Adnan Muhammad Shah1, Xiangbin Yan2, Syed Asad Ali Shah3, Syed Jamal Shah4, Gulnara Mamirkulova5. 1. Department of Management Science and Engineering, School of Management, Harbin Institute of Technology, Harbin, People's Republic of China. Electronic address: adnanshah@stu.hit.edu.cn. 2. Department of Management Science and Engineering, School of Management, Harbin Institute of Technology, Harbin, People's Republic of China. Electronic address: xbyan@hit.edu.cn. 3. Department of Management Science and Engineering, School of Management, Harbin Institute of Technology, Harbin, People's Republic of China. Electronic address: asadshah@hit.edu.cn. 4. Department of Management Science and Engineering, School of Management, Harbin Institute of Technology, Harbin, People's Republic of China. Electronic address: jimmikakakhail@stu.hit.edu.cn. 5. Department of Management Science and Engineering, School of Management, Harbin Institute of Technology, Harbin, People's Republic of China. Electronic address: gulnara-20.91@mail.ru.
Abstract
INTRODUCTION: With the growth in Internet technology, online rating websites encourage patients to contribute actively in rating their physicians. These rating sites provide more information for patients, such as electronic word of mouth (eWOM) and physician trustworthiness. Although several studies in e-commerce have investigated the role of eWOM and seller trustworthiness in the consumer purchase decision-making process and the price premium for products or services, studies on the role of different information sources that reflect the service quality and delivery process in choosing a competent physician remain scarce. This research develops a two-equation model to examine the effect of different signals, i.e., patient-generated signals (PGSs) and system-generated signals (SGSs), on patient choice, which is an important predictor of physicians' economic returns. METHODS: A secondary data econometric analysis and structural modeling using 2896 physicians' real data from a publicly available online physician rating site, i.e., Healthgrades.com, were conducted using a mixed-methods approach. A hybrid text mining approach was adopted to calculate the sentiment of each review. RESULTS: We find that both PGSs and SGSs have a significant impact on patient choice at different stages of health consultation. Furthermore, disease risk negatively moderates the association between PGSs and information search, while the impact of both signals on patient willingness to pay a price premium is positively moderated by the disease risk. CONCLUSION: Our study contributes to the unified framework of signaling theory and Maslow's hierarchy of needs theory by making a clear distinction between PGSs or SGSs and their influence on patient decision-making across different disease risks. Moreover, PGSs and SGSs are two essential factors for physicians to increase their income.
INTRODUCTION: With the growth in Internet technology, online rating websites encourage patients to contribute actively in rating their physicians. These rating sites provide more information for patients, such as electronic word of mouth (eWOM) and physician trustworthiness. Although several studies in e-commerce have investigated the role of eWOM and seller trustworthiness in the consumer purchase decision-making process and the price premium for products or services, studies on the role of different information sources that reflect the service quality and delivery process in choosing a competent physician remain scarce. This research develops a two-equation model to examine the effect of different signals, i.e., patient-generated signals (PGSs) and system-generated signals (SGSs), on patient choice, which is an important predictor of physicians' economic returns. METHODS: A secondary data econometric analysis and structural modeling using 2896 physicians' real data from a publicly available online physician rating site, i.e., Healthgrades.com, were conducted using a mixed-methods approach. A hybrid text mining approach was adopted to calculate the sentiment of each review. RESULTS: We find that both PGSs and SGSs have a significant impact on patient choice at different stages of health consultation. Furthermore, disease risk negatively moderates the association between PGSs and information search, while the impact of both signals on patient willingness to pay a price premium is positively moderated by the disease risk. CONCLUSION: Our study contributes to the unified framework of signaling theory and Maslow's hierarchy of needs theory by making a clear distinction between PGSs or SGSs and their influence on patient decision-making across different disease risks. Moreover, PGSs and SGSs are two essential factors for physicians to increase their income.