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

Citation of this paper

Increasing the efficiency of the dairy value chain in Uganda: Determinants of choice of milk marketing channels by dairy farmers in Kiruhura District, Uganda

A Nkwasibwe, J Mugisha, G Elepu and J B Kaneene1

Department of Agribusiness and Natural Resource Economics, Makerere University, PO B0X 7062, Kampala, Uganda
anthonynkwasibwe@gmail.com
1 Center for Comparative Epidemiology, Michigan State University, 736 Wilson Road Room A109, East Lansing, MI 48824-1314

Abstract

Since the 1990s, the Ugandan dairy sector has been experiencing continuous growth. However, the sector has remained largely informal in terms of milk marketing. Due to this, government through Dairy Development Authority (DDA) and other stakeholders such as the AgShare project have been carrying out several activities such as farmers’ and traders’ trainings on quality and quantity of milk production, handling, and marketing. Emphasis has been on promotion of formal milk marketing from farm gate to final consumers. Therefore, the purpose of this study was to determine factors influencing farmers’ choices and the total proportions of milk sold to the formal milk marketing channel by dairy farmers. This study was conducted in Kiruhura district as part of the AgShare project that was implemented by Makerere University in Uganda. With the assistance of district production and veterinary officers, and village chairpersons, 240 farmers were randomly selected to participate in the study.

Probit and censored Tobit regression model results revealed the most significant determinants of formal marketing choice and the total milk proportions sold to formal channel were (respectively) household size, total volume of milk produced, payment period, source of market information, milk selling price and distance to the milk collection centers. The study recommended public investment in infrastructure such as roads and rural electrification to ease establishment of milk coolers nearer to dairy farmers to participate in the formal channel. On the side of the farmers, formation of more dairy cooperatives for collective marketing supplemented by quality and quantity milk production and handling tailored extension and training activities should be intensified by government and other dairy development partners.

Key words: agribusiness, cattle, dairy economics, milk production


Introduction

Dairying is one of the investment areas in the livestock sector that farmers can venture into to improve their standards of living (ILRI 2007). In Uganda, the dairy sub-sector contributes about 50% of total output from the livestock sector, 20% of the food processing industry, and 4.3% of the national Gross Domestic Product (National Development Plan 2010), thus, the dairy sub-sector acts as a source of food, income, and employment (Ndambi et al 2006). The national cattle population in Uganda has experienced steady growth with about 34% being dairy cattle, giving a 9% milk production growth rate per annum and total national milk output of 14,000 million liters (Wozemba and Nsanja 2008). This growth rate has been attributed to the favourable macroeconomic policy environment and institutional reforms including the privatization of the dairy sub-sector (National Development Plan 2010), increased demand for milk by both consumers and milk processing plants, better herd management, adoption of improved breeds, and improved animal health and support services (UBOS 2008; Mbowa et al 2012).

Milk in Uganda is marketed through formal and informal channels (Staal et al 2003; Ngigi 2005; EADD 2008a; Wozemba and Nsanja 2008b; DDA 2010; Mbowa et al 2012). The formal milk marketing channel that handles only about 20% of the total national milk marketed operates an organized system of milk collection using well established bulking centres with coolers and transport infrastructure (milk tanks). On the other hand, the informal milk marketing channel that controls about 80% of the total milk marketed is characterized by lack of milk collection infrastructure and facilities for pasteurization and hygienic handling of milk, limited quality and safety control, and adulteration of milk with water and other chemicals (Elepu 2006). Due to many players involved in milk trade, the DDA, a dairy sector regulatory body in Uganda has found it difficult to enforce good milk marketing practices (Mbowa et al 2012). This has exposed farmers to low milk prices, yet downstream retail prices are high (MFPED 2012), as well as offering of substandard-quality milk products to consumers (Anjani and Steven 2010). Henriksen (2009) noted that the best motivation for farmers to diversify and invest in dairying is the presence of safe and profitable market outlets. This justifies the need for efficient milk marketing channels in Uganda that are easily regulated and monitored.

For the Ugandan dairy sector to deliver quality-driven market products and exploit value addition benefits, strategies such as offering of input to farmers at subsidized prices, implementing farm trainings on quality production and handling, and licensing of all raw milk traders that meet DDA regulations have been put in place (DDA 2010; Mbowa et al 2012). In addition, the government of Uganda, through other development partners such as Heifer International, TechnoServe, and DANIDA, has initiated grants to support small-scale processors, institutional capacity building on value addition, and support to foreign agro food processors (National Development Plan NDP 2010). All these favorable production, processing, and marketing conditions are meant to promote an efficient dairy chain of which marketing plays a big role. For farmers, who are primary actors in the chain, to benefit several reforms at milk marketing level have been implemented, including training farmers and traders on quality milk handling, facilitating the formation of dairy farmers’ marketing cooperatives, and registering all traders. All these favorable production, processing, and marketing conditions are meant to promote an efficient dairy chain of which formal marketing plays a big role.

Despite these reforms and trainings, the extent to which farmers are choosing between formal and informal milk marketing, as well as, the volume of milk sold to formal milk marketing channels at the farm level, is not empirically known. Previous research in the Ugandan dairy industry has focused on marketing of processed milk (Mbowa et al 2012), dairy productivity (Musinguzi 2002), competitiveness of milk processing firms (Twimukye 2003), and intensification of dairy farming (Baltenweck et al 2007). There is a need to fill the knowledge gap exiting on milk marketing channels’ activities, channel choices and milk sales proportion from determinates. This will help farmers to evaluate and choose the most beneficial marketing channel under the current high demand of dairy products as well as policy-makers and other stakeholders to best address challenges farmers are facing in different marketing channels through institutional and policy reforms. Therefore, this study considered the farmers’ choice of formal and informal milk marketing channels by looking at proportions of milk sold to different marketing channels at farm gate. Specifically, the study characterized dairy farmers participating in different milk marketing channels, determined factors that influence the farmers’ choice of marketing channels and those influencing the proportions of total milk sold by famers to the formal channel. The study was guided by the hypotheses that: A) compared formal to informal channel participants, the majority of farmers who participated in the formal marketing channel belonged to a dairy marketing organization, and B) the volume of milk produced positively influences the likelihood of farmers to participate in the formal milk marketing channel.

Literature Review

The earliest formal conceptions of marketing channels focus on the functions performed by a distribution system and the associated utility of these functions with the overall system (Gundlack et al 2006). Reflecting their presence in industrial and transitional economies, marketing channels gradually came to be viewed as the set of interdependent organizations involved in the process of making a product or service available for use or consumption (Coughlin et al 2001). In agricultural context, the marketing channel is defined depending on the specific organizations that are interdependent and interrelated with agricultural products along with the relevant services that can be transferred from producers to consumers or sellers (Chun-Mei 2011). This institution oriented perspective draws attention to the channel actors (for example, wholesalers, distributors, and retailers) that comprise the distribution system and engage in the delivery of goods and services from the point of conception to the point of consumption (Anderson and Coughlan 2002).

Farmers have many marketing alternatives, such as delivery (sales), storage or time, product form, and pricing (Falkowski et al 2008). The choices made within any of these categories affect prices and incomes. For agricultural products to reach the consumers in different forms--such as raw farm products, processed products, branded products, and specialty (niche) products marketing agents (individual sellers and cooperatives), marketing agreements and bargaining association should exist (Chun-Mei 2011). Agricultural markets offer different forms of products to different customers, and this justifies the different delivery alternatives, including commission houses or brokers, auction houses, terminal markets, farmers’ markets, roadside sales, and international markets (Kohl and Uhl 2002). Producers and consumers are linked together by different marketing channels, which coexist for efficient functioning of the market. These marketing channels are structured differently depending on the members, the form of the product handled, and the pattern relationship among other organizations (Coughlan et al 2001).

Milk, like any other agricultural product, reaches the consumer through various marketing channels. It is sold through itinerant traders (hawkers, neighbors, and restaurants), dairy cooperatives and milk processing factories, national dairies and street vendors (Artukoglu and Olgun 2008; Tsougiannis et al 2008). Further, Falkowsk et al (2008) noted that milk producers deliver milk to dairy processors through two channels: direct collection from the cooling tank at the farm (modern marketing channel) and milk delivery to a collection station operated by a dairy company (traditional marketing channel).

Rajiv (2010) generally classified marketing channels as formal and informal. Massen (2008) defined the informal marketing channel as a marketing system that is unregulated by the government, state, or regulatory authority. It is a market where there are no stationary physical locations outside of the home where the business owners or workers operate their businesses. Omore et al(2004) noted that “informal market” in the dairy sector refers to traders at variance with widely accepted international norms that would emphasize cold-chain organization and pasteurization of marketed milk prior to sale. In addition, Nyakerario (2007) looked at informal markets as those that embrace unofficial transactions between farmers and traders and consumers. Venkatesh (2006) further classified informal marketing channels into two types; licit and illicit informal channels. Within licit informal marketing channels, channel activities would not be illegal if taxes were paid and regulations were followed. Illicit informal markets are markets that produce goods and services that are illegal, therefore, taxes are not collected on income or sales from illicit activities and markets are not regulated by the government or other agencies.

Many scholars such as McCrohan and Sugrue (2001), Ferreira-Tiryaki (2008) and Kulshreshtha (2011) have looked at the informal market as being characterized by low levels of organization, lack of taxation, lack of regulation, lack of legal protection for contract and property rights enforcement, violation of non-criminal law, low wages, transactions mainly conducted in cash, low productivity due to the smaller size of the market, limited access to credit and connection to activities that complement the formal economy. Kristina (2004) concluded that informal markets are traditional supply chains that cannot be taxed and are not monitored by any form of government. These informal markets form black markets leading to shadow economies. On the other hand, Rajiv (2010) observed that formal markets in agriculture can be described as those governed by high quality and food safety standards, and where the activities of dairy traders are monitored (within supermarkets, export chains, and processing industries). Therefore, from the various ways in which the concept of informal and formal markets have been defined, described, and empirically used, the formal milk marketing channel from the milk producer to the next actor in the marketing chain node can be defined as a legal, regulated, monitored, and taxed mode of milk marketing system; whereas the informal is the illegal, unregulated, unmonitored, and non-taxed mode of marketing system.


Materials and methods

Study area

This study which was part of a larger interdisciplinary project (the AgShare project) funded by the Bill and Melinda Gates Foundation under the leadership of Michigan State University (MSU) focused on improving the efficiency of the dairy value chain in Kiruhura district. The study was carried out in Kiruhura district, South Western Uganda. The details of the study design have recently been published in Kaneene et al (2013). Briefly, the district was purposely selected, as it was the major supplier of milk in Uganda with the highest number of farmers depending on dairying as their economic activity (Wozemba and Nsanja 2008). The district had the majority of the dairy value chain stakeholders including dairy farmers, milk processors, milk traders, extension workers, and field veterinarians. In the district, sub-counties, parishes, and villages were randomly selected with the aid of district production, veterinary officers, and village chairpersons. A total of 240 dairy farmers who participated in the study were systematically randomly selected from 16 villages with the aid of farmers’ household lists obtained from the village chairpersons. A cross-sectional survey was carried out between August, 2011 and February, 2012 to collect primary data from the selected dairy farmers using a pre-tested structured questionnaire, available upon request. Data on the dairy farmers’ characteristics, such as sex, age, level of formal education, household size and dairy herd size, volumes of milk produced per month, monthly dairy income, total land size, and main occupation were collected. Regarding milk marketing, emphasis was put on two categories of marketing channels, formal and informal milk marketing, and data including price offered, payment period, average volumes of milk supplied by individual dairy farmers, membership to dairy marketing organizations, farmers’ non-dairy monthly income, distance to milk collection centers, sources of market information, and form of farmer payments by milk buyers was collected.

In this study, a channel was defined as formal if the milk buyers followed DDA regulations and had a trading license, traders were licensed and taxed, and their operations were regulated and monitored. On the other hand, a channel was considered informal if the buyers never followed DDA regulations, had no trading license, not taxed and their activities were not in conformity with the regulations and practices set by the Authority.

Analytic models

To determine the factors associated with a farmer’s decision to participate in the either marketing channel, a probit model was estimated. Following Cragg’s (1971) framework, the ith farmer participation decision in the marketing channel can be expressed as:

 P*i= βXii

With Xi representing a 1◊K vector of factors influencing the participation decision, β is a 1 ɛ K vector of parameter estimates, εi represents a random error term that is assumed to be normally distributed as N(0,1), P*i  represents a latent participating variable. Pi is a binary value if:

Pi = {lifP*i} > 0,  if a farmer participated in the formal chanel

Pi = {0lifP*i} 0,  if a farmer did not participated in the formal chanel

The study noted that some dairy farmers, to some extent, participated in both formal and informal market channels. For simplicity of estimating the probit model, a farmer was considered a participant in the formal channel (equal to 1) if he/she sold over 50% of produced milk to licensed milk traders and handled milk according to the DDA recommended practices. Those who sold over 50% of produced milk to non-licensed traders and never followed the recommended milk handling practices were categorized as informal market participants. 

Where:

Yi = Proportion of average milk sold (ratio of milk sold to milk produced in Interliters) a farmer delivered in the formal channel per month,

X1 = Farmer’s age,

X2 = Household size,

X3 = Farmer’s formal education (number of years in formal schooling)

X4 = Total milk volumes produced per month (iterliters),

X5 = Farmers non dairy monthly income (Uganda shillings), X6 = Distance to milk collection centers (Kilometres),

 X7 = Raw milk price per liter (Uganda shillings),

X8 = Payment period (days),

D1=Source of market information (1=Milk collection centers, 0=other sources),

βi = Coefficients to be determined, and εi = Error term.

To estimate the determinant sof milk proportions sold to formal channels at farm level, a censored Tobit model was used. This model was most suitable since it is regarded as an extension of the probit model and allows the use of the same variables from probit (Hensher et al 2005). Following Holloway et al (2004), the ith farmer derives utility from supplying a certain quantity of milk for sale to a formal channel. The objective is to maximize revenue by supplying a given quantity subjected to production constraints. According to Gujarati (2003), a censored Tobit model considers two categories: first, where the information on regressors and regressed is available, and second, where the information on only the regressors is available but not regressed.

Following Amemiya (1985), the Tobit model was censored at value YL and YU (lower and upper limit) as:

Greene (2003) specified the generalized two-tailed Tobit model as:

The censored Tobit linear model was specified as:

Where

Yi = Proportion of average milk sold (ratio of milk sold to milk produced in liters) a farmer delivered in the formal channel per month,

Yi = Independent variables for the proportions of milk sold,

X1 = Farmer’s age,

X2 = Household size,

X3 = Farmer’s formal education (number of years in formal schooling)

X4 = Total milk volumes produced per month (liters),

X5 = Farmers non dairy monthly income (Uganda shillings)

X6 = Distance to milk collection centers (Kilometers),

X7 = Raw milk price per liter (Uganda shillings),

X8 = Payment period (days),

D1 =Source of market information (1=Milk collection centers, 0=other sources),

βi = Coefficients to be determined, and εi = Error term.


Results

Socio-economic characteristics of Kiruhura dairy farmers

Results in Table 1 show that in Kiruhura district, the formal channel handled 72.11% of the total milk sold by farmers at farm gate. This is contrary to what has been reported on the Ugandan dairy sector that 80% of milk goes through informal marketing channels (Elepu 2006; Wozemba and Nsanja 2008; DDA 2010). Under formal channel, Cooperative unions purchased 38.06% and milk collection centers owned by licensed raw milk traders purchased 34.05% of total milk. The remaining 27.89% milk sales were handled by informal marketing channel (vendors handled 24.99% and restaurants 3.15%). However, some farmers sold milk in more than two market outlets depending on the price offered, volume of milk produced, and the urgency of the need for cash. This finding was attributed to the relatively high level of dairy farm commercialisation in the area with the majority of farmers producing large volumes of milk that could not be absorbed by the informal channel actors. Mbowa et al(2012) noted that the dairy farmers in South Western Uganda transformed their farms into commercial farming, and this was attributed to concentration of DDA activities in the region leaving other cattle keeping areas of Uganda unattended (World Bank 2009).

Table 1. Milk volumes handled by formal and informal market channels

Market channel & actor

Proportion of milk handled

Mean
Liters

Percent
share

Standard
deviation

Formal channels

Dairy cooperative union collection centers (processors)

3,329

38.1

3,942

License raw milk tradersí collection centers

2,761

34.1

3,667

Informal channels

Milk vendors(bicycle and motor cycle)

1,980

24.9

2,247

Restaurants

270

3.15

0.00

Dairy farmers participating in the formal marketing channel in Kiruhura district were significantly older (P ≤ 0.05) than those in the informal channel (Table 2). This could be attributed to resource endowment needed to commercialize dairy farms, a characteristic that is common with old farmers, which translates into more output (Ndinomupya 2010). It was evident that formal channel participants produced significantly (P < 0.01) more milk (monthly average of 4,111 liters per farmer), compared to informal marketing channel participants who produced about 47% less. The high milk production by formal channel participants could be because of significantly (P ≤ 0.05) larger herd size, supported by a significantly larger grazing land ownership (P ≤ 0.1) and significantly (P ≤ 0.06) higher formal education. In addition, a significantly (P ≤ 0.01) larger number of farmers in the formal channel belonged to dairy marketing organizations. The dairy marketing union provided member farmers with the necessary information on milk production and marketing, which was vital in making production and marketing decisions.

Table 2. Comparison of farmersí socio-economic characteristics in formal and informal milk marketing channels

Formal channel (n=129)

Informal channel (n=95)


Mean

Std. Dev.

Mean

Std. Dev.

t

p

Age of the farmer

49.1

12.7

45.9

12.1

1.90

0.05

Farmerís education level (years in school)

8.66

4.86

7.47

4.72

1.85

0.060

Household size

8.86

4.97

9.01

4.21

-0.23

0.81

Total land owned (ha)

131

188

80.3

91.2

2.42

0.016

Total herd size

107

173

70

43.4

1.98

0.049

Monthly milk produced (liters)

4,111

3,481

2,797

2,451

1.90

0.002

Monthly non dairy income (million UGX)

3.51

13.3

2.44

8.92

0.68

0.49

Famers whose main occupation is dairying (%)

89.5

93.0

0.906

0.343

Proportion of hired labour used in dairying (%)

98.1

89.1

0.006

0.938

Proportion of dairy farmers belonging to dairy marketing organization (%)

73.1

8.70

93.2

0.000

Reasons for not participating in the formal channel

Farmers gave various reasons for not selling milk to the formal channel. The major limiting factor was high transport costs as reported by 47% of the farmers (Table 3). High transport costs were as a result of the long distances from farms to milk collection centers, and poor infrastructure development such as slippery and/or impassible roads in the milk producing rural areas. For the milk collection centers to operate they require electricity for chilling milk, as well as, good roads for easy accessibility by milk transportation trucks with tanks, both of which were lacking in the rural areas. This explains why farmers from such rural areas sold much of their milk to the informal channel in order to reduce the risk of losing milk due to its perishable nature while transporting it over a long distance. In addition, the informal channel was not as strict on milk quality as the formal channel. This acted as an incentive for farmers whose milk would be rejected by the formal channel due to failure to meet the required quality standards. About 19% of farmers reported delayed payment as another factor limiting their participation in the formal channel. This was a problem to farmers who had no other sources of income apart from dairying to meet daily cash requirements of the farms and families. Similarly, low milk production among the informal channel participants could not motivate them to transport milk over long distances to the milk collection centers. The transport cost per unit liter of milk would be high and would erode the farmers’ profits as the price offered at the collection center was competitive irrespective of the source of milk. Other reasons for not participating in the formal channel included theft of milk by workers while transporting it to collection centers, low prices, and unfriendly treatment of farmers by milk collection center managers.

Table 3. Farmersí reasons for not participating in the formal milk marketing channel

Reason for not participating

Percent of farmers (n=95)

High transport costs due long distance

47.3

Delayed payments

18.6

Low milk production

12.4

Low price

8.5

Theft of milk and other milk utensils by transporters

7.6

Unfriendly treatment of farmers by buyers

4.7

Determinants of formal milk marketing channel choice

Various factors were hypothesized to influence a farmer’s decision to sell milk through the formal or informal channel. Among the factors investigated were farmer’s age, household size, farmer’s formal education level, volume of milk produced, raw milk price, non-dairy income, distance to milk collection centers, and source of market information (Table 4).

Results from the probit model indicated that a famer’s household size was significantly (P ≤ 0.01) and negatively related to choosing a formal marketing channel, suggesting that the increase in household size leads to reduced farmer participation in the formal channel. Large household sizes and low milk productivity were characteristics of informal channel participants in the study area. Large families are associated with a lot of domestic needs that require instant cash, which is not offered by the formal channel. This forced such farm households to ration the milk produced between the formal channel for savings purposes and more to the informal channel for daily cash to cater to family needs on a daily basis. Although it was earlier found that large households consume a lot of milk, leaving little surplus for sale (Omiti et al 2009; Anjani et al 2011), all the farmers interviewed in Kiruhura had the capacity to produce enough milk for home consumption and for sale.

Table 4. Probit model estimates of factors that influence dairy farmersí choice of formal milk marketing channel

Variable: Dependent variable (1=formal channel, 0=informal channel)

Coefficient

Standard
Error

z
Value

p
Value

Constant

-19.9

3.97

-5.02

0.000

Natural log of farmerís age

0.695

0.432

1.62

0.108

Natural log of household size

-0.460

0.176

-2.64

0.009

Natural log of farmerís education(number of years in school)

0.189

0.119

1.58

0.114

Natural log of total milk produced (liters)

0.384

0.128

3.10

0.003

Natural log of farmerís non dairy income per month (Uganda shillings)

-0.019

0.017

-1.13

0.250

Natural log of distance to milk collection centers ( kilometers)

-0.292

0.096

-3.03

0.002

Natural log of raw milk price per liter (Uganda shillings)

0.384

0.622

3.01

0.000

Natural log of payment period (days)

0.312

0.124

2.99

0.003

Source of market information (1=Milk collection center, 0=otherwise)

1.199

0.211

5.75

0.000

Further, distance to the milk collection centers was found to be negatively and significantly (P ≤ 0.01) related to farmers’ choice of the formal milk marketing channel. The longer the distance farms are away from the collection center, the less important the formal channel became to the farmers. Long distances resulted into high transportation costs, which eventually impacted negatively on farmers’ gross margins. In such situations, farmers perceived it more beneficial to sell milk to the informal channel. Omiti et al (2009) made a similar observation that long distances to markets were associated with high transportation costs. Transportation costs reduce farmers’ participation interests in such markets (Artukoglu and Olgun 2008).

As hypothesized, the volume of milk produced had a positive and significant (P ≤ 0.01) relationship with farmers’ choice of the marketing channel. Farmers that participated in the formal milk marketing channel had large herd sizes, and therefore, large milk production. As milk production increases, farmers’ willingness to participate in the formal channel also increases. This is because of the channel’s capacity to handle large volumes of milk compared to the informal channel. In addition, farmers regarded the formal channel as the most trustworthy and reliable market. Studies by Staal et al(2006) and Sherma et al (2009) found that small and resource-poor dairy farmers were mostly excluded from formal markets mainly because traditional marketing channels are usually very competitive and cost effective in linking producers and consumers, but also due to the high transaction costs involved in modern markets.

The price at which milk was sold in the current study significantly (P ≤ 0.01) influenced farmers’ choice in favor of the formal channel. Price is regarded as a reward offered by markets to suppliers in return for goods and services supplied. The formal channel offered relatively high milk prices compared to the informal channel. This acted as a motivating factor for farmers to choose such a channel in the presence of an alternative available informal channel. In addition, farmers in the formal channel enjoyed other benefits such as reliability of the market, bulk buying, stable prices, consolidated payment, and advance payments in the form of farm inputs such as milk cans and agro veterinary drugs. Artukoglu and Olgun (2008a) and Tsougiannis et al (2008b) noted that the choice of a marketing channel by dairy farmers largely depended on the price offered by that channel. Similarly, QiWen’e and Tang (2009) noted that additional unit on price would increase farmers’ propensity to participate in a specific marketing channel.

The period between milk delivery and payment to farmers also positively and significantly (P ≤ 0.01) influenced farmers’ choice for the formal channel. Farmers considered the periodic payment as a way of saving, as well as, receiving a consolidated farm income that could be helpful in future investments compared to instant cash payments in small amounts. Results show that a change from instant cash (short periods) to fortnight payment period would increase farmers’ choice of the formal marketing channel. This finding is in agreement with Staal et al(2006) who noted that households were less likely to select channels that paid cash or took milk on informal credit, and that they would prefer channels that offered monthly payment or provided formalized credit terms. Artukoglu and Olgun (2008) and Chitika (2008) concluded that such marketing channels acted as farmers’ saving banks.

Milk collection centers as sources of marketing information were significantly (P ≤ 0.01) and positively related to farmers’ choice of the formal channel. Offering marketing information to farmers was one of the services offered by the milk collection centers. Awudu et al(2009) reported that farmers’ marketing participation depended on the source, relevance, and intensity of market information.

Determinants of total milk proportions sold to the formal milk marketing channel

This study found that most factors that influenced the farmers’ choice of the marketing channel also influenced the volume of milk sold in the channel as shown by the Tobit model results (Table 5).

Household size was significantly (P ≤ 0.1) and negatively related to the proportion of milk sold to the formal channel. For every one additional household member in the family there was 10% likelihood decrease in the amount of milk sold to the formal channel. Large households in terms of number of members are expected to have relatively more household needs that require immediate cash, which the informal channel offered. In some cases, some of the large households consumed a large proportion of the milk produced and sold the little that remained to the informal channel as selling it to the formal channel would be less economical. A larger household is labor-inefficient and produces less output that ends up being consumed by the same household members, leaving smaller and decreasing proportions for sale (Alene et al 2008; Ouma et al 2010).

Distance to the milk collection centers was found to negatively and significantly (P ≤ 0.01) influence the proportions of milk sold to the formal channel. It was noted that for every one kilometer dairy farms were away from milk collection centers, there was a likelihood that the proportions of milk sold to formal milk marketing channel reduced by 10.4%. Most of the milk coolers were located in trading centers with an electricity supply, yet the majority of farms were in distant rural areas. Dairy farmers feared losing the milk during long distance transportation as milk being a perishable product. According to Sherma et al (2009), farmers prefer to sell their milk to market outlets that are near to them in order to reduce transportation costs. Omiti et al (2009) reported that the distance from the point of sale is the major constraint to increasing market participation. This finding is similar to that by Alene et al (2008) who observed that there is a decline in the quantities of agricultural output sold to markets as the distance increased away from the farm.

Conversely, an increase in the volume of milk produced on the farm significantly (P ≤ 0.01) increased the likelihood of farmers to sell more milk to the formal channel. One liter increase in milk production would result in a 10.8% increase in total milk sold to the formal channel. This was largely because of the relatively higher price and other market benefits such as large quantities of milk being bought, contractual arrangements with buyers, lump sum payment after a stated period of fifteen days, trustworthiness, and loans offered in terms of farm inputs (such as milk cans and agro veterinary drugs). This is not different from the findings by Anjani et al (2011) and Tsougiannis et al (2008) who found that households producing a higher quantity of milk were more likely to sell through the modern milk supply chain.

The price at which milk was bought had a positive and significant (P ≤ 0.01) influence on the proportions of milk that farmers sold to the formal channel. The formal channel offered a relatively higher price due to collective bargaining power of dairy cooperative unions, licensed raw milk buyers, and large milk producers. Price is an important driver of farmers’ market entry, satisfying the assertion that high price has a two-fold effect: influencing market participation decision and raising the volumes for marketing (Tushemereirwe 2007).

The period within which payment was effected after milk delivery was positively and significantly (P ≤ 0.01) related to milk proportions sold to the formal marketing channel. Results showed that a change from instant cash (short periods) to a fixed fortnight payment period to dairy farmers increased farmers’ likelihood to sell more milk to the formal channel by 11.7%. Formal channel participants looked at periodic payment as a way of saving, as well as, receiving a consolidated income, which they preferred to instant cash incomes coming in small increments as was common in the informal channel. Staal et al (2006) found that households preferred channels that offered monthly payments or provided formalized credit terms. Such payment arrangements, which are common with formal markets, act as farmers’ saving banks (Artukoglu and Olgun 2008a; Chitika 2008b).

The current results showed that provision of market information by milk collection centers that were managed by dairy cooperative unions and licensed raw milk traders positively and significantly (P ≤ 0.01) influenced the proportions of milk farmers sold to the formal channel. Market information originating from these sources was timely and reliable compared to other sources. Similarly, Omiti et al (2009) observed that the use of market information generated by certain marketing channels increased the output sales of the farmers in the market.

Table 5. Censored Tobit model estimates of factors influencing the proportions of milk sold to formal milk marketing channel

Dependent Variable : Proportions of milk sold

Marginal
Effect

Standard
Error

t
Value

p
Value

Constant

1.2583

-5.03

0.000

Natural log of farmerís age

0.201

0.130

1.55

0.123

Natural log of household size

-0.101

0.0559

-1.81

0.071

Natural log of farmerís education (number of years in school)

0.0522

0.0378

1.57

0.119

Natural log of total milk produced (liters)

0.1090

0.0 422

2.58

0.010

Natural log of farmerís non dairy income per month (Uganda shillings)

-0.0053

0.0054

0.310

0.325

Natural log of distance to milk collection centers (kilometers)

-0.105

0.0321

-3.27

0.001

Natural log of raw milk price per liter (Uganda shillings)

0.756

0.1917

3.94

0.000

Natural of log of Payment period duration (days)

0.105

0.0351

3.34

0.001

Source of market information (1=Milk collection center, 0=otherwise)

0.341

0.660

5.2

0.000


Conclusions and recommendations


Conflict of interest

The authors declare that they have no conflict of interest.


Acknoweldgements

Appreciation is extended to Jimmy Bushoboorozi, Roland Ainebyoona, and Ekyorisiima Patience for their assistance in field work, Department of Agribusiness and Natural Resources Economics at Makerere University for the technical guidance, and Bill and Melinda Gates foundation for funding this research through AgShare under leadership of Michigan State University, USA.


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Received 14 February 2015; Accepted 10 August 2015; Published 1 September 2015

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