Background and literature review

It is well acknowledged that children influence purchasing decisions within a family, and this influence is increasingly observable in various societies (Shoham, Dalakas, 2006; Bao et al., 2007; Su and Wang, 2010). Previous studies have shown that the child’s influence on their parents’ decision to buy a product might depend on a broad range of factors. Majority of them may be related with the family characteristics, demographics of the child and a product type.

Studied characteristics of the family typically included their age, education, occupation and income; they were found as being predictors for differences in the influence of child’s on their parents’ purchasing decisions (Akhter et al., 2012; Shergill et al., 2013). Also, it was important on which of the parents the child’s influence was exerted (father or mother);

therefore a gender of the influenced parent was taken into account.

Most of the researchers found that the child’s demographic data (gender, age) have caused the main differences of the influence: elder children have significantly stronger influence than younger ones, and this finding is pretty consistent in numerous studies (Akhter et al., 2012;

Beneke et al, 2011, Martensen, Grønholdt, 2008, Shoham, Dalakas, 2006; Shergill et al., 2013). However, the findings on the influence and importance of a child’s gender are rather diverse. Some authors have found that children’ influence depends on their gender (Beneke et al, 2011, Dikcius, Medeksiene, 2008; Kaur, Singh, 2006; Shoham, Dalakas, 2006), while others did not observe such a dependency (Martensen, Grønholdt, 2008).

A number of studies disclose the relation between the strength of children influence and the type of products purchased (Akhter et al., 2012; Beneke et al, 2011; Dikcius, Medeksiene, 2008; Kaur, Singh, 2006; Martensen, Grønholdt, 2008, Shoham, Dalakas, 2006, Shergill et al., 2013). The common denominator here is that children exert stronger influence on the family decision making processes for products that are relevant to themselves (Martensen, Grønholdt, 2008). Despite of the type of product grouping, children tend to be important players for products at which they are the main users (Aslan, Karalar, 2011).

A number of studies observed that child’s influence might depend on several factors simultaneously (Dikcius, Medeksiene, 2008; Kaur, Singh, 2006; Martensen, Grønholdt, 2008). Ramzy et al. (2012) concluded that the type of product, the age of the child and context of different countries (Egypt and U.S) impact parents’ perceptions of children’s influence on purchase decisions. Very similar factors were found to be important by Shergill et al. (2013).

In the context of these studies, the factor of a country remains the least explored and represents a certain research gap; there is very little exploration on what characteristics of countries are ‘responsible’ for the differences (economic development? culture?). We assume that one of the differentiating factors is culture, since it influences behavioural models within society and therefore – within families. Therefore influence of culture in this context is worth of further examination in similar studies (Shoham and Dalakas, 2006).

When considering cultural influences, researchers often relate cultural dimensions of Hofestde’s (2001) and the interpersonal influences in family purchase situations (Shoham, Dalakas, 2006; Shergill et al., 2013; Su, Wang, 2010; Su, 2011). Such an approach allows seeing the influence of children, linking it with a set of already estimated dimensions.

However, such an approach becomes more difficult, when reliable measurements are not yet available for a selected country. To cope with this, other approaches that help explaining cultural similarities and/or differences may be explored (Ramzy et al., 2012).

In this study, we aim to measure influence of children on purchasing decision within a family in two countries that significantly differ by parameters of their cultural context. We assume that these contextual differences may be reflected in different patterns of a child influence on purchasing decisions within their families. In case of one of the researched countries (Lithuania) all six dimensions, based on Hofstede’s model are known. The country

is described by rather low rank of power distance (42), above average individualism (60), low masculinity (19), relatively lower uncertainty avoidance (65), high long-term orientation (82) and low score on indulgence versus restraint (16) (Borker, 2012). This combination of metrics could be related with certain patterns of a child influence on purchasing decision.

The findings are compared with patterns in another country (Azerbaijan) that has significantly different cultural context, and it allows expecting differences in child influence on purchasing. Unfortunately, there are no established values of Hostede’s cultural dimensions for this country yet, and it creates difficulties in performing studies (Tracy, Matsumoto, 2008). However, the choice of this country for the comparison is based on the fact that both countries have some historical similarities and obvious cultural differences.

Both of them experienced a controversial historical period of being part of the former Soviet Union, which has influenced personal and social identities (Tereskinas, 2009) and behaviours within families. On the other hand – despite not yet established measurements of cultural dimensions, Azerbaijan is perceived as a rather masculine country, having numerous sets of cultural differences from Lithuania. This allows testing children influence on purchasing in the two rather different cultural contexts.

There are several methodological options on studying behavioural patterns within families. It may be directly based in the standpoint of a child (Singh, Aggarwal, 2012), or aim to disclose child’s influence from the point of view of other family members, typically – mothers (Ülger, & Ülger, 2012). The first choice allows concentrating either on the child’s characteristics, typically – age (Singh, Aggarwal, 2012), while the other allows a broader evaluation. The latter approach seems to be prevailing, in part – due to the complexity of collecting data directly from children (Morrow, Richards, 1996). In this study, we analysed child’s influence throughout perception of his/her mother.

Literature analysis enabled to develop the following hypotheses:

H1: Mothers in Azerbaijan evaluate children’s influence on a family’s purchasing decisions higher than those in Lithuania;

H₂: The attitude to a child’s influence on parents’ purchasing decision differs depending on interaction of several factors, such as the country, the child’s gender and the child’s age;

H3 Children have stronger influence on parents’ decisions in purchasing goods for a child’s personal use than in the case when goods for the family are bought.

H4: Azerbaijan children will have higher influence on parents’ purchasing decision related with goods for their use than Lithuanian children;

H₅: The attitude to a child’s influence on parents’ purchasing decision related with goods for the child differs depending on the interaction of the three variables (the country, the child’s gender and the child’s age);

H₆: Azerbaijan children will have bigger influence on parents’ purchasing decision related with goods for the family than Lithuanian children;

H7: The attitude about a child’s influence on parents’ purchasing decision related with products for the family differs depending on the interaction of a set of variables, i.e., the country, the child’s gender and the child’s age.

2. Research methodology

A lot of previous studies have focused on analysis of just one factor at the time. However, some researchers have noticed that the influence of a child on parent’s decision to buy a certain product depended on several interrelated factors together (e.g. a child’s age, type of a product, etc.). Therefore we expect that interaction of the three variables – the country, gender and age – can be a reason for different influence of a child on parents’ buying decisions. In order to prove it, we used a factorial design 2×2×2. The analysis included two different countries (Lithuania and Azerbaijan), two genders (boys and girls), and two age groups, i.e.,

4-12 and 13-18 years of age. As it was mentioned the literature overview, the strength of a child’s influence on parents’ purchasing decision depends on the product. Therefore we included products of the two types: goods aimed for the use of children, and those for the whole family. The group of products for children included 4 types, i.e. goods for school, books, toys, and computer games. The second group (goods for the whole family) included computers, furniture, cars and TV sets. As it was already mentioned above, we analysed child’s influence throughout perception of his/her mother.

The research instrument included a question about overall opinion related with a child’s influence on parents’ purchasing decisions “Children have influence on parents’ purchasing decision”, which was measured on a five point Likert scale from ‘totally disagree’ to ‘totally agree’. Other two questions measured an influence of a child on parents’ decisions to buy different products from two groups of goods – for a child and for a family. The construct of goods for a child included four questions about the influence of a child on parents’ purchasing decision of goods for school, books, toys, and computer games. The second construct was related with purchasing of goods for a family. It included four types of goods, i.e., computers, furniture, cars and TV sets. Each statement of the constructs was measured using a 10 point scale (1 - no influence; 10 – very strong influence). Cronbach’s alpha of the statements showed satisfactory level for the construct “Goods for a child” (α=0.641) and for a construct

“Goods for a family” (α=0.854). The questionnaire included the typical demographic characteristics of the respondent (age, employment and education) and the child (gender, age).

The questionnaire was presented in the Lithuanian language for respondents from Lithuania and it was translated into Russian for respondents from Azerbaijan.

The survey was performed in two countries – Lithuania and Azerbaijan. The respondents were selected using the method of judgmental sampling. In order to avoid situations when daughters have more influence on fathers while boys on mothers, the respondents’ sample was restricted to just women who had a child or children from 4 to 18 years old. If the respondent had several children of the age within the appropriate range, they had to answer only about one child. 100 correctly completed questionnaires from each country were included in the analysis – totally 200 questionnaires. The distribution of questionnaires according to the gender of children was roughly even; according to the age of children, respondents distributed: 59% - 4-12 years old; 41% - 13-18. With regard to the respondents’

(mothers) age, 59% of them were 36-55, and 41% - 26-35 years old.

3. Findings

First of all we analyzed mothers’ attitude to children’s influence on parents’ purchasing decisions. Our findings suggest that overall mothers agree with the statement about children’s influence (M=3.52). In order to evaluate the differences of the result we performed factorial ANOVA. A 2×2×2 full-factorial ANOVA examined the effects of the Country, the child’s Gender and the child’s Age on mothers’ attitude towards child’s influence. We found a statistical effect for the main effect of the Country (F1,192=7.508, p=0.007, partial eta²=0.038). Mothers from Azerbaijan agree more (M=3.76) than those from Lithuania (M=3.33) with the statement that children have the influence on parents’ purchasing decisions. It confirms hypothesis H1. In addition, we noticed that there was a difference in the evaluation depending on the Age of children. In the case of older children (aged 13-18) the average was higher (M=3.74) than in the case of younger children (M=3.35) (F1,192=6.239, p=0.013, partial eta² =0.031). It means older children have stronger influence than younger.

However, in this case the observed power was 0.7, which is lower than the required 0.8.

Therefore the result cannot be valid. None of the other main effects or interactions were found to be statistical. So, hypothesis H2 could not be proved, because interaction of Country×Gender×Age was not significant (F1,192=1.451, p=0.230, partial eta²=0.008).

Table1 Results of a factorial ANOVA for ananlysis mothers’ attitude towards child’s influence

Source Type III Sum

of Squares

df Mean Square

F Sig. Partial Eta² Observed Power^a

Country 7.583 1 7.583 7.508 0.007 0.038 0.778

Gender 1.229 1 1.229 1.217 0.271 0.006 0.195

Age 6.301 1 6.301 6.239 0.013 0.031 0.700

Country×Gender 1.584 1 1.584 1.569 0.212 0.008 0.238

Country×Age 3.912 1 3.912 3.873 0.051 0.020 0.499

Gender×Age 1.528 1 1.528 1.512 0.220 0.008 0.232

Country×Gender×Age 1.465 1 1.465 1.451 0.230 0.008 0.224

Error 193.912 192 1.010

R² =0.142 (Adjusted R² =0.110); a. Computed using alpha =0.05

According to literature, we expected that children will have a greater influence on parents’

decision to purchase goods for a child than goods for a family. Paired sample t test showed significant difference (t=20.954, p=0.000). As it was expected children had stronger influence with regard to goods for a child (M=7.65) than in the case of goods for a family (M=3.37).

Therefore we can confirm hypothesis H3.

The following two hypotheses were related to different importance of the child in purchasing goods for a child depending on the Country, or interaction between a Country, a Gender and an Age. A 2×2×2 full-factorial ANOVA examined these differences. We found a statistical effect for the main effect of the Country (F1,176=12.136, p=0.001, partial eta²=0.065). Mothers from Azerbaijan agree more (M=8.40) than those from Lithuania (M=7.14) with the statement that children have influence on parents’ purchasing decisions to buy goods for children. It confirms hypothesis H4. In addition, we noticed that there was a difference in the evaluation depending on the Gender of children. The boys’ average was higher (M=8.15) than that of girls (M=7.38) (F1,176=4.563, p=0.034, partial eta²=0.025).

However, in this case the observed power was 0.565, which is lower than the required 0.8.

Therefore we cannot accept this result. None of the other main effects or interactions were found to be statistical. So, we could not proof hypothesis H₅, because the interaction of Country×Gender×Age was not significant (F1,176=0.268, p=0.605, partial eta²=0.002).

Table2 The influence of the child on parents’ decision in case of goods for a child

Source Type III Sum

of Squares

df Mean Square

F Sig. Partial Eta² Observed Power^a

Country 57.751 1 57.751 12.136 0.001 0.065 0.934

Gender 21.712 1 21.712 4.563 0.034 0.025 0.565

Age 9.608 1 9.608 2.019 0.157 0.011 0.293

Country×Gender 6.686 1 6.686 1.405 0.237 0.008 0.218

Country×Age 13.019 1 13.019 2.736 0.100 0.015 0.377

Gender×Age 0.512 1 0.512 0.108 0.743 0.001 0.062

Country×Gender×Age 1.274 1 1.274 0.268 0.605 0.002 0.081

Error 837.515 176 4.759

R² =0.111 (Adjusted R² =0.076); a. Computed using alpha =0.05

The final two hypotheses were related to different importance of the child in purchasing goods for family depending on the country, or interaction of a Country, a Gender and an Age.

A 2×2×2 full-factorial ANOVA examined these differences. We found a statistical effect for the main effect of the Age (F1,186=6.326, p=0.013, partial eta²=0.033). In the case of older children (13-18 years old) the average was higher (M=3.99) than in the case of younger children (M=2.99). However, the observed power was 0.706 which is lower than the required

0.8. Hence the result lacks certainty and cannot be accepted. In addition, we can noticed that there is a significant difference depending on the interaction of the Country and the Gender (F1,186=4.559, p=0.034, partial eta²=0.024). It shows that Lithuanian boys (M=4.07) have bigger influence on parents’ decision to buy goods for family than Lithuanian girls (M=2.63).

No significant differences were found in the influence between Azerbaijan boys (M=3.50) and girls (M=3.75) or between the girls in the two countries (MAZ=3.750, MLI=2.635) and the boys (M_AZ=3.50, M_LI=4.07). However, in this case the observed power was 0.565, which is below than the required 0.8. Therefore we cannot be certain about the result. None of the other main effects or interactions were found to be statistical.

Table 3 The influence of the child on parents’ decision in case of goods for a family

Source Type III Sum

of Squares

df Mean Square

F Sig. Partial Eta² Observed Power^a

Country 2.967 1 2.967 0.472 0.493 0.003 0.105

Gender 13.967 1 13.967 2.224 0.138 0.012 0.317

Age 39.731 1 39.731 6.326 0.013 0.033 0.706

Country×Gender 28.632 1 28.632 4.559 0.034 0.024 0.565

Country×Age 10.285 1 10.285 1.638 0.202 0.009 0.247

Gender×Age 3.789 1 3.789 0.603 0.438 0.003 0.121

Country×Gender×Age 2.475 1 2.475 0.394 0.531 0.002 0.096

Error 1168.104 186 6.280

R² =0.088 (Adjusted R² =0.053); a. Computed using alpha =0.05

So, we cannot confirm hypothesis H6, because these was no significant difference between the Countries (F1,186=0.472, p=0.493, partial eta²=0.003). Finally we did not determine the influence of interaction of Country×Gender×Age on the difference of results (F1,186 = 0.394, p=0.531, partial eta²=0.002). It means we have to reject hypothesis H7.