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Interpretive structural modeling of factors representing potential of M-Commerce in agrochemical marketing

Author Affiliations

  • 1Oriental School of Business Management, Oriental University, Indore, MP, India
  • 2Oriental School of Business Management, Oriental University, Indore, MP, India

Res. J. Management Sci., Volume 7, Issue (6), Pages 1-7, October,6 (2018)

Abstract

Present research focuses on investigating the dimensions of services provided by m-commerce in agricultural input marketing considering the opinions of the farmers in the present marketing field. What is to be studied in this research work is to know how worthily it is to use the mobile phone in the agri-input marketing platform for the farmers based in the rural parts of our country. In the present work, interpretive structural modeling (ISM) of factors representing potential of m-commerce in agrochemical industries is accomplished. For this purpose, first of all a systematically designed questionnaire was sent to 152 customers of agrochemical industries and with the help of responses and the principal component analysis, seven factors were investigated. The identified factors were aesthetics, user friendliness, and curiosity for new discovery, ease of use, suitability, reliability and cost. In next step, another systematically designed questionnaire was framed by using interpretive structural modeling approach to find the relationships of the factors.

References

  1. Müller-Veerse F. (1999)., Mobile commerce report., Durlacher Research Ltd.
  2. Sadeh N.M., Chan E. and Van L. (2002)., Open agent environment for context aware m-commerce., Challenges in Open Agent Systems Workshop,(AMAS, 02).
  3. Singh M.D. and Kant R. (2008)., Knowledge management barriers: An interpretive structural modeling Approach., International Journal of Management Science and Engineering Management, 3(2), 141-150.
  4. Sohani N. and Sohani N. (2012)., Developing interpretive structural model for quality framework in higher education: Indian context., Journal of Engineering, Science & Management Education, 5(2), 495-501.
  5. Thakkar J., Deshmukh S.G., Gupta A.D. and Shankar R. (2006)., Development of a balanced scorecard: an integrated approach of interpretive structural modeling (ISM) and analytic network process (ANP)., International Journal of Productivity and Performance Management, 56(1), 25-59.
  6. Sage A. (1977)., Interpretive Structural Modelling: Methodology for Large-scale Systems., McGraw-Hill, New York, NY, 458.
  7. Thakkar J., Kanda A. and Deshmukh S.G. (2008)., Interpretive structural modeling (ISM) of IT-enablers for Indian manufacturing SMEs., Information Management & Computer Security, 16(2), 113-136.
  8. Singh M.D., Shankar R., Narain R. and Agarwal A. (2003)., An interpretive structural modeling of knowledge management in engineering industries., Journal of Advances in Management Research, 1(1), 28-40.
  9. Mandal A. and Deshmukh S.G. (1994)., Vendor selection using interpretive structural modelling (ISM)., International Journal of Operations and Production Management, 14(6), 52-59.
  10. Luthra S., Kumar V., Kumar S. and Haleem A. (2011)., Barriers to implement green supply chain management in automobile industry using interpretive structural modeling technique-An Indian perspective., Journal of Industrial Engineering and Management, 4(2), 231-257.
  11. Müller-Veerse F. (1999)., Mobile commerce report., Durlacher Research Ltd.
  12. Sadeh N.M., Chan E. and Van L. (2002)., Open agent environment for context aware m-commerce., Challenges in Open Agent Systems Workshop,(AMAS, 02).
  13. Singh M.D. and Kant R. (2008)., Knowledge management barriers: An interpretive structural modeling Approach., International Journal of Management Science and Engineering Management, 3(2), 141-150.
  14. Sohani N. and Sohani N. (2012)., Developing interpretive structural model for quality framework in higher education: Indian context., Journal of Engineering, Science & Management Education, 5(2), 495-501.
  15. Thakkar J., Deshmukh S.G., Gupta A.D. and Shankar R. (2006)., Development of a balanced scorecard: an integrated approach of interpretive structural modeling (ISM) and analytic network process (ANP)., International Journal of Productivity and Performance Management, 56(1), 25-59.
  16. Sage A. (1977)., Interpretive Structural Modelling: Methodology for Large-scale Systems., McGraw-Hill, New York, NY, 458.
  17. Thakkar J., Kanda A. and Deshmukh S.G. (2008)., Interpretive structural modeling (ISM) of IT-enablers for Indian manufacturing SMEs., Information Management & Computer Security, 16(2), 113-136.
  18. Singh M.D., Shankar R., Narain R. and Agarwal A. (2003)., An interpretive structural modeling of knowledge management in engineering industries., Journal of Advances in Management Research, 1(1), 28-40.
  19. Mandal A. and Deshmukh S.G. (1994)., Vendor selection using interpretive structural modelling (ISM)., International Journal of Operations and Production Management, 14(6), 52-59.
  20. Luthra S., Kumar V., Kumar S. and Haleem A. (2011)., Barriers to implement green supply chain management in automobile industry using interpretive structural modeling technique-An Indian perspective., Journal of Industrial Engineering and Management, 4(2), 231-257.