درخت حوزه‌های تخصصی

Considering the organizations’ increasing use of social media, many studies are being conducted in this area. Researchers are faced with a variety of research strategies depending on the nature of the research problem and data. If the right research strategy is not employed, the researcher will lose focus, and the time and effort spent will not necessarily serve the research objectives. When choosing a research strategy, the organization’s characteristics should be taken into consideration; otherwise, it may lead to confounding interpretations of the findings. In this regard, the present study aims to introduce an appropriate research strategy for each maturity stage of the organization under study. To this end, using systematic mapping methodology, about 256 articles published within 2011- 2021 were investigated, and the relationship between the types of research strategy used and the different stages of an organization’s maturity in using social media was reported. Specifically, by synthesizing the social sciences research methodology framework and the social media stage of the growth model, a mapping was developed between the research strategies and maturity stages. Based on this mapping, it is expected that the appropriate strategy for research at the first maturity stage is exploratory, and for the second and third stages are observational and descriptive, respectively. When the organization moves to the fourth and fifth levels, archival and causal strategies are recommended for research. Using the results of this research, researchers will be able to identify the right research strategy for the maturity stage of the organization under study and develop the appropriate research design accordingly.

Now a day's software is the baseline for the success of any organization. There is a huge demand of quality software in the customer-oriented market. Regression testing makes it possible but it’s a costly affair. Regression test suite minimization is way to reduce this cost but it is NP hard problem. This paper proposes an effective approach for regression test suite minimization using Artificial Ecosystem Optimization algorithm. To improve its performance a modified Artificial Ecosystem Optimization algorithm is proposed for Test case minimization. To evaluate the performance of proposed approach experiment is conducted in controlled parameter setting on open-source subject program from SIR repository. The results are collected and analyzed in comparison to existing approaches using statistical test. The test results reflect the superiority of proposed approach.