This study focuses on testing the validity of dimensions of restaurants’ menu prices. In addition, the effect of demographic variables on the perception of each price dimension was investigated. The subjects were people living in the capital region who have, at least on occasion, gone to family restaurants. The data were collected by self-administered questionnaires and analyzed by factor analysis, reliability analysis, confirmatory factor analysis, and the ANOVA t-test. The results were that consumers’ perception of restaurant menu prices is not uni-dimensional, but has six dimensions: price-price schema, pricequality schema, value consciousness, low price proneness, price mavenism, sales proneness. Demographic variables partially affect the consumers’ perception of each menu price dimension. The result of the t-test examining dimensions of price according to the demographic characteristic was that females have a higher sales proneness than males. The t-test result according to marriage indicated that married people were higher in price-price schema and quality proneness than unmarrieds. ANOVA according to age indicated that people between ages of 20 to 29 have a higher quality proneness than those of other ages.

Stock price multiple is one of the most well-known equity valuation technique used to forecast equity price. It measures by multiplying “the ratio of stock price to a value driver” by a value driver. The value driver can be earning per share (EPS), sales or other financial measurements. The objective of price multiple technique is to evaluate the value of assets and compare how similar assets are priced in the market. Although stock price multiple technique is common in financial filed, studies on the application of the technique in Thailand is still limited. The present study is conducted to serve three major objectives. The first objective is to apply the technique to measure value of firms in banking sector in the Stock Exchange of Thailand. The second objective is to develop composite price multiple index to forecast equity prices. The third objective is to compare valuation accuracy of different value drivers of price multiple (i.e. EPS, Earnings Growth, Earnings Before Interest Taxes Depreciation and Amortization, Sales, Book Value and Composite Index) in forecasting equity prices. Results indicated that EPS is the most accurate value drivers of price multiple used to forecast equity price of firms in baking sector.