Ajay Kumar
- Research Scholar, Department of Commerce, Deen Dayal Upadhyaya Gorakhpur University, Gorakhpur, Uttar Pradesh, India
Abstract
Online shopping has become a commonplace aspect of today’s consumer landscape due to the rapid growth of e-commerce. This study explores the particular elements that impact rural consumers’ online purchase behavior, whereas a large body of research has concentrated on the online shopping behavior of urban consumers. This study delves into the critical elements that influence rural consumers’ online buying decision-making processes, based on comprehensive surveys and data analysis. The study investigates how social networks influence rural consumers’ online purchasing preferences as well as aspects including product diversity, digital literacy, internet accessibility, and trust in e-commerce platforms. For companies, legislators, and marketers looking to capitalize on this expanding and underserved market niche, this study offers insightful information by illuminating the particular factors that influence online buying behavior in rural locations. By having a better understanding of these variables, tactics may be developed that are more suited to the needs and preferences of rural consumers in the online marketplace. Therefore, the goal of the research is to create a better marketing model that e-commerce companies may use to impact and draw users to their products. In order to get accurate research results, the study will employ a qualitative research approach to conduct one-on-one interviews.
Keywords: Online shopping, Digital marketing,e- commerce, Rural marketing, consumers behaviour.
[This article belongs to E-Commerce for Future & Trends(ecft)]
var fieldValue = “[user_role]”;
if (fieldValue == ‘indexingbodies’) {
document.write(‘Full Text PDF‘);
}
else if (fieldValue == ‘administrator’) { document.write(‘Full Text PDF‘); }
else if (fieldValue == ‘ecft’) { document.write(‘Full Text PDF‘); }
else { document.write(‘ ‘); }
Browse Figures
References
1. Ajzen I. The Theory of Planned Behavior. Handbook of Theories of Social Psychology: Volume One. 2011 Aug 3:438.
2. Akroush MN, Al-Debei MM. An integrated model of factors affecting consumer attitudes towards online shopping. Business Process Management Journal. 2015 Nov 2;21(6):1353-76.
3. Al-Debei MM, Akroush MN, Ashouri MI. Consumer attitudes towards online shopping: The effects of trust, perceived benefits, and perceived web quality. Internet Research. 2015 Oct 5;25(5):707-33.
4. Buchanan ME. Methods of data collection. AORN journal. 1981 Jan 1;33(1):137-49.
5. Cai Y, Krishnamoorthy K. A simple improved inferential method for some discrete distributions. Computational statistics & data analysis. 2005 Mar 1;48(3):605-21.
6. Chung C, Austria KP. Attitudes toward product messages on social media: An examination of online shopping perspectives among young consumers. International Journal of E-Services and Mobile Applications (IJESMA). 2012 Oct 1;4(4):1-4.
7. Crawford S. Evaluation of web survey data collection systems. Field Methods. 2002 Aug;14(3):307-21.
8. Fallman D. The interaction design research triangle of design practice, design studies, and design exploration. Design issues. 2008 Jul 1;24(3):4-18.
9. Glanville R. Researching design and designing research. Design issues. 1999 Jul 1;15(2):80-91.
10. Godin G. The theories of reasoned action and planned behavior: Overview of findings, emerging research problems and usefulness for exercise promotion. Journal of Applied Sport Psychology. 1993 Sep 1;5(2):141-57.
11. Huang WY, Schrank H, Dubinsky AJ. Effect of brand name on consumers’ risk perceptions of online shopping. Journal of Consumer Behaviour: An International Research Review. 2004 Sep;4(1):40-50.
12. Machleit KA, Eroglu SA. Describing and measuring emotional response to shopping experience. Journal of business research. 2000 Aug 1;49(2):101-11.
13. Madden TJ, Ellen PS, Ajzen I. A comparison of the theory of planned behavior and the theory of reasoned action. Personality and social psychology Bulletin. 1992 Feb;18(1):3-9.
14. Mohammed AB. DETERMINANTS OF YOUNG CONSUMERS’ONLINE SHOPPING INTENTION. International Journal of Academic Research. 2014 Jan 1;6(1).
15. Ozdemir A. Shopping malls: Measuring interpersonal distance under changing conditions and across cultures. Field Methods. 2008 Aug;20(3):226-48.
16. Madhavan M, Kaliyaperumal C. Consumer buying behavior-an overview of theory and models. St. Theresa Journal of Humanities and Social Sciences. 2015;1(1):74-112.
17. Soopramanien D. Conflicting attitudes and scepticism towards online shopping: The role of experience. International Journal of Consumer Studies. 2011 May;35(3):338-47.
18. Wu SI. The relationship between consumer characteristics and attitude toward online shopping. Marketing intelligence & planning. 2003 Feb 1;21(1):37-44.
19. Dhawan S, Singh K, Rabaea A, Batra A. ImprovedGCN: An efficient and accurate recommendation system employing lightweight graph convolutional networks in social media. Electronic Commerce Research and Applications. 2022 Sep 1;55:101191.
20. Soni A, Saxena A, Bajaj P. A methodological approach for mining the user requirements using apriori algorithm. Journal of Cases on Information Technology (JCIT). 2020 Oct 1;22(4):1-30.
21. Garg V, Nikam BR, Thakur PK, Aggarwal SP, Gupta PK, Srivastav SK. Human-induced land use land cover change and its impact on hydrology. HydroResearch. 2019 Jun 1;1:48-56.
22. Goyal P, Ferrara E. Graph embedding techniques, applications, and performance: A survey. Knowledge-Based Systems. 2018 Jul 1;151:78-94.
23. Sarkar PK, Prajapati PK, Shukla VJ, Ravishankar B. Evaluation of processed borax as antidote for aconite poisoning. Journal of ethnopharmacology. 2017 Jun 9;205:138-46.
24. Dwivedi YK, Ismagilova E, Hughes DL, Carlson J, Filieri R, Jacobson J, Jain V, Karjaluoto H, Kefi H, Krishen AS, Kumar V. Setting the future of digital and social media marketing research: Perspectives and research propositions. International Journal of Information Management. 2021 Aug 1;59:102168.
E-Commerce for Future & Trends
| Volume | 11 |
| Issue | 01 |
| Received | December 27, 2023 |
| Accepted | December 29, 2023 |
| Published | January 15, 2024 |
function myFunction2() {
var x = document.getElementById(“browsefigure”);
if (x.style.display === “block”) {
x.style.display = “none”;
}
else { x.style.display = “Block”; }
}
document.querySelector(“.prevBtn”).addEventListener(“click”, () => {
changeSlides(-1);
});
document.querySelector(“.nextBtn”).addEventListener(“click”, () => {
changeSlides(1);
});
var slideIndex = 1;
showSlides(slideIndex);
function changeSlides(n) {
showSlides((slideIndex += n));
}
function currentSlide(n) {
showSlides((slideIndex = n));
}
function showSlides(n) {
var i;
var slides = document.getElementsByClassName(“Slide”);
var dots = document.getElementsByClassName(“Navdot”);
if (n > slides.length) { slideIndex = 1; }
if (n (item.style.display = “none”));
Array.from(dots).forEach(
item => (item.className = item.className.replace(” selected”, “”))
);
slides[slideIndex – 1].style.display = “block”;
dots[slideIndex – 1].className += ” selected”;
}