移动数据业务客户忠诚影响因素研究
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摘要
在新技术和新兴商业模式的推动下,全球的移动数据业务呈现了快速发展的势头,而国内庞大的用户规模和政策的支持更增加了这个市场的吸引力。保持客户忠诚度是这个行业的可持续发展的关键因素,然而无论国际还是国内,情况都不容乐观。移动数据业务作为集成了先进的电信、信息和消费类电子技术的创新型服务,结合了移动通信和Internet的特点,交织着多种商业模式,有着自身的特性和规律。了解移动数据业务客户忠诚的形成机制,明确其中的关键要素及其相互之间的关系,对于营销科学的理论和实践都有着重要的意义。
作为新技术、新业务模式的混合体,移动数据业务的客户忠诚影响机制无法照搬已有的研究结论,需要更有针对性的深入研究。主要有以下几个问题:
第一,作为客户忠诚的重要前导因素:服务质量,在移动数据业务领域,至今仍然缺乏能对不同类型的业务进行统一测量的模型和工具;第二,在对移动数据业务客户忠诚的影响因素分析中,几乎没有研究考虑转移壁垒这个重要因素的影响;第三,该领域现有的研究以建立理论模型为主,却很少考虑如何将理论模型更好地转化为决策模型。
基于上述问题,本文的研究工作主要包括三个部分:
首先,从移动数据业务的IT本质出发,提出了基于技术接受模型(TAM)的概念化服务质量维度的分析框架,然后按照严谨的量表开发规范建立了移动数据业务服务质量测量模型及其对应的测量工具。该模型包括内容质量、易用性、稳定快速、交互性、愉悦性和安全隐私共6个维度。经过用户调查数据的实证,表明该模型能够统一测量不同种类移动数据业务的服务质量。
其次,将移动数据业务服务质量的各个维度和其它客户忠诚的重要影响因素,包括客户价值、客户满意以及转移壁垒集成建模,研究它们对于客户忠诚的共同影响以及它们之间的关系,从而建立移动数据业务客户忠诚影响因素理论模型。实证结果表明,客户价值、客户满意和转移壁垒都显著地正向影响客户忠诚,而转移壁垒还具有一定程度的调节效应;服务质量中安全隐私和稳定快速两个维度对客户价值和客户满意的正向影响最为显著;客户满意是用户态度忠诚的最大影响因素,而客户价值是用户再购买行为意向的最大影响因素,这充分表明移动数据业务的客户忠诚的两个部分:行为和情感的心理决策过程存在一定的差异。
最后,提出了整合偏最小二乘法和贝叶斯网的优点,从理论模型导出决策模型的方法,在检验提出的模型结论(理论)与实际营销现象相关度的同时,为企业决策提供更加有效的支持。利用移动数据业务客户忠诚模型的分析结论以及相应的数据,对该方法进行实证,结果支持了决策模型与理论模型的一致性以及有效性。然后,以移动数据业务客户忠诚管理的实际需求为背景,利用已经建立的贝叶斯网决策模型模拟解决移动数据业务营销管理中的实际问题,展示了它强大的预测和诊断能力。
本文一方面可以看作对服务质量和客户忠诚等营销理论在移动数据业务这个特定应用背景下的一次实证研究;另一方面,随着IT技术越来越深入地渗透到我们周围,进而影响我们的工作与生活方式,对相关营销理论的扩展不可避免,本文就是针对IT技术导向的新兴业务客户忠诚相关因素建模的一次尝试。本文对于移动数据业务的服务质量测量以及客户忠诚影响因素的分析结果可以作为移动运营商制定营销战略的参考,而文中提出的将理论模型向决策模型转换的方法,可以直接应用到企业的决策建模过程中。
The mobile data services are blooming in the whole world. Especially in China, with the biggest mobile communication customer base, the potential of mobile data services is unlimited. Customer loyalty is very critical to substainable development of the mobile data services providers. However, the issues of customer loyalty are still significant.
Because the mobile data services are defined as“all kinds of innovative services that combine technologies and concepts from the domains of telecommunication, information technology, and consumer electronics”, the customer loyalty models and results from traditional services can’t be directly employed. There are three questions awaiting for answer. The first is how to measure the service quality of mobile data services. The second is how the service quality, customer value, customer satisfaction, and switching barriers determine the customer loyalty, and how to interact with each other. The third is how to transform the theory model validated by empirical test to decision model, so the important conclusions can be leveraged to alleviate the difficulties in daily marketing actions.
This research aimed to solve aforementioned problems by following efforts:
Firstly, this study developed and validated an instrument to measure user perceived service quality of mobile data services. A TAM-based conceptual framework was proposed to deduce dimensions of service quality dedicated to mobile data services. Using responses from 322 users, a six dimensions scale was validated involving: content quality, ease to use, reliability and speed, interactive quality, enjoyment quality and security/private. This scale provides a useful instrument for researchers who wish to measure the service quality of mobile data services and managers of service provider who want to improve their service performance.
Secondly, an integrated analysis model was built up to further discussion of the relationships among service quality, perceived value, customer satisfaction, switching barriers and customer loyalty intention. Partial Least Square was used to analyze the data to find out the direct effects and moderate effects on customer loyalty. The main findings are as follows: (1) two service quality dimensions: security/private and reliability/speed positively influences both perceived value and customer satisfaction; Content quality and enjoyment positively influences customer value, and interactive quality positively influence customer satisfactory; (2) perceived value positively influences on both customer satisfaction; (3) customer value and customer satisfaction both positively influences customer loyalty intention, but customer satisfaction mostly influence attitudinal loyalty, and custome value mostly influence repurchase intention. Thus implies the decision approach of customers on repurchase and attitudinal is different; (4) the most ignored factor: switching barriers positive influence on customer value; (5) the moderate effects are existing in whole model, but no interactive variables are significant; (6) the proposed model is proven with the effectiveness in explaining the relationships among service quality, perceived value, customer satisfaction, swiching barriers and customer loyalty in mobile data services.
Either Partial Least Square (PLS) or Bayesian networks are limited in building decision models. To overcome this limitation, this study linking Bayesian networks to PLS. The capability of PLS in empirical validation combined with the prediction and diagnosis capabilities of Bayesian modeling facilitates effective decision making from identification of causal relationships to decision support. This study applies the proposed integrated approach to decision support for customer loyalty management in mobile data services. The application results provide insights for practitioners on how to promote the loyalty of customers in mobile data services context.
作为新技术、新业务模式的混合体,移动数据业务的客户忠诚影响机制无法照搬已有的研究结论,需要更有针对性的深入研究。主要有以下几个问题:
第一,作为客户忠诚的重要前导因素:服务质量,在移动数据业务领域,至今仍然缺乏能对不同类型的业务进行统一测量的模型和工具;第二,在对移动数据业务客户忠诚的影响因素分析中,几乎没有研究考虑转移壁垒这个重要因素的影响;第三,该领域现有的研究以建立理论模型为主,却很少考虑如何将理论模型更好地转化为决策模型。
基于上述问题,本文的研究工作主要包括三个部分:
首先,从移动数据业务的IT本质出发,提出了基于技术接受模型(TAM)的概念化服务质量维度的分析框架,然后按照严谨的量表开发规范建立了移动数据业务服务质量测量模型及其对应的测量工具。该模型包括内容质量、易用性、稳定快速、交互性、愉悦性和安全隐私共6个维度。经过用户调查数据的实证,表明该模型能够统一测量不同种类移动数据业务的服务质量。
其次,将移动数据业务服务质量的各个维度和其它客户忠诚的重要影响因素,包括客户价值、客户满意以及转移壁垒集成建模,研究它们对于客户忠诚的共同影响以及它们之间的关系,从而建立移动数据业务客户忠诚影响因素理论模型。实证结果表明,客户价值、客户满意和转移壁垒都显著地正向影响客户忠诚,而转移壁垒还具有一定程度的调节效应;服务质量中安全隐私和稳定快速两个维度对客户价值和客户满意的正向影响最为显著;客户满意是用户态度忠诚的最大影响因素,而客户价值是用户再购买行为意向的最大影响因素,这充分表明移动数据业务的客户忠诚的两个部分:行为和情感的心理决策过程存在一定的差异。
最后,提出了整合偏最小二乘法和贝叶斯网的优点,从理论模型导出决策模型的方法,在检验提出的模型结论(理论)与实际营销现象相关度的同时,为企业决策提供更加有效的支持。利用移动数据业务客户忠诚模型的分析结论以及相应的数据,对该方法进行实证,结果支持了决策模型与理论模型的一致性以及有效性。然后,以移动数据业务客户忠诚管理的实际需求为背景,利用已经建立的贝叶斯网决策模型模拟解决移动数据业务营销管理中的实际问题,展示了它强大的预测和诊断能力。
本文一方面可以看作对服务质量和客户忠诚等营销理论在移动数据业务这个特定应用背景下的一次实证研究;另一方面,随着IT技术越来越深入地渗透到我们周围,进而影响我们的工作与生活方式,对相关营销理论的扩展不可避免,本文就是针对IT技术导向的新兴业务客户忠诚相关因素建模的一次尝试。本文对于移动数据业务的服务质量测量以及客户忠诚影响因素的分析结果可以作为移动运营商制定营销战略的参考,而文中提出的将理论模型向决策模型转换的方法,可以直接应用到企业的决策建模过程中。
The mobile data services are blooming in the whole world. Especially in China, with the biggest mobile communication customer base, the potential of mobile data services is unlimited. Customer loyalty is very critical to substainable development of the mobile data services providers. However, the issues of customer loyalty are still significant.
Because the mobile data services are defined as“all kinds of innovative services that combine technologies and concepts from the domains of telecommunication, information technology, and consumer electronics”, the customer loyalty models and results from traditional services can’t be directly employed. There are three questions awaiting for answer. The first is how to measure the service quality of mobile data services. The second is how the service quality, customer value, customer satisfaction, and switching barriers determine the customer loyalty, and how to interact with each other. The third is how to transform the theory model validated by empirical test to decision model, so the important conclusions can be leveraged to alleviate the difficulties in daily marketing actions.
This research aimed to solve aforementioned problems by following efforts:
Firstly, this study developed and validated an instrument to measure user perceived service quality of mobile data services. A TAM-based conceptual framework was proposed to deduce dimensions of service quality dedicated to mobile data services. Using responses from 322 users, a six dimensions scale was validated involving: content quality, ease to use, reliability and speed, interactive quality, enjoyment quality and security/private. This scale provides a useful instrument for researchers who wish to measure the service quality of mobile data services and managers of service provider who want to improve their service performance.
Secondly, an integrated analysis model was built up to further discussion of the relationships among service quality, perceived value, customer satisfaction, switching barriers and customer loyalty intention. Partial Least Square was used to analyze the data to find out the direct effects and moderate effects on customer loyalty. The main findings are as follows: (1) two service quality dimensions: security/private and reliability/speed positively influences both perceived value and customer satisfaction; Content quality and enjoyment positively influences customer value, and interactive quality positively influence customer satisfactory; (2) perceived value positively influences on both customer satisfaction; (3) customer value and customer satisfaction both positively influences customer loyalty intention, but customer satisfaction mostly influence attitudinal loyalty, and custome value mostly influence repurchase intention. Thus implies the decision approach of customers on repurchase and attitudinal is different; (4) the most ignored factor: switching barriers positive influence on customer value; (5) the moderate effects are existing in whole model, but no interactive variables are significant; (6) the proposed model is proven with the effectiveness in explaining the relationships among service quality, perceived value, customer satisfaction, swiching barriers and customer loyalty in mobile data services.
Either Partial Least Square (PLS) or Bayesian networks are limited in building decision models. To overcome this limitation, this study linking Bayesian networks to PLS. The capability of PLS in empirical validation combined with the prediction and diagnosis capabilities of Bayesian modeling facilitates effective decision making from identification of causal relationships to decision support. This study applies the proposed integrated approach to decision support for customer loyalty management in mobile data services. The application results provide insights for practitioners on how to promote the loyalty of customers in mobile data services context.
引文
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