scholarly journals Using Servqual to Examine Service Quality in the Classroom: Analyses of Undergraduate and Executive Education Operations Management Courses

2013 ◽  
Vol 8 (20) ◽  
Author(s):  
Cyril Foropon ◽  
Ruth Seiple ◽  
Laoucine Kerbache
Keyword(s):  
Service Quality ◽  
Operations Management ◽  
Executive Education

The Interplay Between Online Reviews and Physician Demand: An Empirical Investigation

2021 ◽  
Author(s):  
Yuqian Xu ◽  
Mor Armony ◽  
Anindya Ghose
Keyword(s):  
Service Quality ◽  
Operations Management ◽  
Choice Model ◽  
Healthcare Delivery ◽  
Online Reviews ◽  
The United States ◽  
Patient Choice ◽  
Data Set ◽  
Textual Information ◽  
Time Service

Social media platforms for healthcare services are changing how patients choose physicians. The digitization of healthcare reviews has been providing additional information to patients when choosing their physicians. On the other hand, the growing online information introduces more uncertainty among providers regarding the expected future demand and how different service features can affect patient decisions. In this paper, we derive various service-quality proxies from online reviews and show that leveraging textual information can derive useful operational measures to better understand patient choices. To do so, we study a unique data set from one of the leading appointment-booking websites in the United States. We derive from the text reviews the seven most frequently mentioned topics among patients, namely, bedside manner, diagnosis accuracy, waiting time, service time, insurance process, physician knowledge, and office environment, and then incorporate these service features into a random-coefficient choice model to quantify the economic values of these service-quality proxies. By introducing quality proxies from text reviews, we find the predictive power of patient choice increases significantly, for example, a 6%–12% improvement measured by mean squared error for both in-sample and out-of-sample tests. In addition, our estimation results indicate that contextual description may better characterize users’ perceived quality than numerical ratings on the same service feature. Broadly speaking, this paper shows how to incorporate textual information into an econometric model to understand patient choice in healthcare delivery. Our interdisciplinary approach provides a framework that combines machine learning and structural modeling techniques to advance the literature in empirical operations management, information systems, and marketing. This paper was accepted by David Simchi-Levi, operations management.

Don’t Call Us, We’ll Call You: An Empirical Study of Caller Behavior Under a Callback Option

2020 ◽  
Author(s):  
Brett A. Hathaway ◽  
Seyed M. Emadi ◽  
Vinayak Deshpande
Keyword(s):  
Service Quality ◽  
Waiting Time ◽  
Operations Management ◽  
Call Center ◽  
Structural Model ◽  
Waiting Times ◽  
System Throughput ◽  
Service Channel ◽  
Data Driven Approach ◽  
Alternative Service

Although call centers have recently invested in callback technology, the effects of this innovation on call center performance are not clearly understood. In this paper, we take a data-driven approach to quantify the operational impact of offering callbacks under a variety of callback policies. To achieve this goal, we formulate a structural model of the caller decision-making process under a callback option and impute their underlying preferences from data. Our model estimates shed light on caller preferences under a callback option. We find that callers experience three to six times less discomfort per unit of time while waiting for callbacks than while waiting in queue, suggesting that offering callbacks can increase service quality by channeling callers to an alternative service channel where they experience less discomfort while waiting. However, after controlling for expected waiting times, callers generally prefer waiting in a queue over accepting a callback and waiting offline. This suggests that managers of this call center may want to spend efforts in educating their customers on the benefits of the callback option. Using the callers’ imputed preferences, we are able to conduct counterfactual analyses of how various callback policies affect the performance of this call center. We find that in this call center, offering to hold the callers’ spot in line or to call back within a window (guaranteed timeframe) reduces average online waiting time (the average time callers wait on the phone) by up to 71% and improves service quality by decreasing callers’ average incurred waiting cost by up to 46%. Moreover, we find that offering callbacks as a demand postponement strategy during periods of temporary congestion reduces average online waiting time by up to 86%, increases service quality by up to 54%, and increases system throughput by up to 2.1%. This paper was accepted by Vishal Gaur, operations management.

scholarly journals Consumer satisfaction–based social commerce service quality management

2020 ◽  
pp. 234094442091609
Author(s):  
Nina Shin ◽  
Sangwook Park ◽  
Hyunjung Kim
Keyword(s):  
Service Quality ◽  
Operations Management ◽  
Consumer Satisfaction ◽  
Jel Classification ◽  
Online Marketing ◽  
Service Firms ◽  
Social Commerce ◽  
Quality Factors ◽  
Service Operations Management ◽  
Functional Aspects

Social commerce (s-commerce) is a social media service enabling consumers’ participation in the online marketing and sale of products and services. This study aims to (a) identify key functional and hedonic quality factors that affect consumer satisfaction based on consumers’ perspective and (b) analyze the degree of efficiency of the quality–satisfaction relationship to propose distinct and actionable improvement strategies from the firms’ perspective. The results identified the following key quality determinants: functional aspects of durability and safety, and hedonic aspects of enjoyment, awareness, novelty, and image. The result implies that most s-commerce service firms fail to efficiently convert the enhancement of safety, awareness, and novelty into consumer satisfaction. This study contributes to the stream of literature on both s-commerce and service operations management by determining key service quality elements based on consumers’ perceptions and providing a decision-making aid to firms for quality-satisfaction efficiency improvement. JEL CLASSIFICATION: M10; L20; L81

Consumer Learning from Own Experience and Social Information: An Experimental Study

2020 ◽  
Author(s):  
Andrew M. Davis ◽  
Vishal Gaur ◽  
Dayoung Kim
Keyword(s):  
Service Quality ◽  
Rate Of Convergence ◽  
Market Share ◽  
Operations Management ◽  
Demand Uncertainty ◽  
Social Information ◽  
Demand Characteristics ◽  
Repeated Interaction ◽  
Different Types ◽  
Demand Variability

We investigate how different types of social information affect the demand characteristics of firms competing through service quality. We first generate behavioral hypotheses around both consumers’ learning behavior and firms’ corresponding demand characteristics: market share, demand uncertainty, and rate of convergence. We then conduct a controlled human-subject experiment in which a consumer chooses to visit one of two firms, each with unknown service quality, in a repeated interaction and is exposed to different information treatments from a social network: (1) no social information; (2) share-based social information, which details the percentage of people who visited each firm; (3) quality-based social information, which illustrates the percentage of people who received a satisfactory experience from each firm; or (4) full social information, which contains both share- and quality-based social information. A key insight from our study is that different types of social information have different effects on firms’ demand. First, promoting quality-based social information leads to a significantly higher market share, lower demand variability, and faster rate of convergence for a firm with significantly better service quality. Second, when the higher quality firm has only a marginal advantage over the other firm, promoting only share-based information leads to significantly higher market share and lower demand variability. A third important result is that providing only one type of social information can actually be more helpful to the higher quality firm than providing full social information. This paper was accepted by David Simchi-Levi, operations management.

TQM: Evaluating service quality.

1993 ◽  
Vol 45 (3) ◽  
pp. 31-33 ◽  
Author(s):  
Gregory D. Chowanec
Keyword(s):  
Service Quality
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