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Annals of Public and Cooperative Economics 85:2 2014

TRANSACTION COSTS COMPARISON BETWEEN COOPERATIVES AND CONVENTIONAL APPLE PRODUCERS: A CASE STUDY OF NORTHWESTERN CHINA by Wang LIJIA∗ and Huo XUEXI College of Economics and Management, Northwest A&F University, China

ABSTRACT: The study promotes an analytical framework to monetary the transaction costs for the purpose of assessing the different subfields of transaction cost faced by members in cooperatives and non-cooperatives members, and therefore investigates the role of cooperatives in reducing them using a questionnaire-based survey in Shaanxi province in China. The quantified result of each transaction cost-related item suggests that producers can annually save more than a thousand yuan if they participate in cooperatives. Results also highlight that the medium scale producers would be beneficial most from being a member in cooperatives compared with small- and large-scale ones. By implications, supporting programs referring to improve local road condition, access to internet, and subsidize agricultural cooperatives are highly recommended for policy makers. Keywords: China, comparison, transaction costs, information cost, negotiation cost, enforcement cost, transportation cost.

Transaktionskostenvergleich zwischen Genossenschaften und konventionellen Apfelproduzenten: Eine Fallstudie aus Nordwest-China Die Studie bietet einen analytischen Rahmen fur ¨ die Monetarisierung der Transaktionskosten, um die verschiedenen Unterbereiche von Transaktionskosten abzuschatzen, ¨ mit denen Mitglieder von Genossenschaften und Nichtgenossenschaftsmitglieder konfrontiert sind. Zu diesem Zweck wird mittels einer fragebogenbasierten Umfrage in der chinesischen Provinz Shaanxi untersucht, wie Genossenschaften die Transaktionskosten reduzieren können. Bei jedem Posten, bei dem Transaktionskosten eine Rolle spielen, ergibt sich als monetares ¨ Resultat, dass Produzenten jahrlich ¨ mehr als tausend Yuan sparen können, wenn sie Genossenschaften beitreten. Die Resultate zeigen auch deutlich, dass die mittelgroßen Produzenten, verglichen mit den kleinen und den ganz großen, am meisten davon profitieren wurden, ¨ Mitglied von Genossenschaften zu sein. Folglich ist politischen

∗

This research is supported by the earmarked fund for China Agriculture Research System (CARS-28), and the project of “Effect of Agro-product Transaction Cost on the Farmer Households” Selling Behavior and Specialization Organization Innovation(70973098). E-mail: [email protected]

© 2014 The Authors Annals of Public and Cooperative Economics © 2014 CIRIEC. Published by John Wiley & Sons Ltd, 9600 Garsington Road, Oxford OX4 2DQ, UK and 350 Main Street, Malden, MA 02148, USA

234

WANG LIJIA AND HUO XUEXI

Entscheidungstragern ¨ sehr zu empfehlen, Programme zu unterstutzen, ¨ die darauf abzielen, den Zustand o¨ rtlicher Straßen zu verbessern, Internet-Zugang herzustellen und Agrargenossenschaften zu subventionieren.

´ entre empresas Estudio comparativo de costes de transaccion ´ de manzanas. Un estudio del cooperativas y tradicionales de produccion caso en el Noroeste de China El art´ıculo propone un marco anal´ıtico para monetizar los costes de transacción, con el fin de evaluar las diferentes categor´ıas a las que se enfrentan los miembros de las cooperativas y las empresas no cooperativas. El papel de aquellas en la disminución de estos costes se examina con la ayuda de una encuesta basada en un cuestionario cumplimentado en la provincia de Shaanxi en China. El resultado cuantificado de cada item ligado a los costes de transacción pone de manifiesto que los productores pueden economizar mas ´ de un millar de yuanes anuales si son miembros de cooperativas. Los resultados ponen en evidencia, asimismo, que los productores de dimensión media se benefician mas ´ de ser miembros de una cooperativa que los pequenos ˜ y los grandes. En consecuencia, los autores recomiendan a los responsables pol´ıticos promover programas dirigidos a mejorar el estado de las carreteras locales, el acceso a Internet y subvencionar a las cooperativas de agricultores.

ˆ de transaction entre entreprises cooperatives ´ Comparison de couts et ´ traditionnelles de production de pommes . Une etude de cas dans la Chine du Nord Ouest L’article propose un cadre analytique pour monétariser les couts ˆ de transaction afin d‘évaluer les différentes catégories de couts ˆ de transaction rencontrés par les membres des coopératives et des entreprises non coopératives. Le rôle des coopératives dans la diminution de ces couts ˆ est examiné a` l’aide d’une enquête basée sur des questionnaires menée dans la province de Shaanxi en Chine. Le résultat quantifié de chaque item lié aux couts ˆ de transaction suggère que les producteurs peuvent e´ conomiser plus d’un millier de yuan par an si ils sont membres de coopératives. Les résultats mettent e´ galement en evidence que les producteurs de taille moyenne bénéficieraient davantage d’être membre d’une coopérative que les petits et les grands producteurs. En conséquence, les auteurs recommandent aux décideurs politiques de promouvoir des programmes visant a` améliorer l’état des routes locales et l’accès a` internet et de subsidier les coopératives d’agriculteurs.

1

Introduction

The emergence of cooperatives can be attributed to a combination of economic, farm organization, and public policy factors (Cook, 1995). The most commonly accepted definition of cooperatives is, “A cooperative is a user-owned and user-controlled business that distributes benefits on the basis of use” (Barton, 1989). The definition indicates that the aim of a cooperative is to create benefits to its members and to maximize the utility of its member-patrons (Feinerman and Falkovitz, 1991; Nilsson, et al., 2012). Barton (2000) extends the objective of cooperatives to generate greater profits by obtaining input factors and services at lower price than the price which they would pay elsewhere, © 2014 The Authors Annals of Public and Cooperative Economics © 2014 CIRIEC

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and also by marketing their products at better prices than the price which they would sell through other marketing trade channels. The origin of cooperatives in China can be traced to the establishment of People’s Commune in 1958 which combine the individual farm households together to do agricultural production activities, followed by a practice named Household Responsibility System in 1982 which partially supplanted the egalitarian distribution method, and local managers are held responsible for the profits and losses of an enterprise. Since then, the cooperative institutional system has been developed. Cooperatives as one of the market trading choices has been experienced a rapid development in rural China since the establishment of Law on Cooperatives of People’s Republic of China in 2007 (hereafter, “the Law in 2007”). It is reported that the registered cooperatives is up to 689 thousand by the end of 2012 whereas the number is only 100 thousand in 2008 (Source: State Administration for Industry & Commerce of the People’s Republic of China). The constitution of cooperatives in China is regulated and heavily supported by local or central government, but typically managed by the cooperatives members, especially the ones with greater transaction amount with cooperatives instead of the small producers accounting for the majority of cooperatives. In fact, the Chinese government (Ministry of Finance of the People’s Republic of China, State Administration of Taxation) has implemented a series of support policies on the development of cooperatives since 2007, including the tax incentives with respective to value-added tax free for cooperatives selling their member’s products, as well as selling agricultural inputs (fertilizers, chemical pesticides, sapling, plastic sheeting, etc) to their members; financial supports referring to interest payment on loans when cooperatives buy agricultural machinery, establish cold storage facility, etc.; subsidy policies associating with using water-saving irrigation systems and the conservation tillage equipments, etc. Cooperatives are nonprofit organizations comprising farm householders with similar farm products and a common objective of collectively achieving a goal based on the Law in 2007. The dominant functions of cooperatives are to correct market failure, to assure access to agricultural inputs supplies and markets for their members, to relieve members from the incapability of purchasing agricultural production equipments, to endow members with the benefits of operational economy of scale and thus to enhance member’s negotiation power, to provide specific technical suggestions as well as instructions on farm activities. Members (hereafter, CP) getting benefits from cooperatives services can choose to sell their products both inside and outside the cooperatives, whereby each member can obtain the dividend depending on his/her transaction quantities with cooperatives. For non-cooperative members, that is conventional producers (hereafter, CV), they can get only services provided by the local agricultural institutions or government. Conventional producers can also trade products with cooperatives but without the dividend. Smallholder’s market participation is important to economic growth and poverty reduction. The interventions aims at facilitating smallholder organization, at reducing the costs of intermarket commerce, are central to stimulating smallholder market participation (Barrett, 2008). Indeed, smallholders in China have multiple trade channels available in the sales process, i.e., cooperatives, agents, wholesalers, retailers, agrofirms, etc. Thus, choosing an appropriate trade institutional mode can help reducing the © 2014 The Authors Annals of Public and Cooperative Economics © 2014 CIRIEC

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production and transaction costs of small householders, as it represents a beneficial market choice for them. Householder’s decision on where to sell their crop is not only based on the price they expect to receive in each outlet, but also depends on additional costs related to transacting in these outlets (Vakis et al., 2003). Moreover, small-scale producers are supposed to be subject to bounded rationality. Full rationality requires unlimited cognitive capabilities, while the decision making behavior of human beings could not conform to this ideal full rationality due to the given conditions and constraints (Gerd and Reinhard, 2001). As Simon promotes, these limitations include risk and uncertainty, incomplete information about alternatives of action, as well as complexity in environmental constraints which prevent the actor from calculating the best course of action (McGuire and Radner, 1972). Thus, market imperfect and information asymmetry may give producers an exploitable advantage in their choice of transaction channels. With the average size of family farms rising in recent decades, concerns are being increasingly voiced about the weakness of market power of family farms, and the gradual elimination of competition in non-agricultural components of the agro-food sectors (Heffernan et al. 1999; Harkin and Thomas, 2004). However, small scale producers in China are still in a lower level of social hierarchy and their opinions are often been ignored during negotiating process comparing with their up- and downstream trading partners. Additionally, small scale producers experience many difficulties in their attempts to sell agricultural products. They widely complain of the low prices they received and the difficulties of finding a buyer; they also experience serious problems with transporting products to the market (Lerman and Sedik, 2009).Therefore, these disadvantages result in an increasing need for inter-sectorial coordination within the agro-food sectors. Studies incorporating cost and benefit analysis typically assume that the transaction costs are zero through time. This assumption is inconsistent with the theory of Transaction Cost Economics (TCE) of which adopts a contractual approach to the study of management and organization promoted by Williamson (1973). TCE assumes that exchanges are not costless (Royer, 2011). The presumption of transaction cost approach analysis is that “these costs vary systematically from one institutional mode to another, and each activity is carried out by the institution that can perform it most efficiently (Pollak, 1985, p.583).” In the past three decades, TCE is used to explore a variety of economic relationships, ranging from lateral and vertical integration (Anderson, 1985; Teece, 2010; Yaqub, 2009) to market channel selection, make-or-buy decision (Walker and Weber, 1984; Mudambi and Tallman, 2010), as well as contract arrangement (Runsten, 2009; Schipmann and Qaim, 2011). In an imperfectly competitive market circumstances, it is assumed that parties to a bargaining transaction are equal and legally free. Social relations between trading partners tend to be limited and developing them would be costly (Ring and Van de Ven, 1992). Small scale producers face many hidden costs associated with arranging and carrying out an exchange of goods or services making it difficult for them to gain access to markets and productive assets (Staal et al., 1997). A number of empirical literatures touch on the area of the impact of transaction costs on producer’s cooperative participatory decision-making in developing countries. These farm household level research findings confirm that cooperatives are an appropriate vehicle to reduce transaction costs of small-scale producers, and reveal that high transaction costs prevent inputs and products markets from operating efficiently. The © 2014 The Authors Annals of Public and Cooperative Economics © 2014 CIRIEC


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low educational level, lack of market information, and the long distance to markets of small-scale growers lead to them facing high transaction costs (Matungul et al., 2001; Ortmann and King, 2007). Other studies find that cooperatives help farmers avoid the hazards of being encumbered with a perishable crop with no rural demand. Participatory cooperatives can be helpful in overcoming access barriers to information, services, and the markets within which smallholders wish to produce high value items (Jaffee, 1994). Moreover, farmers receiving higher price for their products when trade with cooperatives also receive an individual benefit due to the joint action of farmers. In other words, members in cooperatives have both individual collective benefits and mutual collective benefits (Gray, 2009). Part of the precursor empirical analysis also revealed the transaction cost-related determinants by identification of some of them as regressors in the decision of market participation. For instance, Ouma et al. (2010) investigate the transaction cost-related determinants of smallholder farmers’ participation decisions in banana markets. The results illustrate that geographical location of households, market information sources, and the travel time to the nearest urban center statistically influence banana producers’ market participation. Holloway et al. (2000) explore the impact of small-scale household-level transaction costs and the choice of production technique on the decision of producers to sell products to marketing cooperatives. Their research findings show that cooperative groups can not only minimize the time required to market products, but also provide a low cost mechanism for increasing small-holder market participation. Conversely, others argue that the small and poorer farmers tend not to participate in cooperative organizations although they might benefit from them. The exclusive from decision-making process of cooperatives can be the primary reason for farmers’ participatory unwillingness (Bernard and Spielman, 2009). As a matter of fact, transaction costs which are usually neglected by producers play an important role in determining market prices. Unlike production costs, transaction costs are difficult to assess as they represent the potential consequences of alternative decisions (Klein et al., 1990). However, for the purpose of transaction cost approach, a crucial question is how much transaction costs are when producers enter market from various trading channels. Fortunately, several researchers become interested in estimating the magnitude of transaction costs during producers’ market participatory decision-making process in recent decade. Vakis et al. (2003) promote a monetary measure of transaction costs in the choice of market participation using data for Peruvian potato farmers, and the results show that the information on market price decreases fixed transaction costs by the equivalent of doubling the price received. Given the previous studies and the gradually important role played by cooperatives in the development of rural economy, and in being a connection between producers and markets in China, we still believe there is a need to explicitly estimate these aspects which are difficult to observe as they are important part of transaction costs. Furthermore, although it is hard to measure the magnitude of transaction costs, understanding the transaction cost-related determinants on producer’s cooperative trading mode selection behavior is still meaningful for promoting policy design aimed at reducing costs and increasing farm households’ income. Thus, we try to keep our methodology and estimation as straightforward and simple as possible in the comparison of transaction costs on the specific market outlet (cooperatives transaction mode) between cooperatives producers and conventional producers. © 2014 The Authors Annals of Public and Cooperative Economics © 2014 CIRIEC

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Figure 1 – Advantages apple production region in China.

In this article, we take the perspective of transaction cost economy, attempt to directly measure the transaction costs faced by small-scale producers, and seek to explain the determinants and consequences of producers’ cooperative mode choice by means of a questionnaire-based survey. In the following section, we describe the sampling procedures and the method applied in the research. We then turn to present the statistical description of farm characteristics of producers, followed by the estimation and comparison of the magnitude of transaction costs between cooperative producers and conventional producers. A final section concludes by discussing the policy implication of the findings and limitations of the study.

2

Data and method

2.1

Sampling procedure

China is the largest fresh apple production country followed by the European Union and the United States in the world. The proportion of fresh apple production of China to the world production was 57.3 percent in 2012 (USDA-ERS, China Agriculture Research System). The fresh apple growing areas are categorized into two major regions based on the geographic location and climate environment (Figure 1): 1) the Bohai Bay region which the fresh apple production accounts for 40.0 percent of the total production in China; 2) the Loess Plateau region which the fresh apple production accounts for © 2014 The Authors Annals of Public and Cooperative Economics © 2014 CIRIEC


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Figure 2 – Ratio of apple production in sample regions from 2006 to 2009. Source: Shaanxi Statistical Yearbook 2007–2010 APS = apple production in sample regions; APG = apple production in apple-growing regions in Shaanxi; APSH = apple production in Shaanxi.

49.7 percent of the total in China (Ministry of Agriculture of the People’s Republic of China, the Planning of Advantages Regions of Apple Production 2008–2015). The fresh apple production in Shaanxi province accounts for more than half of the total production in China (51.0 percent in 2012). Thus, our field survey was conducted in Shaanxi province in China during June to August in 2011. The six county-level samples for this study were selected from 30 apple-growing counties1 employing systematic sampling method depending on apple production in 2009 (Source: Shaanxi Statistical Yearbook 2010). Specifically, Figure 2 depicted the share of apple production in sample regions (APS) to the total apple production in apple-growing regions (APG), and the ratio of apple production in apple-growing regions to the total apple production in Shaanxi province (APSH) in period 2006 to 2009. It illustrates that apple production in apple-growing regions represents averagely 85.9 percent of the total apple production in Shaanxi province. And the proportion of apple production in sample regions to the total apple production in apple-growing counties is about 13.6 percent. Thus, the farm household level data collected from the six counties can be considered as representative samples.

1

Apple growing county is an open economic system which has a clear regional boundary and certain of regional scale. It is an agricultural specialization region based on the social division of labor, and an outcome of spatial agglomeration of agricultural industry. This specialization region primarily deals with apple farm activities. In other words, it takes apple farm as the specialized direction of agricultural regions. From the perspective of development direction, the apple growing county is not a traditional and self-sufficient natural economic system, neither a product economic system purely pursuing the increase of apple outputs, it is a commercial economic system.

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In the sampling procedure, 21 villages were then randomly selected in the six counties. The similar way being used to choose apple grower level samples, and we randomly selected 20 apple producers in each village. In general, we conducted 420 questionnaires including 130 cooperatives apple producers and 290 conventional apple producers. Given the efficiency of questionnaire and the inception of apple orchards (Wang et al., 2013), questionnaires including 15 cooperatives producers and 40 conventional producers were removed from the empirical analysis. Finally, data of 365 apple grower level questionnaires (115 cooperative producers and 250 conventional producers) were employed.

2.2

Probit model

In order to investigate the determinants affecting farm householders’ cooperative participatory behavior, a Probit model first introduced by Bliss (1935) is employed as the dependent variable (participating in cooperatives or not) can only take two values: 1 represents apple producer participating in cooperatives; 0 represents apple producer not participating in cooperatives. Specifically, the Probit model takes the form as: Pr (Y = 1 |X ) = (X α),

(1)

Where Pr represents probability, is the Cumulative Distribution Function (CDF) of the standard normal distribution, Y is the dependent variable which has only two possible outcomes denoting as 1 and 0, X is the vector of independent variables which are assumed to affect the outcomeY , and α is the parameter which are typically estimated by maximum likelihood. Moreover, suppose an auxiliary random variable exists: Y∗ = X α + ε,

(2)

Where ε∼ (0, 1) , Y∗ is a latent variable, Y is an indicator for whether the latent variable is positive: Y=

1 if Y∗ > 0 i.e. − ε < X . 0 otherwise

,

(3)

The equation (1) and (2) are equivalent as follows: Pr (Y = 1|X) = Pr (Y∗ > 0) = Pr (X α + ε > 0) = Pr (ε > −X α) = Pr (ε < X α) (by symmetry of the normal dist) = (X α)

(4)

The probability of an apple producer participating in cooperatives is assumed to be affected by the producer demographics, farm characteristics, and the transaction costs-related variables (see Table 1). © 2014 The Authors Annals of Public and Cooperative Economics © 2014 CIRIEC


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Table 1 – Statistics description (Number of cooperative producer = 115, number of conventional producer = 250) Mean (St. Dev)

Variable description

Variable code

Producer demographics and farm characteristics Age AGE Educational attainment EDU Apple planting acreage APA Apple income AIN Apple production APR Information costs Time to know market information TTI Time to look for potential buyers TTF Expenditure on agricultural fairs EOF Negotiation costs Time to fix trading price and place TTN Time to grade products TTG Enforcement cost Time to wait for the full payment TTW Expenditure on selling apples EOS Loss of buyers’ breaking the contract EOB Transportation costs Apple damage caused by poor road condition EOD Expenditure on transportation EOT

Unit

Cooperative producers (CP)

Conventional producers(CV)

P-value

Years Years Mua Thou. Yuan Tons

53.5 (8.9) 8.9* (2.7) 3.9* (2.2) 23.8* (21.0) 6.3 (4.5)

54.2 (8.4) 7.4* (2.3) 3.0* (1.6) 10.9* (10.7) 5.7 (4.2)

0.4617 0 0.0001 0 0.2281

Hours Hours Yuanb

0.8 (3.3) 0.1* (0.2) 19.7 (52.9)

Hours Yuanb

0.02 (0.04) 3.2* (3.4)

0.17 (1.90) 11.2* (19.5)

0.3839 0

Days Yuanb Yuanb

14.9* (9.4) 9.0* (19.0) 44.3* (301.8)

4.1* (6.8) 187.3* (162.5) 791.6* (1025.6)

0 0 0

Yuanb Yuanb

0.3 (1.0) 0.4* (0.7) 27.4 (254.1)

200.3 (362.8) 263.0 (916.4) 137.74* (249.9) 227.32* (303.2)

0.0737 0 0.7458

0.4793 0.0060

∗ Differences

between CP and CV statistically significant at p = 0.05. Note: a 1 mu = 0.067 hectare; b Average annual 2010 dollar rates used: 1 RMB (Chinese Yuan) = 0.677 US$. (Source: National Bureau of Statistics of China, 2011)

3

Variables descriptions

3.1

Characteristics of producers

The descriptive statistical results show that the differences in educational attainment, apple planting area and apple income between cooperative producers and conventional producers are statistically significant. Particularly, the annual apple income of CPs is averagely 12.9 thousand yuan more than for CVs. Referring to transaction costrelated characteristics, the differences of six variables involving time to search potential buyers, time to grade products, time to wait for the full products payment, expenditure on selling process, loss of buyers’ breaking the contract, and cost of transporting products to transaction sites are statistically significant between cooperative and conventional producers (Table 1). Noting that the difference in annual apple production between cooperative and conventional producers is not statistically significant (Table 1), the seemingly contradictory result can be explained by the distinctions of producers’ apple sales prices between © 2014 The Authors Annals of Public and Cooperative Economics © 2014 CIRIEC

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the two research groups. The survey data illustrate that price of various apple grades2 for cooperative producers are averagely 0.7 yuan/kg greater than for conventional producers. Compared with conventional producers, the higher apple transaction price of cooperative producer imply a better quality of fresh apples and thereby lead to a higher apple income for cooperative producers than conventional producers under the condition of similar average apple production. Overall, producers with better academic education, larger apple planting size, higher apple income, are more likely to participate in cooperatives. For the purpose of investigating apple producers’ cooperative participatory decision from the transaction cost perspective, we asked the producers in the sample regions to choose an ideal transaction outlet. Survey results report that nearly 90 percent conventional producers are willing to trade apples with wholesalers compared with around 46 percent of cooperative producers taking wholesalers as their ideal trading object. Surprisingly, only 44.4 percent cooperative producers prefer to trade with their cooperatives. The paradox between the more benefit from cooperatives and lower transaction willingness of producers can be attributed to the higher purchase requirement and criteria of cooperatives on apple quality associating with size, taste, color, etc. Besides, cooperatives with their own apple brands prefer to purchase organic apples from their members which mean not being allowed to use the chemical pesticides during the planting process in our research areas. According to the field discussion, apple producers broadly complaint of hard to meet the requirement due to the unexpected weather condition which largely affects the physical conditions of apples, and the various insects and disease of apple trees which might need chemical pesticides to be avoided or cured. 4

Transaction costs measurement

In our study, the transaction costs explanatory variables hypothesized to influence producers’ decision of joining in cooperatives are grouped into four subtypes: information cost, negotiation cost, enforcement cost and transportation cost. The measurement scale of each subfield of transaction costs on the basis of field survey questionnaire is illustrated in Table 2. 4.1

Information cost

Perhaps the most neglect aspect of transaction costs is the information cost which is unavailable to measure directly. Field discussions revealed that most of the producers do not realize that obtaining market price information being costly. Before producers making decisions on where to buy input materials (e.g., fertilizer, pesticides, herbicides, 2

In our research regions, apples (Fuji) are always sold after grading according to the fruit size, shape and quality. There are basically three grades: 1) the first-class fruits with apple diameters above 75mm and the sales price is 4.10 yuan/kg for cooperative producers compared with 3.48 yuan/kg for conventional producers; 2) the second-class fruits with apple diameters between 65– 75mm and the sales price is 2.42 yuan/kg for cooperative producers compared with 1.95 yuan/kg for conventional producers; 3) the cull/defective fruits with apple diameters below 65mm and the sales price is 1.39 yuan/kg for cooperative producers compared with 0.94 yuan/kg for conventional producers. © 2014 The Authors Annals of Public and Cooperative Economics © 2014 CIRIEC


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Table 2 – Description of transaction costs-related variablea Variable description

Variable code

Questions

Information costs Time to know market information

TTI

Time to look for potential buyers

TTF

Expenditure on agricultural fairs

EOF

How long did you spend on obtaining market price information prior to sell apples every year? (hours) How long did you spend on looking for potential buyers every year? (hours) How much did you spend on attending agricultural fairs every year? (yuan)

Negotiation costs Time to fix trading price and place

TTN

Time to grade products

TTG

Enforcement cost Time to wait for the full payment

TTW

Expenditure on selling apples

EOS

Loss of buyers’ breaking the contract

EOB

Transportation costs Apple damage caused by poor road condition Expenditure on transportation

EOD EOT

How long did you spend on negotiating with trading buyers prior to sell products every year? (hours) How long did you spend on grading apples before trading with buyers every year? (days) How long did you averagely wait for being fully paid after each transaction every year? (days) How much did you spend on treating the buyers during the sales process every year? (yuan)b How much did you lose caused by buyer’s breaking the contract every year? (yuan) What percentage of apples was damaged or rotten transporting to the sales sites every year? (%)c How much did you spend on transporting apples to sales sites including gasoline, labor use, repairing the transportation vehicles? (yuan)d

Note: a all the data are assessed in 2010. That is the unit of each variable is measured by every year. b Costs of receiving apple buyers include the expenditure on accommodations, food, cigarette, etc. c In order to monetary the loss of transporting apples to the trading sites, we calculate the apple loss caused by the poor road condition as follows: EOD = Pr oduction × Pr ice × Per centage, where pr oduction is the volume of the total apple production in 2010, pr ice represents the average apple price in 2010, per centage denotes the percent of the average damaged and rotten apples during transporting process. d the calculation of expenditure on transportation is: EOT = T r anspor tation cos t per time × total tr anspor ting times per year . The EOT is zero if the trading site is the apple orchard.

etc.) and with whom trade apples, the time spending on searching the information can be seen as part of transaction costs, that is information cost. Indeed, producers face price uncertainty since they may not know in advance what price they will receive before final product delivery (Royer, 2011), thus, knowing the price information prior to transaction can be helpful for small-scale producers to reduce the price lost caused by price uncertainty and information asymmetry. In our questionnaire, thereafter, information cost is measured by three aspects: 1) time to know the market price-related information prior to entering sales process (TTI); 2) time to look for potential buyers (TTF); 3) expenditure on agricultural fairs (EOF). Knowing the prices in different sales outlets before transaction can allow producers to make an optimal decision about where to sell. Basically, apple producers in China have various ways obtaining price information, i.e., local technical service department, cooperatives, apple agents, neighbors, as well as public broadcasts including television, newspapers (agricultural channels and agricultural columns), and internet, etc. © 2014 The Authors Annals of Public and Cooperative Economics © 2014 CIRIEC

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Noting that the expenditure on agricultural fairs is also considered as a way to obtain the latest agricultural information in the questionnaire, however, only 25.5 percent of cooperative producers and 16.8 percent of conventional producers said they had been to agricultural fairs in the survey year 2010. Moreover, considering the ratio of cost on agricultural fairs to the total production costs is only 0.38 percent for CPs and 0.29 percent for CVs, thus we assume the information cost-related variable-expenditure on agricultural fairs-have insignificant effect on producer’s cooperatives participatory decision. That is variable EOF is neglected in the probit model.

4.2

Negotiation costs

The perish ability of the harvest and the small scale family farm put apple producers in a weak bargaining position when negotiate with trading partners. In other words, apple producers in China have little negotiation power in the up-and downstream agricultural market chain. The small apple transaction quantities and the limitation of transportation conditions result in poor negotiation position. Specifically, the transaction quantities with individual producers based on family-planting only accounts for a small proportion of apple buyers’ source of supply. Particularly, the harvest is easily to be substituted by other grower’s harvest because of the similar apple variety and quality within a certain region. It thus forms an atmosphere of more apple producers with less potential buyers which comparatively put small-scale apple producers in a passive bargaining position. The apple buyers generally take the market negotiation power to fix the price and control the delivery time. Therefore, producers who sell apples to agents or wholesalers are likely to incur quite a different negotiation cost than those who sell apples through cooperatives which internalize this part of transaction cost. We apply variable (TTN) “time to negotiate with available buyers to fix the price and transacting place” as one of the indicator to estimate negotiation cost. As discussed previously, the downstream partners of the value chain usually get the bargaining power associating with products trading prices, and combining with the field discussion, most of apple producers prefer to trade with the buyers with whom they have traded in the previous year. Thus it only takes several minutes for apple producers to make a phone call contacting the potential buyers in sample regions. In addition, variable (TTG) “time to grade products” which is barely mentioned in the literatures, is been considered as a vital part of negotiation cost. Apples are usually packed according to different purchase standards for grades prior to sell. It is explicit that apple prices go up with the apple size increase. Although grading apples before selling can benefit for producers on promoting apple values and increasing apple income, the process of grading apple is a time and labor consuming activity which are strongly complaint by conventional producers based on our field discussion. Conversely, for cooperatives producers, the grading work is usually done by the help of cooperatives. Thus, the magnitude of variable TTG is supposed to be lower for cooperatives producers than for conventional producers, and variable TTG is expected to be positively related to producer’s cooperatives participatory behavior. © 2014 The Authors Annals of Public and Cooperative Economics © 2014 CIRIEC


4.3

245

Enforcement costs

Producers face behavioral uncertainty from unbalanced bargaining power and temporal specificity due to the perishable nature of products, which translated into contractual commitment and enforcement uncertainties (Royer, 2011). In our study, enforcement cost is scaled from three aspects: 1) time to wait for the full payment (TTE); 2) expenditure on selling apples (EOS); 3) loss of buyer’s breaking the contract (EOB). The variable (TTW) is supposed to be shorter for conventional producers than for cooperatives producers since the conventional producers trade apples directly with agents or wholesalers, and require the buyers to make instant payments on delivery. For cooperatives producers, they always get the payment after the cooperatives selling most amounts of the products. Although there is a relatively long time postpone to be fully get paid, cooperative producers said that they accepted this delay due to their highly degree of trust in cooperatives. This can be confirmed by the survey data that only 2.7 percent of cooperative producers are not trust in cooperatives. In combination with the survey, what is interesting is to note that apple producers need to cover the accommodation for trading partners during the period of delivery. The apple wholesalers or agents are not locally but from other provinces involving Chengdu, Chongqing, Guangzhou, etc. where are not suitable for apple planting. Thus, apple producers would provide accommodation for those buyers. The cost varied according to the time of delivery process. The longer sales process is, the higher expenditure would be. Generally, this cost could be extremely higher for conventional producers than for cooperatives producers. One more predominant enforcement cost which should be considered is an uninsured risk of breaking the contract (EOB) due to information asymmetry. It could be interpreted as the risk bearing capability of producers. The comparison of the magnitude of the variable between cooperative and conventional producers, to a certain extent, can reflect the possibility of the cooperatives to reduce transaction costs linked to risk. In practice, producers bargain and make deals with transacting partners about the product price and the trading site before delivering. That is, the transaction is between individuals who have little knowledge of one another and who neither trust nor care about one another’s wellbeing. This transaction way makes the individual and smallscale producer particularly vulnerable to a risk of potential buyer breaks the deal when the market price is lower than the bargaining price. Formal agricultural contracts could be crucial instruments for guaranteeing producers from the risk. While the fact is that the ratio of producers signing formal contract with buyers is less than 10 percent in our observatory regions. The extremely lower contract rate can be attributed to two aspects according to the field survey data. First, more than half of the observations think their annually trading amount of products to be too small to sign a contract. On the other side, buyers’ unwillingness to sign contracts with producers could be also the explanation. For cooperative producers, cooperatives are the risk bearer instead of their members. Producers participating in cooperatives can largely improve their risk bearing capacity since they can transfer the loss caused by buyer’s breaking the contract to cooperatives. Therefore, it is expected to be higher for conventional producers to take the loss caused by EOB than for cooperative producers. © 2014 The Authors Annals of Public and Cooperative Economics © 2014 CIRIEC

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4.4


Transportation cost

Transportation cost can be perceived as part of transaction costs if they are specific to a market channel (Hobbs, 1997). In this paper, we particularly investigate and make the comparison of producer’s market participatory behavior between cooperative and non-cooperative market channel. Thus, the transportation cost is also taken as an essential part of transaction costs. Characteristics of transportation costs are estimated by two variables: 1) apple loss due to the poor transportation conditions and bad cold storage facilities (EOD); 2) the expenditure on gasoline, labor use, and vehicle repair (EOT). Variable (EOD) is supposed to be higher for conventional producers than for cooperatives producers. The reasons can be attributed to the provision of cooperatives services associating with products’ cold storage to reduce the rotten rate and better transportation vehicles to lower the damage rate of apples for their members. Also variable EOD is assumed to positively affect producer’s cooperative participatory decision. Referring to variable EOT, the magnitude of this cost is supposed to be lower for cooperatives producers than for conventional producers. According to field discussion, cooperatives would provide transportation service for their members, and also suggest wholesalers /agents who travel around local villages in search of apples to trade with producers at the apple orchard even though its grower-members prefer not to trade with cooperatives. Thereby cooperative producers can save more transportation cost than conventional producers who have to transport apples to the trading site by themselves. Thus, the expected impact sign of this variable is positive. Moreover, the questionnaire-base survey result reveals that apple producers are prone to sell the majority of products to one trading partner for one time even if the trading price would be lower than the market price for the purpose of saving enforcement cost and transportation cost. Since the risk of buyer’s breaking the contract rises with increasing of the number of trading partners and the transportation cost goes up with the growing of transaction frequency.

5

Results

5.1

Production costs measurement

Prior to the estimation of transaction cost, the mostly mentioned costs by producers are the traditional production costs including rent, labor use, fertilizers, chemical pesticides, plastic or paper bags, as well as other costs, such as herbicides, plastic sheeting, etc. Therefore, the traditional production costs of both groups under considerations are calculated. Figure 3 depicts that cooperative producers spend more on each traditional production item than conventional producers, whereas the subtype of transaction cost for cooperative producers is lower than for conventional producers. In fact, producers with higher investment in agricultural inputs, especially in fertilizers, apple bags and labors, gains more benefit from apple farm activity based on our field discussion. Specifically, © 2014 The Authors Annals of Public and Cooperative Economics © 2014 CIRIEC


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Figure 3 – Comparisons of production and transaction costs between cooperatives and conventional producers, 2010. Note: CP = Cooperative producers, CV = Conventional producers, IC = Information cost, EC = Enforcement cost, TRC = Transportation cost.

fertilizers provide the necessary nutrients for plant growing, to protect apples from pesticides; plastic or paper bags is helpful to reduce the residual of chemical pesticides, to improve the color of apples, and also to prevent apple fruits from insects/pests; labors are hired to pruning apple trees, spraying pesticides, bagging apple fruits, etc. With respect to the subtype of transaction costs, cooperative producers have lower transaction costs than conventional producers since cooperatives provide services related to the available of market information, to sell products of members at a higher price than market price, to buy agricultural inputs in bulk with a discount for members, to transporting products for members, etc. These services greatly decrease the transaction costs of producer-members in cooperatives.

5.2

Transaction costs measurement results

The estimation results of the magnitude of each transaction cost-related subtype are illustrated in table 3. Totally, the magnitude of eight subtypes of transaction costs in ten is lower for cooperative producers than for conventional producers except two variables – time to obtain market information and time to fully get paid. Cooperative producers averagely saved more than a thousand yuan (1085.47 yuan) than conventional producers; whereas the time-related transaction costs are greater for cooperative producers (123.21 hours) than for conventional producers (45.12 hours) which primarily attributed to the long time waiting for being fully paid. Specifically, cooperative producers spent 0.41hours more on obtaining market prices information than conventional producers. It implies that cooperatives may not provide sufficiently useful or latest price-related information for their members. Thus, © 2014 The Authors Annals of Public and Cooperative Economics © 2014 CIRIEC

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Table 3 – Transaction costs of apple producers in shaanxi, 2010

Information cost Time to know information Time to search buyers Cost on agricultural fairs Negotiation cost Time to fix price and place Time to grade products Enforcement cost Time to get full payment Expenditure on selling apples Loss of breaking the contract Transportation cost Apple damage caused by poor road condition Expenditure on transportation Total cash cost Total time cost

Percent (%)

CV

DFc

Variable

Unit

CP

Percent (%)

TTI TTF EOF

hours hours yuan

0.76 0.08 19.70

0.6a 0.06a 4.79b

0.35 0.39 27.40

0.78a 0.86a 1.83b

0.41 −0.31 −7.70

TTN TTG

hours hours

0.02 3.15

0.02a 2.56a

0.17 11.25

0.38a 24.93a

−0.15 −8.10

TTW EOS EOB

daysd yuan yuan

14.9 9.04 44.35

96.75a 2.20b 10.79b

4.12 187.28 791.6

73.05 12.51b 52.89b

10.78 −178.24 −747.25

EOD

yuan

200.33

48.72b

263.03

17.57b

−62.70

EOT

yuan yuan hours

137.74 411.16 123.21

33.50b 100.00 100.00

227.32 1496.63 45.12

15.19b 100.00 100.00

−89.58 −1085.47 78.09

Note: a percent = the data of the element of the different transaction cost which the unit is hours/total time cost;

percent of TTWCP =

14.9 × 8 × 100% = 96.75%; 123.21

73.05 × 8 × 100% = 73.05%. 45.12 b percent = the data of the element of the different transaction cost which the unit is yuan/total cash cost; c DF denotes the difference value between cooperatives and conventional apple producers; d 1 working day = 8 hours

percent of TTWCV =

cooperative producers have to turn to other sources to obtain price information. The subtype of enforcement cost-time to be fully paid-is also averagely 11 days higher for cooperative producers than for conventional producers. This is probably because of the way cooperatives paying for their members. Indeed, cooperative producers accept the delay of payment due to their highly degree of trust in cooperatives on the basis of field discussion. Referring to enforcement cost, the exceptionally advantages of cooperatives producers were verified. As a member of cooperatives, apple producer averagely saved about 178.2 yuan on buyers’ accommodation and 747.3 yuan on the loss caused by buyer’s breaking the contract. Conventional producers have to cover the expenditure (187.3 yuan) since they directly trade apples with buyers. Whereas cooperative producers can avoid this cost as they transact with cooperatives whose key function is to service members to sell products. Moreover, the most costly part of transaction cost for cooperative producers is the transportation cost caused by bad road condition and poor storage facilities (48.7 percent) compared with 17.6 percent for conventional producers, while the cost incurred by buyer’s breaking the contract accounts for 52.9 percent of the total transaction cost for conventional producers, compared with 10.8 percent for cooperatives producers (Table 3). © 2014 The Authors Annals of Public and Cooperative Economics © 2014 CIRIEC


5.3

249

Transaction cost analysis of scale

Given the heterogeneity of producers across to the scale of apple cultivation related to apple quality, productivity, negotiation power, risk bearing ability, and competitive capability, we assume that there would be distinctions of transaction costs among various scales of apple producers for both cooperative and conventional ones.3 In practice, small-scale producers care only about obtaining a higher trading price (Banerjee, et al., 2001), they would withdraw from cooperatives or turn to other trading partners (e.g., wholesalers, agents, processors, etc) if they thought the price cooperatives offered is lower than market prices. Whereas for large-scale producer-members, except for the trading price, they also consider the share of revenues4 depending on their transact amount with cooperatives. Thus, different groups of producers across apple orchard farm scale might benefit distinctively from participating in cooperatives. Thereby, an extensive comparison of the magnitude of each element of transaction cost between cooperatives and conventional producers is present in Table 4. Producers with large apple farm size spend more time on acquiring market price information for both cooperative and conventional producers. It implies that the price information becomes more important for producer with the enlargement of apple orchard size. The information cost-related item in Table 4 also shows that the larger apple farm scale is, the more producers spend on attending agricultural fairs. With respect to negotiation cost, as expected, time to grade apples (TTG) is shorter for cooperative producers than for conventional producers regardless of their apple planting scale. And it is extremely high for large scale conventional producers (33.1 hours) compared with only 3.4 hours for cooperatives producers with the same scale. Associating with the time to fix trading price and place (TTN), there is little differences between cooperative producers and conventional producers of various scale except for the largescale conventional producers. They spend relatively much more time (approximately 4 hours) on negotiating with trading partners. The result imply that large-scale conventional producers pay much attention to negotiate with buyers about the prices and transaction place since the better trading place, i.e., apple orchard, producer’s home, reduces the transportation cost. In terms of time to wait for the full payment (TTW), it is easy to understand that cooperatives always pay for their members together after they sell most of products. Thus cooperative producers get paid at the same period irrespective of their apple farm scale. The data in Table 4 shows that small-scale conventional producers have to wait for more than 5 days to be fully paid, followed by the large- and medium-scale producers

3

The statistical results employing SPSS shows that the cumulative frequency and cumulative percentage of producers with apple farm size lower than 3 mu and higher than 6 mu are located at the peak points in the cumulative distribution of the total samples. Therefore, apple producers are grouped into three categories based on the apple farm size: small-scale (0.1mu∼3.0 mu), medium-scale (3.1 mu∼6.0 mu), and large-scale (>6.0 mu). 4 The share of revenues is distributed to grower-member according to his/her transaction quantities with cooperatives. Specifically, member with higher transaction quantities of apple fruits with cooperatives has greater share of revenues compared to those with lower products trading volumes. © 2014 The Authors Annals of Public and Cooperative Economics © 2014 CIRIEC

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Table 4 – Transaction cost of apple producers by scale, 2010 Variable description

Variable code

Unit

TTI

hours

TTF

hours

EOF

yuan

TTN

hours

TTG

hours

TTW

days

EOS

yuan

EOB

yuan

EOD

yuan

EOT

yuan

TCC

yuan

Information cost Time to know market information

Time to look for potential buyers

Expenditure on agricultural fairs

Negotiation cost Time to fix trading price and place

Time to grade products

Enforcement cost Time to wait for the full payment

Expenditure on selling apples

Loss of buyers’ breaking the contract

Transportation cost Apple damage caused by poor road condition Expenditure on transportation

Total Cash Costa

Scale

CP

CV

DF

S M L S M L S M L

0.51 0.69 1.74 0.06 0.10 0.04 6.22 18.75 19.02

0.09 0.30 0.48 0.33 0.51 0.28 30.31 33.69 56.25

0.42 0.39 1.26 −0.27 −0.41 −0.24 −24.09 −14.94 −37.23

S M L S M L

0.02 0.02 0.02 2.73 3.50 3.37

0.04 0.07 3.99 7.59 12.03 33.13

−0.02 −0.05 −3.97 −4.86 −8.53 −29.76

S M L S M L S M L

16.94 12.29 16.56 7.20 10.82 9.38 82.00 20.41 0

5.23 2.00 3.75 171.31 203.78 337.50 803.13 773.17 750.00

11.71 10.29 12.81 −164.11 −192.96 −328.12 −721.13 −752.76 −750.00

S M L S M L S M L

143.94 130.20 420.81 98.80 130.61 281.25 310.79 730.46 338.16

198.52 478.07 440.69 191.06 303.41 172.50 1792.12 1756.94 1394.33

−54.58 −347.87 −19.88 −92.26 −172.80 108.75 −1056.17 −1481.33 −1026.48

Note: S = Small scale; M = Medium scale; L = Large scale a Total Cash Cost = EOF + EOS + EOB + EOD + EOT

waiting for about 4 days and 2 days, separately. It also implies a weak bargaining position of small-scale producers trading with downstream partners. The distinctions of the expenditure on sales process (EOS) are obvious for conventional producers of different planting scales. The cost grows with the inclination of apple farm size (Table 4). Particularly, the large scale conventional producers pay for 337.5 yuan annually. The comparatively huge differences of EOS (328.1yuan/year) between cooperative and conventional producers with the same farm scale have an implication of the benefit of large-scale producers joining in cooperatives to save part of the enforcement cost. © 2014 The Authors Annals of Public and Cooperative Economics © 2014 CIRIEC


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With reference to the loss of buyer’s breaking the contract (EOB), it is over 700 yuan/year higher for conventional producers than for cooperative producers regardless of the scale. It also reveals a declination of EOB with the increase of apple farm size. It makes sense that the smaller farm size of producer is, the lower negotiation power is, the higher probability of buyer’s breaking the contract, and thereby the more loss is.5 According to our field discussion, the conventional producers always prefer to make an unofficial contact (handshake agreement) with buyers before selling products. The main reason of not signing an official contract is the complex procedure and the small transaction quantities of products as they said. Therefore, the handshake agreement brings huge uncertainty of the final transaction and enlarges the probability of buyer’s breaking the agreement due to the weak guarantee. In other word, buyers often pay less than the agreement price if the market price drops, and pay the same price in the agreement if the market price rises. Consequently, producer is the one suffering the loss in both situations. Note that for large scale cooperatives producers, EOB is zero which also reveals a strong negotiation power and a dominant position in apple transaction. Hence, being a cooperative member can largely lower the risk and thereby reduce the loss of buyer’s breaking the contracts. The measurement results of each subtype of transaction cost by apple planting scale claim that conventional producers with medium apple farm scale could save more transportation cost (i.e., apple damage caused by poor road condition and the expenditure on transporting apple to sales sites) than the large- and small-scale ones if they participate in cooperatives. This can be attributed to two reasons. One, the apple transact quantities of small-scale conventional producers is relatively less than the mediumand large-scale ones. Thus, the apple loss incurred by the poor road condition is also small given the same road condition faced by various scale of producers and the measurement way of EOD. Additionally, for large-scale conventional producers, they have comparatively higher bargaining power due to their great trading quantities. Therefore, they can individually negotiate with buyers to transact products at the apple orchard or ask the buyers to cover part of the transportation cost. Thereby, the medium size of conventional producers would be the most benefited group if they participate in cooperatives. On the whole, results estimated by apple farm scale present that the medium scale (3.1 mu∼6.0 mu) producers would be the most beneficial ones from participating in cooperatives (1481.3 yuan/year), followed by small-scale producers (1056.2 yuan/year). The large-scale producers comparatively benefit the least which is around 1026.5 yuan/year.

5.4

Empirical results

A binary probit model is employed to investigate the influents on producer’s cooperatives participatory decision. The regression results demonstrate statistically positive relations between producer’s cooperative participatory decision and the farm characteristics including the academic educational years, apple income and apple production. The 5

Noting that although the transacting amounts of small-scale conventional producers is relatively lower than medium- and large-scale ones, the loss caused by breaking the contract is still greater attributed to the higher probability of breaking the agreement.


252


Table 5 – Regression results

Producer demographics & farm characteristics Age Educational attainment Apple planting acreage Apple income Apple production Information costs Time to know market information Time to look for potential buyers Expenditure on agricultural fairs Negotiation costs Time to fix trading price and place Time to grade products Enforcement cost Time to wait for the full payment Expenditure on selling apples Loss of buyers’ breaking the contract Transportation costs Apple damage caused by poor road condition Expenditure on transportation constant McFadden R-squared

Variable

Coefficient

Std. Err.

Prob.

AGE EDU APA AIN APR

−0.0128 0.6383∗∗ −0.2550 0.0003∗∗∗ 0.0006∗∗∗

0.0477 0.2838 0.3485 0.0001 0.0002

−0.2692 0.0245 0.4643 0.0000 0.0003

TTI TTF EOF

0.2374 −2.3909 −0.0105

0.7906 1.4899 0.0110

0.7640 0.1086 0.3380

TTN TTG

−3.6774 −0.4799∗∗∗

5.0424 0.1219

0.4658 0.0001

TTW EOS EOB

0.4894∗∗∗ 0.1813 −0.0078∗∗∗

0.1062 0.1382 0.0018

0 0.1894 0

EOD EOT C 0.8546

−0.0031 −0.0028∗∗ −5.3506

0.0020 0.0013 4.2250

0.1197 0.0254 0.2054

Note: ∗∗ , and ∗∗∗ denote significance at the 5%, and 1% levels, respectively.

results can be also confirmed by the data in Table 1. With reference to transaction costrelated elements, three variables-time spending on grading apples (TTG), loss of buyers’ breaking the contract (EOB), and the expenditure on transporting apples to trading places (EOT)-are statistically different from zero at the 1% and 5% level, separately. The negative coefficients suggest that producer’s cooperative participatory decision is affected in opposite directions by the three variables. The result is similar as indicated by Ouma et al. (2010) that transaction costs related to transportation have significant negative influence on producer’s market participation. Whereas variable-time to be fully paid (TTW)-has statistically positive relation to producer’s participatory behavior. The findings are also clearly in consistent with the statistical data in Table 1 that cooperative producers spent less time on grading apples, lower apple loss due to the poor road condition during the transporting process and the buyer’s breaking the contract, as well as much longer time to wait for the full payment.

6

Conclusions

This article mainly focuses on developing a monetary analyzing method of transaction cost and investigating the transaction cost-related influence on producer’s cooperative participatory decision, taking apple producers in rural northwestern China as an example. Overall, the quantified results of each transaction cost-related item suggests that cooperative producers can annually save 1085.5 yuan transaction cost compared with conventional producers. Particularly, results of scale highlight that the medium © 2014 The Authors Annals of Public and Cooperative Economics © 2014 CIRIEC


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scale apple producers would be beneficial most from being a member in cooperatives compared with the small- and large-scale groups. Not surprisingly, the individual and conventional producers in China are faced relatively higher transaction costs, especially the enforcement and transportation costs, compared with cooperatives members. Policies associated with encouraging mediumscale producers to participate in cooperatives are strongly recommended as they would be the most benefited ones compared with small- and large-scale producers. On the other hand, our study results also reveal several disadvantages of cooperatives primarily related to the inefficiency of market information provision service for members and the long time delay of payment for member’s products. Thus, refreshing the service ability to encourage producer’s participatory behavior and improving the role of cooperatives in reducing transaction costs should be done simultaneously. In practice, cooperatives should focus on improving services related to market information in the way of using internet (e-commerce) technology, printing agricultural newspapers or posters, and organizing members participating in agricultural fairs or exhibitions, etc. to reduce member’s information cost. The establishment of an efficient operational system of cooperatives also needs to be implemented for the purpose of shortening the delay of payment for their members, and thereafter to lower enforcement cost. Finally, we highly suggest policymakers develop supporting programs referring to infrastructure construction to improve the local road condition and access to telecommunication, and being coupled with subsidizing cooperatives to purchase cold storage facilities to reduce producer’s transportation cost.

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