طراحی الگوی پاردایم ارزش افزوده اطلاعات در نظام های اطلاعاتی مبتنی بر پایگاه داده

Purpose: The purpose of the current research is to design the paradigm model of added value of information in information systems and services using structural equation modeling.

Method: This research was conducted with a quantitative-qualitative combined method with an exploratory nature and the aim of expanding existing knowledge and understanding regarding the added value of information in information systems and services.The method of conducting this research is descriptive-modeling. Description and analysis of information in this research has been done using qualitative mixed methodology (content analysis with three coding approaches) in MAXQDA software and quantitative method (partial least squares) in PLS Smart software.The partial least squares model can be divided into two external models and internal models. The external model shows the relationships between items (interview questions) and factors (hidden variables) and is equivalent to confirmatory factor analysis or measurement model in Lisrel software. The internal model is similar to path analysis and the structural part of a structural equation model.After testing the external model, it is necessary to present the internal model that shows the relationship between the hidden variables.The studied population of this research can be classified into three general groups including: the first group of expert professors, the second group of specialists and experts in information science, and the third group of researchers. The sampling method in this research is a combination of non-probability targeted sampling (judgmental) and snowball sampling. Finally, the opinions of 37 librarians and university experts in the fields of information science and knowledge, information technology and communication, economics and some researchers who are experts in the subject area of the current research were collected in the form of in-depth interviews.

Findings : In the first stage, i.e. drawing the network of concepts, it was found that some proposed concepts overlap with each other and it may be necessary to separate other concepts into separate concepts. At this stage, to select words for research concepts, integration and improvement of concepts in MAXQDA software has been done. After, by drawing the network of concepts and coding them, the most important variables of the research model were obtained which are respectively: advanced search and retrieval with an average of 4.93, information management with an average of 4.84, storage and processing with an average of 4.78, dissemination of information with an average of 4.77, integration with an average of 4.69, description and Organization with an average of 4.66, selection and provision with an average of 4.32, type of information display with an average of 4.25 and self-creation with an average of 4.13. Next, in order to find out the underlying variables of a phenomenon or summarizing a set of data, the factor analysis method was used.The primary data for factor analysis is the correlation matrix based on path analysis between latent and observed variables. In this step, with the confirmatory factor analysis of the research variables and based on the factor loadings of the fitted model, the correlation based on the path analysis between the research variables showed a favorable situation. In the final stage, interpretive structural path analysis in PLS between hidden variables for the value-added paradigm of information in information systems and services is presented that of the analysis of the coefficients of the path between the variables of the research, it was obtained that due to the very strong relationship between the coefficients and the concepts of the research model, it is necessary for experts and practitioners to pay attention to the functional and practical status of the concepts of the research model.

Conclusion:The research results showed that there is a positive and significant relationship between the research variables.In fact, the regression statistic of structural equation modeling based on R2, for the variable criteria of added value of information in information systems and services is equal to 89/. ; It has been calculated that it shows the predictive power of structural equation modeling.According to the results of the research and the increasing production process of electronic publications, if no added value is obtained in the process of converting printed resources to electronic ones, the production of such resources is not worth spending time and human resources. Information services should be able to display the power, expertise and ability of information systems; So that users can recognize the value of the information produced and the expertise of the producers when receiving services. Finally, the theoretical model of the paradigmatic dimensions of added value for information systems and services was presented.