It is becoming increasingly di cult for enterprises to survive under competitive conditions. Enterprises with high levels of institutionalization are able to survive and reap more advantages than their competitors. Excellence models are widespread tools for measuring the degree of institutionalization of enterprises. In this study, European Foundation for Quality Management (EFQM) criteria are evaluated with fuzzy multicriteria decision-making techniques. The fuzzy DEMATEL method is used to determine the interactions amongst the main EFQM criteria. According to the relationship diagram obtained from the Fuzzy DEMATEL method, the weights of the subcriteria are calculated according to the expert evaluations using fuzzy analytic network process method. The criterion \Business Results" has been determined to be the most important criterion. The weights of the criteria are taken as input for the VIKOR method. Then, the institutionalization levels of six institutions, previously evaluated by EFQM, are reevaluated by the proposed approach. As a result, institutions A, B, E, and F achieve Excellence Award, while institutions C and D are assessed to deserve the 4-star competency certi cate. The institutional scores obtained by the proposed method and the scores given by the EFQM evaluators are statistically analyzed to demonstrate that the proposed method has produced meaningful results.
Proper understanding of the conceptual and practical counterparts of Industry 4.0 is of great importance as global competition has made the technology-based production a necessity. The aim of the present study was to propose a model that would predict the existing and future Industry 4.0 levels for companies. The changes of the concepts were examined and interpreted for three di erent hypothetically developed scenarios. In the rst scenario, an organization that was poorly managed in terms of the development of Industry 4.0 was considered. The Industry 4.0 tendency was calculated at 0.04, reaching a steady state after 12 time periods using the Fuzzy Cognitive Maps (FCMs) algorithm. Moderate and well managed organizations were considered in Scenarios 2 and 3, respectively. The Industry 4.0 tendency reached 0.12 after 15 time periods in Scenario 2 and 0.95 at the end of ve iterations in the third scenario with the concept values indicating well managed situation in the latter case. In addition, strategy and organization, smart operation, and smart factory concepts were found to make the most signi cant contribution to the Industry 4.0 level in the static analysis.
Technology provides important contributions to economic growth by increasing productivity in production. One of the most important indicators of technological innovation is research and development (R&D) activities. R&D studies have become necessary for companies to have a competitive advantage and to continue their operations more profitably. The decisions taken by companies and the investments they make have become more important than ever for their institutional future. In this sense, investments and projects in the R&D have become a decisive factor in the future of companies, moving companies away from traditional financial approaches that only aim at cost or profit. Decisions to be made in this issue have a more complex structure than ever, and their effectiveness has become critical for corporations. In this study, a two-stage model is proposed for the decision of an R&D project selection decision of an energy company. In the model, the weights of the criteria are determined using the Fuzzy AHP (Analytical Hierarchy Process) method and the most appropriate project is determined by the Fuzzy TOPSIS (Technique for Order Preference by Similarity to Ideal Solutions) method.
Effectiveness of strategic planning activities prevents to loss of time, money and reputation of organizations. Universities as educational institutions are continuing these studies to provide better quality and more innovative education services. The strategic plan is to ensure the continual improvement of the universities, to be a partner of other national and international universities, to give good education services to students and to be preferred by students. In this study, 2013-2017 strategic plan prepared by Hacettepe University is examined and the long-term objectives of the plan are ranked according to their importance. The aim of ranking the goals that highly contribute to the strategic plan is to use the resources and energy of the institution more accurately in the direction of achieving these goals and to reach its strategies more determinedly. Fuzzy AHP (Analytical Hierarchy Process) and Fuzzy TOPSIS (Technique for Order Preference by Similarity to Ideal Solutions) methods, which are multi-criteria decision-making methods, are used in order to the ranking of strategic goals. The criteria of the SMART (Specific-Measurable-Accessible-Realistic-Time Limited) method is also used for evaluating of the goals. The Fuzzy AHP method is used to determine the weights of these criteria and the Fuzzy TOPSIS method is used to obtain the significance of the goals. The importance degrees of long-term goals have been normalized, and then goals providing high added value to the strategic plan have been determined by using Pareto analysis with 80-20 rule. In this way, strategies that provide high added value to the strategic plan are also determined. With the developed integrated decision-making approach, it is envisaged that more effective strategic planning process will exist as a result of the determination of high value-added goals.
Today, organizations are experiencing problems due to advancements in the environment, community, economy, and technology. In the future, physical and virtual systems, including the whole chain from product design to the distribution to customers and feedback will be required to overcome problems for organizations. Thus, companies need to comprehend and apply Industry 4.0. The most frequently encountered situation in the literature is the absence of research based on the practical experience of Industry 4.0 processes. In this study, the analysis of 9 concepts (Strategy, Leadership, Customers, Products, Operations, Culture, People, Governance, and Technology) is performed by utilizing the fuzzy DEMATEL and fuzzy AHP methods. As a result of both methods, Technology, Operations and Strategy concepts are obtained as the three most important concepts in the same rank in both methods. There is no significant change in the rank of the other concepts. Although close rankings are obtained from both methods, considering the interaction between the concepts and avoid shortcomings of consensus in the method, the ranking obtained by the fuzzy DEMATEL method is preferred to use as input in Fuzzy Cognitive Maps (FCMs). Then a relation map is formed based on their interaction and three alternative scenarios are created for FCMs from defuzzified total relation matrix data. As a result of scenarios, it is more useful for organizations to apply the Industry 4.0 processes to transfer their resources to their activities concerning the Strategies, Technology, and Operations concepts. The aim is to predict the maturity levels of Industry 4.0 of organizations for the future by employing the FCMs methodology. Thanks to the introduced model based on the integration of fuzzy DEMATEL and FCMs, an insight is provided into which concepts should be prioritized about Industry 4.0.
Nowadays, it becomes very important to know the level of institutionalization and as a result what improvements they can make for organizations. Though there are many conceptual studies of institutionalization in the literature, there is no study based on numerical methods that can provide a foresight about institutionalization. In this paper, a new model has been proposed by determining concepts that are effective on institutionalization from literature and expert opinions. Firstly, the relationships between the concepts are taken from the experts linguistically. Linguistic expressions are converted to numerical values using the center of gravity method (COG) used in fuzzy logic applications. Then, three different scenarios were investigated by using the Fuzzy Cognitive Maps (FCMs) algorithm and the future states of the concepts were determined and interpreted. In the first scenario, an organization with poorly managed organizational concepts was considered. The institutionalization tendency in this organization has reached to 0,027 value which is the estimation calculated by FCM algorithm in the future. The second scenario and the third scenario represents a midlevel and good organization respectively. Institutionalization tendency values were 0.97 for the second and third scenarios. However, when the number of iterations representing the time period is examined, it is seen that the organization thought in the third scenario has reached this value before 9 iterations. This is because the organization in the third scenario is well managed in the current situation. With the developed model, the most effective concepts on institutionalization were also identified. It has been determined that the most important concepts affecting institutionalization are process management, information management and strategic management. Compared to the literature, the results seem to be consistent.
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