Mobile Based Agro Advisory Services (MAAS)

67 Pages·2017·1.71 MB·English

by  Sheesham Rana

2017
Mobile Based Agro Advisory Services (MAAS) in
India: An assessment of their effectiveness
Sheesham Rana
ICAR-NAARM, Hyderabad
4/15/2017
Project Guide:
Dr. Bharat S. Sontakki
Head, Extension Systems Management
ICAR- National Academy of Agricultural Research
Management
DECLARATION

I, Sheesham Rana, do hereby declare that the project entitled “Mobile-based
agro advisory services (MAAS) in India: An assessment of their effectiveness”
is original work. The contents of this report are not published before and reflect
the original work done by me during the Final Project component of the Post
Graduate Diploma in Management (Agriculture) at the ICAR-National Academy
of Agricultural Research Management, Hyderabad.

Place: Hyderabad Sheesham Rana
Date: 15/04/2017 PGDMA 1519
ICAR-NAARM, Hyderabad

Sheesham Rana, ICAR-NAARM
CERTIFICATE

This is to certify that Sheesham Rana (PGDMA 2015-17) did the project entitled
“Mobile-based agro advisory services (MAAS) in India: An assessment of their
effectiveness ”. This was carried out as final project under my guidance for the
fulfilment of Post Graduate Diploma in Management (Agriculture) at the ICAR-
National Academy of Agricultural Research Management, Hyderabad.

Place: Hyderabad Dr Bharat S. Sontakki
Date: Head, XSM Division
ICAR-NAARM, Hyderabad

Sheesham Rana, ICAR-NAARM
ACKNOWLEDGEMENT

It is a matter of great privilege for me to be associated with ICAR – National
Academy of Agricultural Research Management, Hyderabad. I would, hereby,
like to thank ICAR – NAARM and all its members whomever I have come across,
for their kind hospitality and cooperation during my project work.
I take this opportunity to personally acknowledge my wholehearted gratitude to
my mentor and advisor Dr Bharat S. Sontakki, Head, XSM Division at the ICAR-
NAARM, Hyderabad for not only guiding me through the project but also
supporting and believing in me regarding the work assigned. I am also very
thankful to the support offered by Mr. Chanchal Pramaik, Data Scientist at TCS,
Hyderabad for the arrangements he made for the survey at CHPCL, Chennai. The
field staff at Chennai was supportive and helped me in completing my survey
successfully. I also thank all the respondents who have given their valuable time,
views and authentic information for this project.
I am also thankful to Dr. Ravindra Naik at Agricultural Research Institute, PJTSAU,
Rajendranagar, Hyderabad for his guidance during the project.
I am also very delighted by the help offered to me by my classmates during the
project. It has been a great learning experience.
At last, I would like to thanks my family, fellow seniors, and friends who are
always there to encourage me.

Sheesham Rana, ICAR-NAARM
Contents
DECLARATION ............................................................................................................................ 1
CERTIFICATE ............................................................................................................................... 2
ACKNOWLEDGEMENT ............................................................................................................... 3
1. Executive Summary ............................................................................................................ 5
2. Introduction ........................................................................................................................ 6
2.1 Objectives: ........................................................................................................................ 7
2.2 Scope of the study ............................................................................................................ 7
2.3 Limitations of the Study ................................................................................................... 7
3. Review of Literature ........................................................................................................... 8
4. Methodology ...................................................................................................................... 9
4.1 Parameters for comparative study of the MAAS Models ................................................ 9
4.2 Limitations for the comparative study: .......................................................................... 10
4.3 Work Plan and Timeline ................................................................................................. 11
Objective 1: Profiles of mobile-based agro advisory services (MAAS) in India .................... 12
5. Results and discussion ...................................................................................................... 13
5.1 Profiles of mobile-based agro advisory services (MAAS) in India ........................... 13
Objective 2: Comparative Analysis of the profiled MAAS Models ........................................ 33
5.2 Comparative analysis of the profiled MAAS models ...................................................... 34
Objective 3: Key Success Factors and Limitations .................................................................. 42
6. Key Success factors for MAAS in India.............................................................................. 43
7. Limitations for the success of MAAS in India: .................................................................. 44
Objective 4: Conduct Effectiveness Study for some of the selected MAAS Models ............ 46
8. Effectiveness Study ........................................................................................................... 47
8.1 mKRISHI ..................................................................................................................... 47
8.2 mKisan ....................................................................................................................... 54
Objective 5: The Way Forward ............................................................................................... 60
9. Summary and conclusions (The Way Forward): ............................................................. 61
10. References ......................................................................................................................... 63
11. Annexure ....................................................................................................................... 64

Sheesham Rana, ICAR-NAARM
1. Executive Summary

The project titled “Mobile Based Agro Advisory Services (MAAS) in India: An Assessment of
their effectiveness” was undertaken with the objective of studying the prevailing MAAS in
India and develop understanding of their models from two perspectives: one from the service
provider’s perspective and second from the user’s perspective. 25 MAAS are selected for
comparative study and two of them were study from user’s perspective. List of parameters
were drawn and the MAAS were compared. To study the two MAAS from user’s perspective,
the end users of MAAS were met and schedule was filled after interaction. The users were
asked different questions about their perception for the MAAS, the main utility they derive
from MAAS and possible improvements they look forward to.
It is evident that MAAS is indeed playing a crucial role in farmer’s life with increasing
affordability and accessibility. Timely information has helped farmer in taking decisions that
are more informed. It directly and indirectly has consequences on the farm income. Farmers
save a lot on the input cost as well as productivity is enhanced. Still the farmers do not use all
the features of MAAS due to poor skills and hesitation of adopting newer things. But the
MAAS offers a promising and indispensable role in our Indian agriculture where real time
personalized information is the need of the hour.
Since the past two decades, it is evident that there are many improvements in the MAAS
models, which directs to suit the farmer’s needs. These models work at both local level and
even at the national level, offering a wide coverage with hyperlocal services which has come
out as a successful model.
What surely is looked forward to is the content development which will be the base success
factor for the success of MAAS in future. Farmers need personalized information that will be
another key aspect to be looked for. Thus, the possible way forward is the inclusive growth
approach encompassing all the stakeholders in the chain and integrating them to maximize
the benefits offered to each.

Sheesham Rana, ICAR-NAARM
2. Introduction

Agriculture has always been the backbone of our economy. It needs to be strengthened more
in order to support and sustain the growing population with scarce resources. Our agriculture
needs to be more precise, judicious and intelligent in order to achieve this. In present day
agriculture, soft resources like knowledge and skills are as important as hard resources like
inputs, and sometimes more important. However, estimates indicate that 60 per cent of
farmers do not access any source of information for advanced agricultural technologies
resulting in huge adoption gap (Mobile Phone Applications for Agricultural Extension in India
Saravanan and Suchiradipta Bhattacharjee). In today’s world, almost everybody owns a
mobile phone. This huge reach, if harnessed in agricultural extension, can change the face of
agriculture altogether in a developing country like India by using it as a medium to
disseminate agricultural information in multimodal form.
In the last few decades, information and communication technologies (ICTs) have provided
immense opportunities for the social and economic development of rural people. Mobile
telephony is one such technology that has developed significantly in the past few years, and
the subscription rate in developing countries has gone up from 22 per 100 inhabitants in 2005
to 91.8 per 100 inhabitants in 2015 (mExtension – Mobile Phones for Agricultural Advisory
Services; Raj Saravanan and Bhattacharjee Suchiradipta, August 2015). Mobile technology
goes beyond geographic, socioeconomic, and cultural barriers. This large increase in mobile
subscriptions, along with the recent roll out of 3G and 4G technology, can play a big role in
agriculture and rural development. Mobile phones are devices that can create, store, access,
and share information anytime and anywhere. However, they are more than that. When
teamed with extension and advisory services, they can help improve the livelihoods of rural
people by getting much needed timely information to their fingertips at potentially low cost.
Many initiatives have been taken in this regard to utilize mobile phones by private sector
(Indian Farmers Fertilizer Cooperative Limited, Nokia, Airtel, Tata Consultancy Services, etc.)
and public sector (Ministry of Agriculture, Universities like Tamil Nadu Agricultural University,
Indian Council of Agricultural Research, State Governments, Indian Meteorological
Department and others) in agricultural advisory service for agronomic practices, weather
forecasts and market price . With increased dependency, the mobile phone is becoming a
common communication platform of the world, especially for agriculture. Keeping in pace
with the current digitization initiatives, our farming is also moving towards digitalization.
Many mobile-based agricultural advisory services (MAAS) have evolved since 2000. However,
empirical studies on assessing their effectiveness are scanty. Hence, the present study was
carried out.

Sheesham Rana, ICAR-NAARM
2.1 Objectives:
The study was undertaken with the following objectives:
1) Understand the profile of mobile-based agro advisory services (MAAS) in India
2) Undertake comparative study of their service models
3) Identify the key success factors and limitations
4) Conduct Impact Assessment study for some selected service models
5) Suggest roadmap for future

2.2 Scope of the study
The study entitled “Mobile-based agro advisory (MAAS) services in India: an assessment of
their effectiveness” aimed at studying 25 such models based in India. The study will help us
in getting a better insight in the way these models are working and their effectiveness in
solving the current agricultural issues that are persistent. Comparative assessment will help
us in viewing these service models from a common perspective based on certain parameters
that are of importance to farmers. This will also help in making recommendations as to what
loopholes exist and how they can be corrected. It may guide a possible roadmap for future
utilizing these technologies.

2.3 Limitations of the Study
 Limitation of time and resources (single student-researcher)
 Limited Coverage
 Mostly secondary information is used, so lacks user perspective
 Variability in the services offered makes it difficult to compare the models on similar
grounds

Sheesham Rana, ICAR-NAARM
3. Review of Literature

Ganesan et. al. (2013) highlighted the potential of MAAS, which was field-tested among the
farmers. This is emerging as an effective modern ICT tool in the agricultural development
services. An effective utilization of this ICT tool can improve farming communities and enable
the speedy recommendation of requisite information in mobile-based user-friendly mode.
The ability to access the information at the right time through any basic mobile phone saves
time and cost of the farmer. However, this study has found that quality of information,
timeliness of information and reliability of information are some of the constraints
experienced by the farmers during the advisories. This study was conducted during December
2010 to June 2012 in Tamil Nadu (Kancheepuram, Erode and Dharmapuri districts). Out of
1200 farmers who had registered to MAAS only 243 had been utilizing the information
services provided through MAAS. Among them only 229 took part in this survey research
during the data collection.
Qiang et. al. (2011) summarize a study of 92 m-ARD apps in Africa, Asia, and Latin America
and the Caribbean. It also presents the findings of 15 detailed case studies of such apps in
Kenya, the Philippines, and Sri Lanka. Most m-ARD apps focus on improving agricultural
supply chain integration and have a wide range of functions, such as providing market
information, increasing access to extension services, and facilitating market links. Users are
also diverse, including farmers, produce buyers, cooperatives, input suppliers, content
providers, and other stakeholders who demand useful, affordable services. These supply
chain integration applications could provide significant economic and social benefits—among
them, creating jobs, adding value, reducing product losses, and making developing countries
more globally competitive. However, the potential development impact of m-ARD apps
mainly lies in their ability to provide access to useful, relevant information and services.
Saravanan and Bhattacharjee (2014) reported that 60 per cent of farmers do not access any
source of information for advanced agricultural technologies resulting in huge adoption gap.
The requirement of field level extension personnel is estimated to be about 1.3 -1.5 million
against the present availability of about 0.1 million personnel. The paper talks about the
status and future prospects of mobile telephony and its implication in agriculture extension
through MAAS.
Saravanan and Bhattacharjee (2015) discussed the philosophy and principles of mExtension,
implementation factors and capacities required to make it a success. The focus has been on
mobile telephony since, it has developed significantly in the past few years, and the
subscription rate in developing countries has gone up from 22 per 100 inhabitants in 2005 to
91.8 per 100 inhabitants in 2015.
Singh (2011) As per the study, the relevance of mobile devices as a medium for delivery of
public services is also evident when we compare the subscriber base of mobile phones to that
of the internet. The total base of internet users in India at the end of 2009 was only 81 million
and the total number of broadband subscribers (with minimum connection speeds of 256
Kbps) was only 11.21 million as on 31st January 20115. Wide access to mobile phones in the
country has made it an ideal platform for Government to resident interface, especially in the
rural areas.
Sheesham Rana, ICAR-NAARM
4. Methodology
The present study was carried during January-April 2017 using exploratory research design.
Details of the methodology followed are:
 Nature and Source of Information:
• Primary information/insights to be collected through interaction with the resource
person
• Secondary information from the literature, websites, reports, articles, etc.
 Sampling Procedure:
• Choice of the application models to be studied- based on information available
• Number of MAAS models Studied- 25
• Effectiveness study of MAAS models: (Purposive sampling of users)
MAAS Survey Location No. of Respondents
Mkrishi CHPCL, Chennai 32
MKisan West Maharashtra 33

 Data Collection and analysis:
• Through personal interaction with the resource persons and secondary searches
• The information collected would be analysed using appropriate statistical tools
4.1 Parameters for comparative study of the MAAS Models
To compare these mobile-based agro advisory service models, two approaches were
considered and accordingly a set of parameters were arrived at for comparative analysis.
Literature review and expert consultation were used to identify the parameters.
1. From the end-user perspective: usability of the application, impact, user experience etc.
2. From the content and service provider perspective: The profile of the services offered,
geography covered, number of subscribers etc.
Comparing from the Service Provider’s Perspective
For the comparison, following parameters are taken into consideration:
1. Service Provider: Private/Public/Joint Venture
2. Operating model
Sheesham Rana, ICAR-NAARM