Last Updated 07 May 2020

Online Consumer Purchasing Behaviors

Category Consumer
Essay type Research
Words 3626 (14 pages)
Views 725

Notes:

all the red highlight need to be paraphrased , because they meet a 16% of a student paper  as tuurnitin says.
(Liang and Lai 2000). & (Li & Zhang, 2002, p. 508) , not in the reference list

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Research Proposal

Examine the online shopping behavior of younger and older shoppers in Dubai as mediated by their attitudes toward internet shopping

February 2008

Introduction

There is different information available for the topic “Online Consumer Purchasing Behaviors”. Growth in the E-commerce has resulted from the growth in the penetration of computers and internet technology in various parts of the world. Internet as a platform offers various opportunities to its users. A user can use internet to search for new products and services, compare the prices and features at the same time. It saves money; energy, time and resources. On the other hand, it also has various limitations for instance unfamiliarity with the transaction processes, security and privacy. Consumers may have security concerns related to confidentiality of information like personal information, social security number, banking or credit card details and other relevant information.

Online shopping is also referred to as online buying, internet shopping or internet buying. This involves the procurement of goods, services and information over the Internet. Online shopping is very similar to traditional shopping in stores. A customer may first have a need for a product, service or information and because of that need the customer will actively engaged in informational seeking behavior in order to locate the desire product, service of information. Even though a customer may not consciously be aware of a need, advertising may attract a customer towards particular goods, products or information that they realize that they will need. Thus information seeking about products may be a passive behavior and the original intent may not have been to seek out the product, service or information. Customers will then evaluate their need for the product, goods or information, assess the alternatives for acquiring them, and then decide on whether or not to acquire them and from what source. When a decision is made to purchase the customer will actively seek to acquire the goods. Once the transaction is complete the customer anticipates that follow up services will be provided for the goods, service or information that was procured. The same processes are similar for online shopping.

Online shopping offers customers unique opportunities that never previously existed with traditional store purchases and that is why this area of study is of interest to me. Online shopping is very relevant to my field which is in information technology. This issue is of personal interest to me as internet shop is an area I am interested in going into, formulating different sites, with designs and so on aimed at obtaining maximal results. I am interested in discovering the mechanisms behind customer choice to be involved in online shopping and those factors that hinder them in order to formulate my own strategies in addressing the needs that may exist. One potential area of research that may follow from this is to discover mechanisms that would encourage more customers to shop online and take advantage of the opportunities that the Internet offers for Business-to-Customer transactions.

The results of this survey would be relevant to me as I contemplate this area but more so to industry leaders who are currently involved in or also contemplating exploring the internet as an option on which to post their goods for sale. This research will also be helpful to consumers in helping them understand the attitudes of other online shoppers and this will influence their behavior.

Literature review

Key Terms

Online shopping – This refers to shopping by way of the internet. This is sometimes referred to as electronic buying (Alsmadi, 2002, p. 134). Compared to traditional sales, where the customer either visits the store, or other alternative formats such as telephone sales, online shopping does not represent a significant portion of the retail market. The online retailing of products and services accounts for only little more than two percent of the total retail sales within the United States (Yang, Lester & James, 2007). Online sales could be in the form of Business-to-Business (B-to-B) transactions, where businesses supply products and services to other businesses, Consumer-to-Consumer (C-to-C) transactions where consumers pass on goods and services to other consumers or Business-to-Consumer (B-to-C) transactions (with which this research is concerned), where businesses offer goods and services directly to the final consumer (Alsmadi, 2002).

Research into online shopping behavior incorporates any Internet activity related to the consumption of goods, services or information (Freiden, Goldsmith, Hofacker & Takacs 1998). Internet shopping includes deliberate consumer browsing behavior in search for information on specific products and services and the eventual purchasing of these goods and services (Ahuha, Gupta & Raman, 2003). Research into the internet shopping behavior of consumers reveals that 52% of consumers use the internet for searching for product information, 42% use it for information on travel land 24% for buying online.( Nie & Erbring, 2000).

Attitude – Consumer online shopping attitude involves the psychological framework of the customer that that comes into play when making decisions about whether or not to shop online (Li & Zhang, 2002). Researchers believe that consumers’ online shopping attitude can greatly impact their actual buying behavior. Any perceived risk in relation to online shopping can have a serious bearing on consumers’ decision making. Researchers propose that the perception of risk by consumers can be one of the greatest obstacles to the growth of online business. Consumers risk usually incorporate issues of privacy and security of personal information, product quality and the security of transaction systems (Shergill & Chen, 2005).

Internet security – More and more transactions are being conducted over the Internet are these transactions often require disclosing credit cards details. However there have been countless reports of individuals who have suffered at the hands of criminals who use the Internet as a means of stealing such personal information from persons conducting business online. Evidently the mechanisms through which businesses attempt to ensure that customer information does not go into the wrong hands, are not very secure. One of the greatest dangers faced by shoppers online is identity theft. Identity theft includes taking another person’s identity and gaining financial benefits from it. Nowadays the traditional concept of identity theft has been redefined and expanded. Within the context of online businesses, identity theft now includes persons stealing usernames, passwords, spying on logging sessions and hijacking the databases of businesses in order to steal private customer information (Das, 2007).

As the Internet has expanded and more technological tools have been developed so too have the rate of identity using these resources. Perhaps the most perpetrated and common form of identity theft is the theft of credit card information. However, there are other online security issues such as phishing where thieves duplicate legitimate websites and, instead of customers accessing the correct website they are directed to these bogus sites who make financial gains from the customer without providing the goods or services they advertise (Lynch, 2005). Since shopping online often requires the disclosure of credit card information, customers are constantly exposed to the risk of credit card fraud and identity theft. Conducting financial transactions online with some business entities risks identity theft and thus the reservation of some consumers to shop online.

The number of incidences of identity theft throughout the United States is tremendous. Statistics suggest that it is one of the fastest growing white-collar crime in the U.S. and is also affected an unknown number of international customers who conduct business online with U.S. enterprises (Lynch, 2005). O’Sullivan (2004) quotes figures which put the loss incurred by financial institutions as a result of identity theft. Over $4.3 in losses were reported for the year 2003 alone. If the total losses incurred by businesses and consumers in that year alone are summed they would be around 53 billion. Credit card fraud affects well over 9.9 million American individuals yearly and it does not appear that the effects are waning. Online transactions are still very much unsafe. The majority of the costs of online fraud, however (47.6 billion) fell to the businesses (Lynch, 2005). This represented a 79% increase over the previous year (Dinev, 2000). This means that on average 10 million Americans are affected by this problem each year and the figures will continue to grow annually.

Victims of identity theft attacks primarily suffer financial losses as well as damages to their credit reputation (Lynch, 2005). The cost of identity theft is not only in terms of direct financial losses but also in terms of the time and additional money that the customer has to invest to restore credibility to their name. One of the societal effects of identity theft to businesses is the loss of confidence and trust in their business and in online shopping in general. Businesses are the ones to suffer when online thieves use stolen information to conduct business with them creating even more financial losses.

As technology increases more opportunities are provided to conduct identity theft on a larger and more sophisticated level. Therefore the internet is opening a world of possibilities for those who have the capabilities to manipulate the system to carry out their unlawful acts.

Bellman et al. (1999) sought to determine the issues that determined consumers’ online shopping behavior. They discovered that the demographic variables of income, education and age were only slightly correlated with online shopping behavior. The greatest correlation with online shopping behavior was found to be previous online shopping experience and an overall positive attitude towards online shopping. Bellman et al. (1999) notes that “Once people are online, whether they buy there and how much they spend has more to do with whether they like to buy online and whether the time they have for buying is limited” (p. 37). Thus it is reasonable to conclude that demographic variables are not as important as attitude in predicting online shopping behavior.

Ahuja, Gupta and Raman (2003) sought to determine the correlation between demographic variables, consumer browsing and buying behavior  and preferences for specific products and services in online shopping. Quantitative data was gathered from two separate survey samples. The fist sample was made up of 190 students, the majority of whom were full-time undergraduates, the second sample consisted of 75 non-students, that is faculty or administrators.

The researchers found that, among students, the main reason for shopping online was convenience (28%), the second reason was price (25%) and the third was saving time (23%).The conveniences students noted for shopping online were that they were able to avoid the customary shopping hassles such as locating parking, dealing with sales personnel and going through check-out lines. Students also noted that prices and timeliness of online shopping were other motivations. Similarly among the non-student group convenience accounted for 31%, saving time 27% and better prices 23%. These findings suggest that consumers are motivated more by convenience than by price in deciding to shop online and that there is little variation between age groups (Ahuja, Gupta & Raman, 2003).

Ahuja, Gupta and Raman (2003) also examined the issues that prevented customers from being willing to shop online. 28% of students and 31% of non-students who did not shop online indicated that their major concern was privacy and security. The second reason was the lack of customer service which involves being able to contact someone during the online shopping process in addition to services after making the purchase. Strangely the researchers found that this group felt that online products are more expensive going contrary to the finding that consumers shop online because of better prices.

Sorce, Perotti and Widrick also assessed the impact that the demographic characteristics of age and consumer attitude had on the online shopping behavior of consumers. The research was conducted among staff and students of a northeast USA university. Using a questionnaire, with open-ended and rating-scale questions, as the data gathering instrument the researchers assessed previous online shopping experience and attitude to online browsing and purchasing of products.

The researchers found that younger consumers found online shopping more convenient than their older counterparts. Attitude towards online shopping was, however, found to be a greater predictor of online buying than age. Individuals with a more positive attitude browsed and purchased online more frequently than those with a poorer attitude. However age was a greater predictor of the quantity of good purchased online. Older customers were more likely than the young to buy a product that they search for online (Sorce, Perotti &Widrick, 2005). These findings go contrary to the findings of Ahuja, Gupta and Raman (2003) where there was little correlation between shopping behavior and age.

Bhatnagar et al. (2000) sought to examine consumers’ perceived product and financial risks towards online shopping. The researchers established that a product was high risk if it was technologically complex, was purchased primarily for satisfying the ego needs of the consumer, was highly priced and was promoted on the basis of its feel or touch, characteristics which cannot be assessed online. High financial risk was set as the level of fear with regard to the online safety of consumers’ personal and financial information. The researchers found that where consumers had fears for both categories of risks that they would be less likely to shop online. Similarly Vellido et al. (2000) found that online shopping behavior was determined by the level of risk that a customer perceives in relation to internet shopping.

The impact of consumer attitude on purchasing behavior has yielded some contrary findings. Yang et al. (2007) surveyed the positive and negative attitudes of American and British university studies using a questionnaire. The researchers report that a negative attitude was positively correlated with online shopping among American consumers while a positive attitude was correlated with online shopping among British consumers.

Evidently the research into consumer online attitude has been substantial. Researches have been conducted among various demographies and in various countries. This research will seek to extend current knowledge of online shopping behavior by examining the online shopping behavior of consumers in an Arabic country. One limitation of the previous studies is that they fail to specific the intensity of consumer’s attitude towards online shopping. Data have simply stated whether or not consumers have a positive or negative attitude without necessarily discussing whether the positive attitude is quite noticeable or negligible. This research will fill in the gap in existing research by highlighting the extent to which consumers have a positive or negative attitude towards online shopping. The findings of this study will be relevant to both consumers and businesses involved or interested in online shopping. An understanding of the situation among Arab consumers would help to further contextualize the attitudes towards online shopping and further understanding on the variables that impact online shopping behavior.

Methodology

Statement of problem

Despite the rapid proliferation of the internet and the options it offers businesses and customers to conduct purchasing transactions online in ways more convenient than the traditional shopping methods, the contribution of online shopping to composite retail sales is still very minimal. Businesses need to identify the factors that are contributing to an unwillingness to make use of online shopping among non-shoppers, to distinguish the factors that motivate online shoppers to buy online and then to attract more customers by adapting their products, services and information to the needs of the consumer so that the online shopping population may increase.

To respond to these issues this study will seek to examine the online shopping behavior of younger and older shoppers as mediated by their attitudes toward internet shopping.

The questions that will guide this research are:

1.      What is the attitude of Dubai consumers to internet shopping?

2.      What are the perceived barriers/limitations to online shopping among students and faculty?

3.      What is the degree to which these factors hinder online shopping behavior?

In order to determine the attitude of consumers to internet shopping the following three factors will be examined - computer/Internet knowledge, access to Internet services and perceived security of Internet transactions.

Participants

Students and employees in universities in Dubai between 17-50 years old will be included in the survey. This research will survey both students and faculty at a university in Dubai. Students are thought to be more comfortable with the internet and associated technologies and are thus felt to be more Internet savvy and less concerned about privacy (Phelps, Nowak & Ferrell, 2000). This group utilizes the internet for a variety of purposes including education, entertainment and shopping. It is important that this group is involved in the survey. Other adults, on the other hand, are felt to be less Internet savvy and it would be useful to determine if this factor impacts online purchasing behavior.

Instrument of research

A researcher constructed questionnaire will be the data collection instrument. The questionnaire will contain different sections. Demographic variables of age, education, income, residence, ethnicity etc will be assessed in the introductory section of the questionnaire. There will be sections assessing general internet behavior and then specific online shopping behavior. There will be a set of items to be rated on the Likert scale that will be used to assess some general attitudes towards internet shopping.

Possible questions

Internet behavior
Access to internet
Where do you access the internet from
n  Don’t access the internet

n  Work?

n  Home?

n  Internet Café

n  Elsewhere (please specify) _______________________________

Use of internet
How often do you use the internet
n  Daily

n  Weekly

n  Monthly

n  Less often

General buying behavior
Have you ever purchased online?
n  Yes

n  No

How often do you buy or order something online?
n  Weekly

n  Daily

n  less often

n  never

Weekly internet use
How many hours per week do you use the internet for?
n  less than five

n  5-9

n  10 or more

Issues related to convenience and comfort
Do you agree that “Purchasing online is convenient process?” Why or why not?

Using the following scale 1 poor – 5 excellent, how would you rate online shopping in terms of the following component
Convenience ………………………….        1          2          3          4          5

Security ……………………………….       1          2          3          4          5

Privacy ………………………………..       1          2          3          4          5

Time …………………………………..       1          2          3          4          5

Reliability …………………………….        1          2          3          4          5

Quality ………………………………..       1          2          3          4          5

Choice/control………………………...        1          2          3          4          5

Effective ………………………………      1          2          3          4          5

Data collection process

E-mails will be sent from the university’s mailing list to recruit participants in the survey requesting that they complete and return the survey. Each participant will be given a deadline by which to complete the survey and return it to the researcher. For individuals who may be less frequent users of the internet and emailing questionnaires will also be passed out at specific locations on the campus of the university. Respondents will be asked to complete the questionnaire and return it immediately so as to avoid the possibility that some would not be returned.

Data analysis

The statistical program SPSS ® 15.0 will be used to facilitate analysis of the data. Descriptive statistics of means, modes and medians will be gathered from the data. Additional tests to be carried out include single and double-factor ANOVA, tests of reliability and validity as well as t-tests and chi-square tests.

Conclusion
There are a few potential limitations to the current study. First the surveys will be passed out around the faculty as well as emailed. It will be possible that there are duplicate submissions by persons who get both the email and the survey passed out on campus. It is also likely that there will be a lower response rate from the emailed surveys than from the onsite surveys because on email there is no mechanism to ensure that the surveys are returned on time.

References

Ahuja, M., Gupta, B. & Raman, P. (2003, Dec). An empirical investigation of online consumer purchasing behavior. Communications of the ACM, 46(12ve), 145-151.

Alsmadi, Dr. S. (2002). Consumer Attitudes Towards Online Shopping In Jordan: Opportunities and challenges. 16 ?????? 2002 - ????? ??????? ?? ????? ?????? - ???????? 15, 131-144.

Bellman, S., Lohse, G. & Johnson, E. (1999). Predictors of online buying behavior. Communications of the ACM, 42(12), 32-38.

Bhatnagar, A., Misra, S. & Rao, H. R. (2000). On risk, convenience and internet shopping behavior.  Communications of the ACM, 43(11), 98-105.

Das, R. (2007). “Identify Theft in E- Commerce Technology Executives Club.” Retrieved May 18, 2007, from http://www.technologyexecutivesclub.com/Articles/security/identifytheft.php

Dinev, T. (2006, Oct). Why spoofing is serious internet fraud. Communications of the ACM , 49(10), 77-82.

Freiden, J., Goldsmith, R. E., Hofacker, C., & Takacs, S. (1998). Information as a product: Not goods, not services. Marketing Intelligence and Planning 16(3), 210-220.

Lockyer, B. (2000, Nov). Hi -Tech Crime -Protecting Yourself in The Computer Age. Crime and Violence Prevention Center, California Attorney General’s Office. p. i-26

Lynch, J. (2005). Identity theft in cyberspace: Crime control methods and their effectiveness in combating phishing attacks. Berkeley Technology Law Journal, 20, 259-300.

Modahl, M. (2000). Now or never: How companies must change to win the battle for the Internet consumer. Harper Business: New York.

Nie, N., & Erbring, L. (2000). Internet use. Stanford Institute for the Quantitative Study of Society: California.

O’Sullivan, O. (2004, Feb). ID theft overstated? Some think so. ABA Banking Journal, 8-10.

Phelps, J., Nowak, G. & Ferrell, E. (2000). Privacy concerns and consumer willingness to provide personal information. Journal of Public Policy and Marketing,19(1), 27-41.

Shergill, G. S. & Chen, Z. (2005). Web-based shopping: Consumers’ attitudes towards online shopping in New Zealand. Journal of Electronic Commerce Research, 6(2), 79-94.

Sorce, P., Perotti, V. & Widrick, S. (2005). Attitude and age differences in online buying. International Journal of Retail & Distribution Management, 33(2), 122-132.

van Noort, G., Kerkhof, P. &Fennis, B. M. (2007, Oct). Online versus conventional shopping: Consumers’ risk perception and regulatory focus. CyberPsychology & Behavior, 10(5), 731-733.

Vellido, A., Lisboa, P. & Meehan, K. (2000, Summer). Quantitative characterization and prediction of online purchasing behavior: A latent variable approach.  International Journal of Electronic Commerce, 4(4), 83-104.

Wu, Shwu-Ing. (2003). The relationship between consumer characteristics and attitude toward online shopping. Marketing Intelligence & Planning, 21(1), 37-44.

Yang, B., Lester, D. & James, S. (2007, Apr). Attitudes toward buying online as predictors of shopping online for British and American respondents. CyberPsychology & Behavior, 10(2), 198-203.

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Online Consumer Purchasing Behaviors. (2018, Jul 07). Retrieved from https://phdessay.com/online-consumer-purchasing-behaviors/

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