移动商务用户信任演化过程及影响因素研究
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摘要
摘要：随着移动技术的迅速发展和普及应用,移动商务已经是大势所趋,并正在改变着人们的工作、生活、行为方式。进入移动商务市场的公司都希望通过这一新的渠道获得更多的客户价值,而成功的移动商务应用则依赖于用户信任。因而,系统地研究移动商务环境下用户信任的演化过程及其影响因素,具有非常重要的现实意义。
本研究构建了移动商务用户信任演化的生命周期概念模型,对其动态演化过程进行了仿真分析。针对其生命周期的具体阶段,分别构建了信任建立路径模型和持续信任模型,通过实证研究,挖掘出影响移动商务信任演化的具体因素。本研究的主要贡献体现在以下几个方面：
首先,基于电子商务用户信任生命周期理论,结合移动商务的特点,提出了移动商务用户信任演化的生命周期概念模型,并将其作为本研究的主线。移动商务用户信任的生命周期,在快速信任、初始信任、持续信任、信任消失(或不信任)几种不同状态中演化。一般情况下,通过互动、交流等方式,用户将逐步地建立起的对某个具体商家的初始信任；在移动商务环境下,由于突发性需求,用户会快速地采纳移动商务的某个具体应用,这就隐含着用户对移动商务的最初的快速信任；不论是由初始信任还是快速信任导致的行为,如果获得了正向的结果,都将促使信任向持续和稳定演化,反之将导致信任的消失甚至是不信任。
其次,本研究运用演化博弈理论,从商家—用户的交易成本入手,构建了移动商务用户信任动态演化模型。对模型进行了动态演化及均衡状态分析,运用Netlogo软件对演化过程进行了计算机仿真。研究发现：在用户与商家的博弈过程中,存在4个博弈平衡点和1个鞍点,和两个2个动态均衡(ESS)状态：(信任,守信),(不信任,失信)。用户信任的建立与演化,不仅仅是用户个体的决策与行为,还受到其所处群体的决策行为影响。对4个博弈平衡点进行合理的控制和调节,可以促使移动商务市场达到(信任、守信)的均衡状态。
第三,构建了移动商务环境下用户信任的建立路径模型,从个人、商家、技术、环境四个方面,将影响移动商务用户信任建立的因素归纳为：基于个性的信任前因(信任倾向)、基于对商家和技术的认知的信任前因(系统质量)、基于环境的信任前因(结构保证)。运用结构方程模型进行实证研究,结果表明：移动商务环境下,用户信任的建立有两条路径：既可以是由于外界“输入”因素影响而快速产生的快速信任；也可以是由于获得二手资料,与商家的互动而逐步建立起来的初始信任。信任信念对信任意向有显著影响；系统质量对信任信念影响最大；结构保证显著地影响用户的信任意向,对信任信念却没有显著影响；个人信任倾向对信任信念、信任意向均有显著且正向的影响。
第四,借用信息系统成功模型,结合信任理论,构建了移动商务用户持续信任模型。以移动软件商店为调查的数据来源,运用结构方程模型进行了实证研究。研究表明,老用户具有更高的移动商务认知度,系统的连接质量对持续信任没有显著影响,用户满意度是影响持续信任的主要因素。用户感知的信息质量、系统质量、服务水平均通过满意度的中介作用正向影响对商家的持续信任。系统质量对用户的持续信任亦有直接正向的影响。研究还特别发现：移情负向影响用户满意度,并由于满意度的中介作用,负向影响对商家的持续信任。这反映了当前移动商务中用户的一种负面态度,启示商家在进行移动营销活动时,要注意与用户联系的频度,避免适得其反的过度问候与宣传。
Abstract:Along with the rapid development and popular application of mobile technology, mobile commerce has already been in the trend and changed people's work, lifestyle and behavior. Companies in the mobile commerce market are hoping to gain more customer value; somehow, successful mobile commerce application relies on customers'trust. Customer's trust is the key element for mobile commerce's success. Therefore, this article systematically studies on the process of customer trust development, which will achieve an important practical significance.
This study first builds the life-cycle conceptual model of customers trust development in m-commerce, and then simulated the dynamic evolution process. To the first stages of the life-cycle, the study constructed the model of establishing route and factors affecting trust. To the stage of stability of the life-cycle, the study constructed the continuous trust model. Via empirical researches, this study disclosed the determinants of customer trust development in m-commerce. The main contributions of this study are reflected as below:
First, the study builds the life-cycle conceptual model of customers trust development in m-commerce based on the life-cycle theory of e-commerce and the characteristics of m-commerce. The stage can be divided to swift trust, initial trust, continuous trust, and untrust (or distrust). In m-commerce environment, due to their own task characteristics, customers may quickly build trust to a specific application of m-commerce, we called this kind of trust as swift trust; through interaction, communication, etc., customers may also gradually build their trust to vendors, we called this kind of trust as initial trust; whether by swift trust or initial trust, if customers obtained positive results, their trust will be continuance and stability, on the contrary, their trust would lead to disappear or even change to distrust.
Second, Based on the evolutionary game, according to the merchants-customers transaction costs; the study analyzes the dynamic evolution and state of equalization of customer trust in m-commerce, and then simulates the process with the Netlogo software platform. The study shows that, in the game between merchants and customers, there are exists4dynamic equilibrium points, one saddle point and two ESS:(trust, honesty),(distrust dishonesty). The establishment and development of customer trust are not only the individual decisions but also limited with the decisions of the colonial that individual lives in. Reasonable control and regulate the5equilibrium points, will lead m-commerce market to the equilibrium state of (trust, honesty).
Third, the study builds the model of establishing route and factors affecting trust according to the establishing steps of the conceptual model in m-commerce. Three factors, which are personal disposition to trust, structural assurance, and perceived system quality from four areas (individuals, businesses, technology, and environment), are proposed for building consumer trust in m-commerce. Via SEM, empirical studies indicate that trust belief has a significant effect on trust intention. Impact on the trust belief is system quality, followed by personal disposition, sex. Structural guarantee significantly affect trust intention, but had no significant effect on the trust and faith. Personal disposition has significant and positive effects on trust belief and trust intention. It reveals that there are two paths to establish m-commerce trust. One way is swift trust. Another way is initial trust, gradually established through interaction. Perceived system quality has a significant impact on initial trust, while structural guarantee and personal disposition have a significant effect on swift trust.
Finally, the study constructs the continuous trust model according to the stability steps of the conceptual model in m-commerce. Considered the impact factors of information systems success, combining trust theory, build a Customers Continuous Trust model in m-commerce. Valid samples were gathered through a survey website, and structural equation modeling is employed to assess the proposed research model and hypotheses empirically. The results show that:customers'satisfaction has a significant effect on continuous trust in m-commerce. Perceived information quality, perceived system quality, and service level positively influence satisfaction. Thus, they will positively influence continuous trust via the mediator of satisfaction. Perceived system quality also has a direct positive impact on continuous trust. The study has a difference discovery with e-commerce:empathy negatively affects customer satisfaction. So, it will be a negative impact to continuous trust in m-commerce.
本研究构建了移动商务用户信任演化的生命周期概念模型,对其动态演化过程进行了仿真分析。针对其生命周期的具体阶段,分别构建了信任建立路径模型和持续信任模型,通过实证研究,挖掘出影响移动商务信任演化的具体因素。本研究的主要贡献体现在以下几个方面：
首先,基于电子商务用户信任生命周期理论,结合移动商务的特点,提出了移动商务用户信任演化的生命周期概念模型,并将其作为本研究的主线。移动商务用户信任的生命周期,在快速信任、初始信任、持续信任、信任消失(或不信任)几种不同状态中演化。一般情况下,通过互动、交流等方式,用户将逐步地建立起的对某个具体商家的初始信任；在移动商务环境下,由于突发性需求,用户会快速地采纳移动商务的某个具体应用,这就隐含着用户对移动商务的最初的快速信任；不论是由初始信任还是快速信任导致的行为,如果获得了正向的结果,都将促使信任向持续和稳定演化,反之将导致信任的消失甚至是不信任。
其次,本研究运用演化博弈理论,从商家—用户的交易成本入手,构建了移动商务用户信任动态演化模型。对模型进行了动态演化及均衡状态分析,运用Netlogo软件对演化过程进行了计算机仿真。研究发现：在用户与商家的博弈过程中,存在4个博弈平衡点和1个鞍点,和两个2个动态均衡(ESS)状态：(信任,守信),(不信任,失信)。用户信任的建立与演化,不仅仅是用户个体的决策与行为,还受到其所处群体的决策行为影响。对4个博弈平衡点进行合理的控制和调节,可以促使移动商务市场达到(信任、守信)的均衡状态。
第三,构建了移动商务环境下用户信任的建立路径模型,从个人、商家、技术、环境四个方面,将影响移动商务用户信任建立的因素归纳为：基于个性的信任前因(信任倾向)、基于对商家和技术的认知的信任前因(系统质量)、基于环境的信任前因(结构保证)。运用结构方程模型进行实证研究,结果表明：移动商务环境下,用户信任的建立有两条路径：既可以是由于外界“输入”因素影响而快速产生的快速信任；也可以是由于获得二手资料,与商家的互动而逐步建立起来的初始信任。信任信念对信任意向有显著影响；系统质量对信任信念影响最大；结构保证显著地影响用户的信任意向,对信任信念却没有显著影响；个人信任倾向对信任信念、信任意向均有显著且正向的影响。
第四,借用信息系统成功模型,结合信任理论,构建了移动商务用户持续信任模型。以移动软件商店为调查的数据来源,运用结构方程模型进行了实证研究。研究表明,老用户具有更高的移动商务认知度,系统的连接质量对持续信任没有显著影响,用户满意度是影响持续信任的主要因素。用户感知的信息质量、系统质量、服务水平均通过满意度的中介作用正向影响对商家的持续信任。系统质量对用户的持续信任亦有直接正向的影响。研究还特别发现：移情负向影响用户满意度,并由于满意度的中介作用,负向影响对商家的持续信任。这反映了当前移动商务中用户的一种负面态度,启示商家在进行移动营销活动时,要注意与用户联系的频度,避免适得其反的过度问候与宣传。
Abstract:Along with the rapid development and popular application of mobile technology, mobile commerce has already been in the trend and changed people's work, lifestyle and behavior. Companies in the mobile commerce market are hoping to gain more customer value; somehow, successful mobile commerce application relies on customers'trust. Customer's trust is the key element for mobile commerce's success. Therefore, this article systematically studies on the process of customer trust development, which will achieve an important practical significance.
This study first builds the life-cycle conceptual model of customers trust development in m-commerce, and then simulated the dynamic evolution process. To the first stages of the life-cycle, the study constructed the model of establishing route and factors affecting trust. To the stage of stability of the life-cycle, the study constructed the continuous trust model. Via empirical researches, this study disclosed the determinants of customer trust development in m-commerce. The main contributions of this study are reflected as below:
First, the study builds the life-cycle conceptual model of customers trust development in m-commerce based on the life-cycle theory of e-commerce and the characteristics of m-commerce. The stage can be divided to swift trust, initial trust, continuous trust, and untrust (or distrust). In m-commerce environment, due to their own task characteristics, customers may quickly build trust to a specific application of m-commerce, we called this kind of trust as swift trust; through interaction, communication, etc., customers may also gradually build their trust to vendors, we called this kind of trust as initial trust; whether by swift trust or initial trust, if customers obtained positive results, their trust will be continuance and stability, on the contrary, their trust would lead to disappear or even change to distrust.
Second, Based on the evolutionary game, according to the merchants-customers transaction costs; the study analyzes the dynamic evolution and state of equalization of customer trust in m-commerce, and then simulates the process with the Netlogo software platform. The study shows that, in the game between merchants and customers, there are exists4dynamic equilibrium points, one saddle point and two ESS:(trust, honesty),(distrust dishonesty). The establishment and development of customer trust are not only the individual decisions but also limited with the decisions of the colonial that individual lives in. Reasonable control and regulate the5equilibrium points, will lead m-commerce market to the equilibrium state of (trust, honesty).
Third, the study builds the model of establishing route and factors affecting trust according to the establishing steps of the conceptual model in m-commerce. Three factors, which are personal disposition to trust, structural assurance, and perceived system quality from four areas (individuals, businesses, technology, and environment), are proposed for building consumer trust in m-commerce. Via SEM, empirical studies indicate that trust belief has a significant effect on trust intention. Impact on the trust belief is system quality, followed by personal disposition, sex. Structural guarantee significantly affect trust intention, but had no significant effect on the trust and faith. Personal disposition has significant and positive effects on trust belief and trust intention. It reveals that there are two paths to establish m-commerce trust. One way is swift trust. Another way is initial trust, gradually established through interaction. Perceived system quality has a significant impact on initial trust, while structural guarantee and personal disposition have a significant effect on swift trust.
Finally, the study constructs the continuous trust model according to the stability steps of the conceptual model in m-commerce. Considered the impact factors of information systems success, combining trust theory, build a Customers Continuous Trust model in m-commerce. Valid samples were gathered through a survey website, and structural equation modeling is employed to assess the proposed research model and hypotheses empirically. The results show that:customers'satisfaction has a significant effect on continuous trust in m-commerce. Perceived information quality, perceived system quality, and service level positively influence satisfaction. Thus, they will positively influence continuous trust via the mediator of satisfaction. Perceived system quality also has a direct positive impact on continuous trust. The study has a difference discovery with e-commerce:empathy negatively affects customer satisfaction. So, it will be a negative impact to continuous trust in m-commerce.
引文
1 资料来源http://tech.sina.com.cn/t/2007-10-21/17101805411.shtml
资料来源KPCB《Top Mobile Internet Trends》
3 数据来源forrester, http://www.forrester.com/Mobile+Commerce+Forecast+2011+To+2016/fulltext/-/E-RES58616?objectid=RES586 16&al=0
4 数据来源：中国电子商务研究中心《2012年度中国电子商务市场数据监测报告》,2013.3.20
1 数据来源GNNIC《2010年中国手机上网行为研究报告》
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资料来源KPCB《Top Mobile Internet Trends》
3 数据来源forrester, http://www.forrester.com/Mobile+Commerce+Forecast+2011+To+2016/fulltext/-/E-RES58616?objectid=RES586 16&al=0
4 数据来源：中国电子商务研究中心《2012年度中国电子商务市场数据监测报告》,2013.3.20
1 数据来源GNNIC《2010年中国手机上网行为研究报告》
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