africa [7] Jibril et al (2020) [2] propose that researchers should in addition investigate factors other than those relating to traditional technology adoption theories and models to determine the factors that influence consumer adoption of online shopping in developing countries, particularly in Africa, because the findings may differ in other contexts and across different product categories and services. Arora and Aggarwal [10], too, suggest that consumer attitudes toward online shopping in developing countries, as well as within different product categories, should be examined in future, while [11] recommend that researchers should investigate the factors that affect the attitudes and online shopping behaviour of emerging consumers.
South African consumers are to an increasing extent integrating digital technology into their daily routines. Despite the fact that 50% of the population has internet and mobile phone access, and more than two-thirds use the internet daily, consumers in South Africa remain slow to adopt online shopping [12]. In 2018, online sales in South Africa totalled R14 billion, accounting for only 1.4% of the total retail market. However, due to Coronavirus-induced lockdowns, the value of the South African online retail market doubled in just two years, resulting in an increase in online sales to more than R30 billion in 2020; Daniel (2021) [13] predicted further growth to more than R40 billion in 2021, accounting for 4% of the total retail market in South Africa. As the pandemic continued, the shopping habits of South Africans consumers changed drastically, as people turned to online purchasing to stock up on essentials [14]. Taka lot, South Africa's largest online retailer, saw a 41% increase in revenue to more than R3.3 billion as a result of the change in consumer behaviour [13]. Consumer demands included faster deliveries, improved after-sales service (McCabe et al, 2019), convenient and secure payments and contactless digital payment methods, [15] and more flexible payment options [14]. Despite the fact that the most recent pandemic doubled the e-commerce turnover, post-pandemic growth rates are expected to be lower [13] and retailers will need to provide a consistent marketing experience across all channels in order to provide consumers with a seamlessly integrated shopping experience [15].
The growing middle class in emerging markets has presented an opportunity for increased spending and consumption [16] especially in emerging markets where online shopping is demonstrating significant growth [17] and in 2021 [18] reported 28 per cent of emerging market consumers in South Africa as shopping online. Researchers and marketing practitioners would therefore benefit from understanding what influences the attitudes of South African emerging market consumers towards online shopping, and their online purchasing behaviour [18].
The attitudes of consumers in developing countries toward technology have changed as their income levels have raised, and this has led to more consumers demanding instant gratification [19]. Consumers are now allocating less time to shopping and more to other activities, which has increased their demand for convenience. In most emerging markets, infrastructure is underdeveloped and businesses have not developed distribution networks in the same way as those in developed countries have [20]. However, as the use of the internet increases and the capabilities of smartphones improve, emerging consumer markets are becoming an appealing business venture for retailers who are digitally equipped and want to operate globally [20]
In order for businesses in emerging township markets to succeed, they need to understand the factors that influence online shopping adoption. However, the rationale for online shopping adoption in emerging township markets is unclear. This makes it difficult for businesses and marketing practitioners to respond to the low levels of online shopping adoption among emerging township consumers. It is worth noting that the majority of South African consumers reside in townships, where unpaved roads, the absence of standardised residential address systems, overcrowding and security concerns are prevalent, and infrastructure is either poor or lacking, all of which hampers the growth of online shopping [21]. Retail Brief Africa (2017) [22] reports that although internet penetration among township consumers is lower than in the rest of South Africa, township consumers nevertheless own smartphones and spend money on buying products such as airtime online. They also spend considerable time online, which is an important consideration when determining factors that influence their adoption of online shopping.
Townships are seen by businesses as key to unlocking the South African e-commerce retail industry, as witnessed by the rapid expansion of retailers into townships in South Africa, and the fact that townships represent about 40% of the national grocery market [23]. Furthermore, the level of adoption by township consumers of online shopping is high [24].
In response to the recommendation by other researchers in terms of closing the knowledge gap regarding the adaptation of online shopping factors for different consumers, the importance of achieving an understanding of the factors that influence the adoption by emerging consumers of online shopping was recognised.
As a result, the study was intended to accomplish the following objectives:
• To determine factors that influences the attitude of emerging township consumers towards online shopping for clothing products in South Africa.
• To determine factors that influences the intention of emerging township consumers to adopt online shopping for clothing products in South Africa.
• To determine the mediation effect of attitude on factors influencing the online clothes shopping intentions of emerging township consumers in South Africa.
Theoretical foundation for the study
Davis (1989) [25] developed the technology acceptance model (TAM) by adapting and expanding the theory of reasoned action (TRA) (Fishbein & Ajzen, 1975) [26] to assess individuals' adoption of new information technologies [27]. The TAM makes use of the theoretical relationship of the TRA so as to better understand and explain adoption behaviour as it relates to information technologies. Since its debut, the TAM has been considered one of the most prominent models devised to explain technological adoption [28].
According to the TAM, perceived usefulness and perceived ease of use influence an individual's attitude, which in turn influences the individual's intention and actual use of a system [29]. An individual's attitude is regarded as their feelings about performing a specific behaviour [26]. Behavioural intentions, on the other hand, are the driving elements that influence adoption behaviour [30]. In addition, the TAM postulates that perceived ease of use, which refers the difficulty level of application perceived by an individual l [31], has a direct impact on perceived usefulness, which is defined as an individual's subjective likelihood that the use of a certain system will improve an action they want to perform [25, 31]. Thus, it can be said that consumers will be willing to engage in behaviour if it requires little effort and is beneficial.
The TAM has been used to study consumer adoption of online shopping, and has proven to be a reliable theoretical foundation [32-35] As a result; the TAM provides a solid theoretical foundation for investigating the factors that influence the attitude and online shopping intention of emerging consumers with regard to luxury-branded products. Bauerová and Klepek (2018) [36] concur, asserting that the TAM can be used to better understand consumer behaviour in relation to online shopping.
Factors influencing emerging consumers’ attitude towards online shopping and intention to shop online
A consumer’s attitude towards behaviour is critical, as attitude is considered to be the most significant antecedent of behavioural adoption intentions [37]. To influence consumer attitudes, online retailers must first identify the determinants that influence attitude and, ultimately, purchase intention in the online shopping environment [11]. Identifying these factors is critical if online retailers are to capitalise on and seize opportunities available, especially in emerging consumer markets [11], where they need to tailor marketing strategies differently to satisfy the consumer’s needs [20]. As a result, insight is required to determine how online retailers can reach consumers and influence their purchasing behaviour.
Convenience has been identified as one of the main factors driving the growth in online shopping [38]. However, despite the potential of this factor, understanding of convenience in emerging markets is still lacking [20]. Numerous studies have shown that consumers who find online shopping to be simple to use and useful are more likely to engage in it [33, 39, 40]. Other factors that have been identified as having a significant impact on consumers' online shopping behaviour include electronic word of mouth (eWOM) [41] and website design [42,43]. However, these are areas to which scholars investigating emerging consumer markets, particularly those in South Africa have paid little attention. Consequently, a better understanding of these factors from the perspective of various consumers, emerging consumers in particular, is vital. Therefore, the study sought to gain a better understanding of online shopping adoption by extending the TAM through the addition of a further three factors, namely convenience, website quality and eWOM, all of which have been shown to influence online shopping attitude and purchase intention.
Conceptual model development and hypothesis testing
Website quality
Consumers use websites as a communication platform to assist them with their online purchases [44]. Logically, online retailers should ensure that the design and characteristics of the website are reliable, credible and of good quality, and provide excellent service during and after the purchase [45] since all these components determine website quality, which has a significant impact on consumers' intention to purchase products and services online [46].
According to Lee et al (2016) [42], the quality of an online retailer's website is essential in predicting the purchase intention of online consumers. Numerous studies on consumer attitudes toward online shopping have affirmed this. Jing, Zaidin, Zakuan, Ismail and Ishak (2015) [47], for example, investigated the relationship between website quality and consumer attitude toward online shopping; the findings revealed website quality to have a positive and significant impact on consumer attitudes toward online shopping The factors influencing online purchase intention among Pakistani youth were researched by [48] who found the relationship between website quality and online shopping intention to be mediated by attitude [48]. In their study exploring student attitudes toward online purchasing behaviour in Malaysia [45] found the quality of a website to have a direct impact on people's attitudes toward online shopping. Moreover, the perceived website image, which relates to the design, credibility and visual appeal of the website, was found to have a positive and significant effect on online shopping attitudes in Sri Lanka [43]. Therefore, the following hypothesis was formulated:
H1a: Website quality has a statistically significant influence on the attitude of emerging township market consumers towards shopping online
H1b: Website quality has a statistically significant influence on the intention of emerging township market consumers to shop online
Convenience
Convenience has been closely linked to the adoption of e-commerce [49] and online shopping platforms [50-53, 20]. Convenience relates to the selection of the most beneficial or simple way of achieving an objective [54]. Consumers in emerging markets perceive convenience to be a means of increasing efficiency, and a convenient online shopping platform is considered to be one that offers a diverse range of products, delivery options, flexible payment options and return policies [20]. As a result, convenience can be a motivator both before and after the purchase.
Consumers are devoting less time to shopping and more to other activities, which has increased their desire for convenience; as a result, their interest has shifted to online shopping [55]. This has made convenience a critical component promoting purchase intent, retention and consumer satisfaction in online shopping environments [56]. According to Arora and Aggarwal (2018) [10], convenience has an important positive effect on consumer online shopping attitudes, especially in developing countries.
Islam (2015) [57] investigated the factors that influence consumers' online shopping behaviour, and reported the existence of a convenient product return policy as having a positive influence on attitudes toward online shopping. Raman (2019) [58] examined the intention of female consumers to shop online and reported convenience as having a significant positive effect on the attitudes of these consumers toward online shopping [58]. The following hypothesis was formulated based on the above findings:
H2a: Convenience has a statistically significant influence on the attitude of emerging township market consumers towards shopping online
H2b: Convenience has a statistically significant influence on the intention of emerging township market consumers to shop online
eWOM
Consumers’ social groups, such as friends and family, play a crucial role in their purchasing decisions, as these social groups affirm their purchasing behaviour by suggesting products, services, brands, shopping channels and retail chains [59]. Electronic word of mouth (eWOM) has been identified as an important factor influencing consumer attitudes toward online shopping [60, 61]. Hussain, Song and Niu (2020) [62] define word of mouth as “informal and interpersonal communication with personal recommendations”. eWOM is an evolving class of word of mouth [41], and encompasses consumer communication via the internet [60]. eWOM is facilitated through social media platforms such as blogs, e-mails, Facebook, Twitter and [63] It has become an important marketing channel that businesses and marketers have infiltrated so as to increase sales and promote their brands [41].
Bachleda and Berrada-Fathi (2016) [64] investigated the impact of eWOM and WOM on consumer trust, attitudes and purchase intentions, and demonstrated that unfavourable eWOM has a negative influence on consumer attitude towards a service provider [64]. In contrast [41] on conducting a study to compare the influence of eWOM on consumer attitudes and purchase intent, and observed that eWOM to have a positive impact on consumer attitudes [41]. As a result, it is possible that eWOM will have a considerable impact on consumer attitudes toward online shopping adoption. Therefore, the following hypothesis was formulated:
H3a: E-word of mouth has a statistically significant influence on the attitude of emerging township market consumers towards shopping online
H3b: E-word of mouth has a statistically significant influence on the intention of emerging township market consumers to shop online
Perceived ease of use
Users are more likely to embrace a technological innovation that is viewed as simple to use than one that is perceived to be more difficult to use [65]. Perceived ease of use refers to the degree to which an individual believes the use of a technological innovation to require no effort [66]. The perceived ease of use of online shopping platforms has been identified as an important determinant of consumer adoption [67, 40] moreover, perceived ease of use has been recognised as the most significant factor affecting consumer attitude towards online shopping [47]. Generally speaking, the simpler to use consumers regard an online shopping platform to be, the more likely they will be to purchase from it.
A number of studies that have investigated consumer online adoption behaviour have found perceived ease of use to have a meaningful influence on attitude toward intention to shop online [32, 19]. More specifically, in a study by [36] that investigated consumer adoption of online grocery shopping, perceived ease of use was found to have an important impact on attitude toward intention to shop online [36]. In the context of an emerging market, [6] examined consumer attitudes toward online shopping; the latter were found to be negatively affected by low perceptions of ease of use [6]. The following hypothesis was formulated based on the preceding findings:
H4a: Ease of use has a statistically significant influence on the attitude of emerging township market consumer towards shopping online
H4b: Ease of use has a statistically significant influence on the intention of emerging township market consumers to shop online
Perceived usefulness
Perceived usefulness is defined as the degree to which an individual believes that embracing a specific system will improve his or her behavioural action [25]. In several studies of online shopping adoption, perceived usefulness has been highlighted as an important factor influencing consumers’ behavioural intentions [39, 40, 19]. This suggests that consumers are more inclined to use technological innovations that they perceive to be beneficial.
According to Mijoska and Blagoeva (2017) [32], who conducted research on the determinants of online shopping adoption among the youth in Macedonia, perceived usefulness was discovered to have a positive and significant impact on attitudes towards purchasing online [32] Through extending the TAM, [19] explored consumer adoption of online shopping. The perception of usefulness was found to have a substantial effect on attitudes towards online shopping intentions [19]. In addition, multiple studies of online shopping adoption have revealed perceived usefulness to have an important positive effect on attitude toward intention to purchase online [36], particularly in emerging consumer markets [6]. consequently, if consumers consider online shopping platforms to be useful, they will choose to shop online. As a result, the following hypothesis was developed:
H5a: Usefulness has a statistically significant influence on the attitude of emerging township market consumers towards shopping online
H5b: Usefulness has a statistically significant influence on the intention of emerging township market consumers to shop online
Attitude as mediator of the relationship between factors and intention to shop online
People’s attitudes are shaped by their beliefs and assessments of the consequences of engaging in a specific behaviour [6]. Thus, if a person’s attitude toward online shopping is positive, they are more likely to purchase products and services online. Schiffman, Kanuk and Wisenblit (2010:234) [68] define attitude as “a learned predisposition to behave consistently in a favorable or unfavourable manner with respect to a given object”. Arora and Aggarwal (2018) [10] concur, stating that the extent to which an individual has a positive or negative assessment of a behaviour is referred to as attitude. The term "online purchase intention" refers to a construct that fuels a consumer's desire to shop online it is therefore vital for retailers to exert a positive influence on consumers' attitudes positively in order to encourage purchase intent.
The attitude of consumers toward online shopping is an important factor in the online adoption process. Several studies on online shopping adoption indicate that a consumer's attitude is a significant predictor of their purchase intention [36, 32, 41, 69, 19]. By integrating the TAM and TPB, [40] developed a means to examine consumers' online purchase intent. The findings show consumer attitudes to have a significant positive impact on their intention to shop online [40].
Studies on online shopping adoption in emerging consumer markets have also found consumer attitude to have a significant influence on purchase intention. For example, a study by [10] investigated the attitudes of female consumers toward online shopping. The findings revealed a significant positive relationship between online shopping attitude and online shopping intention among Indian women [10]. Reyes-Mercado et al (2017) [6] analysed consumer attitudes toward online shopping in India and found these to have a positive and significant impact on purchase intention [6]. In addition, in an investigation of the attributes exerting an influence on online purchase intention among Pakistani youth, [48] found consumer attitudes toward online shopping to have a significant influence on consumers’ intentions to make online purchases [48].
Attitude has been shown to mediate the relationship between several independent variables and dependent variables, as suggested by the TAM [70]. For instance, [48] found attitude to have an indirect impact on the quality of websites and consumers' intentions to shop online, while in similar vein [71] found attitude to serve as a mediator in the relationship between willingness to participate in online co-creation activities and the quality of a website. These findings were further supported by [72], who showed that attitude mediates the influence of website quality on users' intentions to use online shopping apps.
Several researchers have noted the indirect influence of eWOM on behavioural intention through attitude [73, 74]. Furthermore, earlier research in the area of online shopping has demonstrated that attitude mediates the effect of online word-of-mouth on consumers' intentions to make online purchases [72, 75, and 76]. Additionally, in mobile banking [77] mobile-based agricultural extension services [78], online education [49], online food delivery applications [50] and online shopping [78], attitude was found to mediate the relationship between perceived ease of use and behavioural intention [79, 80].
Surprisingly, Noor, Noranee, Noor, Zakaria, Unin and Suaee (2020) [81] concluded that the dimensions of attitudes did not have any impact on purchase intention in the case of online products. Lavuri (2021) [82] identifies a number of factors affecting purchase intention that are mediated by attitude, while [83] concludes that attitude mediates the effect of perceived risk on purchase intention). Vijayan (2020) [84] studied the mediating role of attitude on the relationship between online shopping factors and intention to shop online, reporting that attitude does indeed mediate the relationship between online shopping factors, including perceived risk and intention to shop online. Zainal, Harun and Lily (2017) [85] state that attitude has a partial mediation effect on trust in eWOM source and intention to adopt it, while [86] support the view that attitude mediates security and privacy risks and purchase intention.
Prior research reveals that attitude indirectly affects the relationship between perceived use and behavioural intention, for instance in e-learning [87] mobile banking [77] and online food delivery applications [88]. In addition, attitude was found to mediate the association between perceived usefulness and intention to shop online [79]. The mediating effect of attitude was also confirmed by [88] who found attitude to mediate the association between convenience and behavioural intention to use online food delivery applications. Based on the preceding findings, the following hypotheses were developed.
H6: The attitude of emerging township market consumers towards online shopping has a statistically significant influence on their intention to shop online
H7: The attitude of emerging township market consumers mediates the relationship between website quality and their intention to shop online
H8: The attitude of emerging township market consumers mediates the relationship between e-word of mouth and their intention to shop online
H9: The attitude of emerging township market consumers mediates the relationship between convenience and their intention to shop online
H10: The attitude of emerging township market consumers mediates the relationship between perceived ease of use and their intention to shop online
H11: The attitude of emerging township market consumers mediates the relationship between perceived usefulness and their intention to shop online (Figure 1).
Figure 1: Shows the conceptual model for the study
Research Design, Sampling and Data Collection
Quantitative survey research was the method adopted to achieve the objective of the study, which was to determine the factors influencing the attitude of emerging market consumers towards online shopping. Since the study involved testing the conceptual model developed for the study, a survey was deemed appropriate for this purpose. A survey approach was further supported by existing studies that made use of the same approach. This approach also made it possible to collect data from a larger sample, as is needed in quantitative research.
The data was collected from consumers forming part of the emerging market in the township of Soweto who purchase clothing products online. According to Busitech (2020) [89], clothing is the second largest product type to be bought online since 2020, a fact attributable to the Covid-19 pandemic. Soweto is the largest township in South Africa and is home to a large number of consumers who fall within the emerging middle-class segment. Data was collected online by a research company through sharing an online link to a self-completion questionnaire with the emerging market consumers present in the company’s database. Data was collected in June 2021, and 300 questionnaires were completed in full by the respondents. The sample size matched those of other studies investigating online shopping such as those conducted by [89] and [90].
The questionnaire for the study reported on in this article was designed on the basis of existing literature, which was drawn on to identify factors influencing the attitude of emerging market consumers towards online shopping and their intention to shop online. Sources consulted in designing the questionnaire were: [25, 91-94]. There were 38 items measuring the attitude of emerging market consumers towards online shopping and their intention to shop online: website quality (9), convenience (9), eWOM (6), perceived ease of use (4), perceived usefulness (3), attitude (4) and behavioural intention (3). The questionnaire contained 13 demographic questions. A five-point Likert scale, with 1 indicating “highly disagree” and 5 “highly agree”, was used to measure all the constructs in the conceptual model. Ethical clearance approval was sought from the Department of Marketing and Retail Management at Unisa prior to data collection.
Validity and reliability
The validity of the study was determined using exploratory factor analysis (EFA). The output for the communalities from the EFA had factors with a minimum value of between 0.54 and 0.88, which exceeded the minimum threshold of 0.2 Child, 2006). So as to attain construct validity, the questionnaire was designed on the basis of existing studies.
The Cronbach’s alpha was computed to determine the reliability of the different constructs in the questionnaire. All the constructs had a Cronbach’s alpha of above 0.70 and were in consequence regarded as acceptable The Cronbach’s alpha (α) for convenience was 0.95, for website quality 0.96, eWOM 0.97, perceived ease of use 0.97 and perceived usefulness 0.94. Attitude and purchase intention had a Cronbach’s alpha (α) of 0.97 and 0.92 respectively.
Analysis of data
Data was analysed using the SAS JMP version 15 for Mac and the R language version 3.5.2. Descriptive analyses were conducted and included the mean and standard deviation. Other analysis included EFA and structural equation modelling (SEM), also used to achieve the objectives of the study.
The profile of the respondents is presented in the section below Demographics of the respondents of the population, which consisted of 300respondents, 221 of them, over 70 per cent (73.6%) of the respondents were female, and 25.6% (n=77) were male. The majority of the respondents (70%, n=200) fell within the age group 18 to 29, with 22 per cent (n=65) within the age group 30 to 40 years. The majority of the respondents (72%, n=216) were unmarried. Of the 300 respondents, 37% (n=110) had passed Grade 12, and 178 of them had post school qualification consisting of 23% (n=68) holding diploma or certificate and 38% (115) who held a degree Most of the respondents (62%, n=186) earned between R5 000 and R7 500, with only 9 per cent (n=27) earning above R20 000.
Factor analysis
Principal axis factoring was used to extract online factors influencing shopper attitude towards online shopping intention, followed by a quartimin (oblique) rotation. There were five factors with eigenvalues greater than 1, with a total variance of 81.12. Each of the factors had factor loading of 0.5 and higher, as shown in table 1 below. The exploratory principal factor analysis with axis factoring was carried out in SAS JMP version 15, which is considered appropriate for the correlation patterns between the questions used to determine respondents’ perceptions (Table 1).
| Factors | Factor 1: Website quality | Factor 2: Convenience | Factor 3: E-word of mouth | Factor 4: Ease of use | Factor 5: Usefulness |
|---|---|---|---|---|---|
| When I use the websites there is very little time between my actions and online companies responses | 0.93 | -0.04 | 0.07 | -0.08 | -0.02 |
| The design of shopping websites has a good look and feel | 0.88 | 0.04 | -0.03 | 0 | 0.06 |
| It is easy to find my way around the shopping sites | 0.83 | 0.07 | -0.06 | 0.04 | 0.07 |
| When products or services fail online companies resolve it without me having to spend a considerable amount of time, money and/or energy | 0.81 | 0.04 | 0.11 | 0.01 | -0.16 |
| Information is available for me to make the purchase decision when doing online shopping | 0.78 | 0.06 | -0.05 | 0.11 | 0.1 |
| It is difficult to find appropriate websites | 0.78 | -0.07 | 0.07 | -0.06 | -0.03 |
| The information I need is easily accessible online | 0.78 | 0.09 | -0.07 | 0.12 | 0.08 |
| When I need online support the contact telephone numbers and email addresses of customer service representatives (CSR) are easily found on the websites | 0.78 | 0.02 | 0.09 | -0.02 | -0.04 |
| I can compare information about the product online | 0.77 | -0.01 | -0.11 | 0.2 | 0.15 |
| Online companies inform me of the date and time when I am going to receive my order | 0.73 | 0.12 | -0.01 | 0.09 | 0.07 |
| The whole online purchase process is better than having to go to the store | -0.02 | 0.87 | -0.01 | 0.06 | -0.11 |
| I can save the effort of going to the store | 0.04 | 0.85 | 0.03 | -0.01 | 0.01 |
| Shopping online is convenient | -0.09 | 0.85 | -0.06 | 0.05 | 0.17 |
| Online shopping service efficiency is expected due to the options of delivery | 0.06 | 0.83 | 0.1 | -0.04 | -0.07 |
| Online stores deliver an efficient service | -0.06 | 0.83 | 0.07 | 0.08 | -0.09 |
| Shopping sites provide delivery options | 0.06 | 0.82 | 0.05 | -0.06 | 0.06 |
| I do not have to wait to be served | 0.1 | 0.79 | 0.01 | -0.03 | 0.03 |
| Convenience of buying online It is easy to find my way around the shopping sites | 0.03 | 0.79 | 0.09 | 0.02 | 0.01 |
| I have access to many brands and retailers anywhere anytime I want | 0.08 | 0.77 | -0.1 | 0.03 | 0.14 |
| I buy a product from this online catalogue retailer consumers online recommendations and | 0.03 | -0.02 | 0.89 | 0.03 | 0.05 |
| My ecommunity frequently post online recommendations to buy from this online catalogue retailer | 0 | 0.01 | 0.87 | 0.08 | 0.02 |
| I often read positive online reviews about the products of this online catalogue retailer | 0.05 | 0.05 | 0.82 | 0.03 | 0.05 |
| I often read positive online comments about this online catalogue retailer | -0.01 | 0.04 | 0.78 | 0.06 | 0.11 |
| I often read online recommendations to buy products from this online catalogue retailer | 0.05 | 0.16 | 0.71 | 0.03 | 0.06 |
| I think online shopping is easy to use | 0.04 | -0.02 | -0.03 | 0.92 | 0.03 |
| I think I can shop online without encountering any problems | 0.05 | 0.01 | 0.07 | 0.86 | -0.07 |
| I think internet shopping requires less effort on my part | -0.03 | 0.04 | 0.05 | 0.85 | 0.03 |
| I think I can shop online without any need for assistance | 0 | 0.02 | 0.06 | 0.83 | 0.03 |
| I can find greater variety of products and models online | 0.05 | 0.06 | 0.13 | 0.01 | 0.76 |
| Online shopping makes it easy to compare various products ad brands | 0.01 | 0.02 | 0.15 | 0.09 | 0.74 |
| I can get better prices | 0.1 | 0.08 | 0.16 | 0.06 | 0.61 |
| Cronbach’s alpha | 0.96 | 0.96 | 0.96 | 0.95 | 0.91 |
| Mean score | 3.41 | 3.56 | 3.47 | 3.66 | 3.51 |
| Standard deviation | 0.99 | 0.96 | 1.12 | 1.03 | 1.01 |
Table 1. Factor analysis.
Factor 1 (website quality) had a mean score (M) of 3.47 with a standard deviation (SD) of 0.99. As reflected by the fact that this factor had the lowest M score, the respondents found this factor to have the least influence on their intention to shop online. The second factor, convenience, had an M score of 3.56 (SD=0.96), the second highest, indicating that the respondents agreed that this factor is of importance in online shopping. E-word of mouth, the third factor, had an M score of 3.47 (SD=1.12), and is the factor with the 2nd lowest score, indicating that the respondents agreed that this factor is less important in online shopping. The fourth factor, ease of use, had the highest M score at 3.66 (SD=1.03), which demonstrates its importance in online shopping. The fifth factor, usefulness, which had three items, had an M score of 3.51, showing the agreement of emerging market consumers that usefulness is important in online shopping. An SD closer to 1 indicates that there is variation in the response which therefore means that the response for factor 3, factor 4 and factor 5 varies across the respondence due to the higher SD of above 1.
Model testing
To test the conceptual model developed for this study, the lavaan version 0.6–1 Rosseel, 2012) in R version 3.5.2 (R Core Team, 2018) was used. The maximum likelihood estimation with robust standard errors (maximum likelihood means (MLM)) test analysis was used. MLM is a test analysis which produces a robust (scaled) test statistic. The latent factors were standardised using the R version 3.5.2 with the lavaan library to allow free estimation of all factor loadings; this was done to assess causative relationships among latent constructs To test the model fit, various indices were used and included: chi-square value over degree of freedom, the normed fit index (NFI), the incremental fit index (IFI), the Tucker Lewis index (TLI), the comparative fit index (CFI) and the standard root mean residual (root mean square error of approximation (RMSEA)). According to Hair et al (2006), in order for the model to be considered fit, the goodness-of-fit index (GFI), CFI, TLI, IFI, relative fit index (RFI) and NFI must be greater than or equal to 0.9. However, a value of 0.8 is acceptable (Hair et al, 2006). The values for each of the indices are shown in table 2 below (Table 2).
Model fit index |
Chi-square (X2/DF) | GFI (goodness-of-fit index) | CFI (com-parative fit index) | TLI (Tucker-Lewis index) | IFI (incre-mental fit index) | RFI (relative fit index) | NFI (normed fit index) | RMSEA root (mean square error of approximation) |
|---|---|---|---|---|---|---|---|---|
| Value indicator | 1.4 | 0.78 | 0.97 | 0.96 | 0.98 | 0.92 | 0.93 | 0.049 |
Table 2. Model fit indices.
As shown in Table 2 above, the model fit was moderately good with the following indices: chi-square (681) = 957.424, p = 0.009, relative chi-square = 1.40, RMSEA of 0.049 (90%, CI (0.049, 0.056), standardised root mean squared residual (SRMSR) = 0.039, 0.056, CFI = 0.97 (robust) and TLI of 0.96 (robust). The 90% confidence interval for the RMSEA statistics ranged from 0.049 to 0.056, meaning that it is possible that the population RMSEA statistic could be as low as 0.049 or as high as 0.056. Blunch (2012) and Hancock and Mueller (2010) a model is considered appropriate when its CFI is greater than 0.9 and its RMSEA is less than 0.1.
Hypothesis test results
To achieve the objectives of the study and to test the hypothesis as formulated, two regressions were computed for the structural part of the SEM model. The first regression table shows the results testing the influence of online factors on attitude and intention of emerging market consumers as well as the influence of attitude of emerging market consumers on their intention to shop online (Table 3).
| Intention | Beta coefficient (b) | Std error | z-value | p-value | Std coefficient | Decision |
|---|---|---|---|---|---|---|
| Conv →Att. | 0.25 | 0.083 | 3.014 | 0.003 | 0.212 | Supported |
| Web qual→ Att. | -0.068 | -0.074 | -0.919 | -0.358 | -0.048 | Rejected |
| EU→Att. | 0.056 | 0.07 | 0.795 | 0.427 | 0.049 | Rejected |
| eWOM→Att. | 0.122 | 0.079 | 1.547 | 0.122 | 0.116 | Rejected |
| U→Att. | 0.772 | 0.093 | 8.295 | 0 | 0.621 | Supported |
| Conv→Int. | 0.068 | 0.064 | 1.051 | 0.293 | 0.06 | Rejected |
| Web qual→Int. | 0.07 | 0.088 | 0.802 | 0.423 | 0.052 | Rejected |
| EU→Int. | 0.022 | 0.063 | 0.348 | 0.727 | 0.02 | Rejected |
| eWOM→ Int. | 0.071 | 0.064 | 1.111 | 0.266 | 0.071 | Rejected |
| U→Int. | 0.103 | 0.106 | 0.978 | 0.328 | 0.087 | Rejected |
| Att → Int. | 0.652 | 0.082 | 7.96 | 0 | 0.68 | Supported |
Note: p ≤ 0.001; p ≤ 0.05*
Table 3. Regression analysis.
The SEM model with the z-values with Wald tests was used to test the statistical significance of the influence of online factors on the attitude of emerging market consumers. As is evident from Table 3, usefulness had a much greater effect on attitude towards shopping online, with a beta coefficient of 0.767 (z = 8.493). This was followed by convenience (Conv.), with a beta coefficient of 0.253 (z = 3.073). Website quality (Web. Qual.), e-word of mouth (eWOM) and ease of use (EU) were shown to have no marked effect on emerging market consumers’ attitude (Att.) towards shopping online.
The SEM model with the z-values with Wald tests was used to test the statistical significance of the influence of online factors on emerging market consumers’ intention to shop online. As can be seen from Table 3, convenience (Conv.), website quality (web qual.), ease of use (EU), e-word of mouth (eWOM) and usefulness (U) had no marked effect on consumer intention (Int.) to shop online–this implies that these factors do not influence consumers’ intention to shop online.
The effect of consumer attitude on consumers’ intention to shop online is also reflected in Table 3 above. As can be seen from the table, consumer attitude had an important influence on consumer intention to shop online, as indicated by the beta coefficient (β) of 0.652 (z = 7.960).
To test the mediation effect of attitude on the relationship between factors influencing online shopping and consumer intention to shop online, the SEM model with the z-values with Wald tests was used to test the statistical significance of the influence of online factors on emerging market consumers’ intention to shop online. The results appear in Table 4 below.
Attitude was found to mediate a significant path relationship between convenience and intention to shop online (β = 0.163, p = 0.004); the hypothesis is therefore supported.
Attitude was found not to mediate a significant path relationship between website quality and intention to shop online (β = 0.044, p = 0.362); the hypothesis is therefore rejected (Table 4).
Intention |
Beta coefficient | Std error | z-value | p-value | Std coefficient | Decision |
|---|---|---|---|---|---|---|
| Conv →Att. → Int. | 0.163 | 0.057 | 2.86 | 0.004 | 0.145 | Supported |
| Web qual →Att. Int. | -0.044 | -0.048 | -0.912 | -0.362 | -0.033 | Rejected |
| EU →Att. →Int. | 0.036 | 0.046 | 0.793 | 0.428 | 0.033 | Rejected |
| eWOM→ Att. →Int. | 0.08 | 0.053 | 1.51 | 0.131 | 0.079 | Rejected |
| U →Att. →Int. | 0.503 | 0.09 | 5.62 | 0 | 0.423 | Supported |
Table 4. Indirect effect: mediation effect of attitude.
Attitude was found not to mediate a significant path relationship between ease of use and intention to shop online (β = 0.036, p = 0.428); the hypothesis is therefore rejected.
Attitude was found not to mediate a significant path relationship between eWOM and intention to shop online (β = 0.080, p = 0.131); the hypothesis is therefore rejected.
Attitude was found to mediate a significant path relationship between usefulness and intention to shop online (β = 0.503, p = 0.000); the hypothesis is therefore supported.
The results of the study showed consumer attitude towards online shopping to be dependent on website quality and ease of use, and the relationship between website quality and consumer attitude to online shopping to be negative. Convenience, eWOM and usefulness were found not to influence consumer attitude in online shopping. None of these factors had an effect on consumer intention to shop online.
The study found convenience to have an effect on consumer attitude towards online shopping intention, and that none of the factors influenced shopper intention to shop online. The effect of convenience on consumer attitude towards online shopping is supported by existing studies. However, the effect of convenience on shopper intention to shop online is not supported, since [91, 93] reported that convenience influences intention to shop online. The mediation effect of attitude on the relationship between convenience and intention to shop online was supported. Nurdianasari and Indrianihe (2021) as supported by concluded that there is an indirect relationship between convenience and online shopping intention.
Website quality does not have a statistically significant influence on either the attitude of emerging market consumers towards online shopping or their intention to shop online. These findings are contradicted by who found website quality to exert an influence on both shoppers’ attitude and their intention to shop online. found website quality to influence online shopping. The mediation effect of attitude on the relationship between website quality and intention to shop online was rejected. Nia and Shokouhyar (2020) found website quality to have a direct influence on satisfaction, while found the effect of website quality on consumer intention to shop online to be mediated by trust in online shopping.
Ease of use was shown to have no significant influence on the attitude of emerging market consumers towards online shopping and no significant influence on their intention to shop online. Mandilas, Karasavvoglou, Nikolaidis and Tsourgiannis (2013) reported ease of use as having a moderate effect on attitude towards online shopping, while [94] found it to influence consumers’ attitude towards online shopping. Mutahar et al (2018) concluded that ease of use does influence intention to shop online. Low-income consumers were found to be influenced by ease of use, which implies that factors influencing attitude to shop online differ across market segments The results reported by were surprising, in that ease of use was not found to influence consumer attitude, as was reported in many studies, whereas subsequently supported by reported ease of use as an important factor explaining consumers’ intention to adopt online shopping. The finding that attitude does not mediate the relationship between ease of use and online shopping intention is not aligned with existing studies, since reported there to be an indirect relationship between ease of use and consumer intention to shop online.
EWOM appeared not to have a significant influence on either the attitude of emerging market consumers towards online shopping, or on their intention to shop online. This is surprising, since township consumers rely heavily on word of mouth as a trusted source; this includes reliance on social media [24]. According to eWOM influences online shopping if it is moderated by trust in shopping online. Consumers trust the information provided by other shoppers as online opinions and recommendations are important for online shoppers However, this did not apply in the case of the study reported on here, since the hypotheses were rejected, indicating that consumers did not rely on information from other shoppers. eWOM was also reported by as influencing consumer attitude and the intention of travellers. The hypothesis testing the mediation effect of attitude on the relationship between eWOM and intention to shop online was rejected. Attitude was found by [85] to partially mediate the relationship between trust in e-word of mouth source and intention to follow. Liao, Hu, Chung and Huang (2021) found eWOM to fully mediate the relationship between perceived risk and online purchase intention, which was in contrast to this study finding. Moreover, argued that the mediation effect of eWOM on perceived risk and online shopping intention is weak when there is a high degree of online involvement, which bears out the reason for the absence of the mediation effect of attitude in the study reported on here.
Usefulness has a significant influence on the attitude of emerging market consumers towards online shopping. Usefulness also has a significant influence on the intention of emerging market consumers in engaging in online shopping. Studies by further support the finding that usefulness influences consumer attitude towards online shopping. Similar to this study found usefulness to be the most important factor influencing online shopping, whereas found usefulness to be an important factor influencing consumer intention to shop online. Austermann and Martins (2014) found perceived usefulness to have an impact on the attitude of managers towards social media, and that attitude towards using social media influences the intention. The hypothesis testing the mediation effect of attitude on the path relationship between usefulness and intention to shop online was supported. Bhatti, Riaz, Nauman and Ashfaq (2022) confirm the mediation effect of attitude on the relationship between usefulness and online purchase intentions found the relationship between usefulness and consumers’ intention to shop online to be indirect.
Attitude has a statistically significant influence on the attitude of emerging market consumers towards online shopping. Attitude has the strongest influence on the intention of emerging market consumers to shop online, a finding supported by Other studies to have also reported the influence of attitude on intention to shop online include those [81, 83].
Theoretical contributions
The study reported on in this article offers a number of important contributions to the literature. The first is that the study highlighted the importance of determining whether factors that influence consumer attitude in online shopping also have an influence on consumers’ intention to shop online. Therefore, the study confirmed the absence of a direct relationship between all five variables and consumer intention to shop online. The second contribution is that the drivers of online shopping as indicated in the TAM do not all influence consumer attitude and intention to shop online; for instance, only usefulness was found to influence consumer attitude in online shopping. The study further confirmed that consumer attitude does indeed have an effect on intention to shop online, which proves that the model is partially supported.
The third contribution is the addition of variables such as convenience, website quality and eWOM to the existing variables in the TAM. Contrary to those of existing studies (Zerbini et al, 2020), the findings revealed usefulness to have a greater influence on consumer attitude towards online shopping than consumer attitude on intention to shop online.
The fourth contribution is an interesting finding to the effect that convenience and usefulness, the two factors that were found to influence consumer attitude in online shopping, were also found to have an indirect effect on intention to shop online, while those that did not have an effect on consumer attitude did not have an indirect effect on intention to shop online either.
Practical contributions
The study also makes a practical contribution in that the information will potentially be of value to online retailers and policy makers. This study applied the TAM and added other factors such as website quality, convenience and eWOM to determine consumers’ attitude towards online shopping. Of the five factors, convenience and usefulness were found to have an influence on the attitude of emerging market consumers towards online shopping. Consumer attitude to online shopping was also found to influence consumers’ intention to shop online. The findings showed the convenience and usefulness offered by online retailers to be mediated by consumer attitude in online shopping. This implies that online retailers should change consumer attitude concerning the convenience and usefulness of online shopping as a means to encourage them to shop online.
Online retailers should ensure that the online shopping process is designed to be as convenient as possible to attract consumers shopping for clothes. They can do this by making sure that it is easy for consumers to find the clothing design, sizes, styles and fashion they want, saving them effort when shopping. They should also provide an efficient service and offer consumers delivery options: for example, consumers could opt to have goods delivered to either their home or workplace, with the additional option to collect from a designated location. The website should be easily navigable, allowing consumers to find what they are looking for without any difficulty. Consumers should also be easily able to return the merchandise should it prove unsuitable.
Since usefulness was found to have the greatest effect on consumers’ attitude towards online shopping for clothing, online retailers could provide a variety of products and designs online. The online store should be a one-stop shop for consumers, enabling them to find everything that they are looking for at a single online location. If the online retailer offers a number of clothing products and designs, this gives consumers more options, and they may be less likely to approach competitors. Online retailers such as Superb list and Taka lot make a number of products and brands available so as to offer consumers choice. Consumers should also find it easy to compare the various products and brands within a single online store. One of the reasons consumers shop online is the opportunity that this presents to buy products at competitive prices. Therefore, online retailers should ensure that their prices are as competitive as possible to attract consumers to the online store.
Customers cannot be offered the benefit of the convenience of online shopping and its usefulness without the quality of the website being a consideration. Therefore, online retailers should ensure that the interval between their actions and retailer response is as short as possible. Consumers should be able to find their way around the website easily, and it should be easily accessible to consumers. Retailers should also provide the necessary information about delivery and payment options, and other relevant details. If consumers have complaints or grievances, they should be able to lodge these easily, and receive a prompt response from the online retailer.
In addition, online retailers should design their online shop in such a way that consumers are able to use it without encountering any problems, and if there are any problems, retailers should be available to assist. The online shop should also be designed in such a way that consumers are able to transact without much effort, and they are able to shop without needing assistance from the retailer. Online retailers should ensure that they manage the attitude of emerging market consumers if they want to influence them to shop online, since their attitude towards online shopping was found to influence their intention to shop online.
Convenience and perceived usefulness were found to have an influence on the attitude of emerging market consumers towards online shopping, while website quality, eWOM and perceived ease of use were found to have little influence. The attitude of emerging market consumers was found to influence their intention to shop.
The limitations of the study were twofold. First, the study focused exclusively on emerging market consumers in Soweto. Emerging market consumers are known to be heterogeneous and to have diverse needs, so other studies could investigate emerging market consumers from other areas in South Africa to determine whether the factors influencing their attitude towards online shopping are similar. The second limitation was that the study focused on five factors-website quality, convenience, eWOM, ease of use and usefulness. Subsequent studies could also investigate other factors with the potential to influence the attitude of emerging market consumers towards online shopping.
Competing interests: The authors declare that they have no financial or personal relationships that may have inappropriately influenced them in writing this research article.
Authors’ contributions: K.M.M. completed the research methodology and empirical part of the article. K.N. wrote the literature section of the article.
Funding information: This research was funded by the Unisa Women in Research (WIR) funding programme.
Data availability: The data that support the findings of this study are available from the corresponding author, K.M.M., upon reasonable request.
Disclaimer: The views and opinions expressed in this article are those of the authors and do not necessarily reflect the official policy or position of any affiliated agency of the authors.
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