THE INFLUENCE OF UNAVAILABILITY OF MEDICAMENTS AND LACK OF EMBARRASSMENT ON ONLINE PURCHASING OF MEDICAMENTS
DOI:
https://doi.org/10.61841/9zn8zg94Keywords:
Research, Shopping, Medicaments, Model, Examination, Variables, Software, TransactionsAbstract
The current study aims to address this gap in existing research and attempts to offer a picture of specific determinants that significantly influence the customers’ perceived risk and trust during online shopping of medicaments. A theoretical model was also proposed to explain the influence of all of these encouraging and discouraging factors on the customers’ perceived risk and trust. In order to collect the data needed for the examination of this model, an online questionnaire was distributed, which resulted in 157 valid responses. The impacts of the variables of interest were further quantitatively evaluated by Principal Component Analysis (PCA), using SPSS as the statistical software. Therefore, the discouraging constructs were the most significant constructs affecting consumers’ intention to purchase medicaments online. The fact that the customers’ intention to purchase medicaments online is mostly controlled by discouraging factors may not necessarily be indicative of no potential for this purchase medium. The results of this research could assist online retailers in implementing appropriate strategies in decreasing the consumers’ perceived risk, thus increasing their online transactions.
Downloads
References
[1] Aghekyan-Simonian, M., Forsythe, S., Kwon, W. S., & Chattaraman, V. (2012). The role of product brand image and online store image on perceived risks and online purchase intentions for apparel. Journal of retailing and Consumer Services, 19(3), 325-331.
[2] Almousa, M. (2011). Perceived risk in apparel online shopping: a multi dimensional perspective. Canadian Social Science, 7(2), 23-31.
[3] Benazić, D., Tanković, A. Č., & Music, M. (2015). Impact of perceived risk and perceived cost on trust in the online shopping websites and customer repurchase intention. Paper presented at the Proceedings of the 24th CROMAR congress: Marketing Theory and Practice-Building Bridges and Fostering Collaboration.
[4] Chakraborty, R., Lee, J., Bagchi-Sen, S., Upadhyaya, S., & Rao, H. R. (2016). Online shopping intention in the context of data breach in online retail stores: An examination of older and younger adults. Decision support systems, 83, 47-56.
[5] Chen, Y., Yan, X., Fan, W., & Gordon, M. (2015). The joint moderating role of trust propensity and gender on consumers’ online shopping behavior. Computers in human behavior, 43, 272-283.
[6] Crespo, Á. H., del Bosque, I. R., & de los Salmones Sánchez, M. G. (2009). The influence of perceived risk on Internet shopping behavior: a multidimensional perspective. Journal of Risk Research, 12(2), 259-277.
[7] Dennis, C., Merrilees, B., Kim, J., & Forsythe, S. (2009). Adoption of sensory enabling technology for online apparel shopping. European journal of marketing.
[8] Eggert, A. (2006). Intangibility and perceived risk in online environments. Journal of Marketing Management, 22(5-6), 553-572.
[9] Faqih, K. M. (2013). Exploring the influence of perceived risk and internet self-efficacy on consumer online shopping intentions: Perspective of technology acceptance model. International Management Review, 9(1), 67-77.
[10] Forsythe, S. M., & Shi, B. (2003). Consumer patronage and risk perceptions in Internet shopping. Journal of Business Research, 56(11), 867-875.
[11] Hong, L. M., Zulkiffli, W. F. W., & Hamsani, N. H. (2016). The impact of perceived risks towards customer attitude in online shopping. International Journal, 1(2), 13-21.
[12] Huang, W. y., Schrank, H., & Dubinsky, A. J. (2004). Effect of brand name on consumers' risk perceptions of online shopping. Journal of Consumer Behaviour: An International Research Review, 4(1), 40-50.
[13] Ko, H., Jung, J., Kim, J., & Shim, S. W. (2004). Cross-cultural differences in perceived risk of online shopping.
Journal of Interactive Advertising, 4(2), 20-29.
[14] Kumar, V., & Dange, U. (2014). A study on perceived risk in online shopping of youth in Pune: A factor analysis.
Ujwala, A Study on Perceived Risk in Online Shopping of Youth in Pune: A Factor Analysis (October 1, 2014).
[15] Laroche, M., Bergeron, J., & Goutaland, C. (2003). How intangibility affects perceived risk: the moderating role of knowledge and involvement. Journal of services marketing.
[16] Li, Y.-H., & Huang, J.-W. (2009). Applying theory of perceived risk and technology acceptance model in the online shopping channel. World Academy of Science, Engineering and Technology, 53(1), 919-925.
[17] Lin, P.-J., Jones, E., & Westwood, S. (2009). Perceived risk and risk-relievers in online travel purchase intentions.
Journal of Hospitality Marketing & Management, 18(8), 782-810.
[18] Masoud, E. Y. (2013). The effect of perceived risk on online shopping in Jordan. European Journal of Business and Management, 5(6), 76-87.
[19] Miyazaki, A. D., & Fernandez, A. (2001). Consumer perceptions of privacy and security risks for online shopping.
Journal of Consumer affairs, 35(1), 27-44.
[20] Mortimer, G., Fazal e Hasan, S., Andrews, L., & Martin, J. (2016). Online grocery shopping: the impact of shopping frequency on perceived risk. The International Review of Retail, Distribution and Consumer Research, 26(2), 202- 223.
[21] Nepomuceno, M. V., Laroche, M., & Richard, M.-O. (2014). How to reduce perceived risk when buying online: The interactions between intangibility, product knowledge, brand familiarity, privacy and security concerns. Journal of retailing and Consumer Services, 21(4), 619-629.
[22] Pires, G., Stanton, J., & Eckford, A. (2004). Influences on the perceived risk of purchasing online. Journal of Consumer Behaviour: An International Research Review, 4(2), 118-131.
[23] Sinha, P., & Singh, S. (2014). Determinants of consumers' perceived risk in online shopping: A study. Indian Journal of Marketing, 44(1), 22-32.
[24] Tsai, Y. C., & Yeh, J. C. (2010). Perceived risk of information security and privacy in online shopping: A study of environmentally sustainable products. African Journal of Business Management, 4(18), 4057.
[25] van der Heijden, H., Verhagen, T., & Creemers, M. (2001). Predicting online purchase behavior: replications and tests of competing models. Paper presented at the Proceedings of the 34th annual Hawaii international conference on system sciences.
[26] Wu, W.-Y., & Ke, C.-C. (2015). An online shopping behavior model integrating personality traits, perceived risk, and technology acceptance. Social Behavior and Personality: an international journal, 43(1), 85-97.
[27] Nguyen H.N., Tham J., Khatibi A., Azam S.M.F. (2019). Enhancing the capacity of tax authorities and its impact on transfer pricing activities of FDI enterprises in Ha Noi, Ho Chi Minh, Dong Nai, and Binh Duong province of Vietnam , Management Science Letters
[28] Nikhashemi S.R., Paim L., Haque A., Khatibi A., Tarofder A. K. (2013). Internet technology, Crm and customer loyalty: Customer retention and satisfaction perspective , Middle East Journal of Scientific Research
[29] Pathiratne S.U., Khatibi A., Md Johar M.G. (2018). CSFs for Six Sigma in service and manufacturing companies: an insight on literature, International Journal of Lean Six Sigma
[30] Seneviratne K., Hamid J.A., Khatibi A., Azam F., Sudasinghe S. (2019). Multi-faceted professional development designs for science teachers' self-efficacy for inquiry-based teaching: A critical review, Universal Journal of Educational Research
[31] Sudari S.A., Tarofder A.K., Khatibi A., Tham J. (2019). Measuring the critical effect of marketing mix on customer loyalty through customer satisfaction in food and beverage products, Management Science Letters
[32] Tarofder A.K., Haque A., Hashim N., Azam, S. M. F., Sherief S. R. (2019). Impact of ecological factors on nationwide supply chain performance, Ekoloji
Downloads
Published
Issue
Section
License
This work is licensed under a Creative Commons Attribution 4.0 International License.
You are free to:
- Share — copy and redistribute the material in any medium or format for any purpose, even commercially.
- Adapt — remix, transform, and build upon the material for any purpose, even commercially.
- The licensor cannot revoke these freedoms as long as you follow the license terms.
Under the following terms:
- Attribution — You must give appropriate credit , provide a link to the license, and indicate if changes were made . You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
- No additional restrictions — You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.
Notices:
You do not have to comply with the license for elements of the material in the public domain or where your use is permitted by an applicable exception or limitation .
No warranties are given. The license may not give you all of the permissions necessary for your intended use. For example, other rights such as publicity, privacy, or moral rights may limit how you use the material.
