ارزیابی عملکرد سیستم مدیریت دانش در صنعت توسعه نرم افزار با استفاده از روش فرا ترکیب (مقاله علمی وزارت علوم)
درجه علمی: نشریه علمی (وزارت علوم)
آرشیو
چکیده
هدف: صنعت نرم افزار نمودی از مهارت های نرم و تفکر انتزاعی انسانی. این پژوهش به منظور ارزیابی عملکرد سیستم مدیریت دانش به عنوان یکی از مهم ترین زیرساخت های بهبوددهنده عملکرد در شرکت های نرم افزاری، بر مبنای رویکرد فراترکیب شده انجام شده است. روش شناسی: این پژوهش کاربردی و با روش اسنادی و فراترکیب انجام شده است. برای تجزیه وتحلیل اطلاعات از روش هفت مرحله ای فراترکیب سندلوسکی و باروسو استفاده شده است. یافته ها: یافته ها نشان داد که عوامل سازمانی (فرهنگ، حمایت مدیریت ارشد، استراتژی سازمان، ساختار سازمانی)، عوامل فردی (آموزش، مشارکت کارکنان، دانش و آگاهی نسبت به سیستم های مدیریت دانش، مقاومت در برابر تغییر)؛ عوامل زیرساخت فناوری (کاربرپسند بودن، امنیت داده و اطلاعات، روش های ارتباط و همکاری، میزان یکپارچگی سیستم های سازمانی، کیفیت دانش)؛ فرایند مدیریت دانش (اکتساب دانش، انتقال دانش، خلق دانش)؛ فواید اقتصادی / هزینه (هزینه سرمایه، هزینه عملیاتی) بر روی اریابی عملکرد مدیریت دانش در صنعت توسعه نرم افزار تأثیر می گذارند.Evaluation of Knowledge Management System Performance in the Software Development Industry Using Meta Synthesis Method
IntroductionNew software development models are emerging that help in software development by default. Secure software should be defined based on the fundamental framework of the organization and the fundamental framework of the organization's software, which means that the targeted level of security of various software of an organization depends on the business context and the degree of importance of information in that context. Proper support of the software industry requires a precise and appropriate understanding of the state of this industry as an ecosystem and knowledge of the software product. In addition to having technical complexities, the software industry follows certain economic structures and principles, which are very important in the analysis of the existing support regimes. Without having a secure software production line, the possibility of releasing secure software from this production cycle is impossible. Also, the competitive business environment of organizations depends on the software they have in this field; therefore, considering the level of vulnerabilities, it is reported that in the field of software, the existence of a secure software life cycle, which results in the production and development of secure software, is very necessary (Palumbo et al., 2020). Software companies need to develop knowledge in diverse domains. One of the industries that are very important in the transition from the oil economy due to its great potential in the country, and on the other hand, it realizes a part of the knowledge-based economy, is the software industry, which is struggling with many changes and problems. Due to the intensity of changes in technology and its highly competitive environment, software companies are facing many challenges and uncertainties in providing their products or services in the form of value for customers and also in making money from it. Therefore, it is necessary to provide a suitable solution for software companies to reach their position and the future that can be waiting for them. The present research tries to consider.What are the factors and performance indicators of the knowledge management system in the software development industry?Literature ReviewIn the research, Wang, Ding, and Ming Li (2017) presented a hybrid method for evaluating knowledge management performance based on triangular fuzzy numbers and group support systems. The results showed that the evaluation method has a strong practical and operational capability, and in addition, the evaluation is activated using a group support system. The systematic KMPE method based on an index system can improve the efficiency of organizations in the performance evaluation process. The review goes under these subheadings.Pojadi and Sardjono (2018) investigated "Evaluation of Knowledge Management System for Disaster Management Using Factor Analysis". The results showed that evaluation models can be built through the performance of agents, organizational culture, and information through the knowledge management system, management support and participation, access and updating, and information monitoring. Fu, Jiang, and Chen (2020) modeled an organizational knowledge management system based on artificial intelligence in a research. The key technologies that need to be solved to achieve knowledge integration were pointed out, including the integration of heterogeneous knowledge distributed between companies, the integration of correlation and the integration of knowledge and production processes. Fuzzy theory was used to create a knowledge extraction mechanism and reference model library from the project model to the dedicated reference model. Finally, a layered diffusion model was developed that matches the characteristics of online knowledge transfer. Greco et al. (2021) in their research examined "a method for evaluating knowledge management systems". The results show that WikiIEN is the solution most indicated for the larger public due to its more user-friendly interface and workflow, and sufficient feature set that does not depend on external software.MethodologyThis research is applied in terms of purpose, which was done with a documentary method, meta composite. The meta-composite approach is a type of qualitative study that examines the information and findings extracted from other qualitative studies with a similar and related topic. As a result, the desired sample for the meta-combination of selected qualitative studies is based on the relationship made with research questions (Lindgreen, Palmer, and Vanhamme, 2004). In this research, the combination method has been used in order to compare, interpret, transform, and combine different frameworks and models presented in the field of knowledge management system performance evaluation in the software development industry.ResultsThe purpose of this research is to provide a suitable conceptual framework for identifying the performance evaluation components of knowledge management system in the software development industry with a meta-composite approach. Due to the lack of comprehensive research in the field of identifying factors affecting the performance of the knowledge management system, the performance evaluation indicators of the knowledge management system were first extracted by extensive literature study and based on the frequency of evaluation indicators. The goal is to cover various dimensions of knowledge management system evaluation with a comprehensive study. Due to budget constraints and the economic era with uncertainty, knowledge management implementers need to be able to demonstrate the commercial value of knowledge distribution and reuse in the organization. There are two basic points that all organizations should consider when designing success measures. Therefore, based on the presented conceptual model, managers can evaluate the performance of knowledge management in the software development industry by using organizational factors, individual factors, technology infrastructure factors, knowledge management processes, and economic benefits/costs. DiscussionBased on the presented conceptual model, managers can evaluate the performance of knowledge management in the software development industry by using organizational factors, individual factors, technology infrastructure factors, knowledge management processes, and economic benefits/costs. ConclusionExamining the results showed that components such as organizational factors (culture, senior management support, organization strategy, organizational structure), individual factors (training, employee participation, knowledge and awareness of knowledge management systems, resistance to change); technology infrastructure factors (user-friendliness, data and information security, communication and cooperation methods, degree of integration of organizational systems, knowledge quality); knowledge management process (knowledge acquisition, knowledge transfer, knowledge creation); economic benefits/costs (capital cost, operating cost) affect the evaluation of knowledge management performance in the software development industry.
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