IRANIAN JOURNAL OF MANAGEMENT SCIENCES
Year:2008 | Volume:3 | Issue:11|Papers Count:7

In this research the importance of capital productivity in investment process, especially in value and growth styles is examined. Capital productivity measures the management achievement in employing capital as an important and limited resource of firms, and the extent to which they apply invested capital effectively. An investment strategy is a set of rules, behaviors or procedures, designed to guide an investor's selection of an investment portfolio. We seek to analyze the relation between capital productivity and future stock returns and thereafter the effect of this relationship on return of value and growth styles in Tehran Stock Exchange (TSE). We use return on invested capital ratio as the proxy of capital productivity and capital to enterprise value ratio as the value and growth indicator. Our study contains 11 years (1997-2007) data of active corporations in TSE. It is shown that capital productivity has a significant relation with future stock returns, contains value and growth information, affects these strategies significantly, and eventually results in different returns. It is suggested that investors consider capital productivity in their portfolio selection strategy.

In recent decades the advancement of information technology and its usage in different areas has led to the creation of several models and patterns in the area of Technology Acceptance. The main purpose of this paper is the analytical analysis of three models including theory of reasoned action (TRA), theory of planned behavior (TPB) and technology acceptance model (TAM) with emphasis on internet banking adoption. The mentioned models have been compared based on three criteria: the prediction ability of intention to use, degree of explained variance on intention to use and overall fit of models.Applying structural equation modeling (SEM) and regression analysis, it is shown that the theory of planned behavior (TPB) has better performance compared to the other two models.

Foresight refers to the human ability in visualizing future probable issues and causing improvement. It is a systematic process to identify the future opportunities and requirements and helps organizations make long term decisions. This paper aims to propose an appropriate process framework for foresight studies based on meta-synthesis approach. Therefore, seven foresight frameworks presented by researchers in related articles have been investigated and a new framework is proposed. Comprehensive stages and importance of Information value chain procedure is the main advantage of this framework and consideration of external and internal context effects on foresight studies is important as well. Finally, the proposed framework is evaluated applying expert questionnaire analysis.

In this research information-seeking behavior in using internet and electronic resources has been studied. Research population has been faculty members and post-graduate students of Management and Accounting Faculty of Allameh Tabatabaee University. Using a questionnaire variable including types of information resources, manners, and tools of information retrieval, types of access to resources, and the range of users knowledge have been measured. Findings show that basic knowledge of internet is above average, and the use of internet is more dominant at home than the faculty. Besides, the main use of internet and electronic resources is shown to be for research activities; therefore full text databases have the most use. A significant difference in using Bolean logic and satisfaction rate among different fields has been observed as well.

Due to the high risk and uncertainty of CRM projects, it is necessary to do planning before implementation. Therefore existing and optimal positions must be determined so that the available gap between them would be reduced through suitable investment. In this paper, going over the related literature, CRM critical success factors were extracted and then analyzed using structural equation modeling (SEM). The approved factors were then assigned to different levels of maturity model according to experts' viewpoints. Finally based on RADAR Logic of EFQM, the model variables were measured in a firm and maturity level of the given firm was determined.