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Dr. Satnam Kaur Ubeja Prestige Institute of Management and Research Indore Email:Satnam_ubeja@yahoo.co.in |
Devendra Jain Prestige Institute of Management and Research Indore Email:devendra_jain@pimrindore.ac.in |
Dr. Vipin Choudhary Prestige Institute of Management and Research Indore Email:Vipin_choudhary@pimrindore.ac.in |
Vikas Chauhan Prestige Institute of Management and Research Indore 2- Education and Health Sector Scheme no.54, Near Bombay Hospital, Indore-10 Email:Vikaschauhan299@yahoo.com |
Online shopping has increased tremendously in the past few years in India. It has improved the lifestyle of people in the country. Consumers tend to be attracted by the offers on the online shopping portals. This had resulted in the increase in impulsiveness among the buyers online. The present study is an attempt to understand the effect of impulsiveness among online buyers. For the purpose of study, online shoppers from Indore city were taken. The study indicated the fact that various factors contributed to the impulsiveness among buyers while they do online shopping. Among them unplanned tendency online shopping mood and online shopping experience were major identified factors. Demographic factors like age, gender and occupation of shoppers were also analyzed to know its effect on online impulsive behavior.
Key words: Online shopping, Buying impulsiveness, Demographic factors
Use of internet has increased over past several years. In India the number of internet users are increasing .This technology exploration has caused the increase in communication as well as increase of knowledge among the people across the country. People are using this technology to be a part of larger global society as well as learn the lifestyles of people across the globe. Many people are using this technology to make their life convenient by using online shopping sites such as Amazon.com, Myntra.com, Flipkart.com, e-bay.com etc. These shopping sites offer wide array of products for satisfying the needs of consumers and offering them lifestyle products for increasing their living standards and adding convenience to their life. This internet revolution has contributed to the growth of GDP by nearly 1.6% and is expected to increase by 3% by 2015 as a result of increase in number of internet users and increase in consumption and investment in internet technology (ASSCHOM-2012). This internet technology has given to the birth of E-Commerce which has now become integral parts of our life just like driving home with family. According to Google Report nearly half of the internet users shop online which is nearly about 82 million online shoppers which is expected to grow in coming years. The online shoppers are trying to purchase everything online now owing to increase in products available online and increased number of services offered online such as cash on delivery, return back guarantee if the product is faulty, large number of discounts offered. Now the shoppers have even started purchasing grocery products online through sites such as Araamshop.com and other products like home décor and apparels. Due to increased number of services offered the online shoppers are purchasing those products which they had not planned to purchase.
Online shopping Online shopping is defined as purchasing a product or service via internet through online shop. Since the year 2009 this had increased owing to good IT infrastructure offered by Indian government in many parts of the country. More and more companies had started to open since then in E-Commerce sector. Now these companies are trying to engage the customers everywhere including social networks, e-mails, mobile apps etc. to help them get the products they desire at their doorstep. This increased engagement had made the online shopper more irresistible and makes him an unplanned purchaser.
Impulsive Buying behavior According to American Marketing Association Impulse Buying is defined as “A purchase behavior that is assumed to be made without prior thought or planning.” It is further said that this purchase involves an emotional reaction to the stimulus object.
Rook (1987) defined impulse purchasing as when a consumer experience a sudden, often powerful and persistent urge to buy something immediately. The impulse to buy is hedonically complex and may stimulate emotional conflict. Also impulse buying is prone to occur with diminished regard for its consequences (p. 191)”
Impulse purchasing in online shoppers occurs as a result of many factors as previously done researches indicate such as the web site design, more products offered for sale, ease of navigation, ease of payment etc. But there is a lack of evidence, what is the effect of demographic factors on buying impulsiveness among online shoppers? This study is done to examine such effect.
Badgaiyan and Verma (2014) conducted a study on influence of intrinsic factors on impulsive buying behavior and found that the influence of intrinsic variables on impulsive buying behavior did not vary across gender. They concluded that the constructs of materialism, shopping enjoyment tendency and impulsive buying tendency had significant positive relationship with impulsive buying behavior, the cultural construct of collectivism and two personality traits like extraversion and conscientiousness too showed significant relationship.
Bashir et al. (2013). Predicted impact of cultural values and life styles on impulse buying behavior and the results suggested that there is significant impact of cultural values and life styles on impulsive buying behavior. They found that the gender role is the only one variable of cultural values and life style of customers where significant difference exists between male and female customers while making impulse buying behavior. The results also showed that impulse buying behavior is predicted by security, life satisfaction, gender role, financial satisfaction and complete tasks. They also discussed that Impulse buying is influenced by time, location, personality, economic, and cultural factors.
Bashar et al. (2012). Founded relationship between various demographic variables and different impulse buying patterns related to diversified groups of buyers. Study has identified positive relationship between impulsive and demographic factors, demographic factors, such as the disposable income and age, are related to most impulse buying indicators and to the impulsivity collective indicator. However, Educational qualification and gender produced marginal association with impulsive buying behavior.
Sun and Wu (2011) concluded that online buying impulsiveness is positively affected by Internet addiction, need for arousal and need for material resources. It is negatively affected by task orientation. They described need for arousal as individual differences in chronic need to increase levels of stimulation, the need for material resources is defined as the need to collect and possess material goods and Task orientation represents an enduring disposition to set goals
Rook and Fisher (1995) conducted a study that provides conceptual and empirical evidence that consumers' normative evaluations moderate the relationship between the buying impulsiveness traits and related buying behaviors. They defined buying impulsiveness as a consumer's tendency to buy spontaneously, unreflectively, immediately and kinetically.
Tinne (2010) conducted impulsive buying has four characteristics; first is that it is an unplanned purchase. The second characteristic of impulse buying is the exposure to the stimulus. The stimulus can be considered to be the catalyst which makes the consumer be impulsive. The third characteristic of impulse buying is the immediate nature of the behavior. The consumer makes a decision on the spur of the moment without any evaluation of the consequences of making such a purchase. Finally, the consumer experiences emotional and cognitive reactions.
Muruganantham and Bhakat (2013) conducted a review of impulse buying behavior and highlighted the importance of external stimuli like sales promotion, retail merchandising shopping channel, presence of peers and family as important for impulse buying behavior.
Shirmohammadi et al. (2014) developed a case study on discounts group sites in iran to explore online impulse buying behavior, they found that merchandise attractiveness, enjoyment and ease of use has an important influence that cause impulse buying.
Objective of the Study
· To identify the factors of buying impulsiveness among online shoppers of Indore city
· To assess the impact of buying impulsiveness among online shoppers with respect to gender wise
To know the effects of 34 buying impulsive items on online shoppers, the following null and alternative hypothesis have framed-
· H01: There is no significant difference between male and female online shoppers towards their buying impulsiveness
· HA1 : There is significant difference between male and female online shoppers towards their buying impulsiveness
· H02 : There is no significant difference among online shoppers of different age groups towards their buying impulsiveness
· HA2 : There is significant difference among online shoppers of different age groups towards their buying impulsiveness
· H03 : There is no significant difference among online shoppers of different occupation groups towards their buying impulsiveness
· HA3 : There is significant difference among online shoppers of different occupation groups towards their buying impulsiveness
Data Sources
To design the structured questionnaire the 34 items of buying impulsiveness of online shoppers are taken from extensive study of buying impulsive literature viz. ROOK and Fisher (1995) Scale on Buying Impulsiveness, international journals of marketing, various business review and marketing management magazines etc.
· The primary data is collected from 200 customers of different online shops, spreading across city and having above 20 years of age and already have purchased products from different shopping malls.
· Apart from these 34 items, five categorical variables are also used to know the effects of all factors on the customer satisfaction. The five Categories have selected for the study are as –Age, Gender, Marital status, Occupation and Income.
Sample and Design The design of the present study is descriptive as well as empirical in nature. The main purpose of the study is to find the impact of buying impulsiveness towards online shoppers in Indore city. The sample size is 200 customers. The sample comprised of the respondent above 20 years of age & having experience of online shopping from different online shops. The independent variables comprise of age and income. The entire universal has been divided as:
· Age: The age group were 20-30, 30-40 and 40-50. This was kept so as to cover maximum percentage of universe, grouping in class interval helped in easy tabulation.
· Occupation: It contained the choices of – Service, Business, Student and others
· Gender: It contained the choices of- Male & Female.
· Income: It contained the choices of- below 5 Lacks, below 12 Lacks, 12 Lacks and above.
Data Collection
The questionnaire is split into two sections. First section deals the demographic factors, Second section related to 34 items of buying impulsiveness. The questionnaire had given five point scales rating Highly Dissatisfied to Highly Satisfied and comparative weights one to five, where five is the highest rank.
Tools for Analysis
In the application of statistical tool, cares has been taken and draw a real picture without any manipulation. Factor analysis and ANOVA test applied to minimize the factors to find their effectiveness & variances. The statistical package like SPSS (version 17) used, MS – Excel also used for analysis. The levels of significance were tested of five percent level.
Factor Analysis The normal varimax solution is not obtained directly from a correlation matrix. It is obtained by rotating other types of factor solutions to the varimax form. In the present study it was considered desirable to use the highest factor loading criterion to select customer satisfaction included in buying impulsiveness of different online shoppers. This criterion was uniformly used in the factor analyses carried out on the total sample of the study.
ANOVA Test The generated factors which have got with factor analysis by using SPSS software (17.1) version, with the help of these factors we have applied ANOVA test by using SPSS software(17.1) to measure the variance among different variables. Tukey Karner multiple comparison has been used to get the mean difference and analyzing the results. It has been applied on 5% level of significance, to test the variance between different demographic variables on buying impulsiveness of different online shoppers in Indore city.
Tools for Data Analysis: Data was analyzed using statistical techniques (at 5% level of significance), ANOVA
Reliability and Validity: (ANNEXURE 1) The study found that the reliability of sample of 200 customers was found to be .92 as per Chronbach alpha which was found to be satisfactory. As per KMO bartlets test of validity it was found to be .82 which was also good. Thus the sample was found to be both reliable and valid.
Factors: (ANNEXURE 2) The study explored eight factors that influence the online buying impulsiveness. These factors are tabularized with their items, loads, eigen values and percent of variances. The description of each factor is as follows:
Offers &Visual Web Merchandising It is constituted of six items, namely, Price promotions, Detailed product information, Ease of finding the product, Colorful and vivid product pictures, Ease of navigating a website and more time browsing. In these items ‘Price promotions’ has the highest factor load i.e. 0.661. The total load of this factor is 3.576 with the highest coverage of 10.789 percent of variance. Consumers are more impulsive to buy a product when they found various price offers and product information such as product specifications, functioning and other relevant knowledge. The Internet offers numerous possibilities for comparison shopping to consumers within seconds; they can compare price offers with product features and specifications to other seller and buy immediately when they found profitable deal. In support of that Wong and Zhou (2003) claims that price is a valuable determinant of impulsive buying behavior and Jensen (2011) found that relationship between price, information and impulsive buying more tightly related in the online market then the traditional retail store. Visual web merchandise Included are merchandise descriptions, navigation aids, prominent and eye-catching product display and all other variables which are oriented towards the efficient and effective execution of consumer buying tasks encourage the consumer impulsive buying.
Product Variety & Net Payment It is constituted of five items, namely, wide range of the products, products offered for purchase in alignment, organized layout, I buy things according to how I feel at the moment and Payment methods. The total load of this factor is 3.252 with 10.453 percent of variance. Among these items ‘wide range of the products’ has highest factor load i.e. 0.799. Internet offers a global variety of products and consumers tend to purchase more products online because they have many selection option due to having wide range of products online in support of that wolfinbarger & gilly (2001) suggested that the product selection is one of the reasons why consumer shop online and that perceived larger product variety of online shoppers can increase loyalty (koo, 2006). Payment methods like internet banking, credit and debit cards influence the consumers to shop online because it is convenient and time saving.
Impetuous Behavior It is constituted of five items, namely, Just do it attitude, I would often buy things spontaneously, For me it is fun to buy, I see it I buy it describes me and Buy things online without thinking. The total load of this factor is 3.0 with 9.637 percent of variance. The items ‘Just do it attitude’ has highest factor load i.e. 0.705. This is that because of impulse buying tendency through which the person purchases the products online in an unplanned way. The impetuous behavior or impulse buying tendency is a consumer trait. Faber and Yoon (2000) showed that impulse buying tendency is directly associated with a lack of personal control. They suggest that impulsive buyers lack the cognitive control to stop themselves from purchasing impulsively.
Attachment and Convenience This factor constituted I am likely to buy on impulse due to cross selling, I am likely to buy a related product, I am likely to buy on impulse due to limited time discount, Sometime I feel like buying things spur of the moment, When I have more shopping knowledge and During online shopping because of delivery policy. The total load of this factor is 3.553 with 8.798 percent of variance. In these items ‘I am likely to buy on impulse due to cross selling’ has highest factor load i.e. 0.766.
Exclusivity It is constituted of three items, namely, The exclusive products only sold online, Recommendation from other customers and before visiting the site I don’t have the intention to purchase. The total load of this factor is 1.869 with 6.240 percent of variance. In these items ‘The exclusive products only sold online’ has highest factor load i.e. 0.713. Online shoppers provide wide variety of products which are obtained from deferent territory that shows exclusiveness or uniqueness to the consumer. Impulse buying is also related to the attractiveness and uniqueness of products. People tend to buy those products on impulse which are attractive or unique. The attractiveness or uniqueness of products often develops the temptation to buy the product (Chaubal, 2013 ). When customers get suggestions of “what others have bought”, it could imply feel of presence of others for customer and it is an important factor to persuade people to buy on impulse (Masouleha et al. 2012).
Shopping Fun It is constituted of five items, Reckless about what I buy, when I have more money, while shopping at the web site I felt excited, I feel a sense of thrill when buying something online and since I am a part of online social networking websites. The total load of this factor is 2.467 with 6.220 percent of variance. In these items ‘Reckless about what I buy’ has highest factor load i.e. 0.654. Shopping enjoyment is a buyer’s individual characteristic representing the tendency to find shopping more enjoyable and to experience greater shopping pleasure than others (Goyal and Mittal, 2007). Badgaiyan and Verma (2014) reviewed that shopping enjoyment tendency and impulsive buying tendency had significant positive relationship with impulsive buying behavior and they concluded that the shoppers who enjoyed shopping were found to be more impulsive.
Shopping Mood This factor constituted two items, I carefully plan most of my purchase and Buy now think about it later. The total load of this factor is 1.344 with 5.410 percent of variance. In these items ‘I carefully plan most of my purchase’ has highest factor load i.e. 0.807. Both the items are in opposite sense and totally depend on the consumer mood. In support of that Beatty and Ferrell 1998 concluded that the consumers’ mood state is the factor that influence the willingness to buy on impulse, if an individual is in a good mood, he/she tends to be more generous and less reluctant towards impulse purchases and If someone believes impulse buying is unnecessary or unacceptable then he/she will consciously buy less unplanned.
Availability and refund policy It is constituted of two items, namely, During online shopping when I find the product I want and Regarding online shops refund policy. The total load of this factor is 1.07 with 4.017 percent of variance. In these items ‘During online shopping when I find the product I want’ has highest factor load i.e. 0.631.
(ANNEXURE 3) Age Wise When we did ANOVA analysis of the whole data age wise, it was found that the significance value of F is less than 0.05. This means there is a significant difference among online shoppers of different age groups towards their buying impulsiveness. It describes that the below 30 years age (Mean =1.133) online shoppers are more impulsive while shopping online. The above 50 years age group (Mean = 0.95) of online shoppers are least impulsive and the online shoppers having age group of 30-50 years (Mean= 1.0063) are moderately impulsive while shopping online.
Family Income Wise We did ANOVA analysis of the whole data family income wise, it was found that the significance value of F is less than 0.05. This means there is a significant difference among online shoppers of different family income group towards their buying impulsiveness. It describes that the online shoppers having family income below 5 lacs (Mean=1.133) are more impulsive while shopping online. The above 12 lacs family income group (Mean=0.95) of online shoppers are least impulsive and the online shoppers having family income between 5-12 lacs (Mean=1.0063) are moderately impulsive while shopping online.
T-Test Gender Wise When T test was applied on whole data gender wise, it was found that the significance value of F is greater than 0.05 that means there is no significant difference between male and female online shoppers towards their buying impulsiveness.
The objectives of this study were to investigate the customer buying impulsiveness towards online shopping with respect to Indore City and to study variations in the buying impulsivness with respect to across age, income and gender wise.
Following the study of Wong, a. and zhou l. (2003). , Goyal, B. B.Mittal, A. (2007). , Masouleh, S., Pazhang, M. & Moradi, J. (2012) , an attempt was made to profile the buying impulsiveness towards online shopping. They all have identified many factors related to online shopping impulsiveness; from which we have selected 8 factors of buying impulsiveness and tried to measure the consumer behavior towards online shopping.
In addition, this study shows that the average customer of Indore city in our sample was not very conscious regarding online shopping, due to cross selling they have more interest to purchase product from online, but age and income wise they are quite impulsive about some online shopping offers. It is found that;20-30 age group and above 5 lac income group consumers are very impulsive behavior ,about online shopping which is related to on the spot offers in online for getting customer satisfaction in Indore city. Shopping is funny activity for them. Customers are most recreational in their shopping but they are not promotion conscious, they want variety of products but with quality and good services. They are coming on online shopping option for purchasing products but for getting customer satisfaction, they do not attract to any type of promotion mix, which is available in online shopping.
In addition, this study shows that the average customer of Indore city in our sample was very conscious about online shopping, people are very conscious about extra facilities and services provide by online shopping; they also want clarity in condition from online shopping. Students are quite conscious about any type of satisfaction factors.
Beatty S., Ferrel M.1998. Impulsive Buying: Modeling its Precursors. Journal of Retailing; Vol. 72, 169-191.
Badgaiyan, A. J. and Verma, A. 2014. Intrinsic factors affecting impulsive buying behavior-Evidence from India. Journal of Retailing and Consumer Services, 21(4), 537–549.
Bashar, A., Ahmad, I. and Wasi, M. 2012. A study of influence of demographic factors on consumer impulse buying behavior. International Journal of Management and Strategy, 3(5), 1-18.
Bashir, S., Zeeshan, M., Sabbar, S., Hussain, R. I. and Sarki, I. H. 2013. Impact of Cultural Values and Life Style on Impulse Buying Behavior: A case study of Pakistan. International Review of Management and Business Research, 2(1), 193-200.
Chaubal, A. 2013. Impulse Buying-Understanding the underlying aspects and identifying methods to trigger impulse buying in costumers. IIM Indore Management Canvas. Retrieved from http://managementcanvas.iimindore.in/icanvas/index.php?view=article&catid=34%3Amarketing-and-branding&id=221%3Aimpulse-buying&format=pdf&option=com_content&Itemid=56
Rook, D.W. and Fisher, R. J. 1995. Normative influences on impulsive buying behavior. Journal of Consumer Research, 22(3), 305-313.
Faber, R. and yoon, S. 2000 impulsive buying: its relation to personality traits and cues. Advances in Consumer Research, 27, 179-185.
Goyal, B. B.Mittal, A. 2007 Gender influence on shopping enjoyment—an empirical study. Indian Management Studies Journal, 11(2), 103–116.
Koo. D. 2006. The fundamental reasons of e-consumers’ loyalty to an online store. Electronic Commerce Research and Applications, 5(2), 117-130.
Masouleh, S., Pazhang, M. & Moradi, J. 2012 What is Impulse Buying? An analytical network processing framework for prioritizing factors affecting impulse buying. Management Science Letters, vol. 2, no.4, pp.1053–1064.
Muruganantham, G. and bhakat, R. S. 2013. A review of impulse buying behavior. International Journal of Marketing Studies, 5(3), 153-156.
Sun, T. and Wu, G. 2011. Trait predictors of online impulsive buying tendency: a hierarchical approach. Journal of Marketing Theory and Practice, 19(3), 337–346.
Shirmohammadi, M., Ebrahimi, M. and Ghane, N. 2014. Investigating and priortizing the effective factors on online impulse buying in electronic commerce(case study: discount group sites in iran). European Journal of Business and Management, 6(4), 143-147.
Tinne, W. S. (2010). Impulse purchasing: a literature overview. ASA University Review, 4(2), 65-73.
Wong, a. and zhou l. 2003. consumer impulse buying and in store stimuli in chinees supermarkets. Journal of International Consumer Marketing, 16(2), 37-53.
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ANNEXURE 1
TABLE 1
| Case Processing Summary | |||
| N | % | ||
| Cases | Valid | 141 | 68.1 |
| Excludeda | 66 | 31.9 | |
| Total | 207 | 100.0 | |
| a. Listwise deletion based on all b. variables in the procedure. | |||
| Reliability Statistics | ||
| Cronbach's Alpha | Cronbach's Alpha Based on Standardized Items | N of Items |
| .92 | .92 | 34 |
| KMO and Bartlett's Test | ||
| Kaiser-Meyer-Olkin Measure of Sampling Adequacy. | .87 | |
| Bartlett's Test of Sphericity | Approx. Chi-Square | 2.03 |
| Df | 56 | |
| Sig. | .00 | |
ANNEXURE 2
TABLE 2
| Factors Label and Items | Rotated Factor Loadings |
|
Factor 1: Offers &Visual Web Merchandising
Price_promotions Detailed_product_information Ease_of_finding_the_product Colorful_and_vivid_product_pictures Ease_of_navigating_a_website_ more_time_browsing |
.66
.63 .63 .61 .61 .41 |
|
Factor 2: Product Variety & Payment
wide_range of the products products_offered_for_purchase in alignment organized layout I_buy_things_according_to_how I feel at the moment Payment_methods |
.79
.76 .63 .55 .50 |
|
Factor 3: Impetuous Behavior
Just_do_it attitude I__would__often_buy_things_spontaneously For_me_it_is_fun__to_buy I_see_it_I_buy_it_describes me Buy_things_online without thinking |
.70
.70 .59 .53 .45 |
|
Factor 4: Attachment and Convenience
I_am__likely_to_buy_on_impulse_due to cross selling I_am__likely_to_buy_a_related_product I_am_likely_to_buy_on_impulse_due to limited time discount Sometime_I_feel_like_buying_things spur of the moment When_I_have_more_shopping_knowledge During_online_shopping_because_of delivery policy |
.76
.64 .63 .59 .48 .43 |
|
Factor 5: Exclusivity
The_exclusive_products_only_sold_online Recommendation from other customers Before_visiting_the_site_I_don’t_have_the intention to purchase |
.71
.67 .47 |
|
Factor 6: Shopping Fun
reckless about what I buy When_I_have_more_money While_shopping_at_the_web_site_I_felt excited I_feel_a_sense_of_thrill_when_buying_something online Since_I_am_a_part_of__online_social networking websites |
.65
.56 .43 .42 .40 |
|
Factor 7 : Shopping Mood
I_carefully_plan_most_of_my_purchase Buy_now_think_about_it_later |
.80
.53 |
|
Factor 8 : availability and refund policy
During_online_shopping_when_I_find the product I want Regarding_online_shops_refund_policy |
.63
.43 |
| ANNEXURE 3 TABLE 3 ANOVA | |||||
| Over all data age wise | |||||
| Sum of Squares | Df | Mean Square | F | Sig. | |
| Between Groups | 8034.54 | 2 | 4017.27 | 12.80 | .00 |
| Within Groups | 64016.66 | 204 | 313.80 | ||
| Total | 72051.21 | 206 | |||
| ANOVA | |||||
| Over all income | |||||
| Sum of Squares | Df | Mean Square | F | Sig. | |
| Between Groups | 8034.54 | 2 | 4017.27 | 12.80 | .00 |
| Within Groups | 64016.66 | 204 | 313.80 | ||
| Total | 72051.21 | 206 | |||
