A Hybrid BSC-DEA Model with Indeterminate Information

Strategy is the main source of long-term growth for organizations, and if it is not successfully implemented, even if appropriate ones are adopted, the process is futile. The balanced scorecard which focuses on four aspects such as growth and learning, internal processes, customer, and financial is considered as a comprehensive framework for assessing performance and the progress of the strategy. Moreover, the data envelopment analysis is one of the best mathematical methods to compute the efficiency of organizations. The combination of these two techniques is a significant quantitative measurement with respect to the organization’s performance. However, in the real world, determinate and indeterminate information exists. Henceforth, the indeterminate issues are inescapable and must be considered in the performance evaluation. Neutrosophic number is a helpful tool for dealing with information that is indeterminate and incomplete. In this paper, we propose a new model of data envelopment analysis in the neutrosophic number environment. Furthermore, we attempt to combine the new model with the balanced scorecard to rank different decision-making units. Finally, the proposed method is illustrated by an empirical study involving 20 banking branches. The results show the effectiveness of the proposed method and indicate that the model has practical outcomes for decision-makers.

[1]  Farhad Hosseinzadeh Lotfi,et al.  Performance Evaluation of Banking Organizations Using the New Proposed Integrated DEA-BSC Model , 2016 .

[2]  S. A. Edalatpanah,et al.  Data envelopment analysis based on triangular neutrosophic numbers , 2020, CAAI Trans. Intell. Technol..

[3]  Harish Garg,et al.  Algorithms for possibility linguistic single-valued neutrosophic decision-making based on COPRAS and aggregation operators with new information measures , 2019, Measurement.

[4]  Francisco Gallego Lupiáñez,et al.  Interval neutrosophic sets and topology , 2008, Kybernetes.

[5]  Xi Liu,et al.  The neutrosophic number generalized weighted power averaging operator and its application in multiple attribute group decision making , 2015, International Journal of Machine Learning and Cybernetics.

[6]  Jun Ye,et al.  Generalized Ordered Weighted Simplified Neutrosophic Cosine Similarity Measure for Multiple Attribute Group Decision Making , 2020, Int. J. Cogn. Informatics Nat. Intell..

[7]  Krassimir T. Atanassov,et al.  Intuitionistic fuzzy sets , 1986 .

[8]  Wei Yang,et al.  Triangular Single Valued Neutrosophic Data Envelopment Analysis: Application to Hospital Performance Measurement , 2020, Symmetry.

[9]  Florentin Smarandache,et al.  Refined Literal Indeterminacy and the Multiplication Law of Sub-Indeterminacies , 2015 .

[10]  Surapati Pramanik,et al.  Neutrosophic number goal programming for multi-objective linear programming problem in neutrosophic number environment , 2018, MOJ Current Research & Reviews.

[11]  S. N. Musa,et al.  Fuzzy-based sustainability evaluation method for manufacturing SMEs using balanced scorecard framework , 2018, J. Intell. Manuf..

[12]  Yang Zhang,et al.  Service performance evaluation using data envelopment analysis and balance scorecard approach: an application to automotive industry , 2017, Ann. Oper. Res..

[13]  Teresa García-Valderrama,et al.  Relating the perspectives of the balanced scorecard for R&D by means of DEA , 2009, Eur. J. Oper. Res..

[14]  Esra Karasakal,et al.  A multicriteria sorting approach based on data envelopment analysis for R&D project selection problem ☆ , 2017 .

[15]  Jun Ye Multiple-Attribute Group Decision-Making Method under a Neutrosophic Number Environment , 2016, J. Intell. Syst..

[16]  Farhad Hosseinzadeh Lotfi,et al.  Supply chain performance evaluation with data envelopment analysis and balanced scorecard approach , 2014 .

[17]  Peide Liu,et al.  An extended multiple attribute group decision-making TODIM method based on the neutrosophic numbers , 2016, J. Intell. Fuzzy Syst..

[18]  Jun Ye Aggregation operators of neutrosophic linguistic numbers for multiple attribute group decision making , 2016, SpringerPlus.

[19]  S. A. Edalatpanah,et al.  A Direct Model for Triangular Neutrosophic Linear Programming , 2020, International Journal of Neutrosophic Science.

[20]  Harish Garg,et al.  Novel neutrality aggregation operator-based multiattribute group decision-making method for single-valued neutrosophic numbers , 2020, Soft Comput..

[21]  Huichen Jiang,et al.  Applying Data Envelopment Analysis in Measuring the Efficiency of Chinese Listed Banks in the Context of Macroprudential Framework , 2018, Mathematics.

[22]  Hong-yu Zhang,et al.  outranking approach for multi-criteria decision-making problems ith simplified neutrosophic sets uan - , 2014 .

[23]  Zhao Guoxi,et al.  A Neutrosophic-Based Approach in Data Envelopment Analysis with Undesirable Outputs , 2020 .

[24]  Jun Ye,et al.  Bidirectional projection method for multiple attribute group decision making with neutrosophic numbers , 2015, Neural Computing and Applications.

[25]  Hamidreza Karkehabadi,et al.  A development in balanced scorecard by designing a fuzzy and nonlinear Algorithm (case study: Islamic Azad university of Semnan) , 2012 .

[26]  Hokey Min,et al.  A data envelopment analysis‐based balanced scorecard for measuring the comparative efficiency of Korean luxury hotels , 2008 .

[27]  Michio Sugeno,et al.  Fuzzy identification of systems and its applications to modeling and control , 1985, IEEE Transactions on Systems, Man, and Cybernetics.

[28]  Jun Ye An Improved Neutrosophic Number Optimization Method for Optimal Design of Truss Structures , 2018, New Math. Nat. Comput..

[29]  Sankar K. Pal,et al.  Fuzzy models for pattern recognition , 1992 .

[30]  Abdullah Ozcil,et al.  An Alternative Approach for Performance Evaluation: Plithogenic Sets and DEA , 2020 .

[31]  Avraham Shtub,et al.  R&D project evaluation: An integrated DEA and balanced scorecard approach ☆ , 2008 .

[32]  Florentin Smarandache,et al.  n-Valued Refined Neutrosophic Logic and Its Applications to Physics , 2013, ArXiv.

[33]  Jun Ye,et al.  Neutrosophic number linear programming method and its application under neutrosophic number environments , 2018, Soft Comput..

[34]  Harish Garg,et al.  New logarithmic operational laws and their applications to multiattribute decision making for single-valued neutrosophic numbers , 2018, Cognitive Systems Research.

[35]  Mohammad Izadikhah,et al.  APPLYING BSC-DEA MODEL TO PERFORMANCE EVALUATION OF INDUSTRIAL COOPERATIVES : AN APPLICATION OF FUZZY INFERENCE SYSTEM , 2015 .

[36]  Rıdvan Şahin,et al.  Multi-criteria decision making approach based on PROMETHEE with probabilistic simplified neutrosophic sets , 2019, Soft Computing.

[37]  R. Kaplan,et al.  Using the balanced scorecard as a strategic management system , 1996 .

[38]  Surapati Pramanik,et al.  Bi-level Linear Programming Problem with Neutrosophic Numbers , 2018 .

[39]  Harish Garg,et al.  AN IMPROVED SCORE FUNCTION FOR RANKING NEUTROSOPHIC SETS AND ITS APPLICATION TO DECISION-MAKING PROCESS , 2017 .

[40]  Soroosh Nalchigar,et al.  Information technology project evaluation: An integrated data envelopment analysis and balanced scorecard approach , 2010, Expert Syst. Appl..

[41]  John Frederick D. Tapia,et al.  Evaluating negative emissions technologies using neutrosophic data envelopment analysis , 2021, Journal of Cleaner Production.

[42]  Binshan Lin,et al.  An integration of balanced scorecards and data envelopment analysis for firm's benchmarking management , 2009 .

[43]  Ali Emrouznejad,et al.  Influential DMUs and outlier detection in data envelopment analysis with an application to health care , 2014, Ann. Oper. Res..

[44]  Gento Mogi,et al.  A fuzzy analytic hierarchy process (AHP)/data envelopment analysis (DEA) hybrid model for efficiently allocating energy R&D resources: In the case of energy technologies against high oil prices , 2013 .

[45]  Tser-yieth Chen,et al.  DEA performance evaluation based on BSC indicators incorporated: The case of semiconductor industry , 2007 .

[46]  Jun Ye,et al.  Expression and Analysis of Joint Roughness Coefficient Using Neutrosophic Number Functions , 2017, Inf..

[47]  Lotfi A. Zadeh,et al.  Fuzzy Sets , 1996, Inf. Control..

[48]  Chie-Bein Chen,et al.  Firm operation performance analysis using data envelopment analysis and balanced scorecard: A case study of a credit cooperative bank , 2008 .

[49]  Erkut Düzakin,et al.  Measuring the performance of manufacturing firms with super slacks based model of data envelopment analysis: An application of 500 major industrial enterprises in Turkey , 2007, Eur. J. Oper. Res..

[50]  F. Smarandache,et al.  Correlation Coefficient of Interval Neutrosophic Set , 2013 .

[51]  Wann-Yih Wu,et al.  A balanced scorecard envelopment approach to assess airlines' performance , 2014, Ind. Manag. Data Syst..

[52]  Harish Garg,et al.  Some modified results of the subtraction and division operations on interval neutrosophic sets , 2019, J. Exp. Theor. Artif. Intell..

[53]  E. Najafi,et al.  A Network-Based Data Envelope Analysis Model in a Dynamic Balanced Score Card , 2015 .

[54]  Sérgio Pereira dos Santos,et al.  Integrating the Data Envelopment Analysis and the Balanced Scorecard approaches for enhanced performance assessment , 2012 .

[55]  S. P. Yadav,et al.  A new approach to rank the decision making units in presence of infeasibility in intuitionistic fuzzy environment , 2020 .

[56]  A. Charnes,et al.  Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis , 1984 .

[57]  Florentin Smarandache,et al.  Introduction to Neutrosophic Measure, Neutrosophic Integral, and Neutrosophic Probability , 2013, ArXiv.

[58]  Seong-Jong Joo,et al.  An application of data envelopment analysis for Korean banks with negative data , 2017 .

[59]  Farhad Hosseinzadeh Lotfi,et al.  Acquiring Targets in Balanced Scorecard Method by Data Envelopment Analysis Technique and its Application in Commercial Banks , 2010 .

[60]  Jun Ye,et al.  Similarity measures between interval neutrosophic sets and their applications in multicriteria decision-making , 2014, J. Intell. Fuzzy Syst..

[61]  Peide Liu,et al.  Multiple attribute group decision-making method based on neutrosophic number generalized hybrid weighted averaging operator , 2015, Neural Computing and Applications.

[62]  Jun Ye,et al.  A Projection Model of Neutrosophic Numbers for Multiple Attribute Decision Making of Clay-Brick Selection , 2016 .

[63]  Sapan Kumar Das,et al.  A new ranking function of triangular neutrosophic number and its application in integer programming , 2021 .

[64]  D. Delen,et al.  Balanced scorecard-based analysis of customer expectations for cosmetology services: a hybrid decision modeling approach , 2020 .

[65]  S. S. Appadoo,et al.  A novel method for solving the fully neutrosophic linear programming problems: Suggested modifications , 2019, J. Intell. Fuzzy Syst..

[66]  Walid Abdelfattah Data envelopment analysis with neutrosophic inputs and outputs , 2019, Expert Syst. J. Knowl. Eng..

[67]  Jun Ye,et al.  Single valued neutrosophic cross-entropy for multicriteria decision making problems , 2014 .

[68]  Meryl P Gardner,et al.  Data Envelopment Analysis: A Management Science Tool for Scientific Marketing Research , 2004 .

[69]  Abdorrahman Haeri,et al.  Integration of Balanced Scorecard and Three- stage Data Envelopment Analysis Approaches , 2017 .

[70]  Da Ruan,et al.  Integrating data envelopment analysis and analytic hierarchy for the facility layout design in manufacturing systems , 2006, Inf. Sci..

[71]  S. A. Edalatpanah,et al.  Neutrosophic perspective on DEA , 2018 .

[72]  Yu-Wei Chien,et al.  Combining balanced scorecard with data envelopment analysis to conduct performance diagnosis for Taiwanese LED manufacturers , 2016 .

[73]  S. A. Edalatpanah,et al.  Neutrosophic structured element , 2020, Expert Syst. J. Knowl. Eng..

[74]  Jun Ye,et al.  Optimal Design of Truss Structures Using a Neutrosophic Number Optimization Model under an Indeterminate Environment , 2017 .

[75]  S. A. Edalatpanah Systems of Neutrosophic Linear Equations , 2020 .

[76]  Arindam Dey,et al.  Neutrosophic Shortest Path Problem , 2018 .

[77]  Nabankur Mandal,et al.  Performance evaluation of an insurance company using an integrated Balanced Scorecard (BSC) and Best-Worst Method (BWM) , 2020, Decision Making: Applications in Management and Engineering.

[78]  Avraham Shtub,et al.  Constructing and evaluating balanced portfolios of R&D projects with interactions: A DEA based methodology , 2006, Eur. J. Oper. Res..

[79]  Jun Ye,et al.  Neutrosophic Number Nonlinear Programming Problems and Their General Solution Methods under Neutrosophic Number Environments , 2018, Axioms.

[80]  Cengiz Kahraman,et al.  An Integrated AHP & DEA Methodology with Neutrosophic Sets , 2018, Fuzzy Multi-criteria Decision-Making Using Neutrosophic Sets.

[81]  Lingwei Kong,et al.  Misfire Fault Diagnosis Method of Gasoline Engines Using the Cosine Similarity Measure of Neutrosophic Numbers , 2015 .

[83]  Jin Chen,et al.  Interval-valued intuitionistic fuzzy envelopment analysis and preference fusion , 2020, Comput. Ind. Eng..

[84]  S. A. Edalatpanah A Data Envelopment Analysis Model with Triangular Intuitionistic Fuzzy Numbers , 2019 .

[85]  S. A. Edalatpanah,et al.  A Novel Two-Stage DEA Model in Fuzzy Environment: Application to Industrial Workshops Performance Measurement , 2020, Int. J. Comput. Intell. Syst..

[86]  Kaoru Tone,et al.  Decomposing capacity utilization in data envelopment analysis: An application to banks in India , 2009, Eur. J. Oper. Res..

[87]  R. Dorf,et al.  The Balanced Scorecard: Translating Strategy Into Action , 1997, Proceedings of the IEEE.

[88]  Abraham Charnes,et al.  Measuring the efficiency of decision making units , 1978 .

[89]  Florentin Smarandache,et al.  Data Envelopment Analysis for Simplified Neutrosophic Sets , 2019 .

[90]  Florentin Smarandache,et al.  Introduction to Neutrosophic Statistics , 2014, ArXiv.