Livestock Research for Rural Development 27 (9) 2015 Guide for preparation of papers LRRD Newsletter

Citation of this paper

The role of social capital in technology adoption and livestock development

Barnabas Ntume, Agnes Sarah Nalule1 and Sylvia Angubua Baluka2

Department of Production, Hoima District Local Government P. O. Box 2, Hoima, Uganda
1 Department of Livestock and Industrial Resources, School of Veterinary Medicine and Animal Resources, Makerere University, P.O. Box 7062, Kampala, Uganda
2 Department of Biosecurity, Ecosystems and Public Health, Makerere University; P.O. Box 7062, Kampala
sbaluka3@gmail.com

Abstract

A cross sectional study was conducted to establish the role of social capital in livestock development. Both qualitative and quantitative methods were used to collect data. Using a structured questionnaire, data was collected from 107 livestock farmers from five sub counties purposively selected based on a high livestock population. Qualitatively, five focus group discussions and key informant interviews with livestock development stakeholders were conducted.

Results indicated eleven social groups (networks) and the major ones were faith groups, groups linking social networks to institutions, farmer groups, and family groups. These social groups and networks contributed to acquisition of knowledge (40%), skills (32.2%) and technologies (17.1%%) for livestock development, influenced choice of livestock enterprises (75.7%), determined access to labor (76.6%), influenced work (50%) and enhanced access and utilization of financial services (87%,). The study has shown that a network of friends, relatives and neighbours influenced labour productivity (52.7%), time to start and leave work (32.1%), gender roles or division of labour (12.9%) and time spent on leisure (4.3%). However the influence on labor productivity was more pronounced among people of the same religion (P=0.04) and ethnicity (P = 0.00). The networks influenced farmers mainly as role models (44.2%), decision on income generating activities (32.6%) and source of seed stock (16.3%). Level of education determined the number of extension advisors on a livestock enterprise (P=0.02). Similarly, the more a farmer diversified livestock enterprises the more he/she engaged extension workers in providing trainings and or advisory services resulting in significant adoption of livestock technologies (P=0.00). The most adopted technologies were; disease control (30.6%), breeding (25.9%) and tick control (22.1%). The major extension approaches were farmer group (53.9%) and farm visit (25.1%). Mobile phones enhanced social networks and dissemination of livestock related information (97.2%). Social networks were enhanced through regular meetings of network members, exchange visits and rearing animals together. The study established that social capital plays a key role in livestock development,technology adoption, dissemination and participation in extension activities.

Key words: adoption, networks, socialization, technology


Introduction

The role of social capital in development cannot be overemphasized; it contributes to increased productivity, facilitates coordination, and gives identity and common purpose (Ahlerup et al 2009; Zak and Knack 2001; Narayan and Pritchet 1997; Putman 1995). Social capital refers to all relationships between people such as family, friends, colleagues, communities, groups, culture, ethnicity, associations, institutions, and the norms that shape their interactions (Narayan and Cassidy 2001; Coleman 1988). These relationships are anchored upon bonds of trust, obligation, mutual understanding and shared values which play a vital role in developing and supporting livelihoods of individuals (Bowles and Gintis 2002; Woolcock and Narayan 2000).

Social capital is one of the five types of capital namely financial, natural, physical, human and social capital (Goodwin 2003). Recognizing, building and maintaining these five forms of capital enhances sustainability of economic development. But social capital has a special role of mobilizing and coordinating other forms of capital (Megyesi et al 2010). Social capital facilitates behavioral and attitudinal change, access to new information, markets, credit and skills (Carroll and Rosson 2008, Phulari et al 2010).The variation in social capital between communities explains the differences in their economic development (Lyon 2000, Goodwin 2003). Social capital promotes livestock development through information exchange, skills transfer, exchange of livestock gifts or loans and promoting technology uptake. Livestock development technologies include improved livestock waste management, pasture establishment and management, pasture preservation (hay and silage making), tick control, breeding and improved breed selection, disease prevention and control (Ministry of Agriculture Food Processing Industries (MAFPI), 2013).

At global level, internet-based web technologies (social media) have emerged and are playing a vital role in social lives of people. They have made individuals more connected than before. Individuals enjoy using these social media such as Twitter, Face book, LinkedIn, and they are also empowered through the exchange of ideas. Users enjoy benefits resulting from extensive communication, self-expression, information and knowledge sharing, and enhanced collaboration (Ye et al 2012). The information shared includes health, livestock care and management, reporting on disasters and also enhances communication between business customers (Palen et al 2009; Chou et al 2009; Kane et al 2009).

Despite the government and donor investment in Agriculture, Uganda’s livestock productivity has remained low probably due to failure to recognize the contribution of social capital in livestock development. Although, agriculture remains the mainstay for the majority of Ugandans, agricultural sector in general has continued to register very slow growth in the recent past. Between 2000 and 2010, agricultural sector growth has been generally slow and 13% for the manufacturing and services sectors respectively (Ministry of Finance, Planning and Economic Development (MFPED 2008; Naluwairo 2011), and the livestock sector did not meet the projected national contribution towards improving livelihoods, human nutrition and food security (FAO 2010).

Although several studies have assessed the cause of poor livestock productivity in Uganda and elsewhere, no research has been conducted to analyze the role of social capital in livestock development. There is need to understand the role and contribution of social capital in the delivery of livestock extension services in order to increase adoption of livestock development technologies towards improved productivity and sustainable rural livelihoods in an agricultural based economy like Uganda.


Materials and methods

Study area

A cross sectional study was conducted in Hoima district, Uganda between June and September, 2014. Hoima district is located at 01 24N, 31 18E. The district experiences a bimodal climate and is inhabited by crop farmers and agro-pastoralists with a large part under game reserve. According to Uganda’s most recent livestock census, Hoima had an estimated 110,660 heads of local cattle; 5,740 head of exotic cattle; 187,128 goats; 25,590 sheep; 104,670 pigs; 942,840 local chickens and 107,590 improved chickens (MAAIF and UBOS 2009) kept under different management systems. Crop agriculture and livestock rearing are the main sources of income in Hoima District and about 90% of the population depend on subsistence agriculture (MAAIF and UBOS, 2009). Banyoro are the predominant ethnic group in the district. The study was conducted in five sub counties: Kitoba and Kyabigambire sub Counties in Bugahya County; Kiziranfumbi and Buhimba in Buhaguzi County and Busisi division in Hoima municipality that were purposively selected based on the criterion of having a high livestock population.

Sample selection and sampling technique

Qualitative and quantitative techniques were employed to collect data. Qualitatively, five Focus group (15-20 members per group) discussions from the randomly selected farmer groups in each of the five sub counties following listing of livestock farmer groups were conducted. The selected farmer groups; leadership identified the members for participation in the discussion. The members of the selected livestock farmer groups identified key informants during the discussion and consequently they led the researcher to the key informants for interviews. FGDs were conducted following an interview schedule. A standard structured questionnaire was self-administered to a total of 107 livestock farmers who were randomly selected from five of the study sub-counties to collect quantitative data. Using the livestock farmers list obtained from the district veterinary office, the respondents were randomly selected using lottery sampling technique.

Data analysis

Qualitative data was transcribed from recordings of interviews and FGDs. This data was then analyzed according to the major themes. Quantitative data were collated and thereafter entered into a spread sheet for SPSS 16 computer programme and analyzed to give descriptive statistics. Chi square and t-tests were run to determine significant relationships.


Results

Social demographic characteristics of livestock farmers

The socio demographic characteristics i.e. gender, age, level of education, Religious affiliation and source of livelihoods of the respondents were as shown in Table 1.

Table 1. Socio demographic characteristics of livestock farmers in study areas

Respondent's Variable

Variable options, N=107

Percent (%)

Gender of respondent

Male

66.4


Female

33.6

Age of respondents (years)

18-30

11.2


31.50

55.1


51-70

31.8


>70

1.9

Marital status of respondent

Married

76.6


Single

20.6


Divorced

0.9


Widow

1.9

Highest level of Education

None

13.1


Primary

43.9


Secondary

35.5


Certificate

4.7


Diploma

2.8

Religious affiliation

Catholic

32.7


Protestant

49.7


Born Again

6.5


Moslem

7.5


Seventh Day Adventist

1.9


Others

1.9

Major source of livelihoods

Crop production

44.7


Livestock

35.3


Trading

14


Formal employment

2.3


Casual employment

1.9

Ethnic group

Banyoro

81.3


Bakiga

14


Banyarwanda

0.9


Baganda

0.9


Others

2.8

Household land acreage owned

<1 acre

1.9


1-3 acres

23.4


3-6 acres

32.7


> 6 acres

42.1

Livestock and Poultry kept

Chicken

36.1


Apiary

0.4


Piggery

22.7


Goats

16.7


Cattle

24

Type of labour

Family

19


Hired labour

3.3


Family and hired human labour

56.9


Mechanized

14.4


Oxen traction

5.9


Group labor

0.7

Source of livestock kept

Bought with personal savings

69


NAADS

11.7


Gift

4.1


Donation

14.5


Others

0.7

Networks existing among livestock farmers

Farmers belonged to different social networks with majority belonging to faith groups, farmers groups, family groups, clans, ethnic groups, community burial groups and informal savings groups (Table 2).

Table 2. The social groups and networks in which farmers belong

Social Networks

Frequency
(N=107)

Percent
response

Faith group (Catholic, Protestant, Moslem)

107

100.0

Linking social networks to institutions

97

90.7

Farmers group

96

89.7

Family group

95

88.8

Others (Clan, Ethnic, Community burial & informal saving groups)

91

85.0

Associations

16

15.0

Saving and Credit Cooperatives (SACCO)

13

12.1

Women group

4

3.7

Political Parties

2

1.9

Role of social capital networks in livestock development

Linking social capital networks between farmers and institutions such as non-governmental organizations (NGOs) and government was high (96%). The extension worker played a major role in linking farmers in social networks to development institutions that enabled the farmers to access technical support and resources for their livestock development. Religion played a significant role (P=0.02) in facilitating and enhancing linkages of farmers; social capital networks with institutions. There was overwhelming (98.1%) consent that social capital and networks could develop livestock enterprises and a large proportion (94%) of the respondents who belonged to groups had significant (P=0.00) benefits acquired through group participation.

Social networks and adoption of livestock development technologies by farmers

The study established that majority (75.7%) of the respondents were influenced into adopting livestock rearing and management practices by social networks of friends, relatives and neighbors compared to 24.3% who just followed their inherent initiatives. The networks influenced farmers in different ways; serving as role models (44.2%), donating livestock seed stock and land (16.3%) and guiding choice of income generating activities or enterprises to take on (32.6%) while 7.0% were influenced in other unspecified aspects.

Source of advice on starting a livestock enterprise

Social networks played a big role in selecting the livestock enterprise to undertake. These social networks included farmers to veterinary extension workers (31.9), family members (28%), friends (21.1%), group members (13.8%), politicians (1.7%), neighboring farmer groups (1.3%), while 2.2% were influenced by other undefined factors. Educated farmers had more advisors on the type of enterprise to take on (P=0.02) than the semi illiterate farmers. Similarly, farmers belonging to farmer groups irrespective of level of education had more (P= 0.02) number of advisors. Half of the respondents believed that friends, relatives or neighbors influenced the labor availability.

Social networks and labor productivity

The average working hours per day ranged from 1 hour to 12 hours with majority working between 6-9hours a day (Table 3). However, there seemed to be various social norms and interactions that influenced hours worked per day although fewer respondents (22.6%) acknowledged that they had social norms towards work which included: work norms on time when to go to work (25%), leave work (7.1%) and when to go for leisure (7.1%). While 60.7% of respondents had norms regarding work allocation among family members. Social norms are written or unwritten rules of behaviour within a social group. Furthermore, results indicated that a network of friends, relatives and neighbours influenced labour productivity per day (52.7%), time to start and leave work (32.1%), gender roles or division of labour (12.9%) and time spent on leisure (4.3%). However the influence on labor productivity was more pronounced among people of the same religion (P=0.04) and ethnicity (P = 0.00).

Table 3. Range of working hours per day of respondents

Working hours

Frequency

Percent

1-3hrs

2

1.9

3-6hrs

45

42.1

6-9hrs

48

44.9

9-12hrs

12

11.2

Total

107

100

Access to and source of information about microfinance support

About 60.4% of the respondents had accessed loans for livestock development from the banks and micro finance institutions compared to 39.6% who had not accessed any loans.. However age seemed to play a role in enabling farmers access bank loans (p = 0.03). The older the farmer the easier it was to access the loans. Additionally, social capital networks including having association with farmer group members, family member, Church or fellowship members, neighboring farmer group members already linked to banks or microfinance institutions, and development agencies; staff members played a key role in helping farmers to access bank loans (Figure 1).

There were several institutions operating in the study area that offered loan services. About 31.3% of the respondents obtained financial services from Savings and Credit Cooperatives (SACCOs) and Micro Finance Institutions (MFIs) such as Hoima, Fort Portal and Kasese Micro Finance (HOFOKAM) and Pride (24.1%). Others obtained loans from Centenary Bank (13.3%), Stanbic (4.8%) and DFCU bank (1.2%).

Figure 1. Farmers’ linking social capital networks to loaning institutions
Social capital Networks and Livestock technology uptake

The study revealed that social capital networks contributed to technology uptake. Farmers acknowledged that linking social networks through government and NGOs, helped them to acquire knowledge in livestock husbandry (45.6%), livestock development skills (34.5%), adoption of livestock development technologies (19.5%) and other benefits (0.4%). Linking social networks between farmers and institutions was directly related to the frequency of engagements between farmers and extension workers. Farmers engaged extension workers at different rates within a 12 months period ranging from none to more than six times (Table 4).

Table 4. Farmersí frequency engaging extension workers

Number of times engaged

Percent response

None

8.8

1-3 times

40.2

4-6 times

23.5

> 6 times

27.5

Farmers who had more contacts and engagements with extension workers also had good relationships with extension workers and seemed to receive more benefits from extension workers. There was a significant relationship (P=0.00) between the number of times farmers engaged extension workers and the number of times livestock extension workers gave advice in the last 12 months. Farmers who engaged extension workers more times had received more trainings and or advice and had adopted more livestock technologies (P=0.00).

Institutional actors supporting livestock development technologies

A number of institutions supported livestock development technologies through extension services and/or provision of farm inputs and seed stocks through social network linkages. The government of Uganda through the ministry of agriculture and Animal industry and fisheries (MAAIF) and the national agricultural advisory services (NAADS) program was the major extension service provider. Other key institutional actors included Africa 2000 Network, Hoima Caritas Development Organization (HOCADEO), and Heifer project international (HPI) as sown in Figure 2.

Figure 2. Institutional actors in livestock development through social networks linkages

The major extension approaches included group approach, farm visits, farm based demonstrations, and field days (Figure 3).

Figure 3. Different extension approaches used by Gov’t and NGOs

The more farmers engaged extension workers the more they collaborated (P=0.02) with development agencies promoting livestock development in the area. Farmers who belonged to farmers; groups also had moderate collaborations (P=0.05) with development agencies than farmers wo did not belong to farmers; groups.

Livestock development technology adoption

The technologies most frequently adopted from extension services providers by farmers included disease prevention and control, improved livestock breeding , tick control, pasture management and preservation and animal waste management technologies (Figure 4).

Figure 4. Livestock development technology adoption level by farmers based on advice and trainings by extension workers.
Ways social groups used to increase adoption of extension workers’ advice by farmers

The adoption rate was higher among farmers that belonged to farmers’ groups. Male farmers adopted more advice from extension workers than females. It was also evident that adoption level was higher among educated farmers than semi illiterate farmers. Similarly, farmers with diversified livestock enterprises implemented more technologies than those with single or fewer livestock enterprises. Adoption of technologies was linked to social groups and networks among the farmers that played significant roles in mobilization and information sharing. Farmers laid strategies and guidelines to enhance technology adoption and dissemination including: promoting farmer to farmer information sharing (60.8%), promoting exchange visits (30.7%), setting norms on how to improve their livestock (0.7%) and promoting collective livestock treatment (7.8%). Farmers who belonged to groups and also collaborated with other groups significantly (P = 0.01) developedtheir livestock enterprises).

Benefits of belonging to social networks

Belonging to farmer groups and other social networks helped famers to adopt certain technologies, acquire knowledge and skills in livestock management and development. About 40% of the respondents had acquired knowledge in livestock management from their groups, 32.2% had acquired skills in livestock management while 17.1% had acquired livestock development technologies, assets (0.8%), were able to control animal diseases together (3.7%), and 0.4% were grazing animals together (Figure 5). Farmers that belonged to social groups received significant benefits (p = 0.00) from social networks and institutions. Farmers’ social bonding through social networks and linkages with their collaborating institutions played significant roles (p = 0.01) in determining whether farmers benefit from livestock development.

Figure 5. Benefits of participation in social networks.
Benefits of farmer’s affiliation to farmer groups

The study showed that individual farmers benefited from livestock development technologies through their social networks. The livestock development technologies acquired by farmers from their groups included improved livestock breeds (68.5%), equipment (17.4%) and drugs (6.5%).

Many respondents (44.9%) said that affiliation to farmer groups enabled them to; receive trainings, breeding stock (26.8%), access loans (9.1%), treat animals together (7.1%), access drugs for livestock treatment (5.1%), and 6.1% were inspired to acquire livestock (Figure 6).

Figure 6. Livestock development support obtained from affiliation to farmer groups
Mode of linking with networks

Mobile phones were the most common tool used for socialization, enhancing relationships and disseminating livestock related information and majority of respondents (96.3%) owned mobile phones. However, there was gender disparity in mobile phone ownership and the difference between the gender of respondents and the number of ways the mobile phone had helped them in the development of livestock enterprises was significant (P=0.01). Males seemed to benefit more from mobile phone usage for livestock development than women.

Respondents reported that mobile phones were used in contacting or consulting veterinary extension workers on livestock management (64.8%), sharing experiences with fellow farmers (23.7%), and for conducting livestock business transactions or marketing their livestock (8.7%). Phones enhanced farmer to farmer and farmer to extension worker relationships. A farmer’s possession of a mobile phone influenced development of his or her livestock enterprise and engagement with livestock extension workers (P=0.01). Internet was the least (4.7%) used mode of information dissemination by respondents.


Discussion

Social capital and social networks facilitated development of livestock enterprises. Previous studies by Phulari et al (2010), Carroll and Rosson (2008), Preece and Krichmar (2002) stated that social capital brings about livestock development through pooling of resources such as useful information, employment opportunities, relationships and development skills by members of the network. People within the same social network greatly influenced decisions and activities of one another and generally shared the benefits acquired through group participation. Dasgupta (2002) describes social capital at individual level as a system of interpersonal networks which enhances entrepreneurship skills, cooperation, collaboration and coordination. Mancini et al (2007) stated that collective action was important in uptake of technologies. Narayan and Pritchet (1997) emphasized that increasing linkages between individuals within the social network improved information flow for livestock development. Social networks provide a platform for members to exert influence on other individuals. For instance; if A has a tie with B and B with C, A may be able to exert influence not only on B but also on C Burt (2001).

The traditional extension system in Uganda premises that extension workers play a leading role in providing advisory services to farmers there by influencing farmers’ decisions on livestock enterprises related activities. This study has revealed that social capital and social networks played a bigger role in advising and influencing people towards engaging in a livestock enterprise (Figure 3). Farmers who had attained higher levels of education had access to more advisors regarding the type of enterprise to take on. This was possibly because education enhances social capital (Imandoust 2011). Similarly, farmers who belonged to groups had a significant number of advisors regarding livestock enterprise selection. This was because farmers influenced one another greatly through social networks (Burt 2001) and influencing mind set change within the social networks influences development.

This study revealed that social capital networks influenced the rate of labor productivity of members. Social networks of friends, relatives or neighbours influenced work of people of the same religion and ethnicity significantly. This was consistent with the findings of Aldridge et al (2002) who stated that sometimes social networks do not yield beneficial results but rather negative results. The strong bonds exhibited by some social networks may not be used for economic reasons; as was reported by respondents during FGDs concerning some youth groups within the study area who spent most of their time watching films, sports bating and taking marijuana. In some farmers groups, social networks enabled them to work for longer hours and promoted sharing of responsibility.

Although networks influenced the rate of work per day, this study revealed that a few farmers had norms towards work. Norms may be spoken or unspoken but they are important in sanctioning and regulating behaviour within the social networks by probably acting as standard operating procedures. Narayan and Cassidy (2001); Coleman 1988) stated that norms shape interactions of social capital networks there by facilitating development. Absence of norms towards work within a community means there are no acceptable standards regulating work ethics and leaves farmers with little or no motivation and focus towards work. If all farmers had social norms towards work, they would serve as enablers to work because of the social pressures and expectations from their groups or communities. in the current study area, social norms towards work could be utilized to sanction activities, motives and behaviour of the network members towards improved livestock management.

Credit was important for livestock enterprise development and older people had more access to loans than young ones probably because relationships and assets that are required as collateral or security by banks to access loans accumulate with age. Modernization of agriculture is only possible when farmers can access agricultural credit facilities (Kouser et al 2009).

The current study has demonstrated how social capital plays a role of linking farmers to financial credit facilities or banks which is a prerequisite for agricultural modernization and rural development. Social capital played a pivotal role in linking farmers to banks (Figure 1). Guiso et al (2004) in the study carried out in Italy; found that the level of social capital was positively related to financial development. People with more social capital had higher investment in stock markets and had more access to formal financial institutions (Guiso et al 2004; Sabatin 2006). Similarly Hong et al. (2004) found that in the United States people who knew their neighbors had higher stock market participation rates. This was possibly because they were easy to access as they are located in rural areas near farmers and used social ties of farmers as security for the loans rather than the asset collaterals that are required by commercial banks that tend to exclude the rural poor.

The current study found that the largest number of farmers was linked to banks by their different networks including: farmer group members, family members, neighboring farmer groups and church members. Social capital and networks were more important in connecting farmers to the banks than bank staff. In some banks such as Centenary and HOFOKAM (Microfinance department), social capital and social capital networks in form of farmer groups were aiding farmers to access loans, disseminate information about bank services to farmers besides providing collateral. Because members within the same social network tend to influence each other, more members were drawn to the bank hence increasing uptake of bank loans for livestock development. However farmers mainly picked loans from SACCOs and MFIs probably due to ease of access since these financial institutions are located in rural closer to farmers and used social ties of farmers as security for the loans rather than the asset collaterals that are required by commercial banks that tend to exclude the rural poor.

Linking social capital networks contributed to the acquisition of knowledge, skills and technologies in livestock development. According to Swamson and Rajalahti (2010), knowledge, skills and technology acquisition are the main purpose of extension. Knowledge in livestock management including disease management, tick control and management, farm planning, breeding and selection, and pasture management were acquired by farmers. Various technologies were acquired mainly through the NAADS programme which gave improved breeds, drugs and equipment to farmers.

Education and religion played a significant role towards improving relationships and seeking for extension information. This could be attributed to the confidence gained with education that farmers are able to approach and engage with service providers. Farmers with higher level of education adopted more advice from extension workers. Education exposes and improves one’s access to networks, and gives confidence to make contacts with extension workers (Glaeser et al 2002). The less educated farmers seemed less privileged in seeking for extension services due to lack of self esteem, stigma and failure to express themselves since education affects the quality and quantity of social capital (Imandoust 2011). Farmers who engaged extension workers more often received more trainings and advice from extension workers and were more likely to adopt livestock development technologies. This was because engagements improved the social bonding, commitment, knowledge, confidence and farmers’ trust in extension workers.

The farmers who engaged extension workers more often and belonged to groups had collaborated with a number of development agencies promoting livestock development. This could be attributed to having more access to key information through their groups as observed by Aldridge et al (2002), and development of self efficacy and trust in these institutions (Scheffler et al 2007). The higher adoption among males than females could be attributed to their free mobility, ownership rights and control over key household assets such as land.

Farmer to farmer relationships, farmers’ groups and availability of extension workers increased farmers’ adoption of livestock development technologies. Social groups and networks also played a significant role in enabling technology adoption, knowledge and skills transfer. Excluding social networks in development approaches leads to low yields in livestock development since technology development and dissemination require a system that involves social spheres (Leeuwis and Ban 2004, Knickel et al 2009). The high adoption of disease prevention and control measures and improved breeding techniques could be attributed to the devastating effects of the diseases when they occur and the need for higher productivity associated with improved breeds that enable farmers to achieve their objective of profit maximization.

Mobile phones played a major role in socialization of farmers probably due to their handiness and easy to use even by the illiterate farmers. Men seemed to benefit more from mobile phone use for livestock development than women probably because men are more versatile than women. Oluka et al (2005) attributed men’s phone ownership to owning of most livestock in the household. Phones are ideal tools for disseminating livestock related information and also aid in technology acquisition. Inspite of livestock farmers being sparsely located and extension workers being few, they are connected to each other at any time using mobile phones. The farmers could also access packaged information on livestock via the mobile phone. Wajcman et al (2007) described mobile phones as an important tool for fulfilling information needs. Despite high coverage of mobile phone usage, there was low internet usage in extension which could be attributed to the low education levels. Quan-Haase et al (2002) noted that internet helps to increase the existing patterns of social contact and civic involvement. However, Wellman (2001) believes that internet usage can improve inter-personal transformation from door-to-door to place-to-place and individualized person-to-person networks.


Conclusions


Acknowledgement

The Authors are grateful to Hoima District Local government for providing the good working environment for the research. They are also grateful to the respondents in the sub Counties of Kitoba, Kyabigambire, Kiziranfumbi, Buhimba and Busiisi Division for their time and information they provided which made the research a success. The authors also appreciate all staff in Department of production, Hoima District Local Government who served as research assistants that administered the questionnaires for data collection and during the Focus group discussions and data entry.


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Received 10 July 2015; Accepted 6 August 2015; Published 1 September 2015

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