Marketing dental services using the neural network of Qazvin city 89-90

Number of pages: 115 File Format: word File Code: 31944
Year: 2011 University Degree: Master's degree Category: Medical Sciences
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  • Summary of Marketing dental services using the neural network of Qazvin city 89-90

    Abstract:

    Today, dental clinics are adapting to the changes in the environment. Although marketing may have been considered frowned upon in the past, these days dental clinics are beginning to embrace the benefits of marketing. Customer involvement in choosing healthcare services has grown exponentially. Therefore, clinics must learn to respect the client, discover their needs and improve their satisfaction. In the marketing of dental services, understanding how the customer chooses the clinic is an important issue. Because patients can shop around and compare clinics. Today, how to benefit from competitive advantages through operational strategy is an important issue for business success. Dentists must face these challenges and prepare themselves for the future. There are many features that influence the choice of clinic. In the dentist's marketing strategy, he should know that different groups emphasize different features in choosing a dentist. In this research, customer behavior in choosing a dentist has been searched and analyzed. The data has been collected through a questionnaire from the dental clinics of Qazvin University of Medical Sciences and 14 factors have been taken into consideration in choosing a dentist, and then the factors affecting customer behavior have been divided into four categories, and based on that, people have been placed in different clusters, and finally, a neural network model has been created to predict different clusters of people. Based on the findings of the research, the usefulness of the model has been proven and there are enough reasons to propose a neural network to identify patterns among dental clinic patients. style="direction: rtl;">Chapter One

    1

    Research Introduction

    Introduction

    In today's world, the quality of life and value systems of people have changed dramatically. In the minds of customers, the demand for high quality dental care has grown and the dental operating environment has become more and more competitive. As a result, how to gain competitive advantage is an important issue. Focusing on the customer and providing what they need is one of the best ways to increase their satisfaction. Most of the customers do a clinic tour before choosing a dental clinic. How to choose a dentist is different and the influencing factors are very complex (Wan-I, et al, 2008). Therefore, if there is a method that can be used to find out the relationship between the customer and the dentist or the dental clinic, and with that appropriate marketing strategy, it will be a useful help to improve the competitive advantage.

    Dental clinics are adapting to environmental changes. Although marketing may have been frowned upon in the past, these days clinic managers are beginning to embrace the benefits of marketing (Gronroos, 1990). Marketing is moving from advertising to a holistic view aimed at customer satisfaction. How to gain a competitive advantage by strengthening the operational strategy is an important issue for the success of the dental clinic. Therefore, dentists must learn to respect the customer, develop specific features of dental services, and discover customer needs and improve their satisfaction.

    Customer behavior in choosing a dentist has changed from passive to active. In the relationship between patients and dentistry, the patient can be considered as a customer of dental services in the market of dental services, where the dentist is the main provider (Engie, et al, 1968).In the marketing strategy, it is important for the dentist to know that different groups of clients emphasize different defining characteristics. Based on the surveys, the factors on which the consumer chooses the clinic are listed below:

    Cost of dental services, kindness and courtesy in care, modern equipment and technology, proximity to home, expert dentists, quality of dental care, recommendation of family and friends, full range of services, good environment, reputation, having previous experience with the dentist, quality of work of the staff (Boscarino, et al, 1982)

    Artificial Neural Network)):

    Artificial neural network is an idea for information processing that is inspired by the biological nervous system and processes information like the brain. This system consists of a large number of processing elements called neurons that work together to solve a problem. ANNs, like humans, learn by example and, by processing experimental data, transfer the knowledge or law hidden behind the data to the network structure (Sangler, et al, 1999)).

    Neural network perspective has recently been used more to analyze customer satisfaction and loyalty. Much research has been devoted to the use of neural networks in marketing. Zahavi and Levin have used different types of neural network structures to create prediction models in marketing. (Zahavi, et al, 1997) Crooks used neural network to train customer behavior data to predict potential customers in order to avoid untargeted advertising (Crooks, 1995). Advertising (Curry, 1993). The purpose of this study is to use the neural network to classify the customer's behavior in choosing a dentist.

    3

    For this work, the input data of the network is needed at first. Therefore, a quantitative research using a questionnaire is the first step to search for customer behavior in choosing a dentist in Qazvin city. The collected data, which includes information related to customers' preferences in choosing a dental clinic, is given to the network in the first layer of the network, which includes input neurons. 

    Abstract

    Nowadays, dental clinics are accommodating themselves to the changing environments. Although, marketing may be unpopular in the past, dental clinics start to choose the benefits of marketing these days. The consumer's involvement in healthcare choices has grown exponentially; hence, hospitals must value consumers, survey their requirements and advance satisfaction. It is a significant issue in dental services marketing to understand how consumers will choose a clinic, because patients could shop among clinics and make comparisons. These days, how to get competitive benefit by enhanced operating strategy is an important issue to business success. Dental professionals have to face these challenges and prepare themselves for the upcoming future. There are many features which influence choosing the clinic. In marketing strategy, dentist must know that various groups emphasize different crucial features in choosing clinics.

    In this study, we have analyzed and explored the consumers' behaviors in choosing dental clinics. A data set was collected with survey questionnaire from medical university dental clinics in Qazvin, Iran. Many important factors in choosing clinics were considered. Different consumers' choices were categorized in four types of factors and ranked for different types of consumers. The relationships between demographic features of consumers with their orientations in choosing the dental clinics were also explained. Then, a neural network classification model was developed. The model demonstrates the usefulness of 51.25% classification rate in classifying consumers' styles.

  • Contents & References of Marketing dental services using the neural network of Qazvin city 89-90

    List:

    List

    .

    Chapter One: Introduction of Research

    1- Introduction..

    2

    1-1- The main objectives of the project..

    4

    Chapter Two: Theoretical foundations of research and review of previous studies

    2- Introduction..

    7

    2-1-1 definition of new marketing.

    7

    2-1-2 different dimensions of marketing.

    10

    2-1-3 other definitions of marketing.

    12

    2-1-4 consumer purchase decision process.

    14

    2-1-5 types of purchase problem solving.

    16

    2-1-6 effective factors in the purchase decision process.

    17

    2-1-7 psychological and individual factors. .

    20

    2-1-8 situational factors..

    26

    2-1-9 marketing mix factors.

    26

    2-1-10 creating a comprehensive model to study buyer behavior.

    29

    2-1-11 main components of marketing.

    31

    2-1-12 product quality and providing services to customers.

    38

    2-1-13 the newest realm in marketing.

    38

    2-1-14 the new concept of quality.

    39

    2-1-15 inclusive or comprehensive quality management.

    40

    2-1-16 the new concept of serving Customers.

    40

    2-1-17 The role of the marketing department in product quality.

    41

    2-1-18 Participation in quality improvement.

    2-1-19 A plan to provide services to customers.

    42

    43

    2-2- Models used.

    44

    2-2-1- Linear audit analysis (LDA).

    2-2-2- Artificial neural networks.

    2-2-3- Comparison of classical modeling with neural network modeling.

     

    2-2-4- How the neural cell model works.

    2-2-5- How a neural network works.

    2-2-6- Learning rate ..

    2-2-7- Momentum ..

     

    2-2-8- Training, testing and evaluation of models.

    2-2-9- Review of studies Previous.

     

    Chapter three: Introduction of the research

     

    3- Introduction..

     

    3-1- Type of research..

     

    3-2- Research community..

     

    3-3- Sampling method and sample size.

     

    3-4- Data collection method (work method).

    3-5- Data analysis method.

    3-6- Possibilities and limitations of research.

    3-7- Ethical considerations..

    3-8- Definition of words..

    Chapter Four: Findings

     

     

    4-1- Factor analysis..

     

    4-2- Cluster analysis..

     

    4-3- Demographic statistics of each of the clusters.

     

    4-4- Cluster grouping.

    4-5- Interpreting clusters..

    4-6- Audit analysis or diagnosis analysis.

    4-7- Non-linear modeling and classification by neural network (ANN).

     

    Chapter five: Discussion and suggestions

    5-1- Discussion..

     

    5-2- Suggestions..

     

    Resources 

    Appendix

     

    Source:

     

     

    Wan-I Lee, Bih-Yaw Shih. (2008). The exploration of consumers' behavior in choosing hospital by application of neural network. Expert systems with applications 36, 2008: 806-816.

    Gronroos, C. .Service marketing and management. Lexington Books, 1990:222.

    Engie, J. F., Kollat, D. T., & Blackwei, R. D. . Consumer behavior. NEW York: Holt, Rinehart and Rinehart and Winston, 1968.

    Boscarino, J., & Stelber, S. R. . Hospital shopping and consumer choice. Journal of Health Care Marketing, 2(2), 1982: 15-23.

    Sangler, W. E., May, J. H. & Vargas, L. G. . Choosing data mining methods for multiple classification: Representational and performance measurement implications for decision support.

    Journal of Management Information Systems Management. 45 (9), 1999: 16-21.

    Zahavi, J., & Levin, N. . Applying neural computing to target marketing. Journal of Direct Marketing, 11(1), 1997: 5-24.

    Crooks, T. . Marketing with neural. Marketing with neural networks. Or, you gotta know the territory. Credit World, 84(2), 1995: 18-20.

    Curry, B., & Mouutinho, L. .Neural networks in marketing modeling consumer responses to advertising stimuli. European Journal of Marketing, 27(7), 1993: 5-20.

    Rusta Ahmad, Davar Venus, Ebrahimi Abdulhamid, 2015. Marketing Management. Tehran. Organization of study and editing of humanities books of universities (Department). Humanities research and development center. 125-145.

    Rangebrian Bahram, 1378. Marketing and market management. Tehran. Commercial publishing company. 100-120.

    Fattahzadeh Amir Abbas et al., 2014. Health system reforms: a guide to justice and efficiency. Tehran. Ibn Sina Cultural Institute. 496-488.

     

    Cutler Flip. Cutler in market management. Rezainejad Abdul Reza. Tehran. Fara, 1379: 160-121.

    Richard K. Thomas. Health Services Marketing: A Practitioner's Guide. 1 edition. Springer. 2007:300-250.

     

    J. J. Sutherland, L. A. O´Brien, D. F. Weaver, A Comparison of Methods for Modeling Quantitative Structure-Activity Relationships, J. Med. Chem. 47, (2004)5541-5554.

    Alexander Golbraikh, Min Sehn, Zhiyan Xiao, Yun-De Xiao, Kuo-Hsiung Lee & Alexander Tropsha, Rotational selection of training and test sets for the development of validated QSAR models, Journals of Computer-Aided Molecular Design 17: 241-253, 2003.

    Melody Y. Kiang, A comparative Assessment of classification methods, Decision Support Systems. 2003:441-454.

    Douali L., Villemin D., Cherqaoui D., “Neural Networks: Accurate Nonlinear QSAR Model for HEPT Derivative”, J. Chem. Inf. Comput. Sci. 2003, 43, 1200-1207.

    Helge Malmgren. Artificial Neural Network in Medicine and biology: A philosophical introduction. Opening lecture at the ANNIMAB-1, Gothenburg, May 13-16, 2000.

    P. R. H. Newsome, & G. H. Wright. A review of patient satisfaction: 2. Dental patient satisfaction: an appraisal of recent literature. British Journal, Volume 186, NO.4, February 27, 1999.

    Wan-I Lee, Bih-Yaw Shih, Yi-Shun Chung. The exploration of consumers' behavior in choosing hospital by the application of neural network. Expert System with Application 34, 2008: 806-816.

    Wan-I Lee, Bih-Yaw Shih. Application of neural networks to recognize profitable consumers for dental services marketing- a case of dental clinics in Taiwan. Expert Systems with Applications 36, 2009: 199-208.

    Berkowitz, E. N., & Flexner, W. A. ??. The market for health care services. Journal of Health Care Marketing, 1(1), 1981: 25-54.

    Wolinsky, F. D., & Kurz, R. S. . How the public chooses and views hospitals. Hospital and Health Service Administration, 29 (November/December), 1984: 58-67. Yavas, U., & Shemwell, D. Modified importance-performance analysis an application to hospitals. Hospital and Health Service Administration, 29(November/December), 2001: 58-67.

    Javalgi, R. G., Rao, S.R., & Thomas, E. G. .Choosing a hospital: analysis of consumer tradeoff. Journal of Health Care Marketing, 11(1), 1991:12-22.

     

    Ravi S. Behara, Warren W. Fisher. Modeling and evaluating service quality measurement using neural networks. International Journal of Operations & Production Management, Vol. 22, No.10, 2002: 1185-1162.

    Al Johara A. al-Hussyeen. Factor affecting utilization of dental health services and satisfaction among adolescent females in Riyadh City. The Saudi Dental Journal, 22, 2010: 19-25.

    Hans O Birk, Rikke Gut and Lars O Henriksen. Patients' experience of choosing an outpatient clinic in one county in Denmark: results of a patient survey. BMC Health Services Research, 11, 2011:262.

    Christopher L Corbin, Scott W Kelley, Richard W Schwartz. Concepts in service marketing for health care professionals, The American Journal of Surgery, 181(1), 2001: 1-7.

    Iversen T, Lur?¥s H. Waiting time as a competitive device: an example from general medical practice.

Marketing dental services using the neural network of Qazvin city 89-90