15
The Use of a Mobile - Based Decision Support System in Agriculture: An Interpretive Case Study in Southwest and Central Bangladesh Omar Ismail BA (Honors), Media/Communication Studies Research Supervisor: Professor Dr. Stephen McDowell School of Communication and Information

Omar ismail FSU South Asian Cultural and Media conference

Embed Size (px)

Citation preview

Page 1: Omar ismail FSU South Asian Cultural and Media conference

The Use of a Mobile-Based Decision Support System in Agriculture:

An Interpretive Case Study in Southwest and Central Bangladesh

Omar Ismail

BA (Honors), Media/Communication Studies

Research Supervisor: Professor Dr. Stephen McDowell School of Communication and Information

Page 2: Omar ismail FSU South Asian Cultural and Media conference

1/23/2015Decision Support System, Omar

Ismail

Farmers and Agriculture workers in Bangladesh

There are about 15 million farm households in Bangladesh. (Bangladesh Bureau of Statistics, 2009)

Contributes approximately 17 percent to the national economy. (World Bank, 2015)

Farmers of Bangladesh receives greater extension service from both public and private sectors (Agricultural Services Innovation and

Reform Project, 2003)

About 84 percent of rural farmers are using cell phones (Agroquest Survey, Katalyst, 2013)

Page 3: Omar ismail FSU South Asian Cultural and Media conference

1/23/2015Decision Support System, Omar

Ismail

What is Decision Support System?

A Decision Support System (DSS) is a computer technology solution that can be used to support decision-makingand to solve problems (Shim, et al., 2002)

Page 4: Omar ismail FSU South Asian Cultural and Media conference

1/23/2015Decision Support System, Omar

Ismail

Project Site

WhatSeven smart phone applications developed by mPower Social Enterprise Ltd. to help in agricultural decision-making for both farmers and extension employees.

Where JesoreFaridpurNorailShatkhiraKhulna

Who User of the applications are categorized in: ICT Farmer LeadersInput SellersPrivate Extension Agents Public Extension Agents

Page 5: Omar ismail FSU South Asian Cultural and Media conference

1/23/2015Decision Support System, Omar

Ismail

Theoretical Framework

Islam and Gronlund’s RuTam Model (2011)

Page 6: Omar ismail FSU South Asian Cultural and Media conference

1/23/2015Decision Support System, Omar

Ismail

Methodology: Imperative Case Study

Interview

Focus Group

Participant Observation

Page 7: Omar ismail FSU South Asian Cultural and Media conference

1/23/2015Decision Support System, Omar

Ismail

Three Next Generation Farmers of Bangladesh

Milon

• Lives in Ishapur,

Jessore•Age 26 yrs • Young educated farmer

Zakir Hossain

• Lives in Varashimla,

Shatkhira•Age 47•Runs Agriculture Information and CommmunicationCenter (AICC) in Shatkhira

Rezaul Karim

• Lives in Keshobpur, Jessore•Age 46•Input seller and Farmer

Page 8: Omar ismail FSU South Asian Cultural and Media conference

1/23/2015Decision Support System, Omar

Ismail

Research questions

1) How do the end-users (farmers and extension officers) define the system to be useful in their work?

2) Is it easy for the users to use the mobile application for farming? Conversely, are the applications creating complexity in their normal duties

3) What are the factors playing an important role in using the decision support system?

4) How essential are the facilities provided by the agency in using the decision support system.

Page 9: Omar ismail FSU South Asian Cultural and Media conference

1/23/2015Decision Support System, Omar

Ismail

Findings: Information dissemination

ICT Farmer Leaders/Input Sellers to General Farmers

StrengthsFriendly atmosphere Fearless conversationThe likeliness of using the solutions

WeaknessChances of false interpretationNeed of extensive training Trust issue

Private Extension Agents to General Farmers

Strengths Knowledge of modern ICT tools Faster service Close to the community

Weakness Membership based Charges applicable

for service

Public Extension Agents to General Farmers

Strengths Trustworthy source Well educated and experience Organized

Weakness Large ratio Not available all the time Some agents are fears of technological change

Page 10: Omar ismail FSU South Asian Cultural and Media conference

1/23/2015Decision Support System, Omar

Ismail Source: User Satisfaction Report, 2015 from mPower AESA project team (n= 7)

Findings: Attitude towards Applications

Page 11: Omar ismail FSU South Asian Cultural and Media conference

1/23/2015Decision Support System, Omar

Ismail •Source: User Satisfaction Report, 2015 from mPower AESA project team (n=34)

Findings: Attitude towards Applications

Page 12: Omar ismail FSU South Asian Cultural and Media conference

1/23/2015Decision Support System, Omar

Ismail

Findings: Factors

1. Individial Charecteristicsi. Willingnessii. Awareness

2. Demographic i. Ageii. Genderiii. Occupation

3. Social Influence i. Peer Pressure

4. Facilitating Conditions i. Use of Mobile Phones and internet ii. Choosing Right Usersiii. Training iv. Govt. Digitalization Policy

Page 13: Omar ismail FSU South Asian Cultural and Media conference

1/23/2015Decision Support System, Omar

Ismail

Limitation and Future Directions

• Small user population and limited locality of the overall project region

• Further studies should discuss broader perspective of using mobile applications in Agriculture

Page 14: Omar ismail FSU South Asian Cultural and Media conference

Question Opinion

1/23/2015Decision Support System, Omar

Ismail

Question Opinion

Page 15: Omar ismail FSU South Asian Cultural and Media conference

Question Opinion

1/23/2015Decision Support System, Omar

Ismail

Works cited

Agricultural Services Innovation and Reform Project. (2003). Agricultural Extension in Bangladesh:An Entitlement of All Farmers? ASIRP.

Bangladesh Bureau of Statistics . (2009). Statistical Yearbook. Dhaka: Government of Bangladesh.

Islam, M. Sirajul and Ake Gronlund. "Factors Influencing theAdoption of Mobile Phones among the Farmers in Bangladesh: Theories and Practices." International Journal on Advances inICT for Emerging Regions (2011): 4-14.

Shim, J.P., et al. "Past, present, and future ofdecision support technology." Decision Support Systems.

Vol. 33. Elsevier Science, 2002. 111 –126

World Bank. (2015, April 2). Data of Agriculture,value added. Retrieved April 2, 2015,from www.data.worldbank.org:http://data.worldbank.org/indicator/NV.AGR.TOTL.ZS/countries

Katalyst. (2013) Agroquest Survey. Dhaka: Katalyst