Decision-making model for designing telecom products/services based on customer preferences and non-preferences

The design of the packages of products/services to be offered by a telecom company to its clients is a complex decision-making process that must consider different criteria to achieve both customer satisfaction and optimization of the company’s resources. In this process, Intuitionistic Fuzzy Sets (IFSs) can be used to manage uncertainty and better represent both preferences and non-preferences expressed by people who value each proposed alternative. We present a novel approach to design/develop new products/services that combines the Lean Six Sigma methodology with IFSs. Its main contribution comes from considering both preferences and nonpreferences expressed by real clients, whereas existing proposals only consider their preferences. By also considering their non-preferences, it provides an additional capacity to manage the high uncertainty in the selection of the commercial plan that best suits each client’s needs. Thus, client satisfaction is increased while improving the company’s corporate image, which will lead to customer loyalty and increased revenue. To validate the presented proposal, it has been applied to a real case study of the telecom sector, in which 2135 users have participated. The results obtained have been analysed and compared with those obtained with a model that does not consider the non-preferences expressed by users.Spanish Ministry of Science and Innovation (State Research Agency)Junta de Andalucia PID2019-103880RB-I00 PID2019-109644RB-I00 PY20_0067

Electric Bus Selection with Multicriteria Decision Analysis for Green Transportation

Eren, Tamer/0000-0001-5282-3138; Hamurcu, Mustafa/0000-0002-6166-3946WOS:000531558100202Multicriteria decision-making tools are widely used in complex decision-making problems. There are also numerous points of decision-making in transportation. One of these decision-making points regards clean technology vehicle determination. Clean technology vehicles, such as electric buses, have some advantages compared to other technologies like internal combustion engine vehicles. Notably, electric vehicles emit zero tailpipe emissions, thereby ensuring cleaner air for cities and making these clean technologies preferable to other technologies, especially in highly populated areas for better air quality and more livable cities. In this study, we propose a multicriteria decision-making process using analytic hierarchy process (AHP) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) in the context of an electric bus in the center of Ankara. Six potential electric bus alternatives were evaluated under seven specific criteria. Overall, EV-2 electric buses outperformed other electric bus alternatives based on the chosen criteria. In addition, the stability of the results obtained under different scenarios using this method was established via sensitivity analysis

Evaluation of combined heat and power (CHP) systems using fuzzy shannon entropy and fuzzy TOPSIS

Combined heat and power (CHP) or cogeneration can play a strategic role in addressing environmental issues and climate change. CHP systems require less fuel than separate heat and power systems in order to produce the same amount of energy saving primary energy, improving the security of the supply. Because less fuel is combusted, greenhouse gas emissions and other air pollutants are reduced. If we are to consider the CHP system as "sustainable", we must include in its assessment not only energetic performance but also environmental and economic aspects, presenting a multicriteria issue. The purpose of the paper is to apply a fuzzy multicriteria methodology to the assessment of five CHP commercial technologies. Specifically, the combination of the fuzzy Shannon's entropy and the fuzzy Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) approach will be tested for this purpose. Shannon's entropy concept, using interval data such as the α-cut, is a particularly suitable technique for assigning weights to criteria — it does not require a decision-making (DM) to assign a weight to the criteria. To rank the proposed alternatives, a fuzzy TOPSIS method has been applied. It is based on the principle that the chosen alternative should be as close as possible to the positive ideal solution and be as far as possible from the negative ideal solution. The proposed approach provides a useful technical–scientific decision-making tool that can effectively support, in a consistent and transparent way, the assessment of various CHP technologies from a sustainable point of view

Evaluation of renewable energy alternatives using MACBETH and fuzzy AHP multicriteria methods: the case of Turkey

Energy is a critical foundation for economic growth and social progress. It is estimated that 70% of the world energy consumption could be provided from renewable resources by the year 2050. Renewable energy is the inevitable choice for sustainable economic growth, for the harmonious coexistence of human and environment as well as for the sustainable development. The aim of this paper is to evaluate the renewable energy alternatives as a key way for resolving the Turkey's energy-related challenges because of the fact that Turkey's energy consumption has risen dramatically over the past three decades as a consequence of economic and social development. In order to realize this aim, we comparatively use MACBETH and AHP-based multicriteria methods for the evaluation of renewable energy alternatives under fuzziness. We use 4 main attributes and 15 sub-attributes in the evaluation. The potential renewable energy alternatives in Turkey are determined as Solar, Wind, Hydropower, and Geothermal

Hydrogen technology adoption analysis in Africa using a Doughnut-PESTLE hydrogen model (DPHM)

The hydrogen economy requires the right conditions to produce hydrogen by sustainable routes and provide it to local and international markets for suitable applications. This study evaluated the political, economic, social, technological, legal, and environmental (PESTLE) conditions that can be instrumental in adopting hydrogen technologies most effectively by encapsulating aspects relevant to key stakeholders from hydrogen technology developers through to end-users. For instance, the analysis has shown that countries within a government effectiveness index of 0.5 and −0.5 are leading the planning of hydrogen economies through strategic cooperation with hydrogen technology developers. Furthermore, the combination of a Doughnut and PESTLE analysis created a novel approach to assessing the adoption of hydrogen technologies while evaluating the impact of the hydrogen economy. For instance, the estimated ammonia demand in 2050 and subsequent anthropogenic nitrogen extraction rate will be about two and a half times more than the 2009 extraction rate

A long-term energy efficiency prediction model for the Brazilian automotive industry

According to law number 12.715/2012, Brazilian government instituted guidelines for a program named Inovar-Auto. In this context, energy efficiency is a survival requirement for Brazilian automotive industry from September 2016. As proposed by law, energy efficiency is not going to be calculated by models only. It is going to be calculated by the whole universe of new vehicles registered. In this scenario, the composition of vehicles sold in market will be a key factor on profits of each automaker. Energy efficiency and its consequences should be taken into consideration in all of its aspects. In this scenario, emerges the following question: which is the efficiency curve of one automaker for long term, allowing them to adequate to rules, keep balancing on investment in technologies, increasing energy efficiency without affecting competitiveness of product lineup? Among several variables to be considered, one can highlight the analysis of manufacturing costs, customer value perception and market share, which characterizes this problem as a multi-criteria decision-making. To tackle the energy efficiency problem required by legislation, this paper proposes a framework of multi-criteria decision-making. The proposed framework combines Delphi group and Analytic Hierarchy Process to identify suitable alternatives for automakers to incorporate in main Brazilian vehicle segments. A forecast model based on artificial neural networks was used to estimate vehicle sales demand to validate expected results. This approach is demonstrated with a real case study using public vehicles sales data of Brazilian automakers and public energy efficiency data. According to our results Inovar-Auto targets will be reached in spite of little progress over last four years

Advances in Theoretical and Computational Energy Optimization Processes

The paradigm in the design of all human activity that requires energy for its development must change from the past. We must change the processes of product manufacturing and functional services. This is necessary in order to mitigate the ecological footprint of man on the Earth, which cannot be considered as a resource with infinite capacities. To do this, every single process must be analyzed and modified, with the aim of decarbonising each production sector. This collection of articles has been assembled to provide ideas and new broad-spectrum contributions for these purposes