Key Words: consumer responsiveness, mobile marketing/advertising, purchase decision, customization, Customerization Innovation creates marketing opportunities and challenges. Mobile advertising, an area of mobile commerce, is a form of advertising that targets users of handheld wireless devices such as mobile phones and PDAs. It can reach the target customers anywhere anytime. In order to promo...

Day after day, the Competition in banking sector increases; customer perspective became significant element sector. This shows how important it is to determine point of view and perceptions beneficiaries Islamic banks. The study aims examine Turks Syrian customers' preference behaviors find out reasons affect their choosing between conventional banks Turkey. According findings; age, occupation,...

In the originally published version of chapter 48, Table 1 and equation on page 696 contained errors. This has been corrected.

Today the use of modern technologies in the daily life for satisfying the needs is unavoidable. Follow the news and searching through the internet has affected organizations to provide platform on the Internet for availability of information for the customers. With the development of e-commerce, online shopping plays an increasingly important role in people’s life. With the use of data mining t...

Eliciting non-functional security requirements within a company was one of the major aspects of the SIKOSA project. Scenarios, such as that of METRO presented in this paper, show how besides a company’s internal requirements, customers’ preferences also play an important role. However, conflicts between specific customers’ privacy policies and those of a company need to be detected and dealt wi...

Learning customer preferences from an observed behaviour is an important topic in the marketing literature. Structural models typically model forward-looking customers or firms as utility-maximizing agents whose utility is estimated using methods of Stochastic Optimal Control. We suggest an alternative approach to study dynamic consumer demand, based on Inverse Reinforcement Learning (IRL). We ...