Assessment of Omni channel retailing characteristics and its effect on consumer buying intention
Downloads
Published
DOI:
https://doi.org/10.58414/SCIENTIFICTEMPER.2024.15.spl-2.32Keywords:
Omni channel, Buying intention, Ease of use, Perceived usefulness, Perceived compatibility, Perceived risk, Security.Dimensions Badge
Issue
Section
License
Copyright (c) 2024 The Scientific Temper

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
Omni channel retailing phenomena gain lots of attraction among techno-savvy people because of the convenience. Most of marketers try to reach and capture large potential customers by providing them with various digital inputs through the retailing of Omni channels. Therefore, the study focuses on the identification of omnichannel characteristics’ impact on the buying intention of those customers who purchase their products with omnichannel retailing. College students in the age group 18 to 25, who are studying in urban areas were selected as the respondents for the present study. Out of 500 respondents 441 valid responses have been considered for the final analysis. The outcome demonstrates how Omni channel characteristics positively impact Omni channel consumers’ intentions to buy.Abstract
How to Cite
Downloads
Similar Articles
- Manpreet Kaur, Shweta Mishra, A smart grid data privacy-preserving aggregation approach with authentication , The Scientific Temper: Vol. 15 No. 04 (2024): The Scientific Temper
- Vandana, Ambrish Pandey, Comparative study of delta e of hybrid modulated and digitally modulated screening on different grades of paper , The Scientific Temper: Vol. 14 No. 03 (2023): The Scientific Temper
- R Sharmila, Nikhil S Patankar, Manjula Prabakaran, Chandra M. V. S. Akana, Arvind K Shukla, T. Raja, Recent developments in flexible printed electronics and their use in food quality monitoring and intelligent food packaging , The Scientific Temper: Vol. 14 No. 03 (2023): The Scientific Temper
- Adedotun Adedayo F, Odusanya Oluwaseun A, Adesina Olumide S, Adeyiga J. A, Okagbue, Hilary I, Oyewole O, Prediction of automobile insurance fraud claims using machine learning , The Scientific Temper: Vol. 14 No. 03 (2023): The Scientific Temper
- Pankaj Kumar, Ambrish Pandey, Rajendrakumar Anayath, Study of print suitability of environment-friendly plastics using flexography printing , The Scientific Temper: Vol. 15 No. 01 (2024): The Scientific Temper
- D. Prabakar, Santhosh Kumar D.R., R.S. Kumar, Chitra M., Somasundaram K., S.D.P. Ragavendiran, Narayan K. Vyas, Task offloading and trajectory control techniques in unmanned aerial vehicles with Internet of Things – An exhaustive review , The Scientific Temper: Vol. 14 No. 04 (2023): The Scientific Temper
- Tursunova N. Isroilovna, Dilbar M. Almuradova, Orifjon A. Talipov, Features of diagnosing ovarian tumors in women of pre- and postmenopausal age , The Scientific Temper: Vol. 14 No. 04 (2023): The Scientific Temper
- M. Menaha, J. Lavanya, Crop yield prediction in diverse environmental conditions using ensemble learning , The Scientific Temper: Vol. 15 No. 03 (2024): The Scientific Temper
- S. Deepa, I.S. Arafat, M. Sathya Priya, S. Saravanan, An improved spectrum sharing strategy evaluation over wireless network framework to perform error free communications , The Scientific Temper: Vol. 14 No. 04 (2023): The Scientific Temper
- Remya Raj B., R. Suganya, A novel and an effective intrusion detection system using machine learning techniques , The Scientific Temper: Vol. 15 No. 03 (2024): The Scientific Temper
<< < 7 8 9 10 11 12 13 14 > >>
You may also start an advanced similarity search for this article.

