Imapct factor(SJIF): 5.889
Purchase Habits on the Internet by Gender: A Literature Review
Research Scholar, Ansal University, Gurgaon
Research Scholar, Ansal University, Gurgaon
Research Scholar, Amity University, Noida
Internet is the fastest growing technology globally and as on offshoot e-commerce has become the most significant scientific accomplishment. In business context, e-commerce breaks the boundary of time and space, alters the trade pattern, improves the circulation of merchandize and makes the enterprise have an edge over the others. (Qin,2009)
Global ecommerce penetration increased from 4.0% in 2008 to 6.5% in 2012 and is anticipated to reach 9.3% by 2016, driven by high-growth emerging markets and the decline of specialty retail stores in developed markets (Siemer & Assicoates, 2013)
600 million women in developing nations, or 21 percent, were online in 2013), and another 450 million are expected to gain Internet access by 2016 (HEAVY, 2013)
Although, there has always been a gender gap in the usage of internet globally but this gap in reducing year on year globally as well as in India. In 2012, there were around 125 million internet users in India, in which 40% of the users were Women and around 75% of internet users are between the age group of 15-34 years, the number reached 60 million in 2013. (Adarsha, 2012)
The consumer buying behaviour in online shopping
Consumer buying behaviour has always been one of the most popular areas of research in the field of marketing which is extensively studied and will always be a debatable topic. The consumer buying process being one of the most important areas describes it to be a five step process of Problem identification. Information search, alternative evaluation, purchase decision and post purchase behaviour.
Since the virtual marketing is expanding at astounding rates, understanding the behaviour of the consumer in this virtual set up has become important for marketers to gain a competitive advantage. The increasing number of online transactions and user volumes is evident from the fact that _____percent of world population is online and buy products online.
Attitude towards the offline store was a significant predictor of attitude toward the online store (Kim & Park, 2005) . Consumer’s attitude towards the internet may be an important determinant for internet use for product information search. Helander and Khalid (2000) found that a positive attitude toward e-commerce has a significant influence on shopping from the internet. Internet shopping provides the numerous benefits for consumers such as time saving and search convenience. However, internet shopping may require capability to access the internet and other relevant resources (i.e. high speed internet, modem). According to the theory of planned behaviour (Ajzen, 1985, 1991)
Those who used the internet for purchase believed less difficulty to use and access to the internet, as compared to those who did not use the internet for purchase. The technology acceptance model (Davis, 1989) also presented the similar findings. Pavlou (2003) also found that intention to use the internet for purchasing was determined by perceived ease of the internet use.
( Sukhi, 2013) analyzed consumer shopping behaviour on the Internet based on four aspects, i.e. the Internet marketing environment, product characteristics, familiarity, and promotional offers. It appeared that respondents were younger than 36 years, known as Generation Y, scholarly consumers very open and knowledgeable about information technology for shopping for products and services. These young people tend to place more concern on the familiarity factor in affecting their shopping behaviour on the Internet followed by promotional offers affected greatly as their brands are still not well positioned in consumer minds. This result is comparable to Odunlami & Ogunsiji’s study that promotional offers are a major determinant of consumer online shopping behaviour. Effective implementation of sales promotional tools lead to increase in sales volume and invariably higher profits.
Price, product quality, and variety are important factors for online shopping (Rust, Zeithaml & Lemon, 2000)
The product quality is a focal reason for consumers to buy products via the Internet (Aaker, 1991). Perceived incentives significantly also influence online customers’ intention to repeat purchase through the Internet. Consumers positively inclined towards making an online shopping after receive opinion on product’s promotional offers from friends and relatives or when they see them shopping online (Jarvelainen, 2007)
Literature Review On Online Marketing:- Gender Perspective
Shopping Cart Abandonment
Shopping Cart Abandonment refers to the loss of a customer who is going through the check-out process of an online transaction. Once the consumer selects a product and puts it in his/her shopping cart, he/she takes it to the checkout point. However, in some cases, for various reasons (e.g. long lines, cumbersome and tedious checkout process, etc.) consumers may abandon the cart. This phenomenon is especially pertinent in the context of e-commerce. Studies estimate that approximately 60-75 percent of the shopping carts are abandoned before purchase is made (2002; Eisenberg, 2003; Oliver and Shor, 2003; Gold, 2007). Cart abandonment rates on the average e-commerce site range between 65% to 80%.
Shopping cart abandonment comes right after the consumer has decided to purchase the products, but before the purchase is completed. A lack of understanding and availability of literature regarding this stage in the existing literature from the gender perspective points to the need for this research. Most of the studies have focused on the initial stages of the buying process, i.e. from problem recognition to the evaluation of alternatives stages (Kotler, 1999), or the factors influencing the consumers’ propensity to shop online.
If we go by statistics, More than two thirds of UK shoppers abandon their online shopping carts before making a purchase, according to a survey commissioned by Cloud.IQ. Women are 7 per cent more likely to abandon an online shop than men, according to the study (DAVIES, 2013). The factors influencing consumer online search, consideration, and evaluation play a larger role in cart abandonment than factors at the purchase decision stage. In particular, many customers use online carts for entertainment or as a shopping research and organizational tool, which may induce them to buy at a later session or via another channel (Kukar- Kinney & Close, 2010)
Three Key factors of reasons for shopping cart abandonment (Rajamma et al 2009)
1 Perceived waiting time
2 Perceived risk
3 Transaction inconvenience
Shopping cart abandonment
The results of their study indicated that perceived transaction inconvenience is the major predictor of shopping cart abandonment. The other predictors are-
Perceived risk and perceived waiting time. Positive relationship was found between perceived transaction inconvenience, perceived risk and propensity to abandon the shopping cart. It was also found that propensity to abandon the shopping cart is negatively associated with the perception of waiting time. (Kukar- Kinney & Close, 2010) .Other Legitimate reasons Their minds or deciding they should Not be spending the money, Running out of time especially on mobile devices, Comparing products and moving to some other site, Privacy and security concerns, high shipping costs, Checkout process too long etc.
WOMEN are more likely to:-Save products for later, Take longer to buy and be very sensitive to shipping and handling costs whereas MEN are more likely to Compare prices and not abandon shopping cart. (Conversions on demand, 2014)
Several research issues related to consumer online shopping emerged from the current study. Shift in shopping orientations. Despite different consumer clusters identified in different studies, there is a clear trend that the shopping orientations of online consumers have expanded beyond convenience and variety-seeking. Recreational, economic, and even social-oriented consumers can all be active online shoppers. Therefore, it is important for us to understand how to provide more recreational, experiencing, and socializing functions to meet the needs of diversified online consumers.
Gender Specific Buying Behaviour : Inspite of many studies being conducted on online shopping based on gender, till date no study has been conducted emphasizing on one particular gender buying behaviour-males or females. Minimization of risks with online shopping. The scarcity of studies on how to reduce online shopping risks does not meet the demand of increasing awareness of risks associated with online shopping. Consumers were more concerned about attributes of Web sites associated with perceived risks (e.g., security of information and vendor reliability) than those associated with perceived gains (e.g., convenience) [Bhatnagar and Ghose 2004a], which underlies the importance of reducing online shopping uncertainty and risks
Aaker, D. A. (1991). Managing brand equity: capitalizing on the value of a brand name. New York: Free Press.
Adarsha, 2012. 40% of Internet Users Are Women's In India. [Online] Available at: http://www.careerindia.com/news/2012/10/30/40-percent-of-internet-users-are-womens-in-india-003122.html [Accessed 6 July 2014].
Ajzen, I. (1991), “The theory of planned behavior”, Organizational Behavior and Human Decision Processes, Vol. 50, pp. 179-211.
Bae, S. & Lee, T., 2010. Gender differences in consumers’ perception of online Consumer reviews. Springer Science, pp. 201-214.
Comscore. (2012). State of e-Commerce in India. Comscore,(View date 1 July 2014, http://www.assocham.org/arb/general/Comscore_%20ASSOCHAM-report-state-of-ecommerce-in-india.pdf)
Constantinides, E. (2004). Influencing the online consumer’s behavior: The Web experience. Internet Research, 14(2), 111-126.
Conversions on demand, 2014. A Better Way to Stop Cart Abandonment: Real time Offers, s.l.: Conversions on demand.
CRISIL. (2014). e-tail eats into retail. CRISIL research,(view date: 2 April 2014, http://www.crisil.com/pdf/research/CRISIL-Research-Article-Online-Retail-Feb14.pdf)
DAVIES, J., 2013. 70% of people abandon online baskets prior to purchase prior to purchase. [Online] Available at: http://www.thedrum.com/news/2013/07/02/70-people-abandon-online-baskets-prior-purchase[Accessed September 2014].
Ellen Garbarinoa, M. S., 2002. Gender differences in the perceived risk of buying online and the. Journal of Business Research, p. 8.
Garbarino, E. & Strahilevitz, M., 2004. Gender differences in the perceived risk of buying online and the effects of receiving a site recommendation. Journal of Business Research, p. 768– 775.
Gold, K. (2007), “Tackling the shopping cart abandonment rate”, available www.searchmarketingstandards.com
Goldwyn, C. (2002), “The art of the cart; survey results from a study by Vividence Corporation”, available at: http:// visibility.tv/tips/shopping_cart_abandonment (accessed 17 September 2014)
HEAVEY, S., 2013. Women in India, other developing countries lack in interbet use. [Online] Available at: http://in.reuters.com/article/2013/01/10/internet-access-women-india-developing-idINDEE90902820130110[Accessed 5 August 2014].
Helander, M.G. and Khalid, H.M. (2000), “Modeling the customer in electronic commerce”, Applied Ergonomics, Vol. 31 No. 6, pp. 609-19.
Jarvelainen, J. (2007). Online purchase intentions: an empirical testing of a multiple-theory model. Journal of Organizational Computing, 17(1), 53–74. 36. Khalifa, M., & Limayem, M. (2003). Drivers of Internet shopping. Communications of the ACM, 46(12), 233–239
Kim, J. & Park, J., 2005. A consumer shopping channel extension model: attitude shift toward the online store. Journal of Fashion Marketing and Management, Volume 9, pp. 106-121.
Kukar-Kinney, M. & Close, A. G., 2010. The determinants of consumers’ online shopping cart abandonment.. Journal of the Academy of Marketing Science, 38(2), pp. 240-2540.
Li, H., Kuo, C., & Rusell, M. G. (1999). The impact of perceived channel utilities, shopping orientations, and demographics on the consumer’s online buying behavior. Journal of Computer-Mediated Communication, 5(2), 1-16.
Murphy, G. B. & Tocher, N., 2011. Gender differences in the effectiveness of online trust building information cues: An empirical examination. Journal of High Technology Management Research, pp. 26-35.
Odunlami, I. B., & Ogunsiji, A. (2011). Effect of sales promotion as a tool on organizational performance:a case study of sunshine plastic company. Journal of Emerging Trends in Economics and Management Sciences, 2(1), 9–13.0
Oliver, R.L. and Shor, M. (2003), “Digital redemption of coupons: satisfying and dissatisfying effects of promotion codes”, Journal of Product & Brand Management, Vol. 12 Nos 2/3, pp. 121-34.
Park, J., Yoon, Y. & Lee, B., 2009. The Effect of Gender and Product Categories on Consumer Online Information Search. Advances in Consumer Research, Volume 26, pp. 362-366.
Pavlou, P.A. (2003), “Consumer acceptance of electronic commerce: integrating trust and risk with the technology acceptance model”, International Journal of Electronic Commerce, Vol. 7 No. 3, pp. 101-34
Qin, Z., 2009. Introduction to E-commerce. s.l.:Springer.
Riquelme, I. P. & Sergio, R., 2014. Is the influence of privacy and security on online trust the same for all type of consumers?Electron Markets, pp. 135-149.
Rodgers, S., & Harris, M. A. (2003). Gender and e-commerce: An exploratory study. Journal of Advertising Research, 43(3), 322-329.
Rust, R. T., Zeithaml, V. A., & Lemon, K. N. (2000). Driving customer equity: how customer lifetime value is reshaping corporate strategy. New York: Free Press.)
Shaheen, K. b., 1999. An investigation of Gender Differences in Online Privacy. JOURNAL OF INTERACTIVE MARKETING, 13(4), pp. 24-38.
Siemer & Assicoates, 2013. Siemer Ecommerce Report, Spring 2013, s.l.: s.n.
Stafford, T. F., Turan, A., & Raisinghani, M. S. (2004). International and cross-cultural influences on online shopping behavior. Journal of Global Information Technology Management, 7(2), 70-87.
Strahilevitzb, E. G. &. M., 2002. Gender differences in the perceived risk of buying online and the effects of receiving a site recommendation. Journal of Business Research, p. 8.
Sukhi, N. M., 2013. Consumer shopping behaviour on the Internet: insights From Malaysia. Springer Science, pp. 477-491.
Susskind, A. (2004). Electronic commerce and World Wide Web apprehensiveness: An examination of consumers’ perceptions of the World Wide Web. Journal of Computer-Mediated Communication, 9(3), 1-25.
Ulbrich, F., Christensen, T. & Stankus, L., 2011. Gender-specific on-line shopping preferences. Springer Science, pp. 181-199.
Pacific Institute of Management, Pacific Hills, Airport Road, Udaipur - 313001,