Open Journal of Social Sciences
Vol.04 No.05(2016), Article ID:67649,8 pages
10.4236/jss.2016.45031
Factors Inhabiting ICTs Usage among Farmers: Comparative Analysis from Pakistan and China
Muhammad Yaseen1,2, Shiwei Xu1*, Wen Yu1, Muhammad Luqman1,2, Sadia Hassan3, Muhammad Ameen4
1Agricultural Information Institute, Chinese Academy of Agricultural Sciences, Beijing, China
2Department of Agricultural Extension & Rural Development, University College of Agriculture, University of Sargodha, Sargodha, Pakistan
3Graduate School of Chinese Academy of Agricultural Sciences, Beijing, China
4Department of Agricultural Engineering, Pir Mehr Ali Shah Arid Agriculture University, Rawalpindi, Pakistan
Copyright © 2016 by authors and Scientific Research Publishing Inc.
This work is licensed under the Creative Commons Attribution International License (CC BY).
Received 4 May 2016; accepted 28 May 2016; published 31 May 2016
ABSTRACT
The current study aimed to provide comparative analysis between Pakistan and China regarding factors inhabiting ICTs usage by farmers. Population of this study contained two categories. Firstly, the population was comprised of Punjab
Keywords:
Comparision, Factors, China, Pakistan, ICT
1. Introduction
Use of Information and Communication Technologies (ICTs) in an innovative way for development of agriculture sector which is the most vital part of economy in most of the developing countries. This sector claims to be important being ensures poverty reduction and food security and is responsible for the provision of sustainable livelihoods [1]. With the advancement in communication technologies and its mechanism, extension and rural advisory services are going to be more reliant on ICTs as to be flourishing in more efficient, appropriate and innovative ways for delivery of agro-based advanced technologies to the end-users. Moreover, ICT based extension and advisory services play a vital role in provision of agricultural information and knowledge for farmers. Keeping in view the significance of ICTs in overall agricultural advancement, it is necessary to promote ICT based agricultural information dissemination to enhance agricultural productivity on one hand and also to provide sustainable agricultural information delivery mechanism [2].
Adopting ICTs as source of agricultural information is a very complex and critical procedure. It involves various steps and factors at farmer’s level. Out of these factors, socio-economic profile of farmers placed a prominent position as in adoption process key role is their socio-economics. Various studies have been conducted to investigate socio-economic factors influencing behavior of farming community with regard to ICT based agricultural extension services, approaches and other social activities. Diversified demographic attributes have been supposed to be manipulated by intellectual and social and economic variation associated with behavior [3]. These factors may also be proficient for different policies to promote acceptance of ICT oriented agronomic practices among farmers for support in improving farm productivity and sustainability in agriculture [4]. In contrary to this, it has also been found that there is significant association between some demographics of farmers like age and education of farmers and their development or advancement in their technological information [5]. The relationship between educational profile of farmers with their advancement in ICTs adoption and usage was also presented by Atibioke et al. [6].
With similar notion Arfan, et al. (2015) reported that some demographics of farmers like education, size of farm and income demonstrates a most significant positive linkages with the enhanced knowledge level of the farming community [7]. It was also investigated that the demographic characters should be concentrated to acquire maximum productivity of resources developed for the enhancement of agricultural information and knowledge of the farming community. Likewise, [8] it was also observed that majority (70.1%) of extension staff were men, having almost eleven years working experience and aged more than 40 years. Furthermore, statistical variation was found which indicates that the farmer’s age, education, experience and gender, were considerably related with the benefits perceived by farmers. Some outcomes also exposed that socio-economic factors of youth including young males and females have better information related to profits by agro-based farms [9]. There is a momentous relation between gender and farming scientific implementation [6].
So in the light of above situation the present study was designed to investigate different factors like age, education, size of land holding, family size, professions or occupations etc. which have influence on farmers’ behavior to adopt information commutation technologies in agriculture [10]. The present study is comparative analysis of developing country like
2. Data and Methodology
2.1. Description of Data
The results presented in Table 1 revealed that 55% of farmers from Pakistan have age more than 50 years while 45% have age equal or less than 50 years while in case of China 32.79% of farmers have more than 50 years age
Table 1. Demographic attribute of farmers in Pakistan and China.
and majority (67.21%) of farmers have age equal or less than 50 years. Education level of farmers in
Similarly, land holding size for farmers in Pakistan is equal or less than 12 acres for 41% farmers and more than 12 acres for 59% farmers, in China more than 99% farmers have above 12 acres land size and only less than 1% have equal or less than 12 acres land size. As for as occupation or profession of farming community is concerned in case of
According to results indicated in Table 2, in Pakistan only 6.25% of farmers are utilizing landline telephone while all of the respondents are using mobile phone for the sake of agricultural information, similarly computer, internet, TV, radio and newspaper is used by 38.12%, 11.88%, 80.63%, 10.63% and 7.50% respectively for the propose to get agricultural information. While in
2.2. Population of Study
As the present research was conducted in two countries i.e.
Table 2. Information & communication technologies application in Pakistan and China.
study was consisted of two categories. The first category of the population was comprises of Punjab province of Pakistan which is the largest on the basis of population with a share of 54% of country’s total population [11]. The selection of the
The 2nd category of population comprises of Hebei province of China selected purposively as the study province, because of its locality extremely to north of Yellow River, is situated in north China and its climate is monsoon influenced with cold and dry winter, hot and humid summer. In 2014, GDP of
2.3. Samples and Procedures for Sampling
Multistage sampling design was adopted in this study. Out of the 36 districts of the Punjab four districts D. G. Khan,
2.4. Data Collection and Tool
Household farmers are key stakeholder with regard to agricultural development; therefore, face-to-face interviews method was used with the help of validated and expert reviewed questionnaire. In order to get direct opinion and response of household farmers regarding different parameters included in present study. Questionnaire comprised of different sections like; demographic characteristics of household farmers, agricultural extension teaching methodologies, information & communication technologies etc. Different experts related to agricultural extension, rural development, agricultural economics etc. from
2.5. Model Selection and Analysis
Data analysis was carried out by using STATA software and applying logistic regression model for this study. Application of ICTs among farmers was measured as dichotomous, using value 1 for application of ICTs among farmer and 0 otherwise. Model specification for calculation is given below:
(1)
where is probability of application of computer as ICTs in agriculture by farmers in Pakistan.
(2)
where is probability of application of computer as ICTs in agriculture by farmers in China.
(3)
where is probability of application of internet as ICTs in agriculture by farmers in Pakistan.
(4)
where is probability of application of internet as ICTs in agriculture by farmers in China.
Listed in Table 3 are variables and their explanation which were used in the study.
3. Results and Discussion
The results presented in Table 4 indicate that in Pakistan education of household head is most significant with regard to adoption of computer as ICTs in agriculture because one unit increase in education level of household head will increase the odds of computer application by factor of 2.55. Similarly income and land area of household farmers has significant influence on computer application as ICTs, as one unit increase in income and land area of household will increase odds of computer application by factor of 0.999 and 1.096 respectively. While in case of China income and education of household head has most significant effect on computer application as ICTs tool as data shows that one unit increase in income and education of household head will increase odds of computer application by factor of 1.00 and 1.302 respectively.
The results shown in Table 5 indicate that in Pakistan farming occupation of household head has influence in
Table 3. variables used and their explanation.
Table 4. Factors effecting computer application by farmers in Pakistan & China.
Table 5. Factors effecting internet application by farmers in Pakistan and China.
internet application by farming community as results present that one unit increase in farming occupation will increase odds of internet application by household head by factor of 0.023. While this situation is quite different in China, as education of household head has most significant effect on internet application as ICTs tool that indicates one unit increase in education of household head will increase odds of internet application by factor of 1.383. similarly, family size, age and income has also influence on internet application by household head, as results in Table 5 depicts that one unit increase in family size, age and income of household head it will increase odds of internet application as ICTs by factor of 1.253, 0.935 and 1.00 respectively.
4. Conclusion & Recommendations
Education of household head has significant influence in adoption of computer as ICT tool application in agriculture in
On the basis of results following recommended are drawn for government of Pakistan and China:
1) Education is an import indicator for development, education level of farmer in Pakistan is not satisfactory, while this situation is encouraging in China but government should also increase educational level among farming community.
2) ICTs should be utilized in more innovative way, because farmers of both country (Pakistan & China) are utilizing mobile phone almost 100%, but there is need to maximize innovativeness in the use of ICTs so that farming community ensure food security, sustainable agriculture and livelihood.
3) Government of Pakistan should introduce some policies to boost up household income, land reform policies, and increasing involvement of youth in agriculture activities to ensure application of computer and internet in agriculture with goal to enhance agriculture productivity.
4) Similarly government of China should also ensure involvement of maximum family member in agricultural activities, encouraging youth as well as old aged in agriculture, and by increasing household income to improve application of computer and internet in agriculture to maximize crop productivity.
Acknowledgements
This study was supported by the program CAAS-ASTIP-2016-AII. The authors thanks for support from innovation fund founded by the Chinese
Cite this paper
Muhammad Yaseen,Shiwei Xu,Wen Yu,Muhammad Luqman,Sadia Hassan,Muhammad Ameen, (2016) Factors Inhabiting ICTs usage among Farmers: Comparative Analysis from Pakistan and China. Open Journal of Social Sciences,04,287-294. doi: 10.4236/jss.2016.45031
References
- 1. Arfan, M., Ali S., Safdar, U. and Khan M.A.J. (2015) Study of Association between Demographic Characteristics and Increase in Knowledge of Farmers through Punjab Agricultural Helpline. Journal of Agricultural Research, 53, 287-294.
- 2. Atibioke, O.A., Ogunlade, I., Abiodun, A.A., Ogundele, B.A., Omodara, M.A. and Ade A.R. (2012) Effects of farmers’ Demographic Factors on the Adoption of Grain Storage Technologies Developed by Nigerian Stored Products Research Institute (NSPRI): A Case Study of Selected villages in Ilorin West LGA of Kwara State. Research on Humanities and Social Sciences, 2, 56-63.
- 3. Azilah, M.A., Foziah, J. and Ho, C.S. (2015) The Effects of Socio-Economic Influences on Households Recycling Behaviour in Iskandar Malaysia. ASEAN-Turkey ASLI (Annual Serial Landmark International) Conference on Quality of Life 2014, ABRA International Conference on Quality of Life, AQoL2014, 26-28 December 2014, Istanbul, Turkey. Procedia - Social and Behavioral Sciences, 202, 124-134.
- 4. Burton, R.J.F. (2014) The Influence of Farmer Demographic Characteristics on Environmental Behavior: A Review. Journal of Environmental Management, 135, 19-26. http://dx.doi.org/10.1016/j.jenvman.2013.12.005
- 5. CIA-Central Intelligence Agency (2016) the World Fact Book: South Asia, Pakistan. https://www.cia.gov/library/publications/the-world-factbook/geos/pk.html
- 6. Gao, J., Barbieri, C. and Valdivia, C. (2014) a Socio-Demographic Examination of the Perceived Benefits of Agroforestry. Agroforestry Systems, 88, 301-309. http://dx.doi.org/10.1007/s10457-014-9683-8
- 7. Government of the Pakistan (2015) Economics Survey 2014-15, Ministry of Finance and Economic Affairs, Government of Pakistan, Islamabad Pakistan.
- 8. Government of the Punjab (2016) Budget: Agriculture Department Government of the Punjab, Pakistan. http://www.agripunjab.gov.pk/budget
- 9. Govt. of the Hebei (2015) The People’s Government of Hebei Province. http://www.hebei.gov.cn/english/10718809/10719846/10721308/index.html
- 10. Landini, F. and Bianqui, V. (2014) Socio-Demographic Profile of Different Samples of Latin American Rural Extensionists. Ciência Rural, Santa Maria, 44, 575-581. http://dx.doi.org/10.1590/S0103-84782014000300030
- 11. Philip, T.K. and Isaac, N.I. (2012) Demographic Characteristics, Agricultural and Technological Profile of Acha Farmers in Nigeria. Agricultural Engineering International: CIGR Journal, 14, 89-93.
- 12. Rochecouste, Jean-F., Dargusch, P., Cameron, D. and Smith, C. (2015) An Analysis of the Socio-Economic Factors Influencing the Adoption of Conservation Agriculture as a Climate Change Mitigation Activity in Australian Dry-Land Grain Production. Agricultural Systems, 135, 20-30. http://dx.doi.org/10.1016/j.agsy.2014.12.002
- 13. Yonazi, E., Kelly, T., Halewood, N. and Blackman, C. (2012) eTransform Africa: The Transformational use of ICTs in Africa.
- 14. Zhang, Y., Wang, L. and Duan, Y. (2016) Agri-cultural Information Dissemination Using ICTs: A Review and Analysis of Information Dissemination Models in China. Information Processing in Agriculture, 3, 17-29. http://dx.doi.org/10.1016/j.inpa.2015.11.002
NOTES
*Corresponding author.