Identifying Factors that Impact Online Shopping Behavior in Jordan

Main Article Content

Alaa M. Momani Mamoun Mohamad Jamous Wael M. S. Yafooz

Abstract

Online shopping is one of the most growing and promising activities in the electronic commerce. Analyzing the behaviors belonging to its usage aims to give a deep understanding about the effect of the demographic factors on the actual usage behavior of online shopping. This study investigates the behavioral preferences of the online shopping depending on the impact of the demographic factors of the Jordanian consumers. The demographic factors that have been investigated are: gender, age, education level, employment status, income level, and level of technology experience usage. These factors have been investigated by six behavioral preferences as follows: the most convenient time, place, device for online shopping, consumers’ opinion about offering the same commodity on several online shopping websites, and the delivery speed, and also the most preferred method of payment. This study found that the demographic factors are significantly influencing on the consumers’ preferences of online shopping behavior.

Article Details

How to Cite
MOMANI, Alaa M.; JAMOUS, Mamoun Mohamad; YAFOOZ, Wael M. S.. Identifying Factors that Impact Online Shopping Behavior in Jordan. International Journal of Contemporary Computer Research, [S.l.], v. 1, n. 2, p. 13-20, aug. 2017. Available at: <http://ojs.mediu.edu.my/index.php/IJCCR/article/view/490>. Date accessed: 23 oct. 2017.
Section
Internet computing

References

[1] Mahajan P, Agarwal M. Exploring the Potential of E-Commerce in the Digital Age: Challenges and Opportunities for Commerce Education. IUP J Inf Technol. 2015;11(4):46–56.

[2] Żuchowski W. The Impact of E-Commerce on Warehouse Operations. LogForum-Scientific J Logist. 2016;12(1):95–101.

[3] Forsythe SM, Shi B. Consumer Patronage and Risk Perceptions in Internet Shopping Consumer. J Bus Res. 2014;56:867–75.

[4] Mathwick C. Understanding the Online Consumer: A Typology of Online Relational Norms and Behavior. J Interact Mark. 2002;16(1):40–55.

[5] McKitterick JB. What Is the Marketing Management Concept? In: Bass FM, editor. The Frontiers of Marketing Thought and Science. Chicago, USA: American Marketing Association; 1957. p. 71–81.

[6] Drucker PF. The Practice of Management. Harper & Row; 1993. 416 p.

[7] Levitt T. Marketing Myopia. Harv Bus Rev. 1960;38(4):45–56.

[8] Aldhmour F, Sarayrah I. An Investigation of Factors Influencing Consumers’ Intention to Use Online Shopping: An Empirical Study in South of Jordan. J Internet Bank Commer. 2016;21(2).

[9] Nawaz N, Alajmi WYA. A Study on Consumer Preferences for E Shopping with reference to Bahraini Consumers. Eur J Bus Manag. 2014;6(29).

[10] Modahl M. Now or Never: How Companies Must Change Today to Win the Battle for Internet Consumers. 1st ed. HarperCollins. New York, USA: W W Norton & Co Inc; 2002.

[11] Bellman S, Lohse GL, Johnson EJ. Predictors of Online Buying Behavior. Commun ACM. 1999;42(12):32–8.

[12] Richa D. Impact of Demographic Factors of Consumers on Online Shopping Behaviour: A Study of Consumers in India. Int J Eng Manag Sci. 2012;3(1):43–52.

[13] Nunkoo R, Juwaheer TD, Rambhunjun T. Applying the Extended Technology Acceptance Model to Understand Online Purchase Behavior of Travelers. In: Proceedings of 21st International Business Research Conference. Toronto, Canada: Ryerson University; 2013.

[14] DOS. Department of Statistics, Jordan [Internet]. The Report of the Main Results of the General Census of Population and Housing in Jordan, 2015. 2015 [cited 2016 Jun 26]. Available from: http://www.dos.gov.jo/

[15] Chen LS-L. What Drives Cyber Shop Brand Equity? An Empirical Evaluation of Online Shopping System Benefit with Brand Experience. Int J Bus Inf. 2012;7(1):81–105.

[16] Tai Y-M, Ku Y-C. Will Stock Investors Use Mobile Stock Trading? A Benefit-Risk Assessment Based on A Modified UTAUT Model. J Electron Commer Res. 2013;14(1):67–85.

[17] Zhou L, Dai L, Zhangm D. Online Shopping Acceptance Model - A Critical Survey of Consumer Factors in Online Shopping. J Electron Commer Res. 2007;8(1):41–62.

[18] Hair JFJ, Black WC, Babin BJ, Anderson RE. Multivariate Data Analysis. NJ: Pearson Prentice Hall; 2006. 899 p.

[19] Thompson SK. Sampling. 3rd ed. John Wiley & Sons, Inc., Publication; 2012.

[20] Vincent K, Thompson S. Estimating Population Size with Link-Tracing Sampling. J Am Stat Assoc. 2014;1–23.