387KHON KAEN AGR. J. 43 (2) : 387-398 (2015). KHON KAEN AGR. J. 43 (2) : 387-398 (2015).แก่นเกษตร 43 (2) : 387-398 (2558).

An empirical analysis of smallholder farmers in the supply chain: A case study of navel orange farmers in Gannan, China

Rao Zhiwei1, Christopher Gan2*, Satit Aditto1 and Yaowarat Sriwaranun1

ABSTRACT: The objectives of this paper are to identify the constraints confronting smallholder farmers in the supply chain, and to investigate the relationship between the constraints and the farm and farmer characteristics. The study utilised survey data collected from smallholder navel orange farmers in Gannan, which is the largest navel orange region in China. The smallholder farmers’ constraints were assessed using factor analysis and multiple regressions. The result provides a thematic summary of the farmers’ perceptions on the constraints. Results of the study reveal that the major constraints confronting smallholder navel orange farmers are marketing, transportation and product competitiveness. The results also reveal that most of the farm and farmers’ characteristics such as number of trees, total yield, and education level were inversely related to the constraints confronting the farmers in the supply chain. Based on the relationship between the constraints and farmers’ socioeconomic characteristics, some suggestions including cultivation technology training reinforcement, organization construction, information platform integration, and agricultural insurance is provide to overcome the constraints confronting smallholder navel orange farmers. Keywords: Smallholder farmers, Supply chain, Constraints, Gannan

1 Department of Agricultural Economics. Faculty of Agriculture. Khon Kaen University, Thailand2 Department of Accounting, Economics and Finance, Faculty of Commerce, Lincoln University, New Zealand* Corresponding author: christopher.gan@lincoln.ac.nz

Introduction

In today’s competitive global market, the

nature of business competition is changing from

company versus company to supply chain versus

supply chain (Towers and Burnes, 2003). Supply

chain is a system of organizations, people,

activities, information, and resources involved in

moving a product or service from supplier to

customer (Bowersox, Closs and Cooper, 2002).

Without supply chain, suppliers do not have the

ability to give customers what, when and where

they want.

Supply chains play an important role in

agriculture in providing access to markets for

producers for local, regional and export markets.

Lambert and Cooper (2000) pointed out the

supply chains in agriculture transform a

commodity system organized via spot markets

towards a vertically coordinated system. Such

changes lead to competition between supply

chains in agriculture rather than competition

between individual firms. Ragatz et al. (1997)

noted that the effective integration of farmers into

product supply chains would be a key factor for

industries to achieve the improvements necessary

to remain competitive. Genier, Stamp and Pfitzer

(2008) further revealed better integration of the

farmers into the supply chain in agriculture is

significant to the sustainable development of

agriculture.

The different constraints confronting the

smallholder farmers in the supply chain are

documented in the literature. Marsh and Runsten

(1996) commented that the greatest problem for

smallholder farmers is lack of information about

388 แก่นเกษตร 43 (2) : 387-398 (2558).

market opportunities. Gadde and Snehota (2001)

revealed that millions of smallholder farmers are

at the bottom of agricultural supply chain in Asia

because they have less connection to outside

markets and suffer from low profitability.

The supply chains in China are experiencing

a more rapid development than anywhere in the

world (Hu, Xie and Qiu, 2004). However, Chinese

supply chains in agriculture consist of millions of

smallholder farmers, who are not well structured

and organized in the chain (Zhang and Aramyan,

2009). It is estimated that about 87% of the world’s

500 million small farms are in Asia and the Pacific

region. China accounts for 193 million small farms,

and 95% of the farms are smaller than 2 hectares

(Hazell et al., 2007). Following World Bank (2003),

smallholder farmers is defined as farms with 2

hectares (1 hectare = 15 mu) or less in this study.

Gannan is the largest navel orange planting

region in China, and the third largest producer in

the world. There are 260,000 households with a

total number of 730,000 people engaged in the

navel orange industry. Most of the navel orange

farmers are smallholder farmers due to China’s

land allocation system. The People Government

of Ganzhou (2013) reported that the present

problem in the navel orange farms is high

production with low benefit. Smallholder farmers

as input suppliers are the most direct non-

beneficiary because they lack of pricing rights in

the supply chain (Sahin and Robinson, 2005).

Zhang and Aramyan (2009) pointed out that over

the three decades of market liberalization since

China’s policy of reform and opening up, it has

been suggested that the most challenging task in

the agricultural supply chains in China is to

integrate millions of the smallholder farmers into

the chains.

In an effort to better understand the supply

chain integration issue, it is important to

understanding the difficulties of smallholder

farmers in the supply chain. Therefore, this

research attempts to investigate the constraints

confronting the naval orange smallholder farmers

in the supply chain in Gannan. This study also

investigates the relationship between the

constraints and the farm and farmers’ characteristics.

The remainder of the paper is organized as follow.

Section 2 discusses the survey design and data

collection. Section 3 discusses the empirical

results and the conclusion and suggestions are

summarized in Section 4.

Methodology

Survey Design

A structured questionnaire was used to

collect relevant data from smallholder navel

orange farmers in Gannan. The questionnaire

consists of three sections. Section one addresses

the general farm information. Section two identifies

the constraints confronting smallholder navel

orange farmers in the supply chain. The last

section addresses the demographic and socio-

economic characteristics of the smallholder navel

orange farmers. After a pilot tested on a sample

of 50 farmers, a total of 400 smallholder navel

orange farmers in Gannan were interviewed with

convenience sampling.

389KHON KAEN AGR. J. 43 (2) : 387-398 (2015).

Methods

The survey data were analyzed using three

methods. The farm and farmer characteristics

were described by descriptive statistics. Factor

analysis was used to reduce the items into a more

manageable number of “underlying” factors. It is

then used to identify the underlying constraints

confronting the smallholder farmers in the supply

chain. The relationships between the socioeconomic

variables and the factors extracted from the factor

analysis were examined using multiple regression.

Results and Discussion

Socioeconomic Characteristics of the Farmers

The household and farm characteristics of

the respondents are presented in Table 1. The

results showed 81.6 percent of the respondents

were between 36 and 55 years old, and 12

percent were over 55 years old. The highest

education level of the farmers is vocational school,

which accounts for 1.3 percent while 98.7 percent

graduated with a high school education or lower.

A higher educated farmer was expected to better

perform in terms of cultivation technology and

marketing channel. The average navel orange

farming experience of the farmers was 9.58 years,

and 85 percent of the farmers’ farming experience

was between 6 and 10 years. The average farm

size of household is 11.72 mu (0.78 ha). Consistent

with the small farm size, majority of the farmers

have a limited number of navel orange trees with

an average of 636.21 trees. The annual yield was

33,316.06 kg. With regards to sales, 67 percent

of the farmers sold their products below 2 RMB/

kg. The net farm income of the respondents was

average 44841.18 RMB, with 46.5 percent

between 30,000 and 50,000 RMB. The result

shows majority of the household income is more

than 40,000 RMB. Furthermore, approximately

31.3 percent of the respondents worked off-farm.

They temporarily work at factory and building site

in slack farming season.

Perception of Farmers on Survey Measures

Table 2 summarizes the results of the

smallholder navel orange farmers’ perception

scores on individual survey items. The five highest

score items are “High labor cost”, “High production

input cost”, “Poor new planting technology

extension”, “Little resistance to climate change”,

and “Poor biological pest control technology

extension”. The mean score ranges from 4.66 to

4.42.

The survey results showed that rising “labor

costs” and “production inputs” have increasingly

become a major concerned among smallholder

farmers in Gannan. Compare to the increase in

planting costs, the sale price of Gannan navel

orange exhibited a downward trend. This

discourages the smallholder farmers’ to plant

navel oranges because higher output is not

accompanied by higher profit. This low profit

results is declined growth rate in the planning

areas and annual yields over the years. A major

reason is heavy migration to the city. Young

people (especially productive ones) prefer to work

in city instead of farm work.

390 แก่นเกษตร 43 (2) : 387-398 (2558).

The constraints related to “poor new planting

technology extension” and “poor biological pest

control technology extension” were ranked third

and fifth. This is probably due to smallholder

farmers often have low education level, which can

be a serious obstacle in accessing useful

technological knowledge. Marsh and Runsten

(1996) documented that larger producers could

hire professional experts to advise them, or

outsourcing to experienced managers. But

smallholder farmers generally lack of the funds

and technical assistance. “Little resistance to

climate change” is one of the most important

constraints that farmers are concerned with

(a mean score of 4.49). This reflects that

smallholder farmers’ lack of agricultural insurance

to reduce their losses when they suffered from

natural disaster.

The five lowest score items are “unrestrained

use of chemical fertilizer and insecticide”, “lower

high-quality fruit ratio”, “reneging on the supply

contracts”, “limited regional advantage”, and

“poor brand uniform construction”. The mean

score ranges from 2.40 to 2.75.

The constraint related to “unrestrained use of

chemical fertilizer and insecticide” was ranked

the last with a mean score of 2.40. The reason is

probably due to the smallholder navel orange

farmers who did not think the chemical or

insecticide was unrestrained used because

almost all smallholder navel orange farmers apply

chemical in a similar way. The mean score of

“lower high-quality fruit ratio” is 2.63. This is

because smallholder farmers did not classified

the navel orange into different quality grade.

According to Yin (2007), smallholder farmers

receive less profit due to lack of preliminary

processing, and intermediaries who benefit this

revenue through their own grading and selection

efforts.

The mean score for “reneging on supply

contracts” is 2.70, which reflects the case was not

widespread happened to the smallholder navel

orange farmers. This result is confirmed by Marsh

and Runsten (1996), where some smallholder

farmers renege on the supply contract to sell to

other intermediaries because of higher price.

Smallholder navel orange farmers in Gannan are

not widely accept the constraints of “limited

regional advantage” and “poor brand uniform

construction”, because these constraints do not

impact the smallholder farmers directly. Peng

(2007) revealed the navel orange brand building

is in a backward state, and described the brand

has become the crux factor in marketing.

391KHON KAEN AGR. J. 43 (2) : 387-398 (2015).

Table 1 Household and farm characteristics of sampled farmers (n = 400)

Item Mean Frequency Per. Item Mean Frequency Per.

Gender

Male

Female

Age groups

Less than 25 years

old

26-35 years old

36-45 years old

46-55 years old

Over 55 years old

Highest education

Illiterate

Primary school

Secondary school

High school

Vocational school

Off-farm work

Yes

Household sizes

2 Persons

3 Persons

4 Persons

5 Persons

Over 5 Persons

Farming experience

Less than 10 years

6-10 years

11-15 years

Over 15 years

9.58

383

17

7

19

153

173

48

12

80

184

119

5

125

15

29

143

185

28

9

340

46

5

95.7

4.3

1.7

4.7

38.3

43.3

12

3.0

20.0

46.0

29.7

1.3

31.3

3.7

7.3

35.7

46.3

7.0

2.3

85.0

11.5

1.2

Farm size

Less than 10 mu

11-20 mu

Over 20 mu

Number of trees

Less than 500 trees

501-1,000 trees

Above 1,000 trees

Annual yield

Less than 10,000 kg

10001-30000 kg

30001-50000 kg

Above 50000 kg

Sale price

Less than 2 RMB/kg

Above 2 RMB/kg

Net Farm income

Less than 10,000 RMB

10001 to 30000 RMB

30001 to 50000 RMB

50001 to 70000 RMB

Above 70001 RMB

Household income

Less than 20,000 RMB

20001 to 40000 RMB

40001 to 60000 RMB

60001 to 80000 RMB

Above 80000 RMB

11.72

636.21

33316.06

2.02

44841.18

262

117

21

232

139

29

31

186

144

39

268

132

25

77

186

77

35

14

24

157

124

91

65.5

29.3

5.2

58.0

34.8

7.2

7.8

46.5

36.0

9.7

67.0

33.0

6.3

19.3

46.5

19.2

8.7

3.5

6.0

39.2

28.5

22.8

392 แก่นเกษตร 43 (2) : 387-398 (2558).

Table 2 Ranking of perceptions of constraints by sampled farmers (n=400)

Respondents’ perception on: Mean SD rank

High labor cost 4.66 .962 1High production input cost 4.64 .962 2Poor new planting technology extension 4.56 1.023 3Little resistance to climate change 4.49 .683 4Poor biological pest control technology extension 4.42 .983 5Lack of contract farming 4.30 .872 6Lack of consistent supply 4.28 .739 7Little resistance to plant disasters 4.23 .547 8Variety simplification 4.15 .710 9Poor cultivation technology 4.11 .784 10Without regular communication 4.10 .729 11Lack of waxing 4.10 .555 11Lack of packing 4.10 1.062 11Less marketing opportunities information 4.09 .868 14Poor agriculture subsidy 4.08 .943 15Lack of market demand information 4.07 .643 16Small scale planting 4.03 .749 17Lack of capital to reinvest 4.01 .897 18Low bargaining power 4.00 .589 19Less sales price information 3.96 .408 20Lack of production knowledge 3.96 .671 20Lack of agriculture insurance 3.94 .924 22Lack of an effective legal system of recourse 3.93 1.123 23Low mechanize level 3.91 .635 24Without preferential land lease policy 3.88 .682 25Lack of core enterprise 3.83 .691 26Lack of sufficient cold warehouse 3.75 .712 27Lack of classification 3.75 .569 27High fresh-keeping cost 3.72 .576 29Lack of organic agriculture 3.68 .863 30Poor traffic infrastructure 3.64 .753 31Orchards worse located 3.56 .607 32Lack of loan support 3.46 .549 33Lack of brand protection 3.34 .742 34Outward appearance difference 2.99 .813 35Poor brand uniform construction 2.75 1.013 36Limited regional advantage 2.72 .832 37Reneging on supply contracts 2.70 .527 38Lower high-quality fruit ratio 2.63 .810 39Unrestrained use of chemical fertilizer and insecticide 2.40 .491 40Notes: Items were rated on a five-point Likert scale (1 - strongly disagree; 2 disagree; 3 - neutral;

4 - agree; 5 - strongly agree)

Factor AnalysisIn this section, nine underlying factors were

extracted, representing 69.8 percent of the total variance in responses, which is higher than the minimum requirement of 60 percent as advocated by Malhotra et al. (1996). The number of factors extracted is based on the eigenvalue over 1 (see Hair et al., 2003). A total of 32 items were

included in one of the 9 underlying grouped factors, with 8 items dropped due to lower factor loading or similar factor loading in different factors. All loadings of the survey items were higher than 0.40. According to Zikmund (2003), the higher the absolute value of the individual factor loading, the more a particular individual factor contributes to the underlying factor. It is

393KHON KAEN AGR. J. 43 (2) : 387-398 (2015).

observed that the factor loadings and the interpretation of the individual factors extracted were reasonably consistent and sufficient.

The constraints measures were analyzed in descending order of significance to determine the underlying constraints that confronted the smallholder farmers. According to Sato (2005), it is necessary to assign an identifiable, collective

label to the groups of individual factors of high correlation coefficients, as each of the underlying grouped factors is an aggregation of individual factors use to explain the factor analysis results. Nevertheless, the suggested label is only subjective, and other researchers may come up with a different label. The results are presented in

Table 3.

Table 3 Results of factor analysis of constraints elements - factor loadings

Fac1 Fac2 Fac3 Fac4 Fac5 Fac6 Fac7 Fac8 Fac9Lack of market demand information .879Less marketing opportunities information

.877

Less sales price information .816Without regular communication .697Low bargaining power .663Poor brand uniform construction -.619Lack of capital to reinvest .609* .426Low mechanize level .583Small scale planting .581Little resistance to plant disasters .560 .556*Lack of contract farming .544* .423High fresh-keeping cost .475Reneging on supply contracts .461Poor traffic infrastructure .852Orchards badly located .817Lower high-quality fruit ratio .763Outward appearance difference .663Unrestrained use of chemical fertilizer and insecticide

.648

Limited regional advantage .510Little resistance to climate change .405 .722*Lack of agriculture insurance .652Poor new planting technology extension

.812

Poor biological pest control technology extension

.719

Lack of brand protection .424* .508Lack of packing .908Lack of waxing .898Lack of core enterprise .842High labor cost .571Poor cultivation technology .787Lack of production knowledge .748Poor agriculture subsidy .726Lack of loan support .707Eigenvalue 9.196 3.278 1.958 1.748 1.499 1.367 1.156 1.140 1.00869.8 percent of variance explainedKMO = 0.852Bartlett’s Test of Sphericity p = 0.000Note: Cronbach’s alphas were 0.815, 0.798, 0.639, 0.705, 0.792, 0.866, 0.604, 0.598, 0.459 for factors 1-9 respectively

394 แก่นเกษตร 43 (2) : 387-398 (2558).

Factor 1 is composed of twelve items

primarily focusing on the constraints in marketing.

The factor loadings on this factor are relatively

large amongst all the items. Smallholder navel

orange farmers always lack of market information

about demand, opportunity, price, and sales

channel. Marsh and Runsten (1996) and Bienabe

et al., (2004) documented that marketing is

usually the main constraint restricting smallholder

farmers in fruit supply chain.

Factor 2 includes two items concerned with

transportation. Most navel orange smallholder

farmers faced transportation problem which

results in the loss of product quality and late

delivery, and poor infrastructure services in

remote rural areas caused the transportation cost

to increase.

Factor 3 comprise of five items with regarding

to product competitiveness. The items indicate

that there is low competition in the market due to

low quantities and qualities of the products. zhang

and Aramyan (2009) and Baloyi (2010) confirmed

that the majority of the smallholder farmers

produce products with irregular outward

appearance, and a lower percentage of high

quality products due to the unrestrained use of

chemical fertilizer and pesticide.

Factor 4 is made up of three items concerned

with natural risks. Smallholder navel orange

farmers in Gannan general ly face high

agricultural risk such as the lack of the ability to

withstand natural calamities. Like Peng (2007)

research, the agriculture insurance system is

urgently needed to build to reduce smallholder

farmers’ economic loss in natural calamities.

Factor 5 focuses on extension. Unlike large

scale farmers, smallholder farmers generally lack

plant technology or technical assistance from

professional experts. Moreover, there are not

enough notable agronomists or sk i l led

technologists to teach the navel orange farms of

smallholder farmers in Gannan. These constraints

seriously hinder the future development of the

industry and the competition in the global market.

Factor 6 is concerned with processing.

Smallholder navel orange farmers in Gannan

mixed together their produce of different size,

maturity, and quality because of small volumes.

The convention is to sell the produce in bunch

with the worst price. As Yin (2007) documented,

this is due to lack of processing which can

increase the added value of the products, and

intermediaries capture the revenue through their

own grading and selection efforts.

Factor 7 is transaction cost. Smallholder

navel orange farmers are excluded from the

supply chain due to the processing enterprises’

sourcing strategies, which are influenced by

consumers’ expectations, the safety and

environmental requirements, as well as labor

standards. Following Jaffee and Morton (1995)

and Fang (2003) research, smallholder farmers

who gain access to the processing enterprises

are in a learning stage, because the processing

enterprises is high standards in terms of cost

reduction, raised quality standards, and

increased delivery speed, which are difficult to

meet the requirements for smallholder farmers.

395KHON KAEN AGR. J. 43 (2) : 387-398 (2015).

Fac to r 8 i s re la ted to techno logy .

Technological innovations have long been a

major contributor to progress in agribusiness and

will continue to influence the smallholder farmers’

performance in the supply chain. Marsh and

Runsten (1996) and Kirsten and Sartirius (2002)

revealed the majority of smallholder farmers face

the problems of poor farm knowledge and

technology.

Factor 9 is capital. Smallholder navel orange

farmers in Gannan are well undercapitalized,

which presents a major barrier to reinvesting or

expanding their farms scale. Yu and Weng (2004)

revealed that smallholder navel orange farmers

in Gannan have difficulty accessing loans from

banks compared with the large scale farmers. The

reason could be their farm size is small, or their

limited credit availability.

Constraints Confronting Smallholder Farmers in

Relation to Farm and Farmer Characteristics

The multiple regression is used to determine

which respondent’s characteristics have the

greatest influence on the constraints confronting

smallholder navel orange farmers (See result in

Table 4). The model specification for the

underlying constraints is given as follows:

Yi=a

0+a

1EXP+a

2NUMT+a

3YLD+a

4FINM+a

5A

GE+a6EDU+a

7OFFW+a

8HINM+e

The dependent variable, Yi, measures the

underlying constraints confronting smallholder

navel orange farmers in the supply chain. The

dependent variable is based on the factor

analysis result of section two in the questionnaire,

and the independent variables are farm and

farmers’ characteristics.

With respect to the dependent variable of

“marketing”, respondent’s number of trees is

statistically significant at 1% level of significance

and off-farm work is statistically significant at

5% level. Marketing as the major constraint

confronting smallholder farmers was inversely

related to the number of trees in the orchards and

their off-farm work. It was perceived that more

navel orange trees planted probably facilitate

fa rmers ’ marke t ing p rob lem, because

smallholder farmers lack access to the market

compared with the large scale farmers. If the

farmers have off-farm work, normally they have

more marketing information due to the more broad

human resources network, a similar discussion

was revealed by Fang (2003).

With respect to the dependent variable of

“transportation”, number of trees is statistically

significant at 1% level of significance, and

inversely with transportation. Similar to Yin (2007)

result, lots of smallholder navel orange farmers in

Gannan are located in remote mountain areas and

are geographically dispersed and far away from

lucrative markets. Normally, intermediaries are not

willing to purchase the navel orange in the remote

mountain areas due to the worse traffic, and

except a large quantity of the navel orange.

For product competitiveness, farmer’s age,

education level, and off-farm work are relevant.

Farmer’s age is statistically significant at 5% level,

education level and off-farm work are statistically

significant at 1% level. Older farmers with high

education levels were perceived to be able to

improve the product competitiveness. The older

farmers may produce their products with high

quality based on their experience. This result is

396 แก่นเกษตร 43 (2) : 387-398 (2558).

consistent with findings of Chen et al. (2007). In

contrast, farmers lack of time and energy to

manage the orchards if they have off-farm work,

most of them did not expect to get a lot of profit

from their investment but instead a breakeven is

satisfactory (Yin, 2007).

Processing is inversely related with total yield,

which is statistically significant at 5% level. It was

perceived that high total yield probably facilitate

the processing problem as abundant products

are easier to process compared to a small

amount. The number of trees in the orchards is

inversely related with the transaction cost and

technology. It indicated more navel orange trees

result in less transaction cost and less technology

problem. According to Jaffee and Morton (1995),

smallholder farmers could reduce the transaction

costs through the improvement of the bargaining

power with scale of planting.

Capital problem is positively with farm

experience and inversely with number of trees,

total yield, age and education. Farm experience

is statistically significant at 5% level, and umber

of trees, total yield, age and education are same

statistically significant at 1% level. More farm

experiences probably result in a great capital

problem. The result was confirmed by Chen et al.

(2007), experienced smallholder farmers’ desire

to reinvest or expand production is stronger, but

they have difficulty to obtain the loan support due

to their lack of credit guaranty. Nevertheless, the

other four characteristics adversely affect the

capital problem facing smallholder farmers. This

is due to more navel orange trees planting can

makes smallholder navel orange farmers easier

to get the navel orange planting subsidies. Older

age and higher education level could mean more

capital from other sources such as self-financing

through retained earnings, and family money etc

(Bienabe et al., 2004).

With respect to the constraints of natural risk

and extension, the relationships are ambiguos.

There is no any farmer’s characteristic is

statistically significant at 5% or 1% level. In

summary, much number of navel orange trees

planting can help smallholder farmers alleviate

the constraints, which including marketing,

transportation, transaction cost and capital.

Smallholder farmers with high total navel orange

yields can alleviate the processing problem and

capital problem. Smallholder farmers with higher

education background are confronted with less

product competitiveness and capital problem in

the supply chain. Besides, smallholder farmers

who have off-farm work are confronted with

less marketing problem but more product

competitiveness problem in the supply chain.

397KHON KAEN AGR. J. 43 (2) : 387-398 (2015).

Implication of the Results

Millions of smallholder farmers in Asia

suffered difficulties in the supply chain. The

Chinese fresh fruit and vegetable trade is no

exception. The study results revealed the

relationships between the constraints confronting

smallholder navel orange farmers and their

soc ioeconomic cha rac te r i s t i cs . Some

suggestions to overcome the constraints are

provide on the following aspects.

First, the local government should reinforce

the cultivation technology training among the

smallholder farmers. Most of the smallholder

farmers are not well educated in Gannan, it results

in poor new planting technology confronting them.

Cultivation technology training can effectively help

smallholder navel orange farmers improve the

navel orange products quality and the percentage

of the high quality products.

Second, more farmers’ organization should

be established. Smallholder farmers can only

have market power if they form and participate in

cooperatives. The cooperative can help

smallholder navel orange farmers in Gannan to

secure better terms of trade, such as better

sourcing prices, lower transaction costs, greater

access to training and other services. Collective

action through either producer organizations or

marketing cooperatives, which can also provide

more marketing opportunities to smallholder

farmers.

Finally, farm insurance should be offer to the

smallholder farmers as one of the government’s

initiatives. Farm insurance is an efficient protective

scheme to facilitate smallholder farmers’ losses

when they suffer from serious natural disasters.

But, the insurance companies do not like to offer

the farm insurance to the farmers due to the high

Table 4 Results of multiple regression for constraints and farm and farmer characteristics a (n = 400)

Market-

ing

Transporta-

tion

Product

competitive-

ness

Natural

risk

Exten-

sion

Process-

ing

Transac-

tion cost

Technol-

ogyCapital

Farm experience (year) -.042 -.082 -.010 -.063 .000 .058 .084 -.074 .126**

Number of trees -.256*** -.185*** .086 -.074 -.014 -.002 -.115** -.310*** -.177***

Total yield (kg) -.059 .115* -.084 .032 -.017 -.178** .107 .016 -.189***

Farm income (CNY) .042 -.103 .024 .016 .078 -.010 .099 .096 -.033Ageb .030 .041 -.101** .056 .163* -.037 -.015 -.092* -.164***

Education levelc .026 .093* -.244*** .103* .086 -.069 .051 -.014 -.157***

Off-farm workd -.125** -.061 .189*** -.086 -.023 .103* -.062 -.085 .022Household incomee (CNY) -.034 -.051 .030 .020 .000 .026 .017 .010 -.006R square 0.115 0.076 0.106 0.030 0.038 0.044 0.053 0.115 0.141R2

adj0.097 0.057 0.087 0.010 0.019 0.024 0.034 0.097 0.123

F 6.356*** 4.022*** 5.767*** 1.498 1.942 2.246** 2.735*** 6.352*** 8.023***

a Variables and models significant at P*<0.10, P**<0.05 and P***<0.01.b Measured as a dummy variable where 1 denotes age ≥ 46 years and 0 denotes otherwise.c Measured as a dummy variable where 1 denotes formal schooling beyond secondary school and 0 denotes secondary school education or less.d Measured as a dummy variable where 1 denotes off-farm work and 0 denotes no off-farm work.e Measured as a dummy variable where 1 denotes household income ≥ 60000 RMB and 0 denotes otherwise

398 แก่นเกษตร 43 (2) : 387-398 (2558).

risk and low returns. Therefore, government

should promote the insurance companies to offer

farm insurance to the smallholder farmers by

proper administrative intervention.

Our research does have its limitations,

especially data that was collected from only the

smallholder navel orange farmers in Gannan.

Future studies should include the other key

participants’ perspectives on the constraints

confronting smallholder farmers such as

intermediaries.

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