Evaluating Recognitive Balanced Scorecard-Based Quality Improvement Strategies of Energy Investments With the Integrated Hesitant 2-Tuple Interval-Valued Pythagorean Fuzzy Decision-Making Approach to QFD

This study aims to identify quality improvement strategies for energy investments. For this purpose, a model is proposed which includes 4 different stages. In the first stage, the MCDM problem is identified for evaluating the service development for energy industry. In this framework, quality function deployment (QFD) approach is taken into consideration which includes both customer expectations and technical requirements at the same time to improve the quality in the organization. The second stage is related to the calculation of the correlation coefficients of decision matrices for the criteria by considering hesitant 2-tuple interval-valued Pythagorean fuzzy sets. The third stage includes the weighting of the customer expectations with hesitant 2-tuple interval-valued Pythagorean fuzzy (HIVPF) DEMATEL. In the final stage, TRIZ-based quality improvement strategies of energy investments are ranked by using 2-tuple HIVPF TOPSIS. Thus, the motivation of this study is to figure out the weights of the criteria for quality improvement strategies in energy investments. Also, the most important contribution of this study to the literature is related to the originality in the methodology by proposing a new MCDM model while using hesitant linguistic term sets, linguistic 2-tuple information, interval-valued Pythagorean fuzzy sets properly. The findings indicate that empathy is the most significant criterion for the customer expectations in the energy investments. In addition to this issue, it is also identified that customization is the best factor among the technical requirements of energy investments. Moreover, information and communication facilities and organizational background are found as the best competencies of new service development in energy investments. Furthermore, that prior action and periodic action are the most prominent strategies for quality improvement. While considering these results, it can be said that the pricing policy of the energy companies should be fair to increase customer satisfaction. Additionally, offering flexible payment opportunities on energy bills can have a positive influence on the customer satisfaction in this process. Also, preliminary planning of the project should be done in detail in energy investments. Owing to this issue, customers’ preferences can be identified before the product is placed on the market. In addition, it can be possible to identify the risks that may arise in energy investments with the help of the periodical audits.

[1]  Hu Xu,et al.  Supplier selection in nuclear power industry with extended VIKOR method under linguistic information , 2016, Appl. Soft Comput..

[2]  Juan Pablo Carvallo,et al.  Understanding recent market trends of the US ESCO industry , 2018 .

[3]  Mehrbakhsh Nilashi,et al.  Social media addiction: Applying the DEMATEL approach , 2019, Telematics Informatics.

[4]  Yasir Ahmed Solangi,et al.  Evaluating the strategies for sustainable energy planning in Pakistan: An integrated SWOT-AHP and Fuzzy-TOPSIS approach , 2019, Journal of Cleaner Production.

[5]  G. Chebotareva,et al.  Leading factors of market profitability of the renewable energy companies , 2018 .

[6]  Aled Jones,et al.  Policy making and energy infrastructure change: A Nigerian case study of energy governance in the electricity sector , 2017 .

[7]  B. B. Zaidan,et al.  Survey on fuzzy TOPSIS state-of-the-art between 2007 and 2017 , 2019, Comput. Oper. Res..

[8]  Ashlyn D. Smith,et al.  Combining agriculture and energy industry waste products to yield recyclable, thermally healable copolymers of elemental sulfur and oleic acid , 2019, Journal of Polymer Science Part A: Polymer Chemistry.

[9]  D. Jenkins,et al.  Blockchain technology in the energy sector: A systematic review of challenges and opportunities , 2019, Renewable and Sustainable Energy Reviews.

[10]  H. Di̇nçer,et al.  Multidimensional evaluation of global investments on the renewable energy with the integrated fuzzy decision‐making model under the hesitancy , 2019, International Journal of Energy Research.

[11]  Ramazan Bayindir,et al.  Valuation of reliability assessment for power systems in terms of distribution system, A case study , 2017, 2017 IEEE 6th International Conference on Renewable Energy Research and Applications (ICRERA).

[12]  Renata Korsakienė,et al.  Corporate Governance-Based Strategic Approach to Sustainability in Energy Industry of Emerging Economies with a Novel Interval-Valued Intuitionistic Fuzzy Hybrid Decision Making Model , 2020 .

[13]  Jinbo Song,et al.  Influence of FDI quality on energy efficiency in China based on seemingly unrelated regression method , 2020 .

[14]  G. S. Alʹtshuller,et al.  The Innovation Algorithm:TRIZ, systematic innovation and technical creativity , 1999 .

[15]  Hasan Dincer,et al.  IT2-Based Fuzzy Hybrid Decision Making Approach to Soft Computing , 2019, IEEE Access.

[16]  Kai Wang,et al.  A group decision making sustainable supplier selection approach using extended TOPSIS under interval-valued Pythagorean fuzzy environment , 2019, Expert Syst. Appl..

[17]  Muhammad Akram,et al.  Group decision‐making based on pythagorean fuzzy TOPSIS method , 2019, Int. J. Intell. Syst..

[18]  Mamta Pandey,et al.  Identifying Causal Relationships in Mobile App Issues: An Interval Type-2 Fuzzy DEMATEL Approach , 2019, Wirel. Pers. Commun..

[19]  Luis Martínez-López,et al.  Analysis of balanced scorecard-based SERVQUAL criteria based on hesitant decision-making approaches , 2019, Comput. Ind. Eng..

[20]  Daryoush Habibi,et al.  Optimal allocation of distributed energy storage systems to improve performance and power quality of distribution networks , 2019, Applied Energy.

[21]  Guiwu Wei,et al.  Pythagorean 2-Tuple Linguistic Taxonomy Method for Supplier Selection in Medical Instrument Industries , 2019, International journal of environmental research and public health.

[22]  Jiang Wu,et al.  Cumulative Prospect Theory: Performance Evaluation of Government Purchases of Home-Based Elderly-Care Services Using the Pythagorean 2-tuple Linguistic TODIM Method , 2020, International journal of environmental research and public health.

[23]  Lijun Tang,et al.  The Importance of Customer Expectations: An Analysis of CSR in Container Shipping , 2018, Journal of Business Ethics.

[24]  Serhat Yüksel,et al.  SERVQUAL-Based Performance Analysis of Agricultural Financing in E-Banking Industry , 2020 .

[25]  Muhammet Gul,et al.  AHP–TOPSIS integration extended with Pythagorean fuzzy sets for information security risk analysis , 2019, Complex & Intelligent Systems.

[26]  Yong Deng,et al.  Combining conflicting evidence using the DEMATEL method , 2018, Soft Comput..

[27]  Roy A. Nyberg.  Using 'smartness' to reorganise sectors: Energy infrastructure and information engagement , 2018, Int. J. Inf. Manag..

[28]  Serhat Yüksel,et al.  Defining the Strategic Impact-Relation Map for the Innovative Investments Based on IT2 Fuzzy DEMATEL , 2020 .

[29]  P. A. Ejegwa.  Pythagorean fuzzy set and its application in career placements based on academic performance using max–min–max composition , 2019, Complex & Intelligent Systems.

[30]  Cengiz Kahraman,et al.  A novel interval-valued Pythagorean fuzzy QFD method and its application to solar photovoltaic technology development , 2019, Comput. Ind. Eng..

[31]  Kevin Cullinane,et al.  A comparison of fuzzy DEA and fuzzy TOPSIS in sustainable supplier selection: Implications for sourcing strategy , 2019, Expert Syst. Appl..

[32]  Mohammed Bennekrouf,et al.  An Efficient Approach for Solving Integrated Production and Distribution Planning Problems: Cost vs. Energy , 2020, Int. J. Appl. Logist..

[33]  Gang Zhao,et al.  Decision Making for Principal-Agent Contracts in Intelligent Customization for New Energy Equipment , 2019 .

[34]  Ping-Feng Pai,et al.  Sustainable supply chain management using approximate fuzzy DEMATEL method , 2018 .

[35]  Miltiadis D. Lytras,et al.  Artificial Intelligence for Smart Renewable Energy Sector in Europe—Smart Energy Infrastructures for Next Generation Smart Cities , 2020, IEEE Access.

[36]  Rouzbeh Abbassi,et al.  A novel extension of DEMATEL approach for probabilistic safety analysis in process systems , 2020 .

[37]  Hong-yu Zhang,et al.  Multi-criteria Group Decision-Making Approach Based on 2-Tuple Linguistic Aggregation Operators with Multi-hesitant Fuzzy Linguistic Information , 2015, International Journal of Fuzzy Systems.

[38]  Mehmet Pekkaya,et al.  Evaluation of healthcare service quality via Servqual scale: An application on a hospital , 2019 .

[39]  Boqiang Lin,et al.  Assessing the development of China's new energy industry , 2018 .

[40]  Arsalan Nisar,et al.  Open organizational structures: A new framework for the energy industry , 2016 .

[41]  Huchang Liao,et al.  A novel VIKOR approach based on entropy and divergence measures of Pythagorean fuzzy sets to evaluate renewable energy technologies in India , 2019, Journal of Cleaner Production.

[42]  Chaoyong Zhang,et al.  Stochastic multi-objective modelling and optimization of an energy-conscious distributed permutation flow shop scheduling problem with the total tardiness constraint , 2019, Journal of Cleaner Production.

[43]  Francisco Herrera,et al.  The 2-tuple Linguistic Model , 2015, Springer International Publishing.

[44]  Renata Korsakienė,et al.  IT2 Hybrid Decision-Making Approach to Performance Measurement of Internationalized Firms in the Baltic States , 2019, Sustainability.

[45]  Huseyin Selcuk Kilic,et al.  Comparison of municipalities considering environmental sustainability via neutrosophic DEMATEL based TOPSIS , 2020 .

[46]  L. Proskuryakova.  Foresight for the ‘energy’ priority of the Russian Science and Technology Strategy , 2019, Energy Strategy Reviews.

[47]  Hing Kai Chan,et al.  Exploring critical factors of green business failure based on Grey-Decision Making Trial and Evaluation Laboratory (DEMATEL) , 2019, Journal of Business Research.

[48]  Serhat Yüksel,et al.  Comparing the performance of Turkish deposit banks by using DEMATEL, Grey Relational Analysis (GRA) and MOORA approaches , 2017 .

[49]  Ta-Chun Wen,et al.  Integrating the 2-tuple linguistic representation and soft set to solve supplier selection problems with incomplete information , 2020, Eng. Appl. Artif. Intell..

[50]  Soumava Boral,et al.  A novel hybrid multi-criteria group decision making approach for failure mode and effect analysis: An essential requirement for sustainable manufacturing , 2020, Sustainable Production and Consumption.

[51]  Na Li,et al.  Pythagorean fuzzy interaction power Bonferroni mean aggregation operators in multiple attribute decision making , 2020, Int. J. Intell. Syst..

[52]  Xiaoyun Xia,et al.  Strategic Mapping of Youth Unemployment With Interval-Valued Intuitionistic Hesitant Fuzzy DEMATEL Based on 2-Tuple Linguistic Values , 2020, IEEE Access.

[53]  Hasan Dinçer,et al.  Multi-Faceted Analysis of Systematic Risk-Based Wind Energy Investment Decisions in E7 Economies Using Modified Hybrid Modeling with IT2 Fuzzy Sets , 2020 .

[54]  Mehrbakhsh Nilashi,et al.  Factors influencing medical tourism adoption in Malaysia: A DEMATEL-Fuzzy TOPSIS approach , 2019, Comput. Ind. Eng..

[55]  Andrii Iatsyshyn,et al.  Development of a Virtual Scientific and Educational Center for Personnel Advanced Training in the Energy Sector of Ukraine , 2020 .

[56]  Luis Martínez-López,et al.  Balanced scorecard-based analysis about European energy investment policies: A hybrid hesitant fuzzy decision-making approach with Quality Function Deployment , 2019, Expert Syst. Appl..

[57]  M. Fonseka,et al.  The Effects of Environmental Information Disclosure and Energy Types on the Cost of Equity: Evidence from the Energy Industry in China , 2019, Abacus.

[58]  Francisco Herrera,et al.  A 2-tuple fuzzy linguistic representation model for computing with words , 2000, IEEE Trans. Fuzzy Syst..

[59]  Mauro Carpita,et al.  Use cases for Blockchain in the Energy Industry Opportunities of emerging business models and related risks , 2019, Comput. Ind. Eng..

[60]  Muhammet Deveci,et al.  Evaluation of service quality in public bus transportation using interval-valued intuitionistic fuzzy QFD methodology , 2019 .

[61]  Jiang Wu,et al.  Selecting the Low-Carbon Tourism Destination: Based on Pythagorean Fuzzy Taxonomy Method , 2020, Mathematics.

[62]  HE Tingting,et al.  CODAS METHOD FOR 2-TUPLE LINGUISTIC PYTHAGOREAN FUZZY MULTIPLE ATTRIBUTE GROUP DECISION MAKING AND ITS APPLICATION TO FINANCIAL MANAGEMENT PERFORMANCE ASSESSMENT , 2020, Technological and Economic Development of Economy.

[63]  Suleyman Mete,et al.  Risk assessment for clearing and grading process of a natural gas pipeline project: An extended TOPSIS model with Pythagorean fuzzy sets for prioritizing hazards , 2018, Human and Ecological Risk Assessment: An International Journal.

[64]  Harish Garg,et al.  Linguistic Pythagorean fuzzy sets and its applications in multiattribute decision‐making process , 2018, Int. J. Intell. Syst..

[65]  Selcuk Cebi,et al.  A new risk assessment approach: Safety and Critical Effect Analysis (SCEA) and its extension with Pythagorean fuzzy sets , 2018, Safety Science.

[66]  Mohammad Reza Akbari Jokar,et al.  Sustainable supplier selection: A multi-criteria intuitionistic fuzzy TOPSIS method , 2019, Journal of Manufacturing Systems.

[67]  Serhat Yüksel,et al.  Strategy Selection for Organizational Performance of Turkish Banking Sector With the Integrated Multi-Dimensional Decision-Making Approach , 2019, Advances in Logistics, Operations, and Management Science.

[68]  Sang Soo Lee,et al.  Enhanced accessibility of carbon in pyrolysis of brown coal using carbon dioxide , 2018, Journal of CO2 Utilization.

[69]  Grigorios L. Kyriakopoulos,et al.  Evaluating Customer Satisfaction in Energy Markets Using a Multicriteria Method: The Case of Electricity Market in Greece , 2020, Sustainability.

[70]  Guiwu Wei,et al.  Pythagorean 2-tuple linguistic power aggregation operators in multiple attribute decision making , 2020, Economic Research-Ekonomska Istraživanja.

[71]  Serhat Yüksel,et al.  SERVQUAL-Based Evaluation of Service Quality of Energy Companies in Turkey , 2019, The Circular Economy and Its Implications on Sustainability and the Green Supply Chain.

[72]  M. R. M. Asyraf,et al.  Conceptual design of creep testing rig for full-scale cross arm using TRIZ-Morphological chart-analytic network process technique , 2019, Journal of Materials Research and Technology.

[73]  Sachin Shetty,et al.  Towards a Reliable and Accountable Cyber Supply Chain in Energy Delivery System Using Blockchain , 2018, SecureComm.

[74]  Sung-Young Kim,et al.  Hybridized industrial ecosystems and the makings of a new developmental infrastructure in East Asia’s green energy sector , 2019, Review of International Political Economy.