Description of shopping behaviour

Logistic regression is used to be able to estimate which variables do mostly influence shopping behaviour of consumers. With logistic regression we can predict which of two categories a person is likely to belong to given certain other information. The shopping behaviour of respondents is considered as a categorical dichotomy, for instance; fashion orientate online; Yes=1, No=0. With this regression we can predict to which category (Yes or No) a respondent belongs to, given information about psychographics and demographics. For instance, orientation for fashion online is the dependent variable, demographics and psychographics are independent variables which can predict the outcome of the dependent variable. Variables which participate in predicting the outcome of the dependent variable are the predictors; as mentioned before, Nagelkerke R Square is an indication for the fit of the model.

Variables which were used within this analysis are psychographics, situation at home, work, income, gender, age and education. Table 9 shows a summary of the results of the twelve logistic regression analyses.

Outcomes of the regression analyses are shown in Annex 5 tables 15-26, the complete analyses are shown in Annex B15. Significant results with a Nagelkerke R Square above .100 and an exp(B) value above 1.4 (marked green within annex 5) and below 0.600 (marked red within Annex 5) are discussed below. First, the category fashion is discussed, followed by personal care and groceries.

TABLE 9, SUMMARY LOGISTIC REGRESSION ONLINE AND OFFLINE BUYING BEHAVIOUR

Dependent variable Nagelkerke R

square

Predictors

orientation fashion – online (table 15, Annex 5)

.244 innovative, loyal, shopping enjoyment, income, gender, age and education

.202 innovative, loyal, gender, age and education

buy fashion – offline

.154 innovative, shopping enjoyment, situation and age

orientation personal care – offline (table 20, Annex 5)

.157 innovative, loyal, motivation to conform, shopping enjoyment, gender, age and education

.134 innovative, loyal, price conscious and age

orientation grocery – offline (table 24, Annex 5)

.161 innovative, loyal, motivation to conform, price conscious, gender, age and education

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Fashion

Online orientation

Whether consumers do orientate online for fashion can be predicted by psychographics (innovation, loyalty and shopping enjoyment), income, gender, age and education. In general we can say that young respondents (<30 years old- 30-49 years old) and women (=gender(1)) are very likely to orientate and buy fashion online as well as offline. The fact that younger consumers are more involved in online orientation and buying behaviour probably depends on the habitation to the use of internet, elderly persons are not grown up with the use of computers and the internet. In addition, the more un-innovative a consumers is, the less likely the consumer orientates online for fashion (innovative1 (1)= totally disagree). Further, there are interesting relations found between online orientation for fashion and loyalty as well as online orientation for fashion and shopping enjoyment. Un-loyal consumers (loyal6(2)=disagree on loyalty statement 6) are very likely to orientate online for fashion, and consumers which do not enjoy shopping (enjoyshopping 13 (1) = totally disagree on enjoy in shopping statement 13) are unlikely to orientate online for fashion. Also a relation is found between income and online orientation for fashion, consumers with low incomes (income (1) = income below €1100 and income (2) = income between €1100 and €1600) are unlikely to orientate online for fashion.

Offline orientation

Consumers’ offline orientation behaviour depends on consumers’ innovativity, loyalty, shopping enjoyment, gender, age and education. Un-innovative consumers (innovative4 (1&2)) are very unlikely to orientate offline for fashion, this also occurred for online orientation for fashion. Loyal consumers (loyal6(4)=agree on loyalty statement 6) are likely to orientate offline for fashion while un-loyal consumers are very unlikely to orientate offline for fashion (loyal7(1)=totally disagree on loyalty statement 7). In addition, a relation is found between shopping enjoyment and offline orientation for fashion. When consumers do not enjoy shopping (shopping enjoyment (1&2&3)) they are unlikely to orientate offline for fashion. This outcome was expected, because consumers which do not enjoy shopping are also unlikely to orientate online for fashion. Consumers who do not like to shop are unlikely to orientate for fashion online as well as offline. Women (=gender(1)) and younger (age(1&2)) respondents are more likely to orientate offline for fashion. Since the same results were found for online orientation for fashion, we can conclude that women and younger respondents are more likely to orientate online as well as offline for fashion.

Online buying

Innovativity, loyalty, gender, age and education significantly influence consumers’ online buying behaviour. Un-innovative consumers are very unlikely to purchase fashion online (Un-innovative5(1)= totally disagree on innovativity statement 5). Unfortunately, loyalty statement 6 (loyal 6) gives conflicting results, it shows that un-loyal (un-loyal6(2)) as well as un-loyal (un-loyal6(4)) consumers are very likely to buy fashion online. However, un-loyalty statement 7 (loyal7) shows that un-loyal consumers are very unlikely to buy fashion online.

Offline buying

Consumers’ offline buying behaviour can be predicted by innovativity, loyalty, shopping enjoyment, gender, age and education. Un-loyal consumers are very unlikely to buy fashion offline (loyal7) while according to the other loyalty statement (loyalty(8)) un-loyal consumers are very likely to buy fashion online, these results are in conflict with each other. Consumers which do not enjoy shopping and low educated consumers are very unlikely to buy fashion offline. In addition, women and younger consumers are likely to buy fashion online.

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Personal care

Online orientation

Online orientation behaviour for personal care products depends innovativity, shopping enjoyment, situation at home and age. Consumers under 30 years old are very likely to orientate online for personal care products.

Un-innovative consumers and consumers who do not enjoy shopping are unlikely to orientate online for personal care products.

Offline orientation

Whether consumers do orientate offline for personal care products depends on innovativity, loyalty, motivation to conform, shopping enjoyment, gender, age and education. Un-innovative consumers are very unlikely to orientate offline for personal care products as well as un-loyal consumers and consumers which do not enjoy shopping. When consumers do not need motivation to conform (motivationtoconform12(1&2)) then they are likely to orientate online for personal care products. Also within this analysis a positive relation is found between women and younger respondents and offline orientation for personal care products.

Online buying

Un-innovative consumers are un-likely to buy personal care products online (innovative3(1) & innovative5(1)).

This was an expected outcome because this also occurred for online orientation for personal care products.

Loyal consumers (loyal9(4)) are more likely to buy personal care products online. Price consciousness shows conflicting results, non price conscious consumers (priceconsciousness(1), exp(B)= 3,297) are very likely to buy personal care products online while price conscious consumers (priceconsciousness(4), exp(B)=,571) are very unlikely to buy personal care products online. These results are conflicting because the exp(B) value for price consciousness is above 0 for consumers that totally disagree with the statement and this value is below 0 for consumers that agree with the statement while consumers that totally agree with the statement is has an exp(B) value =0.

Offline buying

Consumers’ offline buying behaviour depends on consumers’ innovativity, loyalty, shopping enjoyment, gender, age and education. Non-innovative consumers (innovative4(1)) are very unlikely to buy personal care products offline. When consumers do not enjoy shopping (shopping enjoyment13(2)), then they are very unlikely to buy personal care products offline. Thereby, the younger the consumers are, the more likely it is that they buy personal care products offline. In addition, low educated consumers are unlikely to buy personal care product offline.

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Groceries

Online orientation

Whether consumers orientate online for groceries depends on innovativity, loyalty, price consciousness and age. Un-innovative consumers (innovative4(2)) are unlikely to orientate online for groceries. Thereby, the less price conscious consumers are the more unlikely it is to orientate online for groceries. In addition, younger consumers are very likely to orientate online for groceries.

Offline orientation

Predictors for offline orientation for groceries are innovativity, loyalty, motivation to conform, price consciousness, gender, age and education. Un-innovative consumers are very unlikely to orientate offline for groceries and innovative consumers are very likely to orientate offline for groceries. In addition, a significant relation is found between motivation to conform and offline orientation for groceries. However, this relation gives contrary results. Significant and clear results were found for age and offline orientation for groceries; the younger consumers are the more likely it is that consumers orientate offline for groceries.

Online buying

As well as for the other categories, innovativity is an important predictor for buying groceries online. Thereby loyalty, price consciousness and work are important predictors. The following significant and interesting results are found; innovative consumers are very unlikely to buy groceries online, this is a remarkable result. Because it was expected that consumers that buy groceries online must be innovative. Thereby, un-loyal consumers are unlikely to buy groceries online. More remarkable is the fact that price un-conscious consumers (priceconsciousness (1&2)) are very likely to buy groceries online (exp(B)= 5,666 and 3,412).

Offline buying

Offline buying behaviour of consumers for groceries can be predicted by innovativity, loyalty, price consciousness, income, age and education. Consumers which indicated they agreed with the statement about innovativity(4) are very likely to buy groceries offline. Thereby, price un-conscious and low-educated consumers are unlikely to buy groceries offline. Women and younger respondents are likely to buy groceries offline.

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5.3.4 CONCLUSION

The objective of this paragraph was to gain insight in consumers’ online and offline shopping behaviour. First, interesting results are discussed for online and offline orientation and buying behaviour. In general, consumers orientate more often online than they actually buy online. Within all three product categories (fashion, personal care and groceries), consumers most frequently orientate and buy online for fashion. In addition, consumers who regularly orientate online for fashion do also regularly orientate offline for fashion. For groceries there is lots of difference between online orientation and online buying behaviour. One out of three consumers regularly orientate online for groceries, while less than one out of ten consumers regularly buy groceries online.

Second, interesting relations were found between personal characteristics and shopping behaviour. For instance, younger consumers are more likely than older consumers to orientate and buy fashion online.

Especially 30-49 year old consumers are often involved in online buying and orientation for fashion (50% of the consumers between 30 and 49 years old buy fashion online). The fact that younger consumers are more involved in online orientation and buying, probably depends on the habitation to the use of internet, older persons are not grown up with the use of computers and the internet. Further, consumers with net household incomes above €2800 are more likely to orientate online for fashion than other consumers (33% of the respondents that orientate online for fashion have a net household income above €2800, while only 29% of the respondents has an income above €2800). This is probably related to the fact that full-time employees are likely to buy fashion online (38% of the online fashion buyers work full-time, while only 31% of the total respondents are fulltime employees). Full-time employees do also orientate, more than other consumers, online for fashion. Also, a positive relation is found between high educated consumers and online shopping behaviour. The higher a consumer is educated the more likely it is that the consumer buys fashion online (43%

of the consumers that buy fashion online is high educated, while 33% of the total respondents is high educated). Consumers online and offline shopping behaviour is related to personal characteristics such as work, income and education. Because these characteristics are often related to each other, it is interesting to investigate the predictive power of personal characteristics. Thanks to logistic regression we are able to predict which personal characteristics influence consumers’ online and offline shopping behaviour.

Interesting results are obtained from the logistic regression analysis. Psychographic as well as socio-demographic characteristics of respondents were used as input variables for estimating which variables significantly influence online and offline orientation and buying behaviour. These analyses show that psychographics are important variables for predicting orientation and buying behaviour. For instance, when consumers enjoy shopping they are more likely to orientate and buy products offline as well as online.

Previously, online shopping was often related to convenience. But, from these results we can conclude that consumers have fun while surfing online to search for information about products and buying products. In addition, this analysis shows that non-price conscious consumers are very likely to buy groceries online. This is probably due to the fact that budget-supermarket (where price conscious consumers often buy their groceries) do not offer the possibility to buy groceries online. Thereby, un-innovative consumers are unlikely to orientate and buy products online. Online shopping has become normal for many consumers, still one third of the respondents within this research indicated that they do not shop online for fashion. Despite, online shopping started in the nineties, some consumers still consider online shopping as an innovation. This is probably related to the fact that younger consumers (below 50 years old) are more likely than older consumers to orientate and buy online. Regarding online shopping behaviour, a generation gap is arisen due to the development of the internet.

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