International Journal of Engineering Technology, Management and Applied Sciences. September 2015, Volume 3, Issue 9, ISSN

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1 The Impact of Demographic Factors on Impulse Buying Behaviour of Online and Offline Consumers (A Case Study of Punjab, Haryana, New Delhi and Chandigarh) Dr (Prof.) K.C Sharma Professor Dr IT Group of Institutes, Banur Prof. Sukhmeet Kaur, Research Scholar Punjab Technical University, Jalandhar ABSTRACT This research paper investigates the impulse buying behaviour of online consumers as against offline consumers. The paper also explores the impact of demographic variables on the impulse buying behaviour of consumers. The research is focused on a well-designed questionnaire based on 500 respondents from the urban areas of Punjab, Haryana, New Delhi and Chandigarh. Data analysis has been done through SPSS software. To study the buying impulsiveness of online consumers as against offline consumers, t-test has been applied which shows that offline consumers are more impulsive in nature. Further, chi-square and regression has been applied to study the association and effect of demographic variables on impulse buying behaviour. The results revealed that two variables gender and marital status affect the impulse buying behaviour. Keywords: Impulse buying behaviour, online and offline buying, demographic factors. 1. INTRODUCTION The Indian retail industry is known to be one of the most vibrant and rapidly growing industries with many domestic and overseas players. It can be been divided into organized and unorganized sectors. Traditionally, it was all unorganized in the form of small kirana stores which were self owned and self-managed but with the advent of globalization, modern retailing transformed into hyper markets, supermarkets, mega store and multiplex malls to suit the changing requirements of the consumers. The concept of online shopping developed progressively, just after the launch of World Wide Web, in the form of e-commerce which is recognized as the process of buying and selling goods or services through Internet and other computer networks. The online shopping websites like ebay.com, amazon.com, flipkart.com, zabong.com, rediffshopping.com, crafts villa.com, snapdeal.com etc brought the concept of online shopping to the new heights. Nowadays, it has become very important for the marketers to understand the buying behaviour of their target markets that what motivates them to buy on impulse. Basically, impulse buying is a mystery in the marketing world as it is known to be a behaviour which the literature and consumers both considered normatively incorrect but still it accounts for a considerable volume of sales of goods and services every year. It is a type of unplanned and unintended planning by the consumers. Omar and Kent (2001) state that impulse buying occurs when customers buy spontaneously, unreflectively and immediately. From the past few years the marketers have realized that impulse buying can generate huge profits if appropriate marketing techniques are used. Literature says that a number of factor affect impulse buying behaviour out of which, the impact of demographic variables on the impulse buying behaviour has always been a matter of discussion among the researchers. Therefore, it is important for the marketers to study the impact of demographic factors like age, gender, marital status, income occupation and education on impulse buying as an emerging pattern. 2. REVIEW OF LITERATURE Coley, Amanda (2003) measured the impulse buying behaviour in relation to the demographic factor- gender. The study investigated the similarities and differences of impulse buying between genders. The research acknowledged the cognitive and affective processes affecting impulse buying behaviour of 277 students from University of Georgia. Analysis of Variance has been applied on the data. The results showed significant 63

2 difference between males and females with respect to unplanned buying. The study also established considerable difference among the product categories like electronics, clothing, books and magazines and sports products etc. Though, it showed no significant difference in relation to entertainment and formal attire. Sakkthivel, A. M. (2006) identified the impact of demographics in influencing Indian Internet users in consuming different services online. The study had been undertaken considering the inevitable role of internet for the societies nowadays. The study reviewed the impact of demographics in offline marketing and concluded that it played a vital role in understanding the buying behavior of the consumers. The findings would help the corporate world to understand the importance of demographics on online purchase which could be adopted and deployed for better use by the marketers. Hodge, Rebecca (2007) explored factors that influence the likelihood of an impulse purchase in an online retail environment. Consistent with diminishing sensitivity (mental accounting and the psychophysics of pricing), the results indicated that the likelihood of a consumer purchasing the impulse item increases with the total amount spent on other items. The study highlighted that the use of pop-ups increased the likelihood of the consumer making an impulse purchase. In addition, the results confirmed that providing a reason to purchase also increases the frequency of the impulse purchase. Hung, Chien-Ju (2008) examined the factors affecting female online impulse buying behaviour by collecting a quantitative online questionnaire. Based on previous literature, five factors including environmental stimuli, promotions and advertising, product-related factors, situational factors and customer impulse buying tendencies were analyzed in this research. According to the results, all factors, except for promotions and advertising, contributed to influencing female online impulse behaviour. The demographic analysis found that online shopping experiences and time surfing on the Internet had a positive impact on female online impulse buying behavior. Rana, S. (2012) investigated the effect of Education, Income and Gender on the impulsive buying tendency among Indian consumers. A sample of 450 shoppers at selected authorized retail outlets and shopping mall in Patiala were taken. The results of ANOVA at 5% level of significance showed that Education and Income of the consumers were more likely to influence impulsive buying than the Gender of the customers. Retailers may use the findings of the study to improve their merchandise assortment and improve the shopping environment. Bashar Abu, et al (2013) investigated the effect of demographic factors on the impulse buying behaviour. Inter-variable correlation and regression analysis were used in the study. The results showed that demographic factors, such as the disposable income and age, positively affect impulse buying behaviour. However, Educational qualification and gender produced marginal association with impulsive buying behaviour. 3. RESEARCH METHODOLOGY Research methodology is the systematic investigation in order to provide solutions to scientific and social problems through the study of research methods. It is a methodical technique to arrive at the result by way of processing and analyzing the problem with the application of various methods/techniques. The research methods are essentially planned, scientific and value-neutral. These methods include theoretical procedures, statistical approaches, experimental studies, numerical schemes etc. So, overall research methodology is said to be the framework used as guidelines for carrying out any research in a scientific and systematic manner. 3.1 Objectives of the Study 1. To study the buying impulsiveness of offline consumers as against online consumers. 2. To measure the impact of demographics variables on the impulse buying behaviour of consumers. 3.2 Research Design Research design is a structure or blueprint for carrying out a research in a logical manner without preconceived notion or prejudice in order to come up with solution of the problem concerned. It elucidates the modus operandi essential for collecting the data or information needed for solving the research problems. The research design in the present stud is Descriptive as well as Empirical so as to authenticate the theoretical framework. 3.3 Scope of the Study The Scope of study includes Impulse buying behaviour of 500 customers in the urban areas of Punjab, Haryana, New Delhi and Chandigarh. 64

3 4. DATA ANALYSIS The data has been collected by using a well-designed questionnaire given to the respondents and also through the direct surveys. In order to study the impulse buying behaviour of offline and online buyers, t-test has been applied. Further, to study the impact of demographic variables, initially chi-square has been applied to check the association between demographic variables and impulse buying and then regression has been applied to study the effect of demographic factors on impulse buying. 4.1 Buying Impulsiveness of Online Impulse Buyers as against Offline Impulse Buyers To study the buying impulsiveness of online and offline buyers, t-test has been applied in order to verify the mean score of two groups of impulse buyers i.e. online impulse buyers and offline impulse buyers to observe whether the two groups are significantly different from each other or not and to explore which mode of buying is generally used by Indian consumers. For this purpose, initially levene s test for equality of variance has been applied which shows that all variables are significant (>0.05) because the variance is homogeneous throughout the data. Table 1.1 represents the mean and standard deviation of two categories of impulse buyers. Category online offline Impulsiveness Score Table 1.1: Impulsiveness Score of Online and Offline Buyers N Std. Deviation Std. Error Online Buyers Offline Buyers Impulsiveness Score Table 1.2 Independent Samples Test between Online and Offline Impulse Buyers Equal variances assumed Equal variances not assumed Levene's Test for Equality of Variances F Sig. t Df t-test for Equality of s Sig. (2- tailed) Difference Std. Error Difference 95% Confidence Interval of the Difference Lower Upper In the table 1.2, Levenes test has been applied to test of homogeneity of variance across the groups under comparison. A non-significant Levene test is desirable. The test statistics is non-significant (p>.05) which means the equal variance across the groups is assumed. The test represents that there is significant difference between online and offline buyers with respect to buying goods on impulse as (p<0.05). Hence, we conclude that online buyers are significantly different than offline buyers while making impulse purchase. After checking the mean scores of online and offline buyers, their impulsiveness score has been measured based 9 items or statements. These statements are explained as follows: 65

4 1. My online shopping behaviour is unplanned leading to unintended purchasing for which I do not consider the consequences of purchasing. 2. I often buy things spontaneously (without considering pros and cons) when I browse online shopwebsite. 3. Just do it describes the way I buy things online. 4. I often buy things online without thinking or examining all aspects of goods. 5. I see it, I buy it describes my buying behaviour. 6. I buy things/goods according to how I feel at the moment (not allowing any consideration to intervene). 7. I carefully plan most of my purchases; sensation does not affect me. 8. Sometimes, I feel a bit reckless about what I purchase. 9. For me, online shopping is for enjoyment and thrill. On the basis of above nine statements, the impulse buyers are divided into three categories viz., High impulse buyers, Medium impulse buyers and Low impulse buyers. The impulsiveness scores and its categorization are discussed as under: Table 1.3: Scores Interpretation for Impulse Buying Impulse Buying Number of respondents Scores Interpretation High 169 (34%) 4-5 Medium 221 (45%) 3-4 Low 107 (21.5%) 1-3 Table 1.3 shows the number of respondents with their score interpretation on impulse buying categories. From the table, it is clear that 34% respondent fall in the category of high impulse buyers. Majority of the respondents i.e. 44.5% fall in the category of medium impulse buyers and 21.5 % of the respondents are low impulse buyers. 4.2 Demographic Variables and Impulse Buying Behaviour Demographic variables such as gender, age, income, occupation, marital status, and education are most frequently used as the basis for the market study. Previous researches have also measured the effect of demographic variables on the buying behavior of consumers. (Dittmar et al. 1996) found that the psychology of males and females is different towards impulse buying. This study investigated the gender issues in impulse buying. (Eysenck, S.B et al. 1985) further investigated the age norms for impulsiveness in the adults. In the present research, first of all, the association between demographic factors and impulse buying has been checked with the help of chi-square statistic. Table 1.4: Chi-Square Test between Gender and Impulse buying behaviour Value df Asymp. Sig. (2-sided) Pearson Chi-Square a Likelihood Ratio Linear-by-Linear Association In the table 1.4, the calculated value of chi square statistic, at 2 degree of freedom, has a value of This value is more than the critical value of 5.991, which indicated that the null hypothesis is rejected. It means that the association between gender and impulse buying behavior is significant at the 0.05 level. So, the alternate hypothesis is accepted. 66

5 Table 1.5 : Symmetric Measures between Gender and Impulse Buying Behaviour of the Consumers Value Approx. Sig. Nominal by Nominal Contingency Coefficient The Contingency Coefficient has been used to measure the strength of association between gender and impulse buying behaviour of the consumers. The value of contingency coefficient should lie between 0 and 1. The 0 value indicates no association, but as it moves towards 1, it establishes a strong association. The table given above indicates that the value of contingency coefficient is This value is significant at 0.05 level, but being less than 0.5 indicate a low association between gender and impulse buying behavior. A strong association does not exist between these two variables. Table 1.6 : Chi-Square Test between Marital Status and Impulse Buying Behaviour Value 67 Df Asymp. Sig. (2-sided) Pearson Chi-Square a Likelihood Ratio Linear-by-Linear Association The results obtained from Pearson chi-square test, at 2 degree of freedom, indicated a value of As this value is more than the critical value of 4.605; the null hypothesis is rejected indicating that the association between marital status and impulse buying behaviour is significant at the 0.10 level. Hence, the alternate hypothesis is accepted. Table 1.7 : Symmetric Measures between Marital Status and Impulse Buying Behaviour of the Consumers Value Approx. Sig. Nominal by Nominal Contingency Coefficient Table 1.7 demonstrates the value of contingency coefficient as This value is significant at 0.05 level, but being less than 0.5 indicate a very low association between marital status and impulse buying behaviour. Results of Chi-Square Test on the other Demographic Variables: The chi-square test has also been applied to the other demographic variables such as area, age, occupation, income and education levels of the consumers, but there does not exist any significant association between impulse buying and these demographic variables. Hence these variables are not primarily important in the current research to find out the level of impulsiveness among the consumers. It might be possible that there are some other demographic factors, not in the scope of current research, which affect the impulse buying tendency of the consumers. 4.3 Effect of Demographic Variables on Score Impulsiveness After studying the systematic association between demographic variables and impulse buying behaviour and checking the difference in mean scores of three categories of impulse buyers, the effect of demographic variables on the score impulsiveness has been measured with the help of regression analysis.

6 Table 1.8 : Regression Model Summary Model R R Square Adjusted R Square Std. Error of the Estimate a a. Predictors: (Constant), area urban, gen male, Hrs, Edu, Income, FreQ, marital married, Age, area rural Table 1.9 Analysis of Variance (ANOVA a ): F-ratio Model Sum of Squares df Square F Sig. ``1 Regression b Residual Total a. Dependent Variable: Score impulsiveness b. Predictors: (Constant), area urban, gen male, Hrs, Edu, Income, Freq, marital married, Age, area rural The table above shows that the score impulsiveness is the dependent variable and the demographic variables are the independent variables. It is apparent that score impulsiveness and demographic variables are positively correlated with each other but the strength of association is low at.205. R square (Coefficient of determination) is.042, which suggests that only 4.2% of the score impulsiveness is affected by the demographic variables. The model is statistically fit at 5% (close to 0.05) confidence level. Model Table 1.10: Regression Coefficients a Unstandardized Coefficients 68 B Std. Error Standardized Coefficients 1 (Constant) Beta Age Edu Income FreQ Hrs Gen male Marital married Area rural Area urban a. Dependent Variable: Score_impulsiveness The results of regression analysis are shown in Table Out of the above nine demographic variables, only two variables i.e. gender (male) and marital (married) are significantly affecting the score impulsiveness. The partial regression coefficient (β) for gender is and the corresponding beta coefficient for the same is Similarly, the partial regression coefficient (β) for marital status is and the corresponding beta t Sig.

7 coefficient for the same is Therefore, the estimated regression equation is explained as under: SI= (G) (M) SI= Score Impulsiveness, G= Gender, MR= Marital Status In the above regression equation, the factors, gender and marital status are significantly affecting the score impulsiveness at 5% and 10 % confidence level respectively. It is proven that Gender has a considerable impact on the impulse buying behaviour of consumers (Dittmar et al. 1995). (Zhang et al., 2007) revealed that Impulse buying behaviour is generally more in males in case of high involvement products such as electronics, furniture etc. Further, married persons are also said to be more impulsive. It might be possible that married persons have more knowledge about shopping the goods and services as they are more experience in the domestic purchasing. In addition, there is a possibility that they frequently buy the family value packs of various goods in order to grab a variety of promotional offers. So impulse buying could be more by married persons as compared to singles. 5. CONCLUSION The study shows that there is significant difference between online and offline buyers with respect to impulse buying and offline buyers are more likely to buy on impulse than the online buyers. In relation to the demographic factors, the results revealed that only two demographic factors viz., gender and marital status are significantly affecting the score impulsiveness. The remaining demographic factors have not shown any significant association with impulse buying in the current research. BIBLIOGRAPHY Bashar Abu, Ahmad Irshad and Wasiq Mohammad A study of influence of demographic factors on consumer impulse buying behaviour. International Journal of Marketing and Management Research, 4 (3). pp Online ISSN: Bloch, P., & Richins, M Shopping without purchase: an investigation of consumer browsing behavior. Advances in Consumer Research, 10(1), pp Coley, Amanda Gender differences in cognitive and affective impulse buying. Journal of Fashion Marketing and Management, 7 (3), pp Clover, V. T. et al Relative Importance of Impulse-Buying in Retail Stores. The Journal of Marketing, 15(1), pp Crawford Gerry & Melewar, T.C The importance of impulse purchasing behaviour in the international airport environment. Journal of Consumer Behaviour: An International Research Review, 3(1), pp Hodge, Rebecca Factors influencing impulse buying during an online purchase. Electronic Commerce Research, 7 (3), pp Hung, Chien-Ju The analysis of factors that influence female impulse buying during online transactions. Masters Dissertation, University of Nottingham. Kau, A.K; Tang, Y.E; and Ghose, Sanjoy Typology of online shoppers. Journal of Consumer Marketing, 20 (2), pp Piron, F Defining impulse purchasing. Journal of Advances in Consumer Research, 18 (1), pp Rana, S Effect of Education, Income and Gender on Impulsive Buying Among Indian Consumer: An Empirical Study of Readymade Garment Customers. Indian Journal of Applied Research, 1(12).pp Richard, Marie-Odile; Chebat, Jean-Charles; Yang Zhiyong; and Putrevu, Sanjay A proposed model of online consumer behavior: Assessing the role of gender. Journal of Business Research, 63 (1), pp Rishi Jit, Bikram An Empirical Study of Online Shopping Behaviour: A Factor Analysis Approach. Journal of Marketing & Communication, 3 (3), pp Rohm, A.J. & Swaminathan, Vanitha A typology of online shoppers based on shopping motivation. Journal of Business Research, 57 (3), pp Sakkthivel, A.M Influence of internet on online buyer involvement towards buying different products and services. International Journal of Electronic Finance, 4 (2), pp