中国B2C电子商务中消费者信任的实证研究

An Empirical Study On Consumer Trust in B2C ecommerce
in China
ABSTRACT
Consumer trust has been more and more recognized as an important factor for a successful e-commerce vendor. Based on the previous research, this paper developed an extended model for analyzing the main attributes of trust of the users in China. A survey regarding the trust of e-commerce users is conducted to empirically test the model. The result shows the perceived reputation and size; the level of multi-channel integration, the system assurance, consumers’ propensity to trust and experienced-based familia rity are all positively related with consumers’ trust in the vendor. The findings may provide the suggestions for the vendors to consider the trustworthy by the consumers.
KEYWORDS
E-commerce; consumer trust; China
I. INTRODUCTION
E-business (electronic commerce) is described as the process of buying, selling, transferring, or exchanging products, services, and/or information via computer networks,including the Internet. There are many advantages driving the growth of e-commerce in the recent decades. Time saving, a greater variety of choices and cheaper prices are the three main advantages. But like the traditional business, problems emerge as e-commerce becomes more popular. The consumers’ trust in e-commerce is becoming the most significant problem. One of the key factors that make an e-commerce successful is the ability to gain consumer trust.
Trust is defined as in this study as a consumer’s positive expectations regarding an e-vendor’s conduct, characterized as faith, confidence and assurance. Trust create positive feelings towards transactions with web retailers, and thus is considered as one of the major mechanisms to reduce perceptions of behavioral uncertainty related to actions of web retailers [7].This research is focused on examining the influential factors of consumer trust by empirical experimentation to provide a basis for
e-commerce vendors to improve their businesses.
II. LITERATURE REVIEW, RESEARCH MODEL AND
HYPOTHESES
Trust is an important factor in many social and economic activities. In the context of Internet business, trust is critical because of the nature and also the limitations of online business—the invisibility of the transaction process, the physical separation between buyers and sellers, the physical separation between buyers [1]. These limitations cause greater uncertainty that all consumers try to avoid when making any purchase decisions.
In prior research, Mayer [2] proposed a model incorporating both a trusting party (trustor) and a party to be trusted (trustee). They discusse d the trustor’s perception about the trustees’ characteristics. Jarvenpaa [3] examined whether customers’ perceptions about the reputation and size of an Internet store affect their trust in the store and Bendoly examined the channel integration on consume r’s loyalty to a multi-channel firm.
Some of the previous research identified and examined the trust in term of one single aspect of the trustees and trustors respectively. Our research develops a research model by involving the attributes all variables from both aspects of trustors and trustees. As shown in Figure 1, the consumer’s trust is mainly influenced by perceived reputation and size, multichannel integration, system assurance, consumer feedback mechanism, propensity to trust and experience.
A. Characteristics of trustees (e-commerce vendors)
a) Perceived reputation and size
Research in traditional industrial buyer-seller relationships revealed that buyer’s perceptions of seller’s reputation and size are the factors of trustworthiness [4].
Reputation is defined as the extent to which buyers believe a seller is professionally competent or honest and benevolent. Reputation is vulnerable because it is harder to form a reputation than to lose it [6]. For instance, due to the Sanlu milk powder event, customers showed great decrease in trust in domestic milk powder producers.
Doney and Cannon [5] defined a seller’s size as its overall size and market share position. Size could indicate many things. Second large size means the business is recognized by a large population of customers, which gives the potential customers a signal that the business is reliable. So we hypothesize that:
H1. The perceived reputation and size of e-commerce vendor is positively related to the level consumers’ trust in the vendor.
b) Multi-channel integration
Daniel and Wilson [8] identified integration across channels to enable multi-channel service as one of the key dynamic capabilities necessary for e-business transformation. A fully integrated channel also enables the vendor to provide a customized service in the most satisfied way for the customers, which in return will increase customer’s confidence in their shopping experience, thus will increase their trust in the vendor. Therefore our hypothesis is:
H2. The level of multi-channel integration of an ecommerce vendor is positively related to the level of consumers’ trust in the vendor.
c) System assurance
System assurance is defined as the dependability and security of a vendor’s online transaction system, which enables transactions through the Internet, be secure and successful [1].A well-established security system lays a solid foundation for a successful e-commerce; it indicates that consumers’ money is guaranteed to be safe, which will consequently increase consumers’ trust in the vendor. Hence, it follows:
H3. The system assurance of an e-commerce vendor is positively related to the level of consumers’ trust in the vendor.
d) Consumer feedback mechanism.
For first-time visitors, other consumers’ feedback and attitudes may work as a necessary reference in forming attitude judgment. [9] [10] [11]. A perfect feedback mechanism should be instantaneous, transparent and honest. A well-established feedback mechanism can give consumers a better view of the business, and increase their trust in the vendor. So we hypothesize that:
H4. A consumer’s evaluation on the website’s feedback mechanism is positively
related to the level consumers’ trust in the vendor.
B Characteristics of trustors. (consumers)
a) Propensity to trust
A co nsumer’s disposition to trust is a general inclination to display faith in humanity and to adopt a trusting stance toward others [12]. Influenced by cultural background, personality type and previous experience, consumers differ in their inherent propensity to trust [2]. This tendency is based not upon experience or knowledge of a specific trusted party, but is instead the result of ongoing lifelong experiences and socialization [13] [14] [15]. Existing research has revealed that an individual’s propensity to trust has a major influence on his/or her trust [12]. Hence we hypothesize that:
H5. Propensity to trust is positively related to the level of consumers’ trust in the e-commerce vendor.
b) Experience-based familiarity
A consumer’s familiarity with the O nline Selling Party (FAM) refers to the consumer’s degree of acquaintance with selling entity, which includes the knowledge of the vendor and understanding its relevant procedures such as searching for products and information and ordering through the Website’s purchasing interface [4]. The more familiar a consumer is with the vendor, the higher trust the consumer has in the vendor. Hence, our hypothesis is:
H6: The level of consumers’ familiarity with the vendor is positively related to the level of co nsumers’ trust in the ecommerce vendor.
III. RESEARCH METHODS
A. Measure
The measures used in this research are mainly adapted from relevant prior studies. 15 questionnaire items are developed and revised by some experts with significant experiences in ecommerce.Some of the items are also revised in accordance with the results of pilot test by 20 e-business consumers. Most of the items are measured using 5-point Likert scale ranged from 1 as strongly disagree to 5 as strongly agree.
B. Data collection
The target group of the online questionnaire is those consumers using e-business website , the leader of B2C e-commerce in China. We communicated with them by using online chatting software and sent questionnaires to them.The total of 500 questionnaires is distributed and 115 usable responses are generated, resulting in 23%.
IV. RESULTS AND DATA ANALYSIS
A. Demographic pro respondents
Table I summarizes the demographic pro descriptive statistics of the respondents. The subjects consist 61 males (53.04%) and 54 females (46.96%). The gender percentage of the China respondents is very comparable to the result of CNNIC [16], which reported that 54.2% of the respondents were males in 2009. In addition, most of our respondents are age from 15 to 30. Moreover, most of our respondents are well educated. The educational level of 95.65% of the respondents is higher than junior college(including junior college). What’s more, 83.48% of the respondents spend more than 2 hours per day on Internet.
B. Reliability and Validity
As mentioned, the pilot test and the experts’ revision were conducted to improve the validity. SPSS was used for statistical analysis. Reliability was examined using Cronbach’s alpha value. As shown in Table II, almost all the alphas for these factors are good enough, and the alpha which including all the influencing factors is 0.943, which is surprisingly high to show that the total performance of the internal consistency for reliability of the result is good.
C. Means, Standard deviations and Correlations
The means, standard deviations and correlations between variable are presented in Table II. Among all the variables, most of the means except the propensity to trust are bigger than 4 and are very close to the mean of the intention to purchase, which was similar to the results of standard deviation. We also calculated the correlation between all the answers of each question and the answers of the question directly related to respondents’ intention to purchase which were seen as the consumer trust.
And the data of correlation was also shown in table 2. We can find that the correlation data for all the influencing factors are larger than 0.6, which means they have direct positive relation with consumer trust, which proved our hypotheses to be correct.
V. DISCUSSION
Overall our results can support our proposed hypotheses. As shown in our results, we can find that the correlation between consumer trust and all these six factors are bigger than 0.6, which means that all these factors are well positively related to the consumer trust.
The first finding from the result of our research is that even though consumers’ propensities to trust has a very low means,but the correlation with consumer trust is still very high. The correlations (0.772 and 0.784) in our result show that the positive relationship between the propensity to trust and consumer’s trust towards e-vendors really exist. Even though more and more people are not willing to trust others, different people’ growing process still shaped their diffe rent standards to trust and rely, which greatly impact their trust on the e-vendor.To make this finding into practices, the vendors can provide more descriptions of the products or services to provide more detailed information.
From the results of research, we found that the result of the experience (familiarity) was very similar to the results of other researches that experience (familiarity) has a significantly positive relationship with consumers’ trust. Our confidence and trust are closely related to the lifelong socialization process with all the people around. In this way, this result would help the e-vendor a lot if the vendor can provide an impression to the consumers that the system or the trading way they use is familiar, and then consumers are likely to relate their experience to the e-vendor, which can greatly increase the consumer trust. What’s more, the e-vendor also can provide detailed flow of the whole trading process to increase consumers’ familiarities for the e-vendor.
By study our research reports, we also found that all these 4 factors of trustees
(Perceived reputation and size, Multichannel Integration, System Assurance, Consumer feedback mechanism) were well related to consumer trust.
Consumer feedback mechanism can reduce cons umers’perceived risk as they can know other purchasers’ opinions toward the e-vendor. The result of the research of Jarvenpaa et al. [3] and Shemwell et al. [17] proved that consumers’perceived risk has the negative effect on consumers’ trust toward vendors. Most respondents supported the idea that if the website could provide more detailed feedbacks, and tried to improve the quality of the information, they would be more willing to purchase from the vendor. In this way, it would be helpful for e-vendors if they can perfect the feedback mechanism and guarantee the quality of the feedback information to show their honesty and good quality.
The perceived reputation and size also showed good relationship with consumers’ trust. Good reputation gives consumers an impression of honesty, and big size can give consumers an impression of satisfying services, which are very important to build consumer trust. In this way, it is helpful for an e-vendor to publicize the successful operation and scale of the website to give the consumers an impression of good reputation and size. That’s why advertisement is a good way to gain consumers’ trust.
Multichannel Integration also has shown its strong relationship with consumers’ trust by analyzing the results of our research. After the survey, we proved our hypotheses, and found the relationship indeed exists. In this way, the e-vendors should provide more detailed information for consumers to contact, and also provide more customized services.
Similar to other researches, we also found that system assurance had close relationship with consumer trust. Trading with the cooperation of third party and applying more functions to help protect consumer’s securities can help improve consumer’s trust which was shown in our research results. In this way, it is necessary for e-vendors to apply secure trading system to win consumer trust. What's more, most of the respondents paid attention to the secure of their private information, so it is also helpful for e-vendors to apply more functions on the protection of consumers’
private information.As many consumers were afraid of the losses resulting from their own mistakes during trading process, so we suggest that the website should provide more detailed directions for new users so that make them feel more confident to buy.
VI. CONCLUSION
The research is to find out what are the main practical factors that can affect consumer trust toward e-business and the research model is developed to test the main relationships between the influential factors and trust. After the data collection and data analysis, we found all the factors, perceived reputation and size, multichannel integration, system assurance, consumer feedback mechanism, propensity to trust and experience, all positively affected the trust. Comparing to previous research, our research have some new findings. First, the propensities to trust for some studies were low, but it still had close relationship with consumer trust. Second, our findings would be helpful for e-vendors to develop business strategies coping with the changing market in China.
The research also has some limitations such as the volume of respondents is not quite large, the cross-sectional survey was done in 2 months. But the result of our research still can almost confirm our hypotheses to be correct. And we believe using correlation function is enough to prove our ideas. And we will continue to do the research to confirm the results and try to conduct some practical implications. The research also supported previous researcher s’ achievements and settled foundation for further research.。