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Narrative comments about dentists on physician review sites have been documented to increasingly influence people's selection of their dentists. From a communication standpoint, these comments are a type of narrative communication that people share their experiences with dentists by telling stories. Based on the frameworks of rhetoric structure theory and extended elaborated likelihood model, this study aimed to examine the effects of such storytelling from two perspectives including narrative structure and narrative focus.

A 4 (narrative structure) × 2 (narrative focus) between-subjects experiment was conducted to examine the proposed hypotheses and research questions

The results showed that a one-sided comprehensive comment focusing on technical competence generated the strongest persuasion effects measured by attitude and behavioral intention. These effects were mediated by perceived narrative credibility and enjoyment.

This study contributes to the extant literature in two ways. First, it extends previous studies of online narrative comments by showing which narrative structure and focus are deemed to be more persuasive when selecting a dentist. Second, it offers a test of two routes of information processing (i.e. cognitive and experiential) to understand the mechanism underlying the effects of narrative comments.

The peer-review history for this article is available at: https://publons.com/publon/10.1108/OIR-08-2020-0359

The purpose of this paper is to examine how limited care patients and comprehensive care patients differ in terms of consumers' behavior in the dentist selection process, in order to help healthcare providers and marketers better promote their practice depending on their patient type.

A survey of 1,150 dental school faculty private practice patients who recently chose their dentist was conducted and 221 responded. The respondents were divided to comprehensive care patients (n=120) and limited care patients (n=90) by self‐perceived need.

The comprehensive care patients were younger and more likely to be highly educated, have a healthcare related profession, and have private dental insurance (p<0.001). The comprehensive care patients were more likely to use information sources such as clinic website, the internet, and the insurance directory (p<0.05), while the limited care patients were more likely to use other dentists. Comprehensive care patients put more value on attributes such as, the dentist is in my insurance network and convenient physical location (p<0.05). In conclusion, comprehensive care patients and limited care patients differed significantly in characteristics and how and why they chose their dentist.

Healthcare marketers can use this study's findings to better promote their practice by selecting appropriate communication channels and focus on attributes that consumers value the most. It is important to apply different strategies to different consumer groups.

Attempts to highlight differences among market segments of dental care customers in terms of the various attributes that determine which dental practitioner they patronize. The market segments are defined based on usage rate. Data were collected from a nationwide sample of 460 consumers in the USA. Using a determinant attribute approach, eight attributes were first isolated from the total set of 18 dental service attributes considered. Finds these eight attributes to be determinant factors in consumer choice of a general dental practitioner. They included quality of service, professional competence, reputation, personality and attitude of dentist, attitude of support personnel, waiting time before treatment, availability of emergency services, and fee charged for services. Multiple discriminant analysis was then performed to find out which determinant attributes are relevant for each of the three usage segments. Indicates that the three market segments differ in terms of the determinant attributes considered while patronizing a general dental practitioner. These findings have significant managerial implications for dental practitioners.

Many booking services in traditional people-processing service areas such as gastronomy were recently transformed into online reservation services. While advantages for platform providers (i.e. a share of the respective business) and merchants (i.e. increased operational efficiency) seem obvious, it is less known about how customers respond to these new forms of online services. This paper aims to illustrate how booking traditional people-processing services online is different from booking it via phone.

This study conceptualized a 2 × 2 experimental survey design by manipulating users’ booking channel (online vs low) and the service complexity of different, less digitized people-processing services (high: dentist vs low: restaurant). After conducting several pretests, the authors surveyed 282 respondents familiar with online booking and reservation.

The results show that the booking channel (online reservation vs phone reservation) affects associated perceived booking risk and negatively affects users’ intention to use the reservation service. Additionally, users’ attitudes toward online reservation moderate the influence of booking channel on perceived booking risk.

To the best of the authors’ knowledge, this is the first research that investigates adoption of online reservation in people-processing services.

Close inspection of many services reveals them to be multiple services (multi‐services). Many others, such as ski resorts, entertainment centres, motorway service complexes and restaurant/hotel developments, are more obviously of a multi‐service type. The inter‐relationship of the component services of a multi‐service is often closely held by the entrepreneur during the early stages of the venture, and may still be the subject of experimentation. Moving from entrepreneurial to professional management requires definition of these service inter‐relationships. Division of the concept into its components to simplify control, and the use of separate performance maximising incentives are hazardous approaches. The first objective of new control systems should be to replicate the entrepreneurial multi‐concept service. Experimentation should be left until later.

Documents how the Dental Service of the Israel Defence Forces (IDF) successfully implemented private sector approaches to reimbursement and staffing in a special project designed to improve prosthodontic care for career military personnel. The innovative public‐private synthesis enabled the IDF to relieve bottlenecks and increase productivity while securing high levels of employee and patient satisfaction. The success of the innovation can be attributed, in part, to specific measures taken to adapt private sector practices to the culture and norms of the public sector and to integrate the new program into the broader organizational framework of the IDF Medical Corps. The recruitment of managers appropriate to the various stages of the organizational change cycle also played an important role in the project′s success. The study is based on in‐depth interviews of senior managers within the IDF medical corps, interviews of the managers directly involved in implementing the change, IDF budget reports and productivity analyses, and a survey of front‐line dentists. The analysis will be of interest to managers of public health care systems from around the world, who are looking to the private sector for innovative ideas on how to improve the efficiency of public programmes.

In recent years, professional service organizations have begun to successfully implement various sales promotion techniques, and potential customers are responding favorably to such promotions. This exploratory research examined the impact of sales promotions on consumer attitudes and intentions. More specifically, the influence of coupon face value on service quality expectations, perceived purchase risks, and purchase intentions was examined. The results indicate that while coupons positively impact the purchase intentions of dental services, the positive impact was negated by negative impacts on service quality expectations and perceived purchase risk. Further results and implications of the study for professional services are addressed.

This paper analyzes the effect of dental insurance on utilization of general dentist services by adult US population aged from 25 to 64 years using the ordered probit model with endogenous selection. Our econometric framework accommodates endogeneity of insurance and the ordered nature of the measure of dental utilization. The study finds strong evidence of endogeneity of dental insurance to utilization and identifies interesting patterns of nonlinear dependencies between the dental insurance status and individual's age and income. The calculated average treatment effect supports the claim of adverse selection into the treated (insured) state and indicates a strong positive incentives effect of dental insurance.

The purpose of the study is to classify the radiographic images into three categories such as fillings, cavity and implant to identify dental diseases because dental disease is a very common dental health problem for all people. The detection of dental issues and the selection of the most suitable method of treatment are both determined by the results of a radiological examination. Dental x-rays provide important information about the insides of teeth and their surrounding cells, which helps dentists detect dental issues that are not immediately visible. The analysis of dental x-rays, which is typically done by dentists, is a time-consuming process that can become an error-prone technique due to the wide variations in the structure of teeth and the dentist's lack of expertise. The workload of a dental professional and the chance of misinterpretation can be decreased by the availability of such a system, which can interpret the result of an x-ray automatically.

This study uses deep learning (DL) models to identify dental diseases in order to tackle this issue. Four different DL models, such as ResNet-101, Xception, DenseNet-201 and EfficientNet-B0, were evaluated in order to determine which one would be the most useful for the detection of dental diseases (such as fillings, cavity and implant).

Loss and accuracy curves have been used to analyze the model. However, the EfficientNet-B0 model performed better compared to Xception, DenseNet-201 and ResNet-101. The accuracy, recall, F1-score and AUC values for this model were 98.91, 98.91, 98.74 and 99.98%, respectively. The accuracy rates for the Xception, ResNet-101 and DenseNet-201 are 96.74, 93.48 and 95.65%, respectively.

The present study can benefit dentists from using the DL model to more accurately diagnose dental problems.

This study is conducted to evaluate dental diseases using Convolutional neural network (CNN) techniques to assist dentists in selecting the most effective technique for a particular clinical condition.