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Current IssueEditorial BoardOnline First ArticlesArchive

Full Research Article

volume 36 issue 2 (june 2021) : 120-125,   Doi: 10.18805/BKAP316

Socio-Economic Factors Influencing Consumers Online Purchase Behavior of Food Products in Bangalore City

S
Sebghatullah Rashid Rasoli
S
Siddayya
M
Mohammad Omer Kunduzi
1Department of Agricultural Marketing, Cooperation and Business Management, GKVK, University of Agricultural Sciences, Bangalore-560 065, Karnataka, India.

  • Submitted30-06-2021|

  • Accepted12-07-2021|

  • First Online 29-07-2021|

  • doi 10.18805/BKAP316

Cite article:- Rasoli Rashid Sebghatullah, Siddayya, Kunduzi Omer Mohammad (2021). Socio-Economic Factors Influencing Consumers Online Purchase Behavior of Food Products in Bangalore City. Bhartiya Krishi Anusandhan Patrika. 36(2): 120-125. doi: 10.18805/BKAP316.

ABSTRACT

Background: Online purchase has a very important role to play in creating consistent demand for farmers’ products and linking them directly to final consumers. Preferences of consumers are the most important driver of online purchases that prosper the linkage between farmers and the final consumers and these preferences are vastly influenced by consumers’ socio-economic characteristics. The current study was conducted to analyse the influence of socio-economic factors on the online purchase of food products in Bangalore city. 
Methods: Individual cross-sectional data were collected using a pre-tested questionnaire from 105 consumers of randomly selected areas of Bangalore city namely, Sahakarnagar, Judicial Layout, Yelahanka, Canara bank layout, Mahadevapura, Sanjaynagar and Jayanagar. Binary logistic regression was applied as the research method to examine the influence of socio-economic characteristics like gender, age, occupation, education, number of family members with income and income (as predictor variables) towards the online purchase of food products (as dependent  variable). 
Result: Results indicated that age (negatively), number of family members earning income and monthly income (positively) significantly influenced the online purchase of food products. Other variables like education, gender (in favour of men) and occupation also influenced (positively) the outcome variable but, statistically were not significant.

REFERENCES


  1. Agyapong, H.A. (2017). Exploring the Influential Factors of Online Purchase Intention in Finland. In International Business. https://core.ac.uk/download/pdf/161426026.pdf 

  2. Banerjee, T. and Banerjee, A. (2018). Web content analysis of online grocery shopping web sites in india. International Journal of Business Analytics (IJBAN). 5(4): 61-73.

  3. Banu, A.M., Rani, M.U., Malini, R., Idhayajothi, R. and Pavithra, G. (2014). A study on customer preference towards online shopping with special reference to Tiruchirappall district. International Journal of Advanced Research in Management and Social Sciences. 3(5): 205-214.

  4. Gujarati, D.N. (2009). Basic Econometrics (5th ed.). McGraw Hill Education (India) Private Limited.

  5. Javadi, M.H.M., Dolatabadi, H.R., Nourbakhsh, M., Poursaeedi, A. and Asadollahi, A.R. (2012). An analysis of factors affecting on online shopping behavior of consumers. International Journal of Marketing Studies. 4(5): 81.

  6. Jayasree, P. (2017). Consumer behavior-Online grocery shopping in India: An overview. International Journal of Advanced Research in Science and Engineering. 6(1): 113-117.

  7. Padmavathi, D. and Priyanka, V. (2016). Role of Demographics in Online Shopping Behaviour – an Empirical Study. Indian Journal of Research. 5(8): 140-142.

  8. Park, H.A. (2013). An Introduction to Logistic Regression: From Basic Concepts to Interpretation with Particular Attention to Nursing Domain. Journal of Korean Academy of Nursing, 43(2): 154-164. https://doi.org/10.4040/jkan.2013.43.2.154

  9. Peng, C.Y.J., Lee, K.L. and Ingersoll, G.M. (2002). An introduction to logistic regression analysis and reporting. Journal of Educational Research. 96(1): 3-14. https://doi.org/10. 1080/00220670209598786

  10. Popovic, A. (2018). Factors Behind Consumer Behavior of Online Customers. Price 2 Spy. https://www.price2spy.com/blog/ consumer-behavior-of-online-customers/

  11. Richa, D. (2012). Impact of Demographic Factors of Consumers on Online Shopping Behaviour/ : a Study of Consumers in India. International Journal of Engineering and Management Sciences. 3(1): 43-52.

  12. Sivanesan, I.R. and Monisha, I.C. (2017). Comparative Study on Factors Influencing Online and Offline Shopping (With Special Reference to Kanyakumari District of Tamil Nadu). International Journal of Research in Management and Business Studies. 4(3): 26-34. www.ijrmbs.com
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    Full Research Article

    volume 36 issue 2 (june 2021) : 120-125,   Doi: 10.18805/BKAP316

    Socio-Economic Factors Influencing Consumers Online Purchase Behavior of Food Products in Bangalore City

    S
    Sebghatullah Rashid Rasoli
    S
    Siddayya
    M
    Mohammad Omer Kunduzi
    1Department of Agricultural Marketing, Cooperation and Business Management, GKVK, University of Agricultural Sciences, Bangalore-560 065, Karnataka, India.

    • Submitted30-06-2021|

    • Accepted12-07-2021|

    • First Online 29-07-2021|

    • doi 10.18805/BKAP316

    Cite article:- Rasoli Rashid Sebghatullah, Siddayya, Kunduzi Omer Mohammad (2021). Socio-Economic Factors Influencing Consumers Online Purchase Behavior of Food Products in Bangalore City. Bhartiya Krishi Anusandhan Patrika. 36(2): 120-125. doi: 10.18805/BKAP316.

    ABSTRACT

    Background: Online purchase has a very important role to play in creating consistent demand for farmers’ products and linking them directly to final consumers. Preferences of consumers are the most important driver of online purchases that prosper the linkage between farmers and the final consumers and these preferences are vastly influenced by consumers’ socio-economic characteristics. The current study was conducted to analyse the influence of socio-economic factors on the online purchase of food products in Bangalore city. 
    Methods: Individual cross-sectional data were collected using a pre-tested questionnaire from 105 consumers of randomly selected areas of Bangalore city namely, Sahakarnagar, Judicial Layout, Yelahanka, Canara bank layout, Mahadevapura, Sanjaynagar and Jayanagar. Binary logistic regression was applied as the research method to examine the influence of socio-economic characteristics like gender, age, occupation, education, number of family members with income and income (as predictor variables) towards the online purchase of food products (as dependent  variable). 
    Result: Results indicated that age (negatively), number of family members earning income and monthly income (positively) significantly influenced the online purchase of food products. Other variables like education, gender (in favour of men) and occupation also influenced (positively) the outcome variable but, statistically were not significant.

    REFERENCES


    1. Agyapong, H.A. (2017). Exploring the Influential Factors of Online Purchase Intention in Finland. In International Business. https://core.ac.uk/download/pdf/161426026.pdf 

    2. Banerjee, T. and Banerjee, A. (2018). Web content analysis of online grocery shopping web sites in india. International Journal of Business Analytics (IJBAN). 5(4): 61-73.

    3. Banu, A.M., Rani, M.U., Malini, R., Idhayajothi, R. and Pavithra, G. (2014). A study on customer preference towards online shopping with special reference to Tiruchirappall district. International Journal of Advanced Research in Management and Social Sciences. 3(5): 205-214.

    4. Gujarati, D.N. (2009). Basic Econometrics (5th ed.). McGraw Hill Education (India) Private Limited.

    5. Javadi, M.H.M., Dolatabadi, H.R., Nourbakhsh, M., Poursaeedi, A. and Asadollahi, A.R. (2012). An analysis of factors affecting on online shopping behavior of consumers. International Journal of Marketing Studies. 4(5): 81.

    6. Jayasree, P. (2017). Consumer behavior-Online grocery shopping in India: An overview. International Journal of Advanced Research in Science and Engineering. 6(1): 113-117.

    7. Padmavathi, D. and Priyanka, V. (2016). Role of Demographics in Online Shopping Behaviour – an Empirical Study. Indian Journal of Research. 5(8): 140-142.

    8. Park, H.A. (2013). An Introduction to Logistic Regression: From Basic Concepts to Interpretation with Particular Attention to Nursing Domain. Journal of Korean Academy of Nursing, 43(2): 154-164. https://doi.org/10.4040/jkan.2013.43.2.154

    9. Peng, C.Y.J., Lee, K.L. and Ingersoll, G.M. (2002). An introduction to logistic regression analysis and reporting. Journal of Educational Research. 96(1): 3-14. https://doi.org/10. 1080/00220670209598786

    10. Popovic, A. (2018). Factors Behind Consumer Behavior of Online Customers. Price 2 Spy. https://www.price2spy.com/blog/ consumer-behavior-of-online-customers/

    11. Richa, D. (2012). Impact of Demographic Factors of Consumers on Online Shopping Behaviour/ : a Study of Consumers in India. International Journal of Engineering and Management Sciences. 3(1): 43-52.

    12. Sivanesan, I.R. and Monisha, I.C. (2017). Comparative Study on Factors Influencing Online and Offline Shopping (With Special Reference to Kanyakumari District of Tamil Nadu). International Journal of Research in Management and Business Studies. 4(3): 26-34. www.ijrmbs.com
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