Determinants of the Choice of Marketing Channel among Small-Scale Honey Producers in Tigrai Region of Ethiopia

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1 Determnants of the Choce of Marketng Channel among Small-Scale Honey Producers n Tgra Regon of Ethopa Kfle Tesfamaram, Assstant Professor, Department of Cooperatve Studes, Mekelle Unversty, Ethopa Tekeste Berhanu(PhD), Assstant Professor, Department of Cooperatve Studes, Mekelle Unversty, Ethopa Abad Afera, Assstant Professor, Department of Management, Mekelle Unversty, Ethopa Abstract Choce of market channels has been studed from dfferent angles n the developng world. However, model dentfyng the relatve sgnfcance of household socoeconomc and transacton cost attrbutes nfluencng channel choces at household level n Tgra regon have never been estmated. In our study, dscrete choce of multnomal logt model used to estmate the market channel choces. The nput for the study was obtaned from household survey conducted n the Tgra regon between Aprl and May In an effort to oversee the overall marketng practce of honey n the regon, ths study also examnes the Ethopa honey export trend for the last 10 years n terms of volume, earnngs and market destnaton. The emprcal analyss, usng multnomal logt model to examne the determnants of the choce of honey marketng channel shows that absence of market lnkage wth ndustral processors largely affects honey producers. Inadequate access to credt and longer dstance ncreased the probablty of sellng to local market and traders relatve to ndustral processors. Household farm sze and number of beehves decreases the probablty of usng local market relatve to ndustral processors. In many studes n the lterature, household demographc features are shown to have sgnfcant nfluence on choces of the market channel. In our study as well, the mpact of these household varables do have sgnfcant mpact on honey choce of honey market channel Keywords: Multnomal logt model, market channel, honey, Tgra regon Introducton Agrculture s the foundaton for Ethopan economy, and the overall economc growth of the country s hghly correlated to the success of the agrculture sector. In 2012/13, real GDP growth was 9.7% moderately lower than the 11.4% growth a year earler. Accordngly, agrculture accounts for about 43% of the country s Gross Domestc Product (GDP), 90% of export, and 85% of employment (NBE, 2013). In response to Ethopa s food securty and agrcultural productvty challenges, the government nsttuted an overarchng strategy of agrcultural development led ndustralzaton (ADLI). One of ADLI s dervatve features s the commercalzaton of smallholder agrculture through product dversfcaton; hence the promoton of apculture s n lne wth the natonal strategy. Moreover, n the growth and transformaton plan (GTP) due emphass was gven for the prvate sector as the drvng force for economc development and emphaszes that the manufacturng ndustres play the prncpal role n the development effort. In order to create a strong lnkage between agrculture and ndustry, the sectoral focus of the ndustral development strategy s agro-based ndustry. Labor ntensve ndustry and technologes, mcro and small enterprses and export orentaton are the core ssues of the strategy (MOARD, 2011). Honey and beeswax producton, processng and exportng are actvtes that fall nto the top prorty agrcultural and ndustral strateges of the country. In accordance wth the strategy, the Mnstry of Trade and Industry (MOTI) s facltatng and montorng the export of apculture products. The Mnstry of Agrculture and Rural Development (MoARD) s also provdng extenson servces to households engaged n honey producton. The apculture products are one of the few products that had the most nclusve ablty to acheve transformaton and growth across all categores of rural household. Ths s because of ts large resource base and low barrers to entry. At present an estmated total of 5 mllon hves exst n Ethopa. Nnety fve percent (95%) of honey producton comes from tradtonal hves (CSA, 2012). The latest avalable data shows that Ethopa s the largest producer of honey n Afrca. From , Ethopa honey producton ncreased 26% from 36,000 metrc tons (MTs) to 45,300 MTs (USAID, 2012). Accordngly, honey export s ncreasng sgnfcantly and s projected to exceed 600 MTs (2.7 mllon USD) per year n 2010/11 compared to a meager 150MTs (500,000USD) n 2005/06. The majorty of honey exports beng shpped to Sudan, Saud-Araba, Yemen, Chna, and Norway. Ethopa honey producton to be compettve n the global as well as domestc market, t s vtal to reduce the transacton costs prevalng along the market chan by dentfyng cost-effectve marketng channels and coordnated supply chans. Ths requres a proper understandng of how the marketng chan s organzed and operates. The extent to whch smallholder producers n honey markets are lnked wth bulk exporters and ndustral processors has not been well studed. Moreover, very lmted emprcal studes have been documented on the Open Access Journals Blue Ocean Research Journals 295

2 determnants of the choce of honey marketng channels n Ethopa. Therefore, the drvng force for ntatng ths study s that very lttle s known about the potental alternatve marketng channels for households on the one hand and the recognton of ts contrbuton to local people wth suffcent ncomes and act as an engne for rural growth and mproved natonal ncomes on the other. Therefore, ths study s bult on the assumpton that market partcpaton decsons and choce of market channels are made n sequence where producers ntally decde whether to sell or not, and then for whom to sell. Therefore, to enhance the ncome of households, t s essental to nvestgate the factor nfluencng choce of marketng channels. Dfferent studes on agrcultural products had shown that farmers decson for whom to sell s nfluenced manly by transacton costs (such as nformaton, negotaton, and montorng costs) and household characterstcs (lke age, educaton, famly sze, beehve, assets, etc.). Objectve Of The Study The overall objectve of the study s to nvestgate the determnants of choces of marketng channel among smallholder honey producers n Tgra regon, Ethopa. The study also ams at attanng the followng specfc objectves.. To examne the Ethopa honey export trend. To dentfy the factors that affect honey producers choces of marketng channel. Methodology P ( y = j) = 1+ ( x jθ ) m exp( x jθ ) exp j= 1, j j base, j = 1,2,3,... m( j j base ) To extract the requred nformaton needed to meet the objectves of the study, two major technques were employed n the study: household and desktop surveys. As the objectve of the household survey was from the outset envsaged extractng qualtatve and quanttatve data about farmers choce of honey marketng channels n Tgra regon, closed-ended (structured) questonnare was adopted n ths survey. A sample of 140 households was selected for the study. The survey covered four Wereda (Dstrct) of the regon. The samplng desgn used was multstage stratfed samplng approach. The largest porton of honeys produced n the study area comes from south eastern and eastern part of the regon. We frst select eleven vllages from four dstrcts that had well-suted for beekeepng practce. Once the dstrcts s stratfed n to the approprate vllages, purposve samplng technques were adopted to obtan the proportonate number of farmers from each vllage and selected based on sellers and non-sellers and type of beehve technology used. Afterwards, random samplng technque was adopted to obtan the requred sample sze of 140 farmers for the ntervews. Wthn tradtonal beehves technology domnatng vllages (comprsng proportonal farmers of 70), modern beehves domnatng (40 farmers) and tradtonal -modern beehves mxed (30 farmers).the survey covered wder ssues related to household demographcs, volume of supply, sellng prces, transacton cost and marketng channel choce, beehve technology type, supply of beekeepng nfrastructure and others were taken n to consderaton. The feldwork was carred out between Aprl and May, The study also utlzed relevant secondary data from Ethopan Revenues and Customs Authorty. Ths data manly used to descrbe the trends n export performance of honey. Descrptve statstcs was used to gve answers for some of the research questons. A multnomal logt model was used to show how household choose among honey marketng channels. Specfcaton of the emprcal model It has become a common practce to apply logt models for data whch are household specfc (Green, 2000). The applcaton of logt models depends on the number of marketng channels nvolved to study decsons related to market channel choce (Lu, 2007; Mamo and Degnet, 2012). When the choce set conssts of only two optons, bnary or probt models are the most frequently used econometrc models for an emprcal analyss. However, f the choce sets are more than two, then the multnomal logt dscrete choce model s used (green, 2000). In ths study we used multnomal logt model wth the ntenton to estmate the determnants of farmers decson to choce market channels to sell ther honey durng 2013/2014 harvestng season. ( 5.2a) Honey marketng decson makng at household level Consderng a dscrete choce problem, there wll be at least one most preferred choce of the honey marketng choce. The probablty of ths most preferred honey marketng choce j s expressed as follows by equa- 5.2a. ton ( ) P ( y j ) = base m = 1+ 1 j= 1, j j exp base ( x ) θ ( 5.2b) j Open Access Journals Blue Ocean Research Journals 296

3 5. In multnomal logt, regressors do not vary across choces; the estmated coeffcents (parameter estmates) ndcate the predcted margnal effects of each x Because multnomal logt requres one of the honey marketng choce (j) varables to be treated as a base category, normalzaton of the choces by one of the categores gves the baselne category (constranng the x correspondng j θ to zero) as expressed by equa- ( ) ton.2b j explanatory varable on the log-odds rato between two outcomes. The log-odds rato s computed as follows: log P m P( y = j) = xj ( y j ) θ = base j= 1 ( 5.3) Ths expresson means that the multnomal logt coeffcents ndcate the effects of an explanatory varable xj on the log-odds rato of the probabltes of choosng honey marketng channel j relatve to the baselne outcome. In fact, dscrete choce models such as multnomal logt and bvarate probt models share the property that ther parameter estmates cannot be nterpreted n a straghtforward manner n terms of choce probabltes. Instead addtonal computatons are requred. In the case of multnomal logt estmates, the probablty of a honey marketng channel choces j rather than the baselne ( ) outcome s shown by.2a 5. Snce the coeffcents of such models are not drectly nterpreted (because they are nterpreted n relaton to a base lne) n contrast to OLS results or Lnear Probablty models, margnal effects are estmated to express the probablty of change n honey marketng channel choces as a functon of each explanatory varable. These effects are evaluated at the mean of each varable. In other words, the log rato of proporton of choces requres the margnal effects and elastctes to be estmated at the mean levels of the varables. The margnal effects are therefore gven by equa- 5.4a. The elastctes of alternatve waste dsposal ( ) ton ( ) categores are provded by equaton.4b 5. y x j = θ yθ y ( 5.4a) y x j x y = θ yθ x j ( 5.4b) Where, θ represents the coeffcent of explanatory varable correspondng to honey marketng channel xj choces j.gven the fact that multnomal logt s a nonlnear probablty model, the estmaton method follows that of Maxmum Lkelhood (ML) procedure. As such, the log-lkelhood s therefore expressed as n m = = 1 j= 1 [ y j] dj ln P = ( 5.5) d =1 Where, j f an ndvdual household chooses a honey marketng channel category j and 0 otherwse. Revew of Lterature A basc approach to establsh any study on scentfc foundaton s to revew the emprcal fndngs of other studes related to the one on hand. As ths study s all about to dentfy the determnants of choce of marketng channels wth varous household and transactons costs varables, t s compellng to lay the ground for these by contemplatng related researches on some agrbusness products. Varous scentfc studes have examned the pattern of the effect of socoeconomc varables n the choce of market channels. Some researchers ndcate that farmer s demographcs and farm characterstcs such as age, gender, martal status, educaton, farm sze, and dversfcaton (Nyaupane et al., 2010; Gong et al., 2004; Ferto, 2002) had sgnfcant nfluences on the choce of market channels. In a more elaborated way, such as, both nsttutonal and techncal factors for example market nformaton flow, nsttutonal envronment whch encompasses formal and/or nformal rule, the use of grades and standards, and the legal envronment do play a major role n reducng transacton costs (Jar, 2009; Mburu et al., 2007). Accordng to Gong et al (2004) the choce of market channels s nfluenced by a number of transacton costs (nformaton access and qualty nspecton), negotaton costs (payment delay and nfluence on agreement) as well as montorng costs (gradng and farm servce). Smlar agreement presented by Mburu et al (2007) state that credt avalablty, nformaton access, polcy related nterventons such as government extenson agent and membershp n cooperatves serve as a key determnants of choce of market channel. Open Access Journals Blue Ocean Research Journals 297

4 Honey Sub-sector, Dynamcs And Trends Honey producton plays an mportant role n lvelhood mprovement of the rural communty(branbear, 2003). Owng to the low cost and local nput requrement of the sector, t can nvte the low ncome communty members to be engaged n the sector(hlm et al., 2011). In addton, beekeepng does not nterfere wth other actvtes; rather t can be practced as supplement of other agrcultural practces such as crop producton as bees are prncpal pollnators of many crop plants. These actvtes of bees not only ncrease the crop productvty but also play an mportant role n healthy functonng of the ecologcal unt. In Ethopa, bees are kept prmarly for the producton of honey. Bee wax s the other product whch s consdered n the producton system. However, bees provde other hgh value hve products such as royal jelly( used n medcnes and beauty products), propols( n medcens, varnshes, and chewng gum) and bee venom(n medcnal products) whch all are currently attractyng the nternatonal market(mutsaers et al., 2005; Anand and Ssay, 2011) Ethopa s assumed to harbor over 10 mllon bee colones. Ths bg number of colones, copupled wth the dverse flora composton and conducve clmate condton promses the country to produce over 500,000 tones of honey and 50,000 tones of bees wax(ssay, 2011). These fgures are much hgher than the current producton of honey and beeswax whch are estmated to be 53,675 and 3,600 tons respectvely(csa, 2011; Rugamba, 2011). Potental of other hve products n Ethopa have not been utlzed htherto. Even for the honey and bees wax products had also been wth lttle emphass for long tme. In recent tmes, however, apculture s ganng consderable attenton by the government. As aresult, dfferent polces and regulaton have alrady been neffect to explot the potental of the subsector as way of tacklng poverty n the country. One of these endeavorss the growth and transfromaton plan(gtp) of the country, partcularly, as amechansm of product dversfcaton. It appears a fttng ndustry wth the current green economy development program of the country. The recent development n honey market of the country s expected to lead towards better producton system. Research studes show that the Ethopan honey export s ncreasng from tme to tme. Table 1 reveals the exported volume of honey n metrc tons (MTs) and earnngs for the last ten years. For smplcty, the trend has been llustrated n the fgure depcted below (Table1). Table 1. Ethopa honey export trend from Year Exported % Share Volume (n tons) Value (USD) Volume Value , , , , ,090, , , ,106, ,409, ,687, Total ,304, Source: Ethopan Revenue and Customs Authorty export database, 2013 The Ethopan honey s exported to more than 14 countres. The Afrcan countres accounts for 66% of the export,european countres about 23%, Asan countres for about 9%, North Amerca accounts exactly one% and others such as oceana accounts less than one%.sudan has been the bggest mporter of Ethopan honey followed by Norway and then Unted Kngdom.the major nternatonal destnaton countres of Ethopan honey snce 1997 to 2012(see table2) Open Access Journals Blue Ocean Research Journals 298

5 Table 2. Foregn market destnaton of Ethopan honey ( ) Country Exported % Share Volume (n tons) Value (USD) Volume Value Sudan ,392, Norway ,859, Unted Kngdom , Yemen , Saud Araba , Unted States , Germany , Somala , Kuwat , Djbout , Unted Arab Emrates , Israel , Australa , Japan , Total ,347, Source: Ethopan Revenue and Customs Authorty export database, 2013 As depcted n above(table 2), the Afrcan countres accountng 66 percent of the total export mported 2,078 metrc tons of honey earnng USD 6.5 mllon to the country. Of the Afrcan countres, Sudan was the bggest consumer mportng 2,053 metrc tons worth USD 6.4 mllon. Apart from the Afrcan countres, European countres have become the second largest buyer of Ethopa honey mportng 726metrc tons worthusd 2.6 mllon.of the European countres Norway was the bggest consumer mportng 498metrc tons value USD 1.9 mllon.unted Kngdom s the second bggest buyer wth 10 metrc tons value USD 612 thousands. Apart from the Afrcan and European countres, Yemen has become the fourth largest buyer of Ethopan honey mportng 143 metrc tons worth USD 539 thousands. The ncreasng export and other domestc market optons for the honey encourage ntensfng producton and ex plotng the country`s potental of apculture. As can be seen n table 2, new destnantons of Ethopa honey exports are beng recoreded.gven these huge potental of the beekeepng ndusty of the country, the choce of the sub-sector for further nvestgaton wll brng pertnent nformaton for knowelege based polcy formulaton and mplemtatons. Household socoeconomc and transacton cost attrbutes In the econometrc models used, a number of varables thought to affect choce of honey marketng channels are ncluded. In order to make the estmaton of the models more clear and make t easer for the reader to understand we specfes(see table 3) how varables n the model are coded (maneuvered) for econometrc analyses n latter chapter n such a way that the requred output can be extracted. Open Access Journals Blue Ocean Research Journals 299

6 Table 3.Varables Measurement Calbraton Varables Measurement unts descrpton Antcpated Sgn Marketng channel choces 1 f a household uses local market 2 f a household uses processors 3 f a household uses traders Sex of the household head 0 = female,1 = male, + Age of household head Number of years + Famly sze of household Number of household members + Educaton level of household Years of schoolng + Sze of landholdng Number of hectares +/- Off-farm ncome 0 = no, 1= yes + Membershp n cooperatves 0 = no, 1= yes + Number beehves Number of beehves + Experence n Beekeepng Number of years + Sze of honey output Klogram + Marketed honey volume Klogram + Prce of honey Brr + Dstance e from honey market Mnutes + Access to honey market nformaton 0 = no, 1= yes + Expertse on grades gradng 0 = no, 1= yes + Access to credt 0 = no, 1= yes + Results and Dscusson The table below (Table 4) presents summary statstcs of socoeconomc and transacton cost varables whch are used n the estmaton of marketng channel choces.farmers use dfferent marketng channels to sale ther honey. These channel alternatves nclude local market (sellng to the consumers n the weekly market), processors and prvate traders. The lterature n marketng channels stresses that farmers prefer a partcular market channel ether because of ts closeness or channel that offers the best prce. Accordngly, most households n the study areas sell honey to prvate traders. Around 42 % of the farmers use prvate traders as a channel choce. Sellng to the local market as well s one of the common channels used. Of the total households surveyed, 39 % of them use local market to sell ther honey. Sellng to the ndustral processors s also at some level a common marketng channel. A good proporton of farmers (19%) preferred to sell to the processors as a choce of channel. Households honey marketng choces are varyngly nfluenced by many factors. Soco-economc characterstcs and transacton cost varables (nformaton, negotaton and montorng costs).it can be observed that most households that sell honey are male-headed; wth only about 21% of the farmers beng female headed.the mean households famly sze were 5.95 persons whch are smlar to the natonal average household sze accordng to the 2005 census. The ablty of farmers to transform ther lfe through access to dfferent resources depends on many factors of whch educaton s one of the most mportant. The survey result showed that more than half (59%) of the farmers attended prmary or more than prmary level of educaton whereas the rest 41 % of them are llterate. Regardng membershp of cooperatve, majorty (70%) of the farmers ndcated as members of cooperatves whle few (5 %) of them has not been a member of any cooperatve type n the past or today. Agrculture remans to be a domnant economc actvty and source of lvelhood for households. Land s one of the major resources of farmers used for farmng. The Open Access Journals Blue Ocean Research Journals 300

7 sze of land owned by farmers n the study area vared from 0 to 4 hectares wth an average holdng of 0.46 hectare. Off- farm actvtes such as petty tradng, homemade drnks, frewood provde addtonal ncome source to 44% of the farmers whle most (56%) of the farmers was lmted access to off-farm ncome generatng actvtes. Other determnants of honey channel choce such as dstance to the preferred market range from a mnmum of 5 mnutes to as far as 4 hours whch can have a bg mpact on the choce to prvate trader sdes than gong that far and sellng to local market or processors. The mean market nformaton and access to credt vew of the farmers (table4) s 0.76 and 0.61 respectvely, whch s closer to one than to zero showng the accessblty of fnancal servces and honey market related nformaton n the vcnty of the households. Table 4. Summary statstcs of channel choce determnants Varable Mean Std. Dev. Mn. Max. Local market Trader Processor Gender of household head Age of household head Household sze Years of educaton Farm sze Membershp coop Off-farm ncome Number of hves Beekeepng experence Volume of producton Volume marketed Average prce Dstance to preferred channel Market nformaton Gradng Access to credt Source: Feld data analyss, 2014 Honey types are classfed based on ther geographcal orgns such as honey from the Atsbe, Aksum, and Tembne. Snce the honey from each area has dfferent characterstcs and aroma. In general, two categores of honey are recognzed to be produced n Tgra regon: - extra whte and red. The color of honey s dependent on the type of flora the bees use for forage. Whte honey are preferred for table honey and fetch hgher prces(brr130-brr150/kg) at farm gate whereas red honey s preferred for honey wnes (local beverage tej) and s sold at farm gate for Brr90-Brr130/ Kg whch s lower than unprocessed, packed table honey retals for Brr170- Brr200/Kg. Further, packed, ndustral processed honey retals n supermarkets and other sales outlets at Brr220 - Brr240/Kg n the cty lke Mekelle. Multnomal Logt Model Results Ths secton presents the result of the multnomal logt regresson model and the result of the sgnfcant varables that determne the choce of market channels n Tgra regon. The varables that were dscussed n the above (table5) were consdered for the model and tested for ther sgnfcance. The econometrc software STATA s used to estmate the parameter coeffcents and predcted margnal values. The drect nterpretaton of the coeffcent estmates from multnomal logt model s msleadng. Therefore, the margnal effect and elastctes are used to descrbe the mpact of varables on market channels choce. Snce the nterpretaton of the parameter estmates of a mult- Open Access Journals Blue Ocean Research Journals 301

8 nomal logt are explaned wth respect to the baselne scenaro specfed, output of three dfferent categores can be outlned. In other words, each of the honey market channel choces can act a base case and allow nterpretaton of the coeffcents n terms of the base case. The dependent varables, honey marketng channels have three choces: 1 = local market (consumers), 2 = ndustral processors and 3 =prvate traders. Accordng to Gujarat (1992), the coeffcent values measured the expected change n the logt for a unt change n each ndependent varable, all other ndependent varables beng equal. The sgn of the coeffcent shows the drecton of nfluence of the varable on the logt. It follows that a postve value ndcates an ncrease n the lkelhood that a household wll change to the alternatve opton from the baselne group. Conversely, a negatve value shows that t s less lkely that a household wll consder the alternatves (Gujarat, 1992; Pundo and Fraser, 2006). Therefore, n ths paper, a postve value mples an ncrease n the lkelhood of changng from not partcpatng n the marketng to ether local market or trader market partcpaton choce. The sgnfcance values (also called as p- values) show whether a change n the ndependent varable sgnfcantly nfluence the logt at a gven level. In ths study, the varables were tested at the 10% sgnfcance level. Accordngly, f the sgnfcance value s greater than 0.1, then t shows that there s nsuffcent evdence to support that the ndependent varable nfluence a change away from the baselne group. If the sgnfcance value s equal to or less than 0.1, then there s suffcent evdence to support a clam presented by the coeffcent value. The elastcty (odd rato) ndcates the extent of the effect on the dependent varable caused by the predctor varables (Hll et al., 2001; Gujarat, 1992) As ndcated n table 6, some predctor varables nfluence market channel choces sgnfcantly. Of the 16 ndependent varables used n the model, fve varables n local market and four varables n trader choces are statstcally sgnfcant at the 10%, 5% and 10% sgnfcant level. In all but one of the cases, the sgns of the estmated coeffcent are consstent wth the a pror expectatons. The exstence of honey value chan actors such as ndustral processors does have sgnfcant mpact n honey marketng by households. In ths case, for mssng market lnkage wth ndustral honey processors farmers forced to sell n unproftable market channels, such as local market and traders are sgnfcantly larger relatve to sellng to processors. Ths relatonshp sgnfes nothng but the result that the mssng market lnkage wth processors households to dump ther honey n local market and wholesaler. The fact that the negatve coeffcent of access to credt (see table 5) for the local market and traders choces depcts that the probablty of sellng honey n those unproftable marketng channels decreases n relatve to the use of ndustral processors when more access to beekeepng related credt are avalable. Varables Table 5. Multnomal logt estmaton for honey market (Base case = Industral Processors) Local market Traders Coeffcent Margnal Elastcty Coeffcent Margnal Effects (θˆ ) (θˆ ) ey ex Effects dy dy dx dx Elastcty ey ex Constant -0.77(0.745) (0.988) - - Household head sex (0.752) (0.465) (0.301) (0.313) (0.245) (0.508) Household head age *** -0.01** 1.13 (0.861) (0.140) (0.260) (0.10) (0.047) (0.151) Household sze (0.753) (0.541) (0.530) (0.324 (0.298) (0.543) Household head educaton 0.22 (0.840) 0.02 (0.264) 0.77 (0.368) (0.422) (0.189) 0.19 (0.268) Farm sze -1.97*** (0.097) (0.410) (0.731) (0.166) (0.958) (0.419) Membershp coop (0.190) (0.265) (0.220) (0.482) (0.600) (0.262) Off-farm ncome (0.715) (0.470) (0.673) (0.278) (0.216) (0.459) Number of hves 0.79* *** (0.008) (0.149) (0.525) (0.010) (0.221) (0.151) Open Access Journals Blue Ocean Research Journals 302

9 Beekeepng experence Volume producton Volume marketed Average prce Dstance n mnutes Access to market nf.+ Gradng + Access to credt *** (0.10) (0.954) (0.311) 0.01 (0.459) 0.01** (0.025) 1.52** (0.038) 1.28** (0.043) -1.38** (0.029) (0.144) (0.593) (0.948) (0.253) 0.002** (0.046) 0.13 (0.282) 0.25** (0.011) -0.24** (0.018) -5.17* (0.007) (0.651) 0.52 (0.317) 0.81 (0.322) 0.81** (0.032) 0.15 (0.862) (0.852) 0.48* (0.007) (0.535) (0.721) (0.198) 0.03** (0.040) 0.004*** (0.058) 1.32** (0.050) 0.23 (0.688) (0.447) 0.01 (0.371) (0.545) (0.411) 0.005** (0.041) 0.002*** (0.056) 0.07 (0.548) -0.17*** (0.100) 0.15 (0.131) (0.153) (0.592) 0.03 (0.948) (0.258) 0.27*** (0.052) 0.21 (0.399) 0.43** (0.026) -0.37** (0.025) Note: N= 140, Pseudo R 2 = , Log lkelhood = , LR ch2(32) = 56.28, Prob> ch2 = * sgnfcant at 1% level, ** sgnfcant at 5 % level, *** sgnfcant at 10% level Source: Feld data analyss, 2014 A one step (for example, from nadequate to adequate market lnkage) mprovement n the market lnkage wth the processors has a hghly sgnfcant mpact (negatve elastcty) on honey marketng n unproftable channels. Households access to market nformaton does as well affect the choce of honey market channel choces. Most of honey producers are not organzed themselves n honey marketng cooperatves whch ncrease ther barganng power and creates vertcally lnkage wth ndustral processors. Absence of such lnk anywhere n the regon results n an ncreased probablty of sellng honey n local markets and traders relatve to ndustral processors. The exstence of ndustral processors also affects the choces of honey market channels. The further s the dstance of processors from households houses, the ncreased (larger) s the probablty of households optng to use nearby local markets and traders to sell ther honey relatve to sellng to processors. A 1% ncrease n dstance results n 0.81% ncrease n sellng honey n unproftable channels, relatve to ndustral processors. Dstance of processors as well ncreases the use of alternatve honey marketng channels lke prvate traders. In the results of our study, t s shown that a 1% ncrease n the dstance of processors ncreases the use of traders by 0.27% relatve to processors. Household experence n beekeepng also, as expected, has a negatve mpact on the use of unproftable marketng channels as compared to processors. An ncrease n household experence n beekeepng by 1% reduces the probablty of sellng n local markets and traders by 5.17 % (see table 5). Ths mples that ncreased n beekeepng experence allows households to use alternatves channel choces such as ndustral processors. Although the exstence of honey processors n the market sgnfcantly affects the choce of honey market channels, outcomes of the study show that household demographc features are largely nsgnfcant n ther nfluence of choce among channel optons. Household demographc features such as sex of household head and number of household members do have negatve effect n sellng honey n local markets and traders but the results of our study show that these varables area nsgnfcant. One hypothess of ths paper s that the exstence of off-farm ncome sources by household members results n better honey marketng practce. The results show that the exstence of more off-farm ncome n the household decrease the probablty of usng unproftable channels as sellng opton relatve to ndustral processors. The mpact of household head age and educatonal status of the household head are found to be nsgnfcant. Possble explanaton could be some sort of awareness change rather than the number of years of educaton or age may be the factors for sellng honey n hgh return choce of market channels. Snce the effect of ths awareness change has not been researched n our study, future study s warranted n ths regard. Concluson and Recommendaton Farmers use dfferent marketng channels to sale ther honey. These channel alternatves nclude local market (sellng to the consumers n the weekly market), processors and prvate traders. The lterature n marketng Open Access Journals Blue Ocean Research Journals 303

10 channels stresses that farmers prefer a partcular market channel ether because of ts closeness or channel that offers the best prce. Accordngly, most households n the study areas sell honey to prvate traders. Around 42 % of the farmers use prvate traders as a channel choce. Sellng to the local market as well s one of the common channels used. Of the total households surveyed, 39 % of them use local market to sell ther honey. Sellng to the ndustral processors s also at some level a common marketng channel. A good proporton of farmers (19%) preferred to sell to the processors as a choce of channel. It was found that farmers would go for the market channel opton offered by market traders nstead of other farmers opton when there was hgh transacton costs reflected n longer tme spent to reach other farmers, hgh transportaton costs, and lack of nformaton on market prce. It s nterestng to see that farmers who have completed some educaton level tend to go for the consumer outlet as compared to traders. Furthermore, the avalablty of extenson servces and credt ncreases the probablty of movng to the consumer and other ndvdual markets decreases dependence on mddle men. The honey producton system n Tgra s constraned by lack capacty to acqure and to employ modern technologes. The scalng up efforts should therefore be nvested from nput accessng to technology adopton, skll development and product market lnkages. Technologes would better be adopted f they are suppled at local level. The followng can be suggested as scalng up strateges a) Avalng and generatng modern technologes at local level: mproved beehves need to be produced at local level based on the local crcumstances. All the supply and mantenance servces are also to be provded locally. b) Proper acquantance of the producers wth mproved technologes through tranngs and through nnovatve farmers. c) Lowerng the prce of nputs by enablng the nput supplers to be more effcent n resource use: the more the prce lowers the more the nput can be used whch n turn the more the nput supplers would be benefted. d) Organzng producers nto cooperatves to buld up capactes for hgh nput technologes e) Follow up and contnues encouragement towards modern technologes f) Proper market lnkage for products so that farmers can hold assets to be nvested back n the sector. g) Informaton center for up-to-date market condtons from regonal to local and f possble natonal level. h) Systematc lnkage of products to bg markets preferably export destnatons ) Organzng producers nto cooperatves so that they able to accesses better markets at dstant destnatons ncludng exports. j) Promotng value addtons through tranngs and nvolvng sklled actors: Technque and vocatonal schools may tran some of ther students towards beekeepng and to enable them be nvolved n the value chan of the sector. References [1] Integrated Value Chan Analyses for Honey and Beeswax Producton n Ethopa and Prospects for Exports. Global Development Solutons,LLC. [2] Allsopp, M. H., De Lange, W. J. & Veldtman, R.(2008).Valung nsect pollnaton servceswth cost of replacement. PLoS, 3, [3] Bahta, S. T. & Bauer, S. (2007). Anlyss of the determnants of market partcpaton wthn the South Afrcan small-scale lvestock sector.tropentag Paper, Tropentag, Wtzenhausen: Utlsaton of dversty n land use systems: Sustanable and organc approaches to meet human needs. [4] CSA (2012). Central Statstcal Authorty, Agrcultural Sample Survey, 2011/12, Report on Crop and Lvestock Product Utlzaton. Statstcal Bulletn 468. FDRE: Adds Ababa. [5] BoPED (2000). Bureau of Plannng and Economc Development, Estmaton of Regonal Gross Domestc Product and Structure of the Economy (1994/ /990 Tgray,32. [6] Ferto, I. & Szabó, G. (2002). The Choce of Supply channels In Hungaran Frut and Vegetable Sector, Economcs of contracts n agrculture. Second Annual Workshop, Annapols, Maryland. [7] Grma, M. & Abebaw, D. (2012). Patterns And Determnants Of Lvestock Farmers Choce Of Marketng Channels: Mcro-Level Evdence. Ethopan Economcs Assocaton Ethopan Economcs Polcy Research Insttute (EEA/EEPRI), Workng Paper No 1. [8] Green, W. H. (2000). Econometrc Analyss.4th edn. Englewwod Clffs, NJ: Prentce Hall. [9] Grewal, R. & Dharwadkar, R. (2002). The Role of the Insttutonal Envronment n Marketng Channels. Journal of Marketng, Open Access Journals Blue Ocean Research Journals 304

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