Decision-Making Taxonomy of DevOps Success Factors Using Preference Ranking Organization Method of Enrichment Evaluation

Due to multitudes factors like rapid change in technology, customer needs, and business trends, the software organizations are facing pressure to deliver quality software on time. To address this concern, the software industry is continually looking the solution to improve processing timeline. Thus, the Development and Operations (DevOps) has gained a wide popularity in recent era, and several organizations are adopting it, to leverage its perceived benefits. However, companies are facing several problems while executing the DevOps practices. The objective of this work is to identify the DevOps success factors that will help in DevOps process improvement. To accomplish this research firstly, a systematic literature review is conducted to identify the factors having positive influence on DevOps. Secondly, success factors were mapped with DevOps principles, i.e., culture, automation, measurement, and sharing. Thirdly, the identified success factors and their mapping were further verified with industry experts via questionnaire survey. In the last step, the PROMETHEE-II method has been adopted to prioritize and investigate logical relationship of success factors concerning their criticality for DevOps process. This study’s outcomes portray the taxonomy of the success factors, which help the experts design the new strategies that are effective for DevOps process improvement.

A New Decision Support Framework with Picture Fuzzy Information: Comparison of Video Conferencing Platforms for Higher Education in India

The purpose of this paper is to present a novel extension of a very recently developed multicriteria decision making (MCDM) algorithm known as the preference ranking on the basis of ideal-average distance (PROBID) method in a picture fuzzy (PF) environment. We use the full consistency method (FUCOM) with picture fuzzy numbers (PFNs) for deriving the criteria weights. We attempt to apply our proposed model for addressing a real-life complex decision making problem in social science research that gets influenced by the dynamics of discrete human behaviors. We compare eight popular video conferencing (VC) tools used for teaching-learning and meeting purposes in India using our novel integrated multicriteria decision making (MCDM) framework of FUCOM-PROBID with PF information. The criteria have been derived using the theoretical foundation of usability and user experience (UX). Based on the opinion of the decision makers (DM) or users who took part in the study, we find that ease of operations, compatibility with multiple systems and devices, quality of the voice, and video transmission and features are given more emphasis while Zoom, Microsoft Teams, and Google Meet are found to be preferable options to the users. The result of the proposed model shows stability and robustness as evident from the validation test and sensitivity analysis.

Effective selection of countries in sub-Saharan Africa for new market entry by independent wind power producers

When independent power producers (IPPs) assess new market entry opportunities, subjective decision making can result in an unfavourable outcome. Multi-criteria decision analyses (MCDA) objectify the decision process and help to achieve better results. The aim of this study is to determine and rank the most important criteria for market entry and then determine which selected countries in sub-Saharan Africa are most favourable for wind IPPs. A combination of MCDA methods was used to rank seven countries. Nineteen criteria, identified in the literature reviewed, were included in the analyses. In the first phase of the study an industry expert survey was conducted and the analytical hierarchy process (AHP) was used to rank the criteria in order of importance. In the second phase, a preference ranking organization method for enrichment evaluation (PROMETHEE) was employed to rank the countries from most to least favourable for IPP market entry. The expert survey and AHP showed that political and economic criteria are more important than technical and social criteria. The PROMETHEE model ranked South Africa followed by Ethiopia as the most favourable markets for wind IPPs to enter. These countries have strong natural wind resources but only South Africa offers incentives specifically for on-grid renewable energy. The methods used in this study are not restricted to the wind industry and can be expanded to different technologies and industries to assist with decision making.

Comparative Multicriteria Analysis Methods for Ranking Sites for Solar Farm Deployment: A Case Study in Greece

This study investigated the prioritization and ranking problem of the appropriate locations at which to deploy solar photovoltaic (PV) farms. Although different Multicriteria Decision Making (MCDM) methods can be found in the literature to address this problem, a comparative analysis of those methods is missing. The aim of this study is to compare four different MCDM approaches to evaluate and rank suitable areas for the deployment of solar PV farms, with the island of Rhodes (Greece) being used as an example. Feasible areas for the location of such facilities were identified with the use of Geographical Information Systems (GIS), by applying certain exclusion criteria found either in the national legislative framework or in the international literature. Data were obtained from Greek open geospatial data. The feasible sites were evaluated and ranked using four different MCDM methods: the Analytical Hierarchy Process (AHP), the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), the VIKOR (VIseKriterijumska Optimizacija I Kompromisno Resenje), and the PROMETHEE II (Preference Ranking Organization METHod for Enrichment of Evaluations) method. The best alternative rated according to three TOPSIS, VIKOR and PROMETHEE is site (S2). The second-best alternative in the above three methods is site (S1), while the worst is site (S3). The best alternative rated according to AHP (S4) is in sixth position according to TOPSIS and in fifth position VIKOR and PROMETHEE. The comparison demonstrated that different MCDM techniques may generate different ranks. The simultaneous use of several MCDM methods in energy siting problems is considered advantageous as it can help decision makers to select the most sustainable sites, avoiding the disadvantages and availing the advantages of each method.

Maintenance Preventive Analysis in Additive Manufacturing Equipment using Analytic Hierarchy Process

Maintenance preventive (PM) on equipment is a very important issue for an effective manufacturing system, since the improper MP might cause many problems affecting productivity, precision, flexibility and quality of the products negatively. On the other hand, analysis of MP equipment among many alternatives can be a multicriteria decision making (MCDM) problem. In this study, an integrated approach which employs analytic hierarchy process (AHP) and preference ranking elements, is proposed for the MP equipment of 3D printer machine. The AHP is used to analyze the structure of the equipment problems and to determine weights of the criteria, and this method is used to obtain final ranking. Proposed approach is applied to a problem of 3D printer machines to be established a MP strategy.

Evaluation of Outranking Border Region Sustainable Development in Papua Province – Papua New Guinea Using PROMETHEE

The border area of Indonesia - Papua New Guinea is one of the border areas of Indonesia which has complex characteristics. Apart from differences in geographical conditions, this border region also has characteristics of customary territories that are not owned by other border areas in Indonesia. This complexity causes high variations in the performance of regional or district development in the RI-PNG border area. This study was conducted to evaluate the performance of sustainable regional development through the PROMETHEE (Preference Ranking Organization Methods for Enrichment Evaluation) method. The results of the analysis show that areas that tend to be open with access to other areas in Indonesia such as Merauke and Jayapura tend to have better performance than other border areas. These results can be used as lessons learned in sustainable regional development planning in other border areas.

Selection of Electric Vehicles for the Needs of Sustainable Transport under Conditions of Uncertainty—A Comparative Study on Fuzzy MCDA Methods

All over the world, including Poland, authorities are taking steps to increase consumer interest in electric vehicles and sustainable transport as a way to reduce environmental pollution. For this reason, the electric vehicle market is dynamically and constantly developing, more and more modern vehicles are introduced to it, and purchases are often subsidized by the government. The aim of the article is to analyse the A–C segments of the Polish electric vehicle market and to recommend the most attractive vehicle from the perspective of sustainable transport. The aim of the research was achieved with the use of three multi-criteria decision aid (MCDA) methods, which deal well with the uncertainty and imprecision of data that occur in the case of many different parameters of electric vehicles. In particular, the following methods were used: the fuzzy technique for order of preference by similarity to ideal solution (TOPSIS), the fuzzy simple additive weighting (SAW) method, and the new easy approach to fuzzy preference ranking organization method for enrichment evaluation II (NEAT F-PROMETHEE II). Electric vehicle rankings obtained using each method were compared and verified by stochastic analysis. The conducted analyses and comparisons allowed us to identify the most interesting electric vehicles, which currently appear to be the Volkswagen ID.3 Pro S and Nissan LEAF e+.

A Linear Programming Based DEA-PROMETHEE Approach for Performance Evaluation

Companies follow their objectives with some critical success factors (CSF), and they know their bottlenecks and strong points. This provides decision support for them, but this method ignores overall performance and ranking issues. In this study, a comprehensive methodology is recommended to find out an effective solution to the performance evaluation problem for making strategic performance management. Two methods are used from different areas as a framework. To select the higher-performing departments, Data Envelopment Analyses (DEA) is used as a linear programming-based main method. Moreover, a Multi-Criteria Decision Making (MCDM) method is proposed, Preference Ranking Organization Method for Enrichment Evaluations (PROMETHEE), to increase the discrimination power of DEA and eliminate undesirable results because of determining weight bounds. These two methods are combined, and a comprehensive solution model is presented in the study. In the end, a case study is given for a real-life example, an integrated DEA-PROMETHEE method is applied to the case. When the case results are examined, the proposed model produces more logical weight values and better results.

A Decision Support Tool for Supplier Evaluation and Selection

The supplier selection process is considered one of the most relevant decisions in supply chain management due to its effect on the product quality and on buyer performance. Supplier selection is often unstructured, and is generally based on the lowest-price proposal. However, this type of selection involves a high risk, sometimes resulting in project delays, poor quality of acquired goods, and large financial losses. Price is undoubtedly an important criterion when choosing a supplier; however, other equally important criteria must be considered. Therefore, supplier selection should be formulated as a multi-criteria decision-making (MCDM) problem. This study uses the PROMETHEE-GAIA (Preference Ranking Organization Method for Enrichment of Evaluations—Geometrical Analysis for Interactive Assistance) method to classify and select suppliers in an agrifood company. One of the advantages of this method is that it allows decision-makers to set their preferences considering all the relevant criteria simultaneously, and their relative importance. The case study demonstrates that PROMETHEE constitutes a flexible MCDM tool for supplier evaluation and selection, rank the different alternatives, and provide valuable insights. The results show that the supplier selection process has a strong point related to the existence of two groups of suppliers, one focused on economic criteria and other related to the innovative capacity. However, a flaw emerges, as little relevance is associated to the environmental criterion.

Scenario-Based Comprehensive Assessment for Community Resilience Adapted to Fire following an Earthquake, Implementing the Analytic Network Process and Preference Ranking Organization Method for Enriched Evaluation II Techniques

Natural hazards bring significant influences on and socioeconomic loss to cities and communities. Historic events show that fire following earthquake (FFE) is the most influential uncertain disturbance on the urban infrastructure system. Under the FFE scenario, the concept of resilience is widely implemented to make up the shortcomings derived from the traditional disaster management methodology. Resilient cities and communities are required to improve the systemic performance in responding to the FFE. To fulfill these goals, measuring community resilience is an essential work for municipal policy makers. Therefore, this study conducted a comprehensive assessment on community resilience adapted to the FFE scenario. The systematic literature review (SLR) was employed to identify the indicators, and the analytic network process (ANP) technique was implemented to determine their weights. 20 indicators were extracted, and 4 communities that encountered FFE in China were selected for the empirical analysis. Thereafter, the preference ranking organization method for enriched evaluation (PROMETHEE) II technique was selected through using the multicriteria decision analysis (MCDA) methods selection framework to fulfill the comprehensive assessment. The results were discussed and demonstrated with graphical analysis for interactive aid (GAIA) technique. The findings revealed that the G Community won the highest score and had the strongest performance. However, H Community had the lowest score and the weakest performance. The proposed comprehensive methods could benefit the decision-makers and the policy executors achieving the community resilience adapted to the FFE scenario by improving the effective indicators.