From free to paid: Customer expertise and customer satisfaction on knowledge payment platforms
From free to paid: Customer expertise and customer satisfaction on knowledge payment platforms
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从免费到付费：知识付费平台上的客户专业知识和客户满意度
DOI：
10.1016/j.dss.2019.113140
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发表时间：
2019
影响因子：
7.5
通讯作者：
Zhang Mingyue
中科院分区：
文献类型：
--
作者：
Zhang Jin;Zhang Jilong;Zhang Mingyue
在这项研究中，我们调查了哪些因素是影响客户满意度的付费知识，特别是在不同的客户群，通过整合用户活动的免费和付费平台。考虑到知识获取的复杂性，我们首先提出了一种新的测量“客户专业知识”的基础上，文本挖掘，作为客户细分的标准。利用价值感知多样性理论，我们假设一个概念模型，提出具有不同专业知识的客户会对知识和历史知识消费交易的价格做出不同的反应，客户满意度。我们通过层次OLS回归对模型进行了实证检验，数据来自Zhihuan和Zhihu Live。通过区分专家型和新手型顾客，发现：（1）专家型顾客对价格的敏感性较低;（2）历史价格对新手顾客的满意度有正向影响，对专家型顾客有负向影响;（3）专家型顾客受历史满意度的影响较小。
In this study, we investigate what factors are influential to customer satisfaction of paid knowledge, especially among different customer segments, by integrating user activities on both free and paid platforms. Considering the complexity of knowledge acquisition, we first propose a novel measurement of “customer expertise” based on text mining, as a criterion for customer segmentation. Drawing upon the value-percept diversity theory, we then postulate a conceptual model proposing that customers with different expertise would react differently to the price of knowledge and historical knowledge-consuming transactions, in terms of customer satisfaction. We test the model empirically through the hierarchical OLS regression with data collected fromZhihuandZhihu Live. Distinguishing expert and novice customers, we have findings that (1) expert customers are less sensitive to price; (2) historical price positively influences the satisfaction of novice customers, but negatively for expert customers; (3) expert customers are less influenced by historical satisfaction, which have important implications for market targeting and knowledge pricing strategy.