Research purpose: The purpose of this study was to investigate the buying behaviour of mature consumers (older than 55) in Port Elizabeth shopping malls.

Motivation for the study: The perception of mature shoppers as old people with limited financial resources is untrue. This study investigates the behaviours of mature shoppers.

Research design, approach and method: A model guided the investigation. The authors facilitated four focus groups to gain insight into mature consumers’ buying behaviours. A field survey followed with a sample of mall shoppers (n = 680). The authors performed content analysis of the focus group material and used SPSS and AMOS programs to analyse the data quantitatively.

Main findings: Focus group interviews revealed specific buying behaviours of mature shoppers. The survey showed significant relationships between various determinants that influence respondents’ buying behaviours with adequate model fit indices. These results confirmed the convergent and discriminant validity of the model that comprises mall shopping anticipation, experience and patronage.

Practical/managerial implications: Mature shoppers’ expectations exceeded their experiences, suggesting dissatisfaction with some aspects of their experiences. Retailers and shopping mall managers need to redesign malls if they wish to cater for the segment of ageing shoppers and their spending power.

Contribution/value-add: The study contributes to the research available in South Africa on service at shopping malls that cater for mature consumers.

A number of studies have noted the attractive financial status of the mature segment (Hu & Jaspers, 2007; Laukkanen, Sinkkonen, Kivijarvi & Laukkanen, 2007; Moschis, Bellenger & Cusari, 2003; Walker & Mesnard, 2012). Freeman (2008) estimated that there are over 78 million people older than 50 living in the United States of America (USA) with a combined disposable income of over three trillion dollars. According to the McKinsey Report (Roxburg et al., 2009), asset classes in the mature market in South Africa are likely to grow more rapidly in the near future. McKinsey estimates that there are 2.8 billion adults, who are not part of formal financial systems, in emerging markets, of which South Africa is one, with discretionary income. Bank deposits and household incomes will increase as aging people open savings accounts. Walker and Mesnard (2012) estimated that the income share for the over-60s in South Africa will increase from 11.7% in 2005 to 16.5% in 2020.

The stereotyped perception of the mature market as a vulnerable group of people, much opposed to change and with limited financial resources, is untrue. Too often, marketers stereotype older consumers and ignore them in their marketing strategies. Birtwistle and Tsim (2005) reported, in a study of mature women’s clothing, that retailers in the United Kingdom were more interested in targeting fashionable young consumers and do not understand the needs of the mature market. It is also incorrect to believe that mature consumers will not try new products. Leventhal (1997) argues that aging consumers will definitely try out products, but for different reasons to younger consumers. Younger consumers will consider new products because it is trendy. Mature consumers consider new products that fit their aging needs, such as reader-friendly labels, helpful sales staff and increased print size (Laukkanen et al., 2007). Mattila, Karjaluoto and Pento (2003), in a study on Internet banking adoption amongst mature customers in Finland, found that over 30% of wealthy and well-educated mature males made e-banking their primary mode of making payments. Moschis and Nguyen (2008) observed that affluent mature people depend more on themselves to decide which financial services they will use. They consider themselves knowledgeable enough and do not care much about advice from children or relatives.

Gerontographics uses the theory that people change their outlooks on life when they experience major life events, such as retiring, losing a spouse or developing chronic health concerns, as its basis. Studies that the Centre for Mature Consumer Studies at the University of Wisconsin-Madison in the United States of America (USA) conducted revealed that these life changes occur as people age physically, psychologically, socially and spiritually. These life changes influence older consumers’ restaurant selection preferences (Moschis, Bellenger & Cusari, 2011), housing preferences, (Moschis et al, 2003), past and present preferences for food products and grocery stores (Moschis, 1996) as well as retail stores (Moschis, Sneath & Mathur, 1995).

Despite the growing importance of the mature consumer market, it is often the least understood market segment and marketers treat it as a homogeneous stereotypical group (Harris, 1993; Lazer, 1986). However, because of pioneering work at the Centre for Mature Consumer Studies, which George Moschis spearheaded in the 1990s, the mature market in the USA was segmented into four life stages: healthy indulgers, healthy hermits, ailing out goers and frail recluses. Authors such as Shufeldt, Oates and Vaught (1998), who investigated lifestyle as an important factor in the purchase of drugs by the elderly, and Leinweber (2001), who focused on the key values of older consumers, further recognised the heterogeneity between various sub segments of the mature market.

In South Africa, Benecke et al. (2011) identified three life style clusters with regard to the mature market’s media selection: old optimists, young up-beats and younger opinionists. The researchers observed a negative attitude towards advertising amongst mature people. Respondents felt neglected in advertising messages because they thought that media experts preferred to target younger consumers.

It seems that, because of its size and potential spending power, the mature market in South Africa deserves closer attention from the retail industry and academia. Mall operators should view mature consumers in South Africa as important because of their average high discretionary income and time to patronise shopping malls. Harris (1993) alludes to the fact that today’s senior citizens are living a more active and positive life. They are open to buying new products, planning and engaging in new activities, such as exploring different shopping malls. In contrast to their younger counterparts, mature consumers are more demanding in their expectations of shopping malls and less inclined to patronise malls if their service is poor.

Visser, Du Preez and Du Toit (1996) profiled mature female clothing shoppers in South Africa and identified three segments: clothing moderates, clothing enthusiasts and clothing unconcerned. They found no significant differences between the three groups with regard to evaluative criteria for clothing and clothing store attributes. A follow up study by Visser and Du Preez (1998) confirmed previous findings that segmenting mature apparel consumers is essential for sustained growth of this market. In another study, by Du Preez, Visser and Zietsman (2007), of South African male apparel consumers, the authors found that shopping mall behaviour differed with regard to their motivation for patronage, shopping companions and preferences for mall activities. Visser and Du Preez (2001) concluded that information about South African apparel shoppers is scant and that researchers should follow a multi-cultural approach that focuses on this market segment.

1. What are the expectations, experiences and patronage patterns of mature mall shoppers?

2. What are the relationships between the expectations, experiences and patronage mentioned above?

3. How should mall managers and store managers in malls attract mature shoppers to shop at malls?

The second objective of this study was to develop an instrument for measuring consumers’ expectations, experiences and patronage of mall shopping.

The third objective was to use the instrument in a quantitative survey of mature consumers in Port Elizabeth shopping malls.

The fourth objective was to derive guidelines for mall managers and store managers in malls on how to attract mature shoppers to shop at malls.

FIGURE 1: Theoretical model – Factors that influence mall shopping patronage.

Personal factors, such as specific needs, life styles and values, could influence mall shopping expectations. Hu & Jaspers (2007) report that mature consumers look for healthy food options, value quality more than quantity, are more inclined to utilitarian shopping and buy apparel for pleasure or need rather than conformity. Joung and Miller (2002) found that older female consumers, who actively participated in leisure and formal social activities, were interested and involved in fashion and enjoyed apparel shopping. Lumpkin and Hite (1988) observed that retailers emphasise profit related factors whilst elderly consumers want convenience and product related aspects.

Older consumers, who see themselves as experienced and astute shoppers who look for quality and service, emphasise the importance of shopping as a way of socialising and a leisure pursuit. According to Myers and Lumbers (2008), ’perceived age’ rather than chronological age should be the basis for determining marketing strategies that aim at the mature market.

With regard to emotional factors, previous studies (Donovan, Rossiter, Marcoolyn & Nesdale, 1994; Sherman Mathur & Smith, 1997) showed that, when shoppers felt happy and enjoyed the environment, they tended to stay longer in a store, buy more items and spend more. Customers prefer others to see them as individuals. Therefore, friendly and helpful staff members, who are sympathetic and sensitive to the needs of elderly customers, will contribute to a pleasurable shopping experience (Hu et al., 2007; Lumpkin, 1985). Unlike the generations that have followed, the mature market is not a product of an impersonal, mass-produced world (Huey, 2011). Goodwin and McElwee (1999) observed that senior citizens bought at outlets with a higher level of service quality than at other stores, even if the prices were marginally higher. Focus group discussions revealed that elderly respondents often found it difficult to find shopping mall staff members who are able and willing to help them.

Silvers (1997) found that the lives of people in their fifties are unsettled and have lots of variation. Essentially, consumers are staying younger in their minds and shopping behaviours and many do not feel their ages because of their lifestyles and emotional outlooks on life. They see shopping trips as fun, social experiences and enjoy trips to leisure destinations such as cinemas or health clubs. Liaw (2007) investigated the influence of several store environment cues on shopping mood and patronage satisfaction. He found that visual elements, such as design and perceptions of store employees, had positive relationships with buying emotion, consumption behaviour and customer satisfaction. Myers and Lumbers (2008) state that retailers need to market the shopping behaviours of older consumers as ’experience driven‘. This, according to the authors, is important if older consumers are going to choose shopping as a way of spending leisure time.

Based on these research findings, the authors formulated two hypotheses for testing the model in the South African context:

Hypothesis 1 (H₁): There is a positive relationship between personal factors and mall shopping anticipation.

Hypothesis 2 (H₂): There is a positive relationship between emotional factors and mall shopping anticipation.

Petermans and Van Cleempoel (2010) emphasise that, when they design a retail store environment for the mature market, designers should not overlook the importance of creating an efficient, user friendly and aesthetically pleasing shopping environment that pays particular attention to intangible social aspects. Older consumers’ consumption satisfaction does not come only from consuming tangible possessions but also from intangible experiences, such as feeling welcome in a retail store.

With regard to the situational factors that influence shopping experiences, Goodwin and McElwee (1999) investigated the store attributes that discriminated between various segments of mature consumers. The authors found that special discounts and check out tills for senior citizens seemed to be more important to the older segment than to younger shoppers. Walker and Mesnard (2012) investigated mature shoppers’ needs in a global maturing consumer study. They found that mature consumers sought quality products, are loyal to brands and are not particularly sensitive about prices. Kim, Kang and Kim (2005) investigated the relationship between loneliness and older consumers’ mall patronage motives. They found that lonely elderly consumers patronise shopping malls where there is a variety of services, such as entertainment (cinemas and restaurants), hair salons and banks. Mature shoppers also regarded close, adequate and easy parking as important, according to Meneely et al. (2009). Hu and Jaspers (2007) observed that mature shoppers preferred surface parking to ramp parking for safety reasons and because of difficulties with negotiating stairs.

A study in the United Kingdom and Ireland (Meneely et al., 2009) revealed that overcrowding was a concern for older people when shopping for food. They found that the size of supermarkets and queuing at checkouts had a negative effect on food shopping experiences. It also seemed that product relocation caused confusion and anxiety amongst older people. Sometimes, mature shoppers gave it as a reason for not shopping in particular supermarkets. Therefore, from a consumer perspective, it seemed that convenience, clarity and reliability are important situational variables that influence mall shopping experiences. Huey (2011) comments that seniors are the last people who enjoy personal relationships with the people who sell them goods and services.

It follows that environmental and situational factors can play important roles in mall shopping experiences. Consequently, the authors formulated two hypotheses for testing the model in a local context:

Hypothesis 3 (H₃): There is a positive relationship between mall shopping experiences and mall environment.

Hypothesis 4 (H₄): There is a positive relationship between mall shopping experiences and situational factors.

As the literature suggests (Du Plessis & Rousseau, 2007), the total shopping experience will determine the extent to which malls meet or realise expectations in practice. This issue relates to the disconfirmation paradigm that states that, when a discrepancy, positive or negative, occurs between prior expectations and the actual performance of a product or service, it will result in either post-purchase satisfaction or dissatisfaction with the product or service.

When performance outcomes exceed expectations, it usually leads to positive disconfirmation and satisfaction. However, if performance is lower than expectations it will lead to negative disconfirmation and dissatisfaction with products or services. A further consequence of negative disconfirmation may be post-decision regret, which is a strong feeling that a shopper has made a wrong purchase or choice of shopping mall. This can be a very severe emotional experience, especially when consumers cannot reverse their purchase decisions or shopping mall selections (Hoyer & MacInnes, 2003).

Based on these research findings, the authors formulated a hypothesis to test in this study:

Hypothesis 5 (H₅): There is a positive relationship between mall shopping anticipation and mall shopping experiences.

Many authors (Patterson, 2007; Pettigrew, Mizerski & Donavon, 2005) have found that increased store loyalty amongst older consumers relates to the extent to which they receive personal attention, value brand names and the shopping mall’s reputation. Dholakia (1999) suggests that satisfaction with an activity is a necessary precondition for repeat behaviours, especially when product or store choice exists. Wesley, Le Hew and Woodside (2006) support the view that mall visit satisfaction influences intention to visit the mall.

Huey (2011) states that seniors enjoy personal relationships with the people who sell them goods and services. The idea of exclusivity also works well with seniors. Weaver, Moschis and Davis (2011) suggest that life-event experiences and circumstances create physical, social and emotional demands to which everyone, young and old, must adapt during their lives. Members of the mature market are especially prone to buying products that are not necessarily suitable for, and available to, everyone. Moschis et al. (1995) observed that many older adults appear to be loyal to retail outlets, especially when they promote a variety of quality products and services primarily for older persons. These authors also report that store location and the nature of the layout are key motivating factors for attracting mature consumers. Handy and Clifton (2001) reported that shopping location improved the quality of life in that consumers did not have to travel long distances to shopping malls. Residents in a particular neighbourhood valued local shopping opportunities greatly. With regard to the nature of store layout, mature consumers often find it hard to navigate large shopping malls with too many hard-to-reach products on shelves that are either too low or too high (Walker & Mesnard, 2012).

Corlett (1999) and Kesner (1998) suggested that the discounts and award programmes that stores offer to senior citizens, as well as special personal services, relationship marketing and customer education, are good strategies for building store loyalty, increasing purchase frequency and promoting mall patronage. Huey (2011) emphasises that the informational approach usually succeeds with seniors because they are often sceptical and distrustful of innovations. Because their buying habits are conservative, they want specific ‘reasons why’ they should buy. They also appreciate the presence of information centres in shopping malls and the mail that they read carefully. Goodwin and McElwee (1999) state that stores could promote the special features of ‘traditional brands’ with increased in-store assistance to attract mature consumers to a particular shopping mall.

Therefore, one can assume that mature consumers’ anticipations and experiences in shopping malls will influence their mall patronage (frequency, location and nature).

Consequently, the authors formulated two hypotheses for testing the model in Port Elizabeth:

Hypothesis 6 (H₆): There is a positive relationship between mall shopping anticipation and mall shopping patronage.

Hypothesis 7 (H₇): There is a positive relationship between mall shopping experience and mall shopping patronage.

Survey: To obtain participants for the quantitative phase of the study, the authors envisaged a field survey, consisting of a non-probability sample with respondents who patronise three major shopping malls in Port Elizabeth.

• How often do you visit a shopping mall?
• Which shopping mall in Port Elizabeth do you prefer and why?
• How much time do you usually spend in a shopping mall?
• How much money on average do you spend when you visit a shopping mall?
• Which time of day and week do you usually go to the mall?
• What kind of stores do you visit most often in malls?
• What suggestions do you have for making shopping malls more attractive for mature shoppers?

Survey: The authors used a self-administered survey questionnaire, consisting of 45 items, in the quantitative study. They derived the items in the questionnaire from the literature and the focus group responses that Table 1 and Table 2 give. They used a five-point Likert-type rating scale to collect the data.

The questionnaire included items that relate to the variables in the conceptual model. The authors tested the 45 items in a pilot study. The pilot study involved ten respondents from a retirement village. They had to complete the questionnaire and comment on the clarity of the items. The respondents did not experience any problems with the clarity of the items. The first 15 items focused on personal factors (PF) and emotional factors (EF) as drivers of MSA, which the authors measured as the summated PF and EF scores. The next 21 items focused on mall environment (ME) and situational factors (SF) as drivers of MSE, which the authors measured as the summated ME and SF scores. The last nine items focused on mall shopping patronage.

The authors calculated the summated measures as the mean of the applicable item responses (see Annexure A). They ranged between a low score of 1 (disagree completely) and a high score of 5 (agree completely). The questionnaire ended with questions that related to demographic variables such as age category, gender, employment status (full, part time or retired) and marital status (married, divorced or widowed).

The interviews the first author facilitated explained the purpose of the research. After that, the respondents completed an ethical information consent form. This form explained that respondents could leave the interview at any stage if they felt uncomfortable about any questions he asked requesting information or about the discussion in general. The respondents also gave permission for him to make audio recordings of the discussions.

A post-graduate student transcribed the focus group interviews, which took place on four successive Saturday mornings in the department of industrial psychology. A research assistant in the department verified the correctness of the information.

Survey: Seventy graduate students at the Nelson Mandela Metropolitan University (NMMU), South Africa, carried out the fieldwork in February 2012 as part of a practical assignment. All fieldworkers received a proper briefing on sample selection and interview procedures. The authors instructed the fieldworkers to interview shoppers whilst they were shopping inside shopping malls and who were aged 55 years or older. They could be either full-time or part-time workers or retired. The fieldworkers used convenience sampling (willingness to be interviewed) to select respondents and interviewed them during mornings and afternoons over a four-week period. Each fieldworker had to interview ten respondents. Fieldworkers then had to write a one-page report on their fieldwork experience. From these reports, it was clear that respondents did not have any difficulty with answering the questionnaire because the questions were simple, straightforward to answer and had undergone testing in a pilot survey.

Survey: The authors used two statistical software applications to analyse the data. They used SPSS to calculate descriptive and inferential statistics and to perform exploratory factor analysis. They subsequently used AMOS to perform confirmatory factor analysis and structural equation modelling (SEM) to test the hypotheses of the model.

Table 1 summarises the main themes from the analysis of the data the authors collected from the four focus groups about consumers’ perceptions of shopping malls in Port Elizabeth. These results use the content analysis of the transcripts the authors recorded during the group interview sessions as their basis. The findings of the interviews, which Table 1 gives, support the notion that older respondents are critical in their perceptions of service delivery at shopping malls because they grew up in a different era (Goodwin & McElwee, 1999). This may also be because of their wider range of experiences and tendencies to compare shopping malls in different locations and cities. From the interviews, it did not seem that the respondents were loyal to a particular shopping mall. They tended to search for items wherever it was most convenient at a particular time.

Table 2 summarises the focus group participants’ most favourable and unfavourable perceptions of shopping malls in Port Elizabeth. Unfavourable perceptions exceeded the favourable ones. This illustrates the participants’ critical mind-sets. Responses to the opening question on what comes to mind when participants hear or think about the word ‘shopping mall’, the words ‘no parking’, ‘claustrophobic’, ‘stressful‘ and ‘boring’ featured prominently. Favourable responses included the words ‘bargains’ and ‘retail therapy’. The latter refers to the enjoyment of the variety available in malls.

Table 2 shows that participants appreciated some of the attractions shopping malls offered. Their unfavourable responses focused strongly on poor service delivery and the special needs of mature shoppers, which respondents believed would attract more mature shoppers to shopping malls in Port Elizabeth. Respondents were looking for competent employees, quality products and reasonable prices.

During the interviews, the authors noted that participants were offended if others referred to them as old or elderly although they admitted to expecting special treatment as senior citizens. Many of the unfavourable comments, such as ’high volumes of shoppers’ and ‘noise’, are beyond the control of managers. Most of the respondents indicated that they visited shopping malls on weekday mornings before noon to avoid ’the rush caused by school children and normal hour workers’.

In summary, the focus groups evoked mixed signals and images of the term ’shopping malls’ amongst mature consumers. These tentative results required further investigation in the quantitative phase of the study. The recorded protocols of the focus group interviews were the basis for generating items the authors used in the Likert-type rating scale questionnaire.

The reliability values Table 4 gives were disappointing, although acceptable in exploratory research, with the exception of MSP. These results suggest that the instrument needs revising to increase the reliability of the derived scores. An aspect that may have contributed to the low alphas is that a 45-item questionnaire may be too long for many elderly consumers to respond to and needs shortening in follow-up research.

Figure 2 shows the relationships between the factors, according to Pearson product-moment correlations. The figure also shows the goodness-of-fit indices for the model and the requirements for acceptable model fit with regard to chi-square (χ²/df < 3.00) and root-mean-squared-error (0.05 < RMSEA < 0.08), whilst the goodness-of-fit index (GFI) is just below the recommended threshold value of 0.90 (Browne & Cudeck, 1992). The correlations between the factors are all statistically (r > 0.075 at α = 0.05 level) and practically (r > 0.30) significant. The SEM results (see Figure 2) confirm all the hypotheses. Therefore, one can conclude that the model that comprises personal factors, emotional factors, mall environment, situational factors and mall shopping patronage with mall shopping anticipation and mall shopping experience shows adequate convergent and discriminatory validity.

Figure 2 shows that the strongest path coefficients were between mall shopping anticipation and emotional factors and between mall shopping experiences and mall environment. Therefore, one can conclude, from the model, that feelings about service quality and past pleasurable experiences influence mall-shopping anticipations for mature shoppers strongly. These findings support those of Hu and Jaspers (2007). Furthermore, the high correlation between mall shopping experience and mall environment suggests that mature consumers value store location, design and security greatly. These findings support those of Walker and Mesnard (2012) and Liaw (2007).

FIGURE 2: Factors that influence the mall shopping patronage of mature consumers.

The frequency distribution in Table 5 shows that, for all the factors, most respondents gave positive ratings (3.4–5.0). The most positive factors were EF, MSA and PF. This suggests that shopping malls should be sensitive to the needs of elderly customers with friendly and helpful staff and a variety of services (such as banks and hair salons) in terms of emotional factors (EF). In terms of personal factors (PF), this suggests that shopping malls should consider mature shoppers’ physical limitations, provide quality or luxury merchandise and stock ample health food products.

It is interesting to note from Table 5 that the respondents gave positive ratings for the mall shopping experience factors (MSE, ME and SF). This suggests that mature shoppers were generally satisfied with mall shopping in Port Elizabeth. However, one should note that the mean scores for these factors are at the bottom of the positive range of the response scale (3.4–4.2). This suggests that there is room for improvement and that shopping malls should prioritise aspects such as adequate parking facilities, special discounts for elderly consumers and a wider variety of goods. There were significantly large differences between the mean scores for MSA and MSE (M_MSA = 4.27, M_MSE = 3.71, t = 27.41, df = 679, p < 0.0005, d = 1.05). This suggests a discrepancy between mature consumers’ anticipations and actual experiences in shopping malls. Their expectations exceeded their experiences significantly, suggesting disconfirmation and post purchase dissatisfaction with some aspects of their shopping mall experiences. These discrepancies correspond to some of the critical comments the focus groups gave (see Table 2).

MSP, the factor that pertains to shoppers’ mall shopping patronage, obtained the lowest mean score (M_MSP = 3.47), although it was still in the positive range of the scale. Given that higher scores for this factor suggest regular loyal patronage with a recreational element (such as window-shopping), it follows that the patronage of mature shoppers in the sampled population is not at the desired level.

The main conclusion from the empirical research supported the literature that mature mall shoppers have specific needs and preferences. The authors observed significant relationships between mall shopping anticipation, mall shopping experiences and mall shopping patronage amongst mature consumers. Furthermore, mature shoppers’ anticipations were significantly higher than were their experiences in shopping malls. In addition, the authors found that mature shoppers’ mall shopping patronage needs improvement. These findings suggest that mall managers must carefully consider and sustain the needs of mature shoppers if they are to sustain the continuous patronage of mature shoppers in a highly competitive mall-shopping environment.

Furthermore, the results suggest that mature shoppers want high quality products at good prices in easy-to-open packages with easy-to-read labels, especially with regard to nutrition and health products. These findings have implications for shelf layout, packaging and clear labelling. Store managers must understand that, compared to younger working class shoppers, who are busy raising their families, have limited time for shopping and want to leave stores as soon as possible, mature shoppers are wiser, more experienced and have plenty of time for scrutinising products as well as for gathering information before they make decisions. Mature shoppers are also looking for social and leisure experiences.

Mature shoppers are an important market segment in South Africa. Store managers need to monitor them continuously because of their potential purchasing power. Shopping mall managers need their support and should focus on the personal preferences and emotional needs of elderly shoppers as well as on store environment and reasonably priced quality merchandise to increase mall shopping patronage.

Implications that relate to the model indicate that mall shopping patronage is the culmination of a variety of factors that shopping mall managers need to address. These factors are especially important when they cater for highly critical and experienced mature consumers.

One cannot generalise the findings of this study because of its exploratory nature and limited scope. One needs to extend research in the field to other regions in order to verify tentative shopping preferences and the patronage of mature shoppers.

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