کشف رفتار مصرف کنندگان در انتخاب بیمارستان با استفاده از شبکه عصبی

The economic in Taiwan has been dramatically improved in the last two decades. During this period, the national health insurance was first conducted in 1995 and plans of health insurance payment have been modified several times. Demands of high quality and service on medical care are brought up in consumers’ mind. Nowadays, hospital operating environment is getting more and more competitive. Therefore, how to take the advantage of competitiveness is the urgent topic of gaining advantage of competitiveness. The research applied neural network to classify consumers’ behavior in choosing hospitals. A quantitative research of questionnaire was first conducted to explore consumers’ behavior in choosing hospitals in southern Taiwan. Factors of consumers’ behavior were categorized into four types. Then, a back propagation neural network classification model was developed. The model demonstrates the usefulness of 85.1% classification rate in classifying consumers’ styles. Finally, their marketing implications were discussed. Based on the results of the research, the evidence is enough to suggest that the neural network model is useful in identifying existing patterns of hospitals’ consumers.

The living quality and value systems of people have been dramatically changed when the economics of Taiwan was improved in the last two decades. Demands on high quality of medical care were brought up in consumers’ mind. Nowadays, hospital operating environment is getting more and more competitive. Consequently, how to take the advantage of competitiveness is the urgent topic of gaining advantage of competitiveness. Focusing on consumers and providing what they need is one of best ways to increase satisfaction. Most consumers did hospital shopping before they choose a hospital. The behavior of how people choose is diverse and its influencing factors are very complicated. Thus, if there are any method which can be used to find out the relationship between consumers and doctors or hospitals, and serve with proper marketing strategy, it will be a good help on improving advantage of competitiveness.

A neural network classification model was successfully developed to identify factors which are concerned by different types of consumers. A questionnaire survey was conducted to collect data among consumers of hospitals in southern Taiwan. Then, a neural network classification model was used to recognize consumers’ demographic data into different types consuming orientation. The correct classification rate of the model is 84.78%. Meanwhile, the result was evaluated by the discriminant analysis. Press’s Q statistic of 114.79 is greater than the critical value of 6.63 (χ2 value with 1 df is statistically significant at an α of 0.01). That is, the classification accuracy of the test on the model is greater than that expected by chance and it has higher accuracy than the method of discriminant analysis. Based on the results of the research, the evidence is enough to suggest that the neural network model is useful in identifying existing patterns of the data. The advantages of using the model are highlighted and marketing implications are demonstrated. Authors believe that the model is useful and suitable as an analyzing tool for marketing planners on the market strategy planning. Meanwhile, the powerful classification power will be helped to understand what goes on between input and output.