Analysis of Consumer Preference for Green Tea with Eco-Friendly Certification in China

Abstract

The eco-friendly certification system is designed to ensure safe agricultural products to consumers while minimizing environmental pollution. However, despite its advantages, it is not widely adopted due to a possible decrease of farmers’ income. In order to provide implication for activating the eco-friendly certification system, this paper examines the attributes of green tea which affect consumers’ preferences and estimates consumers’ willingness to pay (WTP) for the eco-friendly certification in China. A choice experiment survey is employed for data collection, and the random utility model is used to estimate the preference for the certification and quality of green tea. The attribute that yields the highest marginal WTP turns out to be the organic certification for which WTP is $115.9/250 g higher than for no certification. Also, the analytical results indicate that the group with high trust is willing to pay up to $214.6/250 g more for green tea with organic certification compared to the one with no certification. The empirical results suggest that it is important to build the consumers’ awareness and trust toward the certification to activate the eco-friendly certification system.

1. Introduction

Food consumption behavior has changed due to the changes in consumption conditions, demographic structure, and climate change [1,2]. In the past, the strategy of increasing productivity in agriculture rather than considering the environment has been pursued [3,4]. However, as consumers’ preferences for food safety and health increase [5,6], more consumers value environmental conservation by linking agricultural production with the environment. The eco-friendly certification system is the most representative policy implemented to ensure food safety and preserve the environment in the agricultural sector. The eco-friendly certification system applies detailed certification standards in the different ways to each country. In China, based on different certification standards, the eco-friendly agriculture certification system is divided into organic certification, green food certification, and non-pollution certification [7]. Although eco-friendly certified agricultural products, safe agricultural products, and certified foods cannot be regarded as exactly the same expression, eco-friendly agricultural products are recognized as safe foods by consumers since they restrict chemical materials such as fertilizers and pesticides during production. Therefore, the eco-friendly certification system is implemented to provide safe agricultural products to consumers while minimizing environmental pollution [8].

Despite the advantages of the eco-friendly certification system, it is not easy to establish and activate the system. One of the main reasons for this difficulty can be the high cost of eco-friendly production methods. A possible explanation is that the increase in price cannot cover the increase in production costs due to the low awareness and trust of the consumers [9]. Previous studies have shown that promoting consumers’ awareness could increase their willingness to pay (WTP) for eco-friendly agricultural products [10,11]. In other words, the activation of eco-friendly agricultural production and the certification system is determined by the consumer’s WTP for eco-friendly agricultural products. Therefore, in order to activate the eco-friendly certification system in China, it is necessary to examine the current status of the certification system and consumers’ preferences for the system.

The eco-friendly certification system for agricultural product aims to reduce the impact of agriculture on the environment and provide safe agri-food to consumers. However, additional cost and effort are required, which can lead to a decrease in farmers’ income. In order to activate the eco-friendly certification, certified agricultural products need to be priced higher than that of products with no certification. Also, the higher price should be caused by consumer’s WTP. In this context, two research questions are investigated in this paper. First, which one will have a more positive effect on farm income: whether farms should produce eco-friendly agricultural products or just produce high-quality agricultural products? Second, which one among the awareness of the eco-friendly certification system and consumers trust in the certification schemes has a greater effect on consumer’s willingness to pay? The product we chose to investigate these research questions is tea. Tea is a product that many Chinese consumers consume on a daily basis, and the quality of tea is relatively clear to Chinese consumers. In addition, consumers’ awareness and trust in the eco-friendly certification are easily distinguished. Therefore, we examine the attributes of tea that affect consumers’ preferences the most and estimate consumers’ WTP for the eco-friendly certification. We analyze the differences in the consumers’ WTP for the eco-friendly certification according to consumers’ awareness and trust of the certification. The other purpose of this study is to suggest policy recommendations for activating the eco-friendly certification based on the estimated results.

This study ensure the objectivity of the results by using the most frequently used choice experiment for estimating the amount of WTP. The novelty of this study can be stated in three points. First, we compare consumers’ WTP for eco-friendly certified products with that for high-quality products. Second, we classify consumers into two groups and compare their WTP according to consumers’ awareness and trust in the eco-friendly certification. Third, we compare changes in consumer preference share by composing scenarios according to changes in the quality and the certification.

2. Literature Review

A number of studies have been conducted on consumers’ preferences for eco-friendly agricultural products worldwide. The literature review of this study focuses on the consumers’ WTP for eco-friendly agricultural products, and it is divided into worldwide and China’s eco-friendly certification. Some studies compared eco-friendly food with local food and analyzed consumers’ consumption behaviors, awareness, and WTP [12,13,14]. Xie et al. [15] estimated consumers’ WTP for US organic broccoli and imported broccoli. They found the positive effect of providing information about USDA certification standards on consumer valuation of imported organic agricultural products. Illichmann and Abdulai [16] investigated the German consumers’ heterogeneous preferences of organic apples, milk, and beef by grouping them according to whether they trust the value of the organic food. The results showed that consumers’ trust had a positive effect on organic food consumption. Jeong and Han [17] analyzed the characteristics of Korean consumers by using the data on experiences in purchasing eco-friendly agricultural foods and examined the correlation between the experience and the policy for expanding the consumption. In addition, Kim and Lee [18] identified that the reputation of organic products has a significant effect on consumers’ purchasing behavior of eco-friendly agricultural products in Korea. Muhammada et al. [19] revealed that United Arab Emirates (UAE) consumers’ WTP for organic food is increasing due to more awareness on healthy food. Furthermore, Ricci et al. [20] showed that consumer trust has a positive effect on purchase decision of eco-friendly convenience food in Italy. Janssen and Hamm [21] also claimed that the consumers’ trust played an important role on purchase decision of organic food in Germany.

In recent years, many studies have also investigated consumers’ preferences for eco-friendly agricultural products in China. Yu [22] analyzed the consumers’ awareness of three different eco-friendly certifications in Guangzhou City and found that more awareness can increase the WTP for the non-pollution certificated food. Xing [23] used the choice experiment (CE) method to estimate the consumer’s WTP for food labels, including origin, organic certification, and nutritional ingredients. She found that consumers are willing to pay the highest premium for the organic label of milk. Zheng [24] used contingent valuation method (CVM) to elicit the WTP for organic rice and organic pork of residents in Beijing city and revealed a positive effect of consumers’ trust on purchase decision of organic food.

One of the first investigations in the case of studying consumers’ preferences for tea was performed in 2007. Ye [25] compared the consumption of organic tea and ordinary tea in China and estimated that consumers are willing to pay 39.96% more for the organic tea. Recently, Yang et al. [26] pointed out that China’s organic tea market is not activated. They used CVM to analyze the consumers’ WTP for organic tea in Fuzhou City. The results showed that those with a monthly income of more than 5000 yuan ($700) are willing to pay 797.76 yuan/kg ($111.69/kg) more for organic tea. Additionally, Liu [27] and Su [28] investigated the consumers’ awareness of organic tea and discovered that consumers’ awareness has a positive effect on their WTP for organic tea. However, despite the importance of tea consumption in China, few studies have analyzed the WTP for attributes of tea. In other words, there is a large gap in the literature concerning the demand on specific attribute of tea in China.

3. Eco-Friendly Certification System and Current Status of China’s Tea Market

According to Yu [29], China’s eco-friendly agriculture certification system is divided into organic certification, green food certification, and non-pollution certification due to certification standards. Organic certification prohibits the addition of synthetic materials such as pesticides and fertilizers in the production process. In contrast, green food certification and non-pollution certification require limited synthetic materials, such as chemical pesticides (Figure 1). Non-pollution certification is the most basic certification in line with food safety legislation in China, and green food certification is the certification system combining the global flow of agricultural development. Green food certification and non-pollution certification are managed by China’s Ministry of Agriculture (MOA) and only implemented in China [29]. However, the relatively strict green food certification, which was introduced in China in 1989, has higher awareness and trust than those of pollution-free certification [30]. In the case of tea, the eco-friendly certification system is applied to the industry. Therefore, tea is classified into organic tea, green food tea, and non-pollution tea [31].

As of 2019, the total production area of tea exceeded 3.07 million hectares and the total consumption reached 202.6 million tons in China. Furthermore, green tea takes the largest share of production and consumption of tea in China, accounting for more than 60% of production and consumption (Figure 2).

In China, organic certification was implemented in the tea industry in 2000. The planted area of organic-certified tea increased from 20,000 ha in 2006 to 46,000 ha in 2014, and to 110,000 ha in 2018 (Figure 3). The share of area for organic tea within the total tea-planted area increased from 1.7% in 2014 and to 3.8% in 2018. In addition, the production of organic tea continues to increase from 88,000 tons in 2014 to 193,000 tons in 2018, and the share of organic tea in total tea production had reached 7.4% by 2018.

The number of tea-producing firms with organic certification in China increased from 400 in 2010 to 1583 in 2017 (“Certification of Organic Products and Development of Organic Industry in China 2018”). In the case of tea with green food certification, the total planted area reached 200,000 ha by 2018. However, it is difficult to say that this proportion of the planted area (6.5%) is high (“Yunnan Tea Industry Green Development Bulletin”). Therefore, we can infer that the eco-friendly tea market has not been widely activated yet in China.

According to the FiBL survey on organic agriculture worldwide, the recorded organic farmland in the world was more than 72.3 million hectares in 2019 (which is 1.5% of the world’s agricultural land). Globally, the country with the largest organic farmland is Australia (35.7 million hectares), followed by Argentina (3.7 million hectares) and Spain (2.4 million hectares). China has the seventh-largest market of organic farmland (2.2 million hectares). In 2019, the global organic food market reached more than 113.2 billion dollars. The US is the largest organic food market in the world with a market size of 50.6 billion dollars, followed by Germany (13.6 billion dollars), France (12.8 billion dollars) and China (9.6 billion dollars). In terms of the organic tea market, China’s organic tea area reached 106 thousand hectares in 2019, 58% of the world’s organic tea area. Although it accounts for a high proportion of the world’s organic tea area, it currently only accounts for less than 10% of China’s total tea planted area.

4. Methodology

As a type of stated preference method for estimating the monetary value, many researchers choose the CE to analyze consumers’ WTP, along with CVM and experimental auctions (EA) [32,33]. Based on the random utility model, CE is based on the behavior of choosing the best alternative to maximize their utility. In this study, the random utility model is used to estimate the preference for green tea and the marginal WTP by using the conditional logit model for an empirical estimation.

Let $U_{ij}$ denotes the utility obtained by a consumer $i$ from an alternative $j$ in the alternative set ($S_i$), which is expressed as Equation (1).

$$U_{ij}=V_{ij}\left(Z_{ij}\right)+e_{ij}=Z_{ij}\beta +e_{ij},$$

(1)

where the consumer $i$’s utility $U_{ij}$ is divided into the observable deterministic term $V_{ij}$ and unobservable stochastic term $e_{ij}$, and $Z_{ij}$ is the vector of attribute in the choice alternative j. The $V_{ij}$ is the multiplication of the vector ($Z_{ij}$) and coefficient ($\beta$) of the choice alternative j. The relationship of consumer’s utility is U_ij > U_ik (j and k∈S_i, j ≠ k) if the consumer i chooses alternative j between the choice alternatives j and k. Then, the probability can be expressed as Equation (2).

$$P_{ij}=Pr\left(V_{ij}+e_{ij}\ge V_{ik}+e_{ik}\right)=Pr\left(V_{ij}-V_{ik}\ge e_{ik}-e_{ij}\right)for all k\ne j$$

(2)

Conditional logit assumes that error term $\left(e_{ij}\right)$ is iid and follows the extreme value distribution, the probability of the consumer $i$ choosing the alternative j among the total alternatives $K$ can be expressed as Equation (3) [34,35].

$$P_{ij}=\frac{\exp \left(V_{ij}\right)}{{\sum }_{k=1}^K\exp \left(V_{ij}\right)}=\frac{\exp \left(Z_{ij}\beta \right)}{{\sum }_{k=1}^K\exp (Z_{ij}\beta )}$$

(3)

If the observable utility term $V_{ij}$ is assumed to be a linear function as Equation (4).

$$V_{ij}=Z_{ij1}{\beta }_1+Z_{ij2}{\beta }_2+\cdots +Z_{ijl}{\beta }_l,$$

(4)

where $X_{ijl}$ represents the l-th attribute of the attribute vector ($Z_{ij}$). Then we apply conditional logit model, where the price is used as a continuous variable in the indirect utility function $V_{ij}$ and no choice option is used as a dummy variable. In this case, the standard willingness to pay ($WT{P}_s$) can be derived as Equation (5) [36]. And the marginal willingness to pay $\left(MWT{P}_{Zl}\right)$ would be Equation (6).

$$WT{P}_s=\frac{dV/d{D}_s}{dV/d{Z}_p}=-\frac{{\beta }_s}{{\beta }_p},$$

(5)

$$MWT{P}_{Zl}=\frac{dV/d{Z}_l}{dV/d{Z}_p}=-\frac{{\beta }_l}{{\beta }_p},$$

(6)

where $D_s$ stands for the dummy variable for the selection of the alternative choice (no choice) S, $Z_l$ stands for l-th attribute variable, and $Z_p$ represents the attribute of price.

5. Data

5.1. Experiment Design

When a consumer makes a decision to purchase a particular item, the choice is not based on only one specific attribute but on a variety of attributes at the same time. Therefore, there exists a limit on determining how much important each attribute is for a consumer [37]. A choice experiment (CE) is able to estimate the monetary value of each attribute. However, it is essential to determine the attributes of a specific product and the attribute levels [38]. In this paper, the product to be estimated is green tea, which is produced, processed, and sold widely in China. Attributes and their levels of green tea are shown in

Table 1. Attributes of green tea and levels.

Attributes	Levels
Place of production Size of production firm Certification Type of green tea Price (yuan/250 g)	North of Yangtze River *, Southern China, Jiangnan, Southwest Large, Medium *, Small No certification *, No-pollution, Green, Organic Mingqian, Yuqian, Others * 200, 300, 400, 500

Note: * denotes the criterion for dummy variables in the analysis.

. Except for the certification attribute, we selected other attributes and levels, referring to Yang et al. [26] and Liu [27]. In order to analyze consumers’ preferences, general attributes such as place of production, size of producing firm, types of green tea and price are included in this experiment. In terms of the production place, there are 19 provinces producing tea in China, which can be divided into four major producing regions. Based on these four regions, the place of production attribute is divided into North of Yangtze River, Southern China, Jiangnan, and Southwest regions. In terms of the producing firm size, there are many tea brands in China, but consumers do not have high awareness of brands. Therefore, based on the production scale of enterprises, which consumers more easily recognize, the size of producing firm attribute is classified into large firm, medium firm, and small firm. Based on the current certification systems mentioned above, the eco-friendly certification attribute is classified into no cetification, no-pollution, green and organic certifications. In addition, since the quality of tea differs by harvesting time, the type of green tea is divided into “Mingqian Tea”, “Yuqian Tea” and others based on the tea-harvesting time (season). In terms of the price attribute, its level includes 200 yuan/250 g ($28/250 g), 300 yuan/250 g ($42/250 g), 400 yuan/250 g ($56/250 g) and 500 yuan/250 g ($70/250 g), reflecting the current market price.

Given all attributes and levels of green tea in Table 1, a full design of 576 (4 * 3 * 4 * 3 * 4) profiles are created. Realistically, since all of the constructed choice profiles cannot be investigated, 16 choice profiles are derived through orthogonal design by using the SPSS Statistics program. Therefore, 8 choice sets, randomly drawn from 16 profiles, were presented to each respondent. Each choice set includes two choice profiles and a “no choice” option. A sample of a choice set is shown in

Table 2. A sample of a choice set used in a choice experiment.

A	B	C
North of Yangtze River Small production firm No-pollution Mingqian 300 yuan	Jiangnan Large production firm Organic Yuqian 500 yuan	Neither A nor B

.

5.2. Data Collection

A questionnaire survey was conducted on 362 Chinese consumers from December 13 to 31, 2019 through a web survey platform (Wenjuanxing, http://www.wjx.cn, accessed on 2 November 2021). In addition to the attributes of Table 1, the questionnaire includes consumers’ gender, age, education, monthly income, residence of city, and awareness and trust of the eco-friendly certification system. The socioeconomic characteristics of the respondents are shown in

Table 3. Characteristics of the respondents.

Classification		Frequency	Ratio (%)	Classification		Frequency	Ratio (%)
Gender	male	154	42.5	Residence of city	New First-tier city	134	37.0
	female	208	57.5		Second-tier city	91	25.1
Age	~20	13	3.6		Third-tier city	88	24.3
	20~29	137	37.9		others	49	13.5
	30~39	121	33.4	Economic zone	Northeast	96	26.5
	40~49	56	15.5		North coast	62	17.1
	50~	35	9.7		East coast	68	18.8
Monthly Income (yuan)	~2000	35	9.7		South coast	49	13.5
	2000~4000	72	19.9		Others	87	24.0
	4000~6000	79	21.8	Awareness	Don’t know	58	16.0
	6000~8000	80	22.1		Heard of it	168	46.4
	8000~10,000	59	16.3		knows little	114	31.5
	10,000~	37	10.2		Knows well	22	6.1
Education	High school and below	53	14.6	Trust	Don’t trust	10	2.8
	Bachelor degree	235	64.9		Hardly trust	119	32.9
	Graduate or above	74	20.4		Trust little	214	59.1
Total	362	100			Trust well	19	5.3

According to China’s 11th Five Year Plan, the Chinese government proposed a new method of dividing 31 provinces in mainland China into eight economic zones based on the economic development situation of different regions. They are Northeast (Liaoning, Jilin and Heilongjiang provinces), North Coast (Beijing, Tianjin, Hebei, and Shandong provinces), East Coast (Shanghai, Jiangsu and Zhejiang provinces), Middle Reaches of Yellow River (Shanxi, Henan, Shaanxi and Inner Mongolia provinces), South Coast (Fujian, Guangdong and Hainan provinces), Middle Reaches of Yangtze River (Anhui, Jiangxi, Hubei and Hunan provinces), Southwest (Guangxi, Chongqing, Sichuan, Guizhou and Yunnan provinces), and Northwest (Xizang, Gansu, Qinghai, Ningxia and Xinjiang provinces).

. Specifically, in our sample, the ratio of women is 57.5%, slightly higher than that of men. Regarding age, the ratio of respondents in the 20~29 (37.9%) and 30~39 age groups (33.4%) are relatively higher. Most of the respondents hold a bachelor’s degree (64.9%). 37.0% of respondents are living in first-tier cities, 25.1% in second-tier cities, 24.3% in third-tier cities, and 13.5% in fourth-tier cities. Moreover, those respondents who are from the northeast economic zone account for 26.5% of the total sample, followed by east coast (18.8%), north coast (17.1%) and south coast (13.5%). Respondents with an average monthly income of 6000~8000 yuan ($840~$1120) account for the highest proportion (22.1%), followed by 4000–6000 yuan (($560~$840), 21.8%), 2000–4000 yuan (($280~$560), 19.9%), 8000–10,000 yuan (($1120~$1400), 16.3%), more than 10,000 yuan (($1400), 10.2%) and less than 2000 yuan (($280), 9.7%). In addition, the questionnaire also included consumers’ awareness and trust of the certification system. Awareness results indicate that respondents who answered ‘heard of it’, ‘knows little’, ‘don’t know’, and ‘knows well’ account for 46.4%, 31.5%, 16.0%, and 6.1% of the overall sample, respectively. “Trust” results show that consumers who responded ‘trust little’, ‘hardly trust’, ‘trust well’ and ‘don’t trust’ account for 59.1%, 32.9%, 5.3% and 2.8%, respectively.

6. Estimation Results

The estimation results of this study consist of logit model results, marginal WTP, and preference share (Figure 4). Also, an implication is included at the end of the estimation result.

6.1. The Conditional Logit Model

Table 4. Estimation results for green tea attributes.

Variables		Coefficients	Standard Deviation	t-Value
Place of production	Southern China	0.162 *	0.097	1.67
	Jiangnan	0.232 **	0.102	2.27
	Southwest	0.234 **	0.113	2.06
Size of production firm	Large	0.178 **	0.085	2.09
	Small	0.145 **	0.072	2
Certification	Non-pollution	0.320 ***	0.110	2.92
	Green	0.397 ***	0.099	4.02
	Organic	0.692 ***	0.087	7.97
Type of green tea (Production season)	Mingqian	0.240 ***	0.091	2.64
	Yuqian	0.471 ***	0.110	4.28
Price		−0.00084 ***	0.000	−4.07
Choice Dummy		0.303 **	0.135	2.25
Observations		362
Log Likelihood	−2878.92	x2 (12)		605.33
Pseudo R	0.10	Prob > x2		0.00
Where the odds ratio is the ratio of the probability of being selected to the probability of not being selected, the natural logarithm in this case is applied to the odds ratio ($\frac{P_i}{1-P_i}$).

Note: ***, ** and * denote significant at 1, 5, and 10%, respectively.

is the estimated result of the conditional logit model. The test result of the goodness-of-fit Chi-square statistic (605.3) is greater than 26.22 (degree of freedom 12) which is the threshold of 1 percent significance level. It means that the null hypothesis that all estimated ${\mathsf{\beta }}_i$’s are zero would be rejected. All of the variables are estimated as dummy variables except for the price variable. In the case of “place of production”, North of Yangtze river is excluded as a reference; for “size of production firm”, “certification” and “type of green tea”, medium production firm, ordinary size firm, and other type are excluded.

According to the estimation results, the variables of “certification” and “type of green tea” are estimated to be statistically significant at the 1% level. Large and small for “size of production firm” and Jiangnan and Southwest for “place of production” are estimated to be statistically significant at the 5% level. In addition, Southern for “place of production” are estimated to be statistically significant at the 10% level. The estimated coefficient of “price” turns out to be −0.00084. In other words, as the price increases, the value of the commodity ($\ln (P_i/1-P_i)$) decreases, which is suitable for the economic theory [39]. In the result, the choice probability of Southern China, Jiangnan, and Southwest for “place of production” are estimated as 0.162, 0.232 and 0.234, which are higher than the choice probability of North of Yangtze river. The choice probability of large and small for “size of production firm” are 0.178 and 0.145 which are higher than that of the medium size firm. The choice probability of non-pollution, green, and organic for “certification” are 0.320, 0.397, and 0.692, respectively, which are higher than that of the tea with no certification. Finally, the choice probability of Mingqian and Yugian for “type of green tea” are estimated to be 0.240 and 0.471, which are higher than the choice probability of Others (fall season green tea).

6.2. Marginal Willingness to Pay for Each Attribute

Table 5. Marginal willingness to pay (WTP) for each attribute.

Variables		MWTP (yuan/250 g)	Standard Deviation	t-Value
Base		363.1 ***	132.15	2.75
Place of production	Southern China	194.0	128.08	1.52
	Jiangnan	277.1 *	146.70	1.89
	Southwest	279.8 *	156.36	1.79
Size of production firm	Large	212.9 *	114.81	1.85
	Small	173.1 *	101.60	1.70
Certification	Non-pollution	382.8 **	157.99	2.42
	Green	474.7 ***	161.89	2.93
	Organic	827.6 ***	228.64	3.62
Type of green tea (Production season)	Mingqian	287.2 **	128.88	2.23
	Yuqian	564.0 ***	195.74	2.88

Note: ***, ** and * denote significant at 1, 5, and 10%, respectively.

shows marginal WTPs. The marginal WTP for the green tea with the attributes of being produced in North of Yangtze river, by medium size firm, with no-certification (Ordinary) and in fall season (Others) is estimated to be 363 yuan ($50.82) per 250 g. According to the results of marginal WTP by attribute level, consumers are likely to pay 277 yuan ($38.78) and 280 yuan ($39.20) more for Jiangnan and Southwest tea compared to the one from North of Yangtze river. “Southern China” is not statistically significant at the 10% level. In addition, consumers are more willing to pay 213 and 173 Yuan for the Large and Small size firms and 287 yuan ($40.18) and 564 yuan ($78.96) for Mingqian tea and Yuqian tea. Lastly, consumers are willing to pay 383 yuan ($53.62), 475 yuan ($66.46), and 828 yuan ($115.92) more for non-pollution, green, and organic tea. In summary, consumers prefer green tea produced in Jiangnan and Southwest over that from North of the Yangtze, and consumers like green tea produced by large and small firms more than the one produced by medium firms. In addition, consumers show a higher WTP for certificated green tea such as non-pollution, green, and organic. Moreover, Yuqian is revealed to be the most preferred type of green tea. These results are very remarkable in a sense that the marginal WTP for organic certification is the highest, and the next is Yuqian attribute. It means that consumers care more about safety and the quality in green tea.

6.3. Marginal Willingness to Pay According to Awareness and Trust of Certification

Unlike other attributes, since the government implemented the certification system for green tea, the marginal WTP for certificated green tea depends on how much consumers are aware of the certification system and how much the green tea produced under the certification system is reliable. Therefore, it is necessary to classify consumers according to their awareness and trust for the certification system. We divided all samples into four groups: a high awareness group, a low awareness group, a high-trust group, and a low-trust group. After that, we estimated the marginal WTP for these differentiated groups. The results are shown in

Table 6. Marginal willingness to pay for awareness and trust of green tea certification (yuan/250 g).

Classification		Average	Awareness		Trust
			High Awareness Group	Low Awareness Group	High Trust Group	Low Trust Group
Place of production	Southern China	194.0	204.7	177.1	222.2	140.1
	Jiangnan	277.1 *	275.6	252.2	669.6	84.6
	Southwest	279.8 *	18.5	367.3 **	630.4	116.1
Size of production firm	Large	212.9 *	191.0	219.5 *	472.6	53.6
	small	173.1 *	93.6	208.7 *	262.7	133.3
Certification	Non-pollution	382.8 **	615.1	291.4 *	519.3	126.5
	Green	474.7 ***	834.3 *	326.8 **	773.9 *	132.9
	Organic	827.6 ***	1051.1 *	719.2 ***	1532.7 *	300.7 ***
Type of green tea (Production season)	Mingqian	287.2 **	211.4	304.4 **	599.2	104.2
	Yuqian	564.0 ***	503.0	553.4 ***	1308.1 *	192.1 *

Note: ***, ** and * denote significant at 1, 5, and 10%, respectively.

. According to the estimation results classified by awareness level, the group with high awareness is 1051 yuan ($147.14) more willing to pay for green tea with organic certification than that with no certification. This is 332 yuan ($46.48) higher than the one from the group with low awareness (719 yuan ($100.66)). The group with high awareness is more willing to pay by 834 yuan ($116.76) for green tea with green certification than that with no certification. This is 507 yuan ($70.98) higher than the one from the group with low awareness (327 yuan ($45.78)). This result suggests that the WTP for certificated green tea increases as consumers’ awareness rises. According to the estimation results on the trust level, the group with high trust is willing to pay by 1533 yuan ($214.62) more for green tea with organic certification than that with no certification, which is 1232 yuan ($172.48) higher than the group with low trust (301 yuan ($42.14)). On the other hand, there is no significant difference in the marginal WTP for other attributes classified by awareness and trust. In other words, the increase in marginal willingness due to increased trust of consumer is greater than the one due to increased awareness of consumer.

These estimation result imply that it is imperative not only to promote the certification system of green tea but also to increase consumers’ trust in the certification of green tea. In other words, in order to invigorate the certification system, increasing the consumer’s trust through strict follow-up management is required.

6.4. The Results of Preference Share

Using the estimated results in Table 4, we calculated the consumers’ preference share by the attribute level of green tea. The preference share is shown in

Table 7. Calculated preference share.

Option	Place of Production	Size of Production Firm	Certification	Type of Green Tea (Production Season)	Price (yuan/250 g)	Preference Share (%)
1	North of Yangtze River	Small	Non-pollution	Mingqian	300	5.2
2	Southern China	Large	Green	Mingqian	500	5.8
3	North of Yangtze River	Large	Ordinary	Mingqian	200	4.2
4	North of Yangtze River	Large	Green	Yuqian	400	6.7
5	Southwest	Small	Ordinary	Yuqian	500	5.1
6	Jiangnan	Large	Organic	Yuqian	300	12.4
7	Southern China	Small	Organic	Mingqian	400	8.1
8	Southwest	Medium	Green	Mingqian	300	6.1
9	Southern China	Medium	Non-pollution	Yuqian	200	7.2
10	Southwest	Large	Non-pollution	Others	400	4.9
11	North of Yangtze River	Medium	Organic	Others	500	4.3
12	Jiangnan	Small	Green	Others	200	6.0
13	Jiangnan	Large	Non-pollution	Mingqian	500	5.7
14	Southern China	Large	Ordinary	Others	300	3.6
15	Southwest	Large	Organic	Mingqian	200	10.7
16	Jiangnan	Medium	Ordinary	Mingqian	400	3.8

. There are 16 alternatives calculated by Equation (3). According to the results, the highest preference share is option 6 (Jiangnan, Large, Organic, Yuqian, and 300 yuan), for which share is calculated as 12.4%. The preference shares of option 15 (Southwest, large, organic, Mingqian, 200 yuan) and option 7 (Southern China, small, organic, Mingqian, 400 yuan) are calculated to be 10.7% and 8.1%, respectively. On the other hand, the preference share of option 14 (Southern China, large, ordinary, others, 300 yuan) is estimated to be the lowest (3.6%).

The choice options calculated to produce high preference share mainly include organic certification of green tea and Mingqian or Yuqian, as indicated by the results in Table 7. It means that the preference share depends on the certification and the quality. Therefore, it would be useful to evaluate the change in preference share according to the quality and the certification of green tea. By performing this analysis, we can then identify the attribute which has the most significant effect on the consumer’s choice.

For the scenario analysis, first, we estimated changes in the preference share due to the changes in the type of green tea (production season). We set four different scenarios and then estimated changes in preference share for each scenario. The results are shown in

Table 8. Preference share changes according to changes in type of green tea (Scenarios 1 to 4).

		Place of Production	Size of Production Firm	Certification	Type of Green Tea	Price (yuan)	Preference Share (%)
					(Production Season)
Baseline (A)	A	Southwest	Large	Ordinary	Yuqian	300	19.7
	B			Non-pollution	Mingqian	500	18.2
	C			Green	Mingqian	500	19.7
	D			Organic	Others	400	22.6
	E			Green	Others	200	19.9
Scenario1	A	Southwest	Large	Ordinary	Yuqian	300	18.8
	B			Non-pollution	Yuqian	500	21.9 (3.7)
	C			Green	Mingqian	500	18.8
	D			Organic	Others	400	21.6
	E			Green	Others	200	19
Scenario2	A	Southwest	Large	Ordinary	Yuqian	300	18.7
	B			Non-pollution	Mingqian	500	17.3
	C			Green	Yuqian	500	23.6 (3.9)
	D			Organic	Others	400	21.5
	E			Green	Others	200	18.9
Scenario3	A	Southwest	Large	Ordinary	Yuqian	300	17.3
	B			Non-pollution	Mingqian	500	16
	C			Green	Mingqian	500	17.3
	D			Organic	Yuqian	400	31.8 (9.3)
	E			Green	Others	200	17.5
Scenario4	A	Southwest	Large	Ordinary	Yuqian	300	17.6
	B			Non-pollution	Mingqian	500	16.3
	C			Green	Mingqian	500	17.6
	D			Organic	Others	400	20.2
	E			Green	Yuqian	200	28.4 (8.6)

Note: ( ) is changes in preference share compared to baseline (A).

. The baseline (A) was set by assuming that the place of production (Southwest) and size of producing firm (Large) are the same, and the other attribute levels (certification, type of green tea, and price) for the baseline were selected and combined. Corresponding preference shares are estimated to be around 20% (18.2~22.6 %). Scenarios 1 and 2 change the attribute level from Mingqian to Yuqian, scenarios 3 and 4 change from Others to Yuqian. As a result, when regular Mingqian is changed to Yuqian as scenarios 1-B and 2-C, the preference share rises 3.7% and 3.9%, in other words, from 18.2% to 21.9% and from 19.7% to 23.6%. Converting from Others to Yuqian as in scenarios 3-D and 4-E, the preference share rises 9.3% and 8.6% from 22.6% to 31.8% and from 19.9% to 28.4%.

Using the same process as above, we set 4 different scenarios according to the change of the certification and then estimated the change in the preference share (

Table 9. Preference share changes according to changes in certification of green tea (Scenarios 5 to 8).

		Place of Production	Size of Production Firm	Certification	Type of Green Tea	Price (yuan)	Preference Share (%)
					(Production Season)
Baseline (B)	A	Southwest	Large	Ordinary	Yuqian	500	16.8
	B			Green	Others	300	18.4
	C			Ordinary	Mingqian	200	17.1
	D			Green	Yuqian	500	25.0
	E			Organic	Others	400	22.7
Scenario5	A	Southwest	Large	Organic	Yuqian	500	28.7 (11.9)
	B			Green	Others	200	15.8
	C			Ordinary	Mingqian	400	14.7
	D			Green	Yuqian	500	21.4
	E			Organic	Others	400	19.5
Scenario6	A	Southwest	Large	Ordinary	Yuqian	500	15.8
	B			Organic	Others	200	23.3 (4.8)
	C			Ordinary	Mingqian	400	16.1
	D			Green	Yuqian	500	23.5
	E			Organic	Others	400	21.4
Scenario7	A	Southwest	Large	Ordinary	Yuqian	500	14.3
	B			Green	Others	200	15.7
	C			Organic	Mingqian	400	29.2 (12.1)
	D			Green	Yuqian	500	21.3
	E			Organic	Others	400	19.4
Scenario8	A	Southwest	Large	Ordinary	Yuqian	500	15.5
	B			Green	Others	300	17.0
	C			Ordinary	Mingqian	200	15.8
	D			Organic	Yuqian	500	30.9 (5.9)
	E			Organic	Others	400	20.9

Note: ( ) is changes in preference share compared to baseline (B).

). Scenarios 5 and 7 change the attribute level from ordinary to organic, scenarios 6 and 8 change the attribute level from green to organic. As a result, if we convert the attribute from Ordinary to Organic as scenario 5-A and 7-C, the preference share rises 11.9% and 12.1% from 16.8% to 28.7% and from 17.1% to 29.2%. Changing from green to organic as in scenarios 6-B and 8-D, the preference share rises 4.8% and 5.9% from 18.4% to 23.3% and from 25.0% to 30.9%.

Comparing the result from Table 8 and the one from Table 9, when we convert the quality(type) level of green tea, the preference share increases about 3.7%~9.3%. If we change the certification level of green tea, the preference share increases about 4.8%~12.1%. These results provide an important insight that the increase in consumers’ preference is induced more significant by the certification than the increase in the quality improvement.

6.5. Implication

The overall estimation results imply that the group with high awareness is more willing to pay for the green tea with eco-friendly certification than for the one with no certification, and the group with high trust is more willing to pay for green tea with eco-friendly certification. In addition, it is revealed that the difference in the WTP according to the awareness level is smaller than the difference in the WTP according to the trust level. Based on these results, we can suggest policies to promote the certification system and enhance consumers’ trust in order to activate the certification system for eco-friendly agricultural products. First, the government should come up with an effective promotion strategy for the eco-friendly certification system. It is also necessary to block the sale of non-certified agricultural products which disguise as agricultural products having eco-friendly certification. This policy will increase the consumers’ trust toward the certification system.

In terms of production, the consulting is needed ins selecting organic, green food, or non-pollution food certification by considering the conditions and circumstances of individual farms. Since consumers are willing to pay for organic products more than green products, the price is likely to be high. However, if the cost and effort required to produce organic products exceed the price increase, the production of green or pesticide-free products is more reasonable than the production of organic products. In other words, the government’s consulting policy is needed so that producers can select the optimal eco-friendly certification in consideration of production conditions. If the profitability of producers is guaranteed through product differentiation by adopting the eco-friendly certification, the eco-friendly certification system would be activated.

7. Conclusions

This study examines the current status of the agricultural certification system in China and analyzes consumers’ perceptions and preferences. We select green tea as the research object since it is one of representatives of a favorite food in China. We estimate consumers’ WTP to analyze the preference for the certification and the quality (type) of green tea. The attributes of green tea used for preference analysis are the place of production, size of production firm, the type of the certification, type of green tea, and the price. The marginal WTP for each attribute is estimated. We also estimate the change in the marginal WTP according to consumers’ awareness and trust of the certification.

The analysis results indicate that the highest marginal WTP is identified to be the organic certification, and consumers are willing to pay 828 yuan ($115.92) per 250 g more for organic tea than for the tea with no certification. The marginal WTP for Yuqian is estimated to be 564 yuan ($78.96), which is higher than WTP for the green tea produced during the fall season. It implies that consumers care about the safety and the quality in green tea production. In order to compare consumers’ marginal WTP with different food safety concerns in terms of awareness and trust, we divide consumers into four groups. The group with high awareness is willing to pay 1051 Yuan ($147.14) more for green tea with organic certification than for the tea with no certification. It is 332 yuan ($46.48) higher than the one from the group with low awareness. Moreover, the group with high trust is willing to pay 1533 yuan ($214.62) more for green tea with organic certification than for the one with no certification. It is 1232 yuan ($172.48) higher than the one from the group with low trust. These results imply that it is essential to promote the certification system, and establish a strict follow-up management system to increase consumers’ trust in the certification. Moreover, these improvements should be promoted towards consumers in order to invigorate the certification system for green tea.

Using the estimated results, we calculate the share of consumer preference. The results show that when changing the quality (type) level of green tea, the preference share increases about 3.7%~9.3%. When changing the certification level of green tea, the preference share increases about 4.8%~12.1%. These results provide important insight that the increase in consumers’ preference by the certification is greater than the increase in consumers’ preference by the quality improvement.

Through the estimated WTP and changes in preference share, we can find solutions for the raised research questions. Under the assumption that the difference in production cost is small, the estimation results in this paper strongly imply that producing eco-friendly certified tea rather than high-quality tea will have a more positive impact on farm income. In addition, the simulation results indicate that the activation of eco-friendly certification in China is a more effective way to secure consumers trust in the certification schemes than to promote it.

Since this study uses the data from a web survey, there is a limitation that the sample does not completely represent the whole population. Moreover, conditional logit, the analysis method selected in this study, has limitations. Since conditional logit estimates the average change in the respondent’s attributes, it has the advantage of being able to easily estimate the change in preference share according to the changes in attributes such as the quality or the certification system. However, according to the independence of irrelevant alternatives (IIA) property assumption, there is a disadvantage that changes in individual attributes of respondents, and substitutions between attributes are not accurately reflected in the estimation results. Therefore, in the future studies, it is recommendable to compare the results in the present study with the results using methodologies such as mixed logit or nested logit that compensate for the disadvantages of conditional logit.