Dalian University No. 10, Xuefu Ave., Economic Technological Development Zone, Dalian , P. R. China Corresponding author:

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1 International Journal of Innovative Computing, Information and Control ICIC International c 2011 ISSN Volume 7, Number 12, December 2011 pp THE STRENGTH OF TRUST: DISCUSSION ON THE INFLUENCING FACTORS OF THE CHINESE FARMERS ADOPTION OF MOBILE AGRICULTURAL SCIENCE AND TECHNOLOGY KNOWLEDGE SERVICE Yunfu Huo 1,2,, Lin Ma 3 and Deli Yang 2 1 Institute of E-Commerce and Logistics Dalian University No. 10, Xuefu Ave., Economic Technological Development Zone, Dalian , P. R. China Corresponding author: huoyunfu@dlu.edu.cn 2 School of Management Dalian University of Technology No. 2, Linggong Road, Ganjingzi District, Dalian , P. R. China 3 Qi Ming Hai Tong Information Technology Co., Ltd Dalian , P. R. China Received September 2010; revised February 2011 Abstract. Numerous scholars have pointed out that the mobile service has played an important role in dissemination of knowledge in science and technology, but for now, the mobile service has not played an intermediary role in the dissemination of knowledge of agricultural science and technology as it should be in our rural areas. According to the relative theories and literature, this article builds a theoretical model of the farmer s adoption behavior of the mobile agricultural knowledge services from the angles of the adoption of mobile technology, the expectations of usefulness, communication channels, trust, the adoption intention and the adoption behavior. Based on the survey, use the exploratory factor analysis, confirmatory factor analysis and structural equation model to verify the above theoretical model. In conclusion, the mobile technology adoption, the expectations of usefulness effect the adoption of behavior indirectly through the adoption of intention; trust is an intermediary variable for the communication channels to impact the adoption intention then to the adoption behavior. Thereby enhancing the farmer s adoption intention, popularizing rate of mobile service in rural areas and improving the farmer s trust can enhance the intermediary role of mobile service in diffusing the knowledge of agricultural science and technology. Keywords: Trust, Mobile service, Knowledge of agricultural science and technology, Farmers adoption behavior 1. Introduction. Theory and practice show that information technology has become the key to economic growth [1]. Information technology promotes sustainable economic growth through three channels: information technology which in produce (information technology and equipment production, Information technology to assist the production, etc.) provides new products or new services (Internet, etc.), improve the contact between in business and customer (e-commerce, etc.). More than half of China s population is farmers 1. The development of agriculture is very important in China. Therefore, use information technology to promote the basic driving of Chinese agricultural development in agricultural production, but also solve agricultural problems about China s strategic selection. In survey that was done by J. Rolfe et al. (2003), 47% of the surveyed farmers 1 CNNIC The 26th China Internet Development Statistics Report. 6979

2 6980 Y. HUO, L. MA AND D. YANG think that the Internet can make them accept information better [2]. It has basically had the reality basis that uses the Internet to disseminate the knowledge of agricultural science and technology in rural China. Main features: First, Internet access of the Chinese farmers increased more and more, until June 2010, and the scale of rural Internet users has reached million, accounting for 27.4% of Internet users, an increase of 7.7% in half year. Second, there are not only a lot of agriculture-related sites, but their contents are also rich 2, including the agricultural management, consultation service of agricultural technology, and network market of agricultural production that forms a full range of agricultural information system. However, the current network as a carrier of agricultural science and technology, the role is not obvious, in the dissemination of knowledge. In most rural areas of China, especially in backward rural areas, getting agricultural science and technology approaches is mainly dependent on interpersonal communication, followed by radio and television 3 [3-5]. Many scholars have pointed out that the Internet played a huge role in the spread of the scientific knowledge (H. Bonfadelli, 2002). In view of mobile technology and its applications, penetration in Chinese farmers was significantly higher than other information technology, through the mobile Internet disseminating agricultural science, and technology has increasingly become a very important mobile business applications. Actuality of Chinese farmers adoption of the mobile services of agricultural technology knowledge inspires us to consider the issue from two perspectives: first, the demand intensity of agricultural production is not high for scientific and technological knowledge in China; second, Chinese farmers have serious obstacles, in the adoption of mobile phone knowledge of agricultural science and technology. This paper examines this issue from the second view, mainly. To solve the above problem, we will use an empirical study and test a series of hypothesis by questionnaire, then we can get influencing factors which effect the users adoption behavior of mobile services of agricultural science and technology, and their internal structures. This paper s research ideas are Theoretical Analysis Modeling Empirical Model Revise Conclusion. The paper consists of six sections. Section 2 is the literature review. Section 3 is theoretical basis and hypothesis. Section 4 constructs theory model. Section 5 is empirical. Section 6 is hypothesis testing, model revise and results discussion. And Section 7 is conclusions and prospect. 2. Literature Review. Adoption behavior theory has always been a hot point; most research has focused on the adoption of the technology or service. M. Parthasarathy et al. (1998) studied the behavior after the adoption of online services [6]; S.-Y. Hung et al. (2003) studied the key factors of the adoption of WAP services, as a case of Taiwan [7]; N.-M. Yaghoubi (2010) studied the acceptance model of the adoption of an on-line banking technology [8]; A. Agwu et al. (2008) studied the behavior of farmers to adopt agricultural production technology through the broadcast to spread, in Enugu State in southern Nigeria [9]; G. Dinpanah et al. (2010) studied the role of the Farmer Field School on farmers adoption of biological control technology in rice production [10]; R. Rustam (2010) studied the role of knowledge in the Farmer Field School, community skills and pest management adoption and diffusion process [11]; J. C. Walton et al. (2010) studied the influencing factors of using PDA/GPS technology, in the process of farmers growing cotton [12]. Through the analysis of the literature, we can see that the adoption behavior 2 Administrative Units of Agriculture Website; Golden Agriculture Project; Agricultural Enterprises Website. 3 This is mainly thanks to the project that makes every village have TVs and radios.

3 THE STRENGTH OF TRUST: DISCUSSION ON THE INFLUENCING FACTORS 6981 of the theoretical basis has been perfect, and that the most researchers used the method of empirical, which has guiding significance for this paper. The Internet s role has also been confirmed by numerous studies, in the dissemination of knowledge. I. L. Kondratova et al. (2002) think that the Internet is the most effective medium for the dissemination of knowledge in the digital age [13]; C.-C. Lin et al. (2008) confirmed the ability of students uses the network that has the relations with the regional culture course grades, so that the network s role was proved in the dissemination of knowledge [14]; J. Jiang et al. (2010) think that the Internet is a medium for knowledge trade, and as the form of case studied the key influencing factors of knowledge trade on the Internet [15]. These studies confirm that the Internet has become an important means of dissemination of modern knowledge, from different angles. Currently, it is not so much about using mobile network to disseminate the knowledge of agricultural science and technology. Research content of existing literature focused on the application of the Internet in rural areas, mainly. N. Leroux et al. (2001) studied the main reasons that effect the development of agricultural B2B e-commerce [16]; X. Hu et al. (2009) studied Real-Time Intelligent System for Order Processing in B2C E-Commerce [17]; B. A. Gloy et al. (2000) studied the influencing effects that affect the U.S. largescale farmers to adopt the computer and the Internet [18]. These studies showed that the sensitivity of network technologies is: agricultural e-commerce, large-scale farmers and agricultural enterprises in the area of agricultural production. However, for small-scale farmers, in particular, China s small-scale farmers, the research is rare in the area of mobile commerce adoption. In summary, from the perspective of small-scale farmers, this paper studies the farmers behavior of adopting mobile services of agricultural science and technology knowledge, uses the theory of adoption behavior, abstracts the key influencing factors, and forms an adoption mode. It can be used in rural areas, using the mobile commerce to disseminate the knowledge of agricultural science and technology. 3. Theoretical Basis and Hypothesis Adoption intention and adoption behavior. Adoption intention is the tendency and the motivation that individuals want to adopt a particular behavior. Theory of planned behavior, the behavior intention of individuals is the best variables of prediction behavior. If individuals have the stronger adoption intention for some behavior, then he has more possible to adopt that behavior. Therefore, the farmers adoption intention of knowledge services of mobile agricultural science and technology will affect the adoption behavior of the farmers who live in the difference place, to adopt agricultural science and technology knowledge services. H1: The farmers adoption intention of knowledge services of mobile agricultural science and technology will affect the adoption behavior of adopting agricultural science and technology knowledge services Internet technology adoption. Based on the Technology Acceptance Model (TM A), the adoption behaviors were shown by most of researchers. The model considered that perceived usefulness of Internet and perceived easeness of use affect people s attitudes for ultimate technology adoption, thereby affecting the ultimate adoption of technology [19]. And because of its high degree of predictability for IT technology adoption, it was accepted widely. Farmers adopt the knowledge of mobile agricultural scientific and technological. First is the use of mobile technology adoption, although the Chinese mobile phone users in rural areas become more and more, but there are still obstacles. S. Purao (1998) showed that the cost and the network s knowledge are the the significant barriers to impact the

4 6982 Y. HUO, L. MA AND D. YANG adoption of Internet technology [20]. Lack of the technical capacity is another reason that the using rate of mobile commerce adoption is low in the rural areas. H2a: Farmers adopt mobile technology that will affect farmers adoption intention of agricultural science and technology services. H2b: Farmers adopt mobile technology that will affect farmers adoption behavior of agricultural science and technology services The usefulness expectation of the knowledge service. Fishbein and Ajzen (1975) think that people s attitude about adopting the certain behavior depends on the estimates and the expected of this behavior s result [21]. Farmers adopt mobile services of agricultural science and technology knowledge, based on the benefits of this knowledge. That is, adopting mobile services of agricultural science and technology knowledge has more value than getting the service from the other channels. It includes three aspects: easier access to knowledge; acquired knowledge is more useful than before; the effect of using this knowledge is more easily observed [22]. Therefore, the farmer perceived usefulness of mobile services of agricultural science and technology knowledge is the important influencing factor for adopting the mobile service of science and technology knowledge. H3a: The usefulness expected for mobile service of agricultural science and technology knowledge will affect farmers adoption intention of agricultural science and technology knowledge. H3b: The usefulness expected for mobile service of agricultural science and technology knowledge will affect farmers adoption behavior of agricultural science and technology knowledge Communication channels of adoption behavior. Channels play an important and intermediary role in the knowledge, skills and behaviors spread. Technical innovation diffusion theory, which is technical innovation through a period of time, via channels of information communication, was accepted in a social group and disseminated, widely. Rogers (2003) also emphasized the role of channels for accessing to information in the product diffusion process [23]. N. Meade et al. (2006) pointed out that the channels of access to information are the key variables for constructing the macroeconomic diffusion model [24]. H. Kuo et al. (2010) studied the consumer behavior model on auction websites [25]. In addition, different communication channels, different degree of trust in it, so that the trust of its dissemination of information by different degrees. As the innovative products and services, mobile services of agricultural science and technology knowledge and its process of adoption should also be able to apply the diffusion theory to explain. H4a: The information communication channels of mobile service of agricultural science and technology knowledge will affect farmers trust in mobile service of agricultural science and technology knowledge. H4b: The information communication channels of mobile service of agricultural science and technology knowledge will affect farmers adoption intention of mobile service of agricultural science and technology knowledge. H4c: The information communication channels of mobile service of agricultural science and technology knowledge will affect farmers adoption behavior of mobile service of agricultural science and technology knowledge Trust. Trust is an important concept in the area of social exchange. It happened in the situation of neither a contract nor a dominant mechanism to avoid the risk of opportunism in the circumstances. Therefore, trust is seen as a general mechanism for reducing social complexity and risk [26]. Gefen et al. (2003) introduced the trust variable in the TAM (technology acceptance model), and pointed out the trust had important effects on

5 THE STRENGTH OF TRUST: DISCUSSION ON THE INFLUENCING FACTORS 6983 behavior intention [27]. In the process of adopting the mobile service of agricultural science and technology knowledge, the trust mainly represents trust in the spread channels of mobile service of agricultural science and technology knowledge. H5a: Trust affects the farmers adoption intention of the mobile service of agricultural science and technology knowledge. H5b: Trust affects the farmers adoption behaviors of the mobile service of agricultural science and technology knowledge. 4. Construct Theoretical Model. According to the foregoing analysis, constructing the theoretical model, as shown in Figure 1, reflects the impact path for different influencing factors that is the farmers adoption intention and adoption behavior for on-line agricultural science and technology knowledge. Figure 1. The theoretical model of the farmer s adoption behavior of the mobile agricultural science and technology knowledge services 5. Empirical Analysis Questionnaire design. The model includes six factors, each of which uses multiindex measures. These measures will be compiled into Likert 7-scale, as shown in Table 1. In order to improve the content validity of scale, some of these measures adapted their own literature. The Adoption of Mobile, that is TAM, had 4 measures, and adapted from [7,8,25]; Usefulness, that is USE, had 3 measures, and adapted from [7,10,25,28]; Communication Channels, that is CC, had 3 measures, and adapted from [7,10,28]; Trust, that is TRU, had 3 measures, and adapted from [25,29]; the Behavior of Intention, that is BI, had 3 measures, and adapted from [10,28,29]; the Behavior of Adoption, that is BA, had 3 measures, and adapted from [7,30] Data collection. To ensure the representative of the data, the author selected 50 undergraduate and 3 graduate students in survey. They came from 22 provinces in the rural areas of China. Use the summer holiday to visit the farmers have been live, and fill out the questionnaires. After investigation, 437 questionnaires were collected, of which 213 questionnaires were defective (incomplete answer, obvious to cope it), and effective percentage of the questionnaires is 51.26% Data analysis Questionnaire reliability. Use the SPSS 17.0 to count the Cronbach s alpha coefficient, to determine the reliability of the questionnaire, the results shown in Table 2. Data in the table show all the indicators are more than 0.70, and that all indicators of the overall Cronbach s alpha coefficient were 0.780, which shows the reliability of the questionnaire is acceptable.

6 6984 Y. HUO, L. MA AND D. YANG Table 1. The measures of the factors and the source Factors Measures Measure content Source TAM1 I think the current price of mobile access (device + user fees) can be accepted; [7] TAM2 I found very easy to use mobile services; [7,28] TAM I think that the use of mobile services is the future TAM3 trend; [28] TAM4 If I had the devices which can access to mobile services, I will apply mobile technology. [25] USE1 Now, the mobile agricultural science and technology knowledge services can meet my needs; [7,28] USE USE2 Use the mobile agricultural science and technology knowledge services that will save me a lot of time; [10,28] Use the mobile agricultural science and technology USE3 knowledge services can increase crop yield, reduce pests and diseases. [25] CC1 I must see other people to use the mobile agricultural science and technology knowledge services, then I will use it; [7] CC I understand the mobile agricultural science and technology knowledge services, through advertising and [10] CC2 brochures, then, start to use it; CC3 I got the information for using the mobile agricultural technology knowledge services from relatives or friends. [28] TRU1 When I am accepting the mobile agricultural science and technology knowledge services, if ask for the personal information, I will refuse; [29] The website or company that provides the mobile agricultural TRU science and technology knowledge services, TRU2 should keep its promise; [29] I believe that the mobile agricultural science and technology TRU3 knowledge services provide all of the approach and knowledge are right. [25] BI1 When I heard that there are the mobile agricultural science and technology knowledge services, I have an idea of trying it; [29] When I meet the question that I do not understand BI BI2 in labor, I would like to solve it through the mobile agricultural science and technology knowledge services; [28] Use the mobile agricultural science and technology BI3 knowledge services to solve the questions, and I have [10] more sense of achievement. BA1 I would like to recommend the mobile agricultural science and technology knowledge services to other people; [7] BA BA2 I always use the mobile agricultural science and technology knowledge services; [30] BA3 I will continue to use the mobile agricultural science and technology knowledge services. [30]

7 THE STRENGTH OF TRUST: DISCUSSION ON THE INFLUENCING FACTORS 6985 Table 2. Cronbach s alpha of the latent variable, AVE and the composite reliability Variables Cronbach s alpha The composite AVE name coefficient reliability TAM USE CC TUR BI BA Exploratory factor analysis. Using SPSS17.0 to analyze the survey data by factor analysis. KMO value is And it passed the Bartlett s sphericity test (p < 0.000). Extraction method uses the principal component analysis (PCA), and rotation method uses standardization of the orthogonal rotation method with Kaiser. According to the principle that the characteristic values are greater than 1, 6 factors were extracted. The result was shown in Table 3. Table 3. Rotated component matrix a Factors Measures TAM TAM TAM TAM USE USE USE CC CC CC TRU TRU TRU BI BI BI BA BA BA a: After 6 iterations, the convergence rotation Confirmatory factor analysis. Using LISREL8.7 to examine the confirmatory factor analysis, and calculate the AVE values of each variable and the composite reliability, as the following Table 2. The values of AVE, except BA (AVEBA = ), are greater than 0.5, and the composite reliability are all greater than 0.7. In order to test the discriminatory validity of scales, study the square root of AVE and the correlation coefficient, as shown in Table 4. We can see that the square root of AVE

8 6986 Y. HUO, L. MA AND D. YANG is greater than the correlation coefficient from Table 4. The discriminatory validity is shown good. Table 4. The square root of AVE and correlation coefficient a TAM USE CC TRU BI BA TAM USE CC TRU BI BA a. Correlation coefficients were listed in the lower left; the square root values of AVE were diagonal elements. 6. Hypothesis Testing, Model Revise and Results Discussion Hypothesis testing and model revise Hypothesis testing. Use LISREL8.7 to test the theoretical models. Standardized coefficients and T values of each path are shown in Table 5. Table 5. The test results of the hypothesis about the model Hypothesis Standardized coefficients of path T values Results H Support H2a Support H2b Reject H3a Support H3b Reject H4a Support H4b Reject H4c Reject H5a Support H5b Reject Note: p < 0.05; p < Table 5 shows that the behavior of intention impact on the behavior of adoption was supported; the adoption of mobile impact on the behavior of intention was supported, but impact on the behavior of adoption was rejected; usefulness impact on the behavior of intention was supported, but impact on the behavior of adoption was rejected; communication channels impact on the trust was supported, but impact on the behavior of intention was rejected, also the behavior of adoption; the trust impact on the behavior of intention was supported, but impact on the behavior of adoption was rejected Model revise. According to the test results, delete the path which was rejected ( t < 1.96), following the principles of t from small to large every time. When delete a path, we need to recalculate it. Finally, we can get the modified model as shown in Figure 2. The fit indices of the modified model were shown in Table 6. The first line is the recommended values and the second line is the actual values.

9 THE STRENGTH OF TRUST: DISCUSSION ON THE INFLUENCING FACTORS 6987 Figure 2. The modified model and significant Table 6. The recommended value and actual value of fit indices Fit indices χ 2 /dx GFI AGFI NFI IFI CFI RMR RMSEA Recommended values < 5 > 0.9 > 0.8 > 0.9 > 0.9 > 0.9 < 0.05 < 0.08 Actual values Results discussion. (1) The ordering of the factors that influence farmers to adopt mobile agricultural knowledge services. The structural model shows that, the adoption of mobile, usefulness, the communication channels, trust, and adoption behavior and so on, all of these will have a direct or indirect effect on farmers adoption. The ordering of the influencing factors was shown in Table 7. Table 7. The ordering of the factors that influence farmers to adopt mobile agricultural knowledge services Factors Direct effect Indirect effect Comprehensive effectiveness Ordering TAM USE CC TRU BI (2) The adoption of mobile affects the behavior of intention, not the behavior of adoption. That means whether access to mobile networks has no direct effect on adoption behavior of mobile agricultural science and technology knowledge services in rural areas. However, when asked if have the intention for adopting the mobile knowledge services, TAM shows a certain influence. This also explains that mobile commerce is not a major dissemination channel of agricultural scientific and technological knowledge. (3) Usefulness affects the behavior of intention, not the behavior of adoption. Farmers adopt the mobile agricultural science and technology knowledge services that are not directly caused by the usefulness; it approves the conclusions of the second discussion: mobile commerce is not a major dissemination channel of agricultural scientific and technological knowledge.

10 6988 Y. HUO, L. MA AND D. YANG (4) Information communication channels affect trust, not directly affect the behavior of intention and the behavior of adoption. The channels get the new services form agricultural science and technology knowledge will affect the farmers degree of trust. The degree of trust affects farmers behavior of intention, thus indirectly affects the behavior of adoption. 7. Conclusions and Prospect. This paper inspired us to get the following conclusions: (1) Mobile commerce service does not play a significant role in the dissemination of agricultural science and technology knowledge. This is also the reason of the generally small influencing coefficients. Therefore, to get mobile commerce in the dissemination of agricultural science and technology knowledge which play an important role, we must vigorously promote in many ways. (2) The behavior of intention as an intermediate variable plays a very big role. Therefore, promoting the dissemination of knowledge of agricultural science and technology by mobile commerce service, its primary task is to improve farmers behavior of intention, Penetration of mobile technology and perceived usefulness for mobile agricultural science and technology knowledge services in rural areas. (3) Trust is another important mediating variable. Different channels of information dissemination significantly impact on the trust of farmers on the new services, and thus, impact the behavior of intention and the behavior of adoption. So, selecting the most trusted channel to promote this new service is very important. Innovative results of this paper are that clearly enhancing the farmer s adoption intention, popularizing rate of mobile service in rural areas and improving the farmer s trust can enhance the intermediary role of mobile service in diffusing the knowledge of agricultural science and technology. So far, these have not described in the other literature, but also a lot of the history papers were read by authors, and to be the appropriate theory to guide practice, and through empirical analysis to get the conclusions. At the same time, through this paper s study, we found that penetration rate of mobile technology in rural areas, the adoption intention and trust are the important factors for affecting farmers to adopt mobile services of agricultural science and technology knowledge. Authors will do further research on these three aspects. Acknowledgment. This work is supported by the National Natural Science Foundation, China (Approval No ). REFERENCES [1] S. D. Oliner and D. E. Sichel, The resurgence of growth in the late 1990s: Is information technology the story? Journal of Economic Perspectives, vol.14, no.4, pp.3-22, [2] J. Rolfe, S. Gregor and D. Menzies, Reasons why farmers in Australia adopt the Internet, Electronic Commerce Research and Applications, vol.2, pp.27-41, [3] N. Li, L. Wang, Q. Liu, W. Chen and R. Wang, Farmers altitude towards two key propaganda means, Management of Agriculture Science and Technology, vol.22, no.2, pp.19-22, [4] X. Wang, H. Li and J. Duan, Application of Internet in rural areas of the northwest: HuangYang Chuan mode as a case, Journalistic University, vol.1, pp.61-65, [5] N. W. Lo and K.-H. Yeh, A novel authentication scheme for mobile commerce transactions, International Journal of Innovative Computing, Information and Control, vol.6, no.7, pp , [6] M. Parthasarathy and A. Bhattacherjee, Understanding post-adoption behavior in the context of online service, Information Systems Research, vol.9, no.4, pp , [7] S.-Y. Hung, C.-Y. Ku and C.-M. Chang, Critical factors of WAP services adoption: An empirical study, Electronic Commerce Research and Applications, vol.2, pp.42-60, 2003.

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