Authors	Author full names	Author(s) ID	Title	Year	Source title	Volume	Issue	Art. No.	Page start	Page end	Page count	Cited by	DOI	Link	Affiliations	Authors with affiliations	Abstract	Author Keywords	Index Keywords	Molecular Sequence Numbers	Chemicals/CAS	Tradenames	Manufacturers	Funding Details	Funding Texts	References	Correspondence Address	Editors	Publisher	Sponsors	Conference name	Conference date	Conference location	Conference code	ISSN	ISBN	CODEN	PubMed ID	Language of Original Document	Abbreviated Source Title	Document Type	Publication Stage	Open Access	Source	EID
	Modak M.; Pathak K.; Ghosh K.K.	Modak, Mousumi (57193531511); Pathak, Khanindra (7004581276); Ghosh, Kunal Kanti (57213261862)	57193531511; 7004581276; 57213261862	Performance evaluation of outsourcing decision using a BSC and Fuzzy AHP approach: A case of the Indian coal mining organization	2017	Resources Policy	52			181	191	10	60	10.1016/j.resourpol.2017.03.002	https://www.scopus.com/inward/record.uri?eid=2-s2.0-85014637301&doi=10.1016%2fj.resourpol.2017.03.002&partnerID=40&md5=540901e82449213421ea9ecfd3158c90	Vinod Gupta School of Management, Indian Institute of Technology Kharagpur, Kharagpur, 721302, India; Department of Mining Engineering, Indian Institute of Technology Kharagpur, Kharagpur, 721302, India	Modak M., Vinod Gupta School of Management, Indian Institute of Technology Kharagpur, Kharagpur, 721302, India; Pathak K., Department of Mining Engineering, Indian Institute of Technology Kharagpur, Kharagpur, 721302, India; Ghosh K.K., Vinod Gupta School of Management, Indian Institute of Technology Kharagpur, Kharagpur, 721302, India	Mineral and mining sectors are always of a great concern to any nation due to its major contribution to the economy. In India, the demand for coal is continuously on rise due to its ever increasing need from the growing power sectors and steel industries. In spite of the large coal reserves, India has to import coal from overseas sources to address the perpetual demand-supply gap. In order to reduce the dependence on imported coal, to ensure an affordable price to the domestic customers as well as to achieve operational efficiency, the state-owned coal mining organization of India have now started taking initiatives to outsource some of the operational activities involving private agencies. To realize the success of outsourcing, it is indispensable to consider it as part of the corporate decision. Such decision essentially considers all possible attributes of strategy planning for performance improvement. The study focuses on the development of an effective performance evaluation framework based on Balanced Scorecard (BSC) and Fuzzy Analytic Hierarchy Process (FAHP) to analyze the suitability of organization's strategic decision of outsourcing in alignment with the organizational performance for the Indian coal mining organization. BSC administers strategic elements of decision making in assessing the performance of the firm whereas FAHP, on the other hand, is applied to determine the relative importance weight of criteria in regard to organizational objectives taking into consideration the vagueness and ambiguity of information as characteristics of decision-making problems. The findings of the present study establish the proposed framework as an analytical tool in strategy formulation and provide rationale guidance to management with regard to performance improvement. © 2017 Elsevier Ltd	Balanced Scorecard (BSC); Coal mining; Fuzzy Analytic Hierarchy Process (FAHP); Outsourcing; Performance evaluation	India; Analytic hierarchy process; Coal; Coal mines; Decision making; Outsourcing; Steelmaking; Ambiguity of information; Balanced scorecards; Coal mining; Decision-making problem; Fuzzy analytic hierarchy process; Operational efficiencies; Organizational performance; Performance evaluation; analytical hierarchy process; coal mining; corporate strategy; mining industry; outsourcing; performance assessment; Proven reserves							Abdolshah M., Javidnia M., Astanbous M.A., Eslami M., An integrated approach to analyze strategy map using BSC-fuzzy AHP: a case study of auto industry, Manag. Sci. 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Eval., 12, 4, pp. 1-8, (2007); Yu C.-S., A GP-AHP method for solving group decision-making fuzzy AHP problems, Computers and Operation Research, 29, pp. 1969-2001, (2002); Yuksel I., Dagdeviren M., Using the fuzzy analytical network process (ANP) for Balanced Scorecard (BSC): a case study for a manufacturing firm, Expert Syst. Appl., 37, pp. 1270-1278, (2010); Zadeh L.A., Fuzzy sets, Inf. Control, 8, pp. 338-353, (1965)	M. Modak; Vinod Gupta School of Management, Indian Institute of Technology Kharagpur, Kharagpur, 721302, India; email: mousumimodak10@gmail.com		Elsevier Ltd						03014207				English	Resour. Policy	Article	Final		Scopus	2-s2.0-85014637301
	Nguyen T.-L.; Nguyen P.-H.; Pham H.-A.; Nguyen T.-G.; Nguyen D.-T.; Tran T.-H.; Le H.-C.; Phung H.-T.	Nguyen, Thi-Ly (57221722966); Nguyen, Phi-Hung (57214384983); Pham, Hong-Anh (57303081400); Nguyen, Thi-Giang (59054299700); Nguyen, Duc-Thinh (57658707300); Tran, Thi-Hoai (57660587400); Le, Hong-Cham (57660904300); Phung, Huong-Thuy (57659028300)	57221722966; 57214384983; 57303081400; 59054299700; 57658707300; 57660587400; 57660904300; 57659028300	A Novel Integrating Data Envelopment Analysis and Spherical Fuzzy MCDM Approach for Sustainable Supplier Selection in Steel Industry	2022	Mathematics	10	11	1897				55	10.3390/math10111897	https://www.scopus.com/inward/record.uri?eid=2-s2.0-85131841402&doi=10.3390%2fmath10111897&partnerID=40&md5=2e58c8999bd3eb0549eeb8246976945f	Department of Industrial Engineering and Management, National Kaohsiung University of Science and Technology, Kaohsiung, 80778, Taiwan; Research Center of Applied Sciences, Faculty of Business, FPT University, Hanoi, 100000, Viet Nam; Department of Business Management, National Taipei University of Technology, Taipei, 10608, Taiwan	Nguyen T.-L., Department of Industrial Engineering and Management, National Kaohsiung University of Science and Technology, Kaohsiung, 80778, Taiwan; Nguyen P.-H., Research Center of Applied Sciences, Faculty of Business, FPT University, Hanoi, 100000, Viet Nam, Department of Business Management, National Taipei University of Technology, Taipei, 10608, Taiwan; Pham H.-A., Research Center of Applied Sciences, Faculty of Business, FPT University, Hanoi, 100000, Viet Nam; Nguyen T.-G., Research Center of Applied Sciences, Faculty of Business, FPT University, Hanoi, 100000, Viet Nam; Nguyen D.-T., Research Center of Applied Sciences, Faculty of Business, FPT University, Hanoi, 100000, Viet Nam; Tran T.-H., Research Center of Applied Sciences, Faculty of Business, FPT University, Hanoi, 100000, Viet Nam; Le H.-C., Research Center of Applied Sciences, Faculty of Business, FPT University, Hanoi, 100000, Viet Nam; Phung H.-T., Research Center of Applied Sciences, Faculty of Business, FPT University, Hanoi, 100000, Viet Nam	Supply chain sustainability, which takes environmental, economic, and social factors into account, was recently recognized as a critical component of the supply chain (SC) management evaluation process and known as a multi-criteria decision-making problem (MCDM) that is heavily influenced by the decision-makers. While some criteria can be analyzed numerically, a large number of qualitative criteria require expert review in linguistic terms. This study proposes an integration of Data Envelopment Analysis (DEA), spherical fuzzy analytic hierarchy process (SF-AHP), and spherical fuzzy weighted aggregated sum product assessment (SF-WASPAS) to identify a sustainable supplier for the steel manufacturing industry in Vietnam. In this study, both quantitative and qualitative factors are considered through a comprehensive literature review and expert interviews. The first step employs DEA to validate high-efficiency suppliers based on a variety of quantifiable criteria. The second step evaluates these suppliers further on qualitative criteria, such as economic, environmental, and social factors. The SF-AHP was applied to obtain the criteria’s significance, whereas the SF-WASPAS was adopted to identify sustainable suppliers. The sensitivity analysis and comparative results demonstrate that the decision framework is feasible and robust. The findings of this study can assist steel industry executives in resolving the macrolevel supplier selection problem. Moreover, the proposed method can assist managers in selecting and evaluating suppliers more successfully in other industries. © 2022 by the authors. Licensee MDPI, Basel, Switzerland.	DEA; MCDM; SF-AHP; SF-WASPAS; spherical fuzzy; steel industry; supplier selection; sustainability; Vietnam						FPT University; National Kaohsiung University of Science and Technology, NKUST	Funding text 1: Funding: This study was funded by FPT University, Vietnam, under Decision No. 304/QD-DH FPT, issued on 12 April 2022.; Funding text 2: This study was funded by FPT University, Vietnam, under Decision No. 304/QD-DH FPT, issued on 12 April 2022. The authors would like to express their heartfelt appreciation and gratitude to Vietnamese experts and policymakers for their contributions to this study. This study presents a portion of Thi-Ly Nguyen’s PhD thesis, which was completed under the supervision of Chia-Nan Wang at the National Kaoshiung University of Science and Technology in Taiwan and in line with the guidance of Phi-Hung Nguyen, FPT University, Vietnam.	Wu C., Barnes D., A Literature Review of Decision-Making Models and Approaches for Partner Selection in Agile Supply Chains, J. Purch. Supply Manag, 17, pp. 256-274, (2011); Verghese K., Lewis H., Environmental Innovation in Industrial Packaging: A Supply Chain Approach, Int. J. Prod. Res, 45, pp. 4381-4401, (2007); Hsu C.W., Kuo T.C., Chen S.H., Hu A.H., Using DEMATEL to Develop a Carbon Management Model of Supplier Selection in Green Supply Chain Management, J. Clean. 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Res, 50, pp. 1377-1394, (2012); Govindan K., Diabat A., Shankar K.M., Analyzing the Drivers of Green Manufacturing with Fuzzy Approach, J. Clean. Prod, 96, pp. 182-193, (2015); Mangla S., Madaan J., Chan F.T.S., Analysis of Flexible Decision Strategies for Sustainability-Focused Green Product Recovery System, Int. J. Prod. Res, 51, pp. 3428-3442, (2013); Govindan K., Khodaverdi R., Jafarian A., A Fuzzy Multi Criteria Approach for Measuring Sustainability Performance of a Supplier Based on Triple Bottom Line Approach, J. Clean. Prod, 47, pp. 345-354, (2013)	P.-H. Nguyen; Research Center of Applied Sciences, Faculty of Business, FPT University, Hanoi, 100000, Viet Nam; email: hungnp30@fe.edu.vn		MDPI						22277390				English	Mathematics	Article	Final	All Open Access; Gold Open Access	Scopus	2-s2.0-85131841402
	Li Z.; Marinova D.; Guo X.; Gao Y.; Deng Y.	Li, Zhidong (56970271200); Marinova, Dora (6701561637); Guo, Xiumei (50661439200); Gao, Yuan (57221270177); Deng, Yong (57699474400)	56970271200; 6701561637; 50661439200; 57221270177; 57699474400	Evaluating pillar industry's transformation capability: A case study of two Chinese steel-based cities	2015	PLoS ONE	10	9	e0139576				12	10.1371/journal.pone.0139576	https://www.scopus.com/inward/record.uri?eid=2-s2.0-84947715019&doi=10.1371%2fjournal.pone.0139576&partnerID=40&md5=ddc9fcb561211fa977ab3453c0808154	School of Management, Hefei University of Technology, Key Laboratory of Process Optimization and Intelligent Decision-Making, Ministry of Education, Hefei, China; Curtin University Sustainability Policy (CUSP) Institute, Curtin University, Perth, Australia; Southwest University, China	Li Z., School of Management, Hefei University of Technology, Key Laboratory of Process Optimization and Intelligent Decision-Making, Ministry of Education, Hefei, China, Curtin University Sustainability Policy (CUSP) Institute, Curtin University, Perth, Australia; Marinova D., Curtin University Sustainability Policy (CUSP) Institute, Curtin University, Perth, Australia; Guo X., Curtin University Sustainability Policy (CUSP) Institute, Curtin University, Perth, Australia; Gao Y., Curtin University Sustainability Policy (CUSP) Institute, Curtin University, Perth, Australia; Deng Y., Southwest University, China	Many steel-based cities in China were established between the 1950s and 1960s. After more than half a century of development and boom, these cities are starting to decline and industrial transformation is urgently needed. This paper focuses on evaluating the transformation capability of resource-based cities building an evaluation model. Using Text Mining and the Document Explorer technique as a way of extracting text features, the 200 most frequently used words are derived from 100 publications related to steel- and other resource-based cities. The Expert Evaluation Method (EEM) and Analytic Hierarchy Process (AHP) techniques are then applied to select 53 indicators, determine their weights and establish an index system for evaluating the transformation capability of the pillar industry of China's steel-based cities. Using real data and expert reviews, the improved Fuzzy Relation Matrix (FRM) method is applied to two case studies in China, namely Panzhihua and Daye, and the evaluation model is developed using Fuzzy Comprehensive Evaluation (FCE). The cities' abilities to carry out industrial transformation are evaluated with concerns expressed for the case of Daye. The findings have policy implications for the potential and required industrial transformation in the two selected cities and other resource-based towns. © 2015 Li et al.		China; Cities; Industry; Models, Theoretical; Steel; steel; Analytic Hierarchy Process technique; Article; building industry; China; controlled study; Expert Evaluation Method; Fuzzy Comprehensive Evaluation method; Fuzzy Relation Matrix method; industrialization; information processing; iron and steel industry; pillar industry; policy; transformation capability; city; economics; industry; theoretical model; trends		steel, 12597-69-2; Steel, 			National Natural Science Foundation of China; National Natural Science Foundation of China, NNSFC, (71301041); National Natural Science Foundation of China, NNSFC	This paper is financially supported by the National Natural Science Foundation of China (No. 71301041).	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Lu Y.D., Yu J., Sustainable development study of resource-based city from the perspective of circular economy, Advanced Materials Research, 361-363, pp. 1535-1538, (2011); Guo X., Marinova D., Hong J., China's shifting policies towards sustainability: Alow-carbon economy and environmental protection, J Contemp China, 22, 81, pp. 428-445, (2013)			Public Library of Science						19326203		POLNC	26422266	English	PLoS ONE	Article	Final	All Open Access; Gold Open Access; Green Open Access	Scopus	2-s2.0-84947715019
	Li C.; Qin J.; Li J.; Hou Q.	Li, Cuiping (57206621900); Qin, Jiexuan (55991869200); Li, Jiajie (56480265800); Hou, Qian (55522667400)	57206621900; 55991869200; 56480265800; 55522667400	The accident early warning system for iron and steel enterprises based on combination weighting and Grey Prediction Model GM (1,1)	2016	Safety Science	89			19	27	8	66	10.1016/j.ssci.2016.05.015	https://www.scopus.com/inward/record.uri?eid=2-s2.0-84973103429&doi=10.1016%2fj.ssci.2016.05.015&partnerID=40&md5=e953ca7c3b2f2176544587ff35b7780e	School of Civil and Environmental Engineering, University of Science and Technology Beijing, No. 30 Xueyuan Road, Haidian District, Beijing, 100083, China; Ministry of Education, Key Laboratory of High Efficiency Mining and Safety for Metal Mines, University of Science and Technology Beijing, No. 30 Xueyuan Road, Haidian District, Beijing, 100083, China; Norman B. Keevil Institute of Mining Engineering, University of British Columbia, 517-6350 Stores Road, Vancouver, V6T 1Z4, BC, Canada; China Association of Work Safety, No. 21 North Hepingli Road, Dongcheng District, Beijing, 100713, China	Li C., School of Civil and Environmental Engineering, University of Science and Technology Beijing, No. 30 Xueyuan Road, Haidian District, Beijing, 100083, China, Ministry of Education, Key Laboratory of High Efficiency Mining and Safety for Metal Mines, University of Science and Technology Beijing, No. 30 Xueyuan Road, Haidian District, Beijing, 100083, China; Qin J., School of Civil and Environmental Engineering, University of Science and Technology Beijing, No. 30 Xueyuan Road, Haidian District, Beijing, 100083, China, Ministry of Education, Key Laboratory of High Efficiency Mining and Safety for Metal Mines, University of Science and Technology Beijing, No. 30 Xueyuan Road, Haidian District, Beijing, 100083, China; Li J., Norman B. Keevil Institute of Mining Engineering, University of British Columbia, 517-6350 Stores Road, Vancouver, V6T 1Z4, BC, Canada; Hou Q., China Association of Work Safety, No. 21 North Hepingli Road, Dongcheng District, Beijing, 100713, China	In order to prevent the occurrence of accidents in iron and steel enterprises, it is essential to change the risk management pattern from post-emergency response to hazard control and prevention. Based on the characteristics of iron and steel enterprises, this paper investigates the early warning system for accidents for iron and steel enterprises, aiming for the adoption of accident prevention and hazard control. An early warning index system and an early warning model were constructed based on production types and accident statistics of the enterprises. On account of the factors that influence accidents, this early warning index system contains 3 hierarchies with 5 composite indexes and 22 thematic indexes. The indexes have been quantified, regularized, and their weights were determined using a combination weighting method based on the Analytic Hierarchy Process and the Entropy Weight Method. The early warning index model was established according to Grey System Theory GM (1,. 1), and the comprehensive early warning indexes were calculated by Multi-objective Linear Weighted Function. The thresholds were then determined, the early warning levels were identified, and the early warning signals were output accordingly. The feasibility and validity of the proposed early warning model was tested and verified through its application in a functioning industrial plant. © 2016 Elsevier Ltd.	Combination weighting; Early warning index system; GM (1,1) early warning model; Iron and steel enterprise; Risk early warning	Accidents; Hazards; Industrial plants; Iron; Risk management; Combination weighting; Early-warning indices; Early-warning models; Iron and steel enterprise; Risk early warning; accident prevention; Article; controlled study; devices; early warning system; entropy; feasibility study; hazard assessment; human; iron and steel industry; occupational accident; priority journal; risk management; validity; System theory					National Natural Science Foundation of China, NSFC, (51174032); Program for New Century Excellent Talents in University, NCET, (NCET-10-0225); Fundamental Research Funds for the Central Universities, (FRF-TP-09-001A)	The research presented in this paper was supported by the National Natural Science Foundation of China ( 51174032 ), the Program for New Century Excellent Talents in University ( NCET-10-0225 ) and the Fundamental Research Funds for the Central Universities ( FRF-TP-09-001A ).	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J., 23, pp. 92-97, (2013); Hu D., Analysis on Coal Mine Safety Accident Causes and Forewarning Management Research, Business Management, (2010); Hu J., Zhang L., Ma L., Liang W., An integrated method for safety pre-warning of complex system, Safety Sci., 48, pp. 580-597, (2010); Li Z.L., Xie A.L., Research on target tracking and early-warning for the safety of coal mine production, Appl. Mech. Mater., pp. 925-929, (2014); Niu Q., Zhou Y., Wang Z., Coal safety early-warning system base on self-organization neural networks, Comput. Eng. Des., 27, pp. 1752-1753, (2006); Quansah J.E., Engel B., Early warning systems: a review, J. Terr. Obs., 2, pp. 24-45, (2010); Salzano E., Garcia Agreda A., Di Carluccio A., Fabbrocino G., Risk assessment and early warning systems for industrial facilities in seismic zones, Reliab. Eng. Syst. Safe., 94, pp. 1577-1584, (2009); Chinese Accidents Inquiry System, Beijing, (2013); Wang N., Study on Fore-Warning System of Urban Road Traffic Safety, Transportation Planning and Management, (2007); Wang T., Wang G., Chen Y., A model of online public opinion pre-warning based on fuzzy comprehensive evaluation, J. Intell., 31, pp. 47-58, (2012); Crude Steel Production, (2015); Yang F., Metallurgical Production Safety Technology, (2010); Yu Z., Jiang F., Zhu Q., Li J., Research on multivariate hierarchical analysis and evaluation on rock burst hazard, The 2nd International Symposium on Mine Safety Science and Engineering, Beijing, pp. 1-9, (2013); Zheng G., Zhu N., Tian Z., Chen Y., Sun B., Application of a trapezoidal fuzzy AHP method for work safety evaluation and early warning rating of hot and humid environments, Safety Sci., 50, pp. 228-239, (2012); Zhou J., Liu Z., The research on the control and warning of ecological security based on GM (1,1) model, J. Arid L. Resour. Environ., 25, pp. 15-19, (2011)	J. Li; Norman B. Keevil Institute of Mining Engineering, University of British Columbia, Vancouver, 517-6350 Stores Road, V6T 1Z4, Canada; email: jiajie.li@alumni.ubc.ca		Elsevier B.V.						09257535		SSCIE		English	Saf. Sci.	Article	Final		Scopus	2-s2.0-84973103429
	Hao H.; Wu H.; Wei F.; Xu Z.; Xu Y.	Hao, Hao (57199957314); Wu, Haolong (59147141500); Wei, Fangfang (57200231846); Xu, Zhaoran (25423311300); Xu, Yi (59147455500)	57199957314; 59147141500; 57200231846; 25423311300; 59147455500	Scrap Steel Recycling: A Carbon Emission Reduction Index for China	2024	Sustainability (Switzerland) 	16	10	4250				1	10.3390/su16104250	https://www.scopus.com/inward/record.uri?eid=2-s2.0-85194356625&doi=10.3390%2fsu16104250&partnerID=40&md5=362b403df454d93b2376bb7fd895a4e2	College of Economics and Management, Shanghai Polytechnic University, Shanghai, 201209, China	Hao H., College of Economics and Management, Shanghai Polytechnic University, Shanghai, 201209, China; Wu H., College of Economics and Management, Shanghai Polytechnic University, Shanghai, 201209, China; Wei F., College of Economics and Management, Shanghai Polytechnic University, Shanghai, 201209, China; Xu Z., College of Economics and Management, Shanghai Polytechnic University, Shanghai, 201209, China; Xu Y., College of Economics and Management, Shanghai Polytechnic University, Shanghai, 201209, China	Accurately assessing carbon emissions from recycling scrap steel is essential for reducing emissions in the steel industry, especially in China, the world’s largest crude steel producer. In this study, a carbon emission reduction index was introduced to evaluate the effectiveness of recycling scrap steel in reducing emissions. The index considers the three processes used in scrap steel recycling: blast furnace ironmaking, converter steelmaking, and electric arc furnace steelmaking. This study developed an evaluation model using fuzzy analytic hierarchy process and iterative cluster analysis to determine the reduction of carbon emission. From a life cycle perspective, this study identified primary factors contributing to emissions, including fuel, raw materials, electric energy, and auxiliary materials. Then, the carbon emission reduction index for scrap recycling was developed by examining the production of one ton of steel and each additional ton of scrap steel, which can provide valuable insights into the environmental impact of scrap recycling. Finally, the study forecasts the future Carbon Emission Reduction Index for steel scrap recycling. The study indicates an increase in the carbon emission reduction index for scrap recycling prior to 2017, followed by a decrease about 11.8% from 2017 to 2018 and increases from 2018 to 2021. Finally, it dropped by 8.7% per cent in 2022. Similarly, the carbon emission reduction index for electric furnace steelmaking increased prior to 2019, then subsequently decreased. It is changing by ten per cent a year. Additionally, the scrap recycling index experienced a significant decrease of 90% in 2015, followed by a gradual increase until 2017 and then a consistent decrease every year thereafter. The index suddenly rose in 2021 and then decreased change for policy reasons. The forecast results suggest a gradual increase in the carbon emission reduction index per ton of steel scrap in the future. In conclusion, the practicable modeling methodology has the ability to assist government organizations and private enterprises in devising efficient green and low-carbon development tactics. © 2024 by the authors.	carbon emission; index; recycling; reduction; scrap steel; steel industry	China; carbon emission; cluster analysis; environmental impact; index method; iron and steel industry; life cycle analysis; recycling; steel					National Office for Philosophy and Social Sciences, NPOPSS, (20BGL200); National Office for Philosophy and Social Sciences, NPOPSS	This work was supported by the National Social Science Foundation of China (grant no. 20BGL200).	Adoption of the Paris Agreement, (2015); Special Report: Global Warming of 1.5 °C, (2018); Xie Y., Liu X.R., Chen Q., Zhang S.H., An integrated assessment for achieving the 2 °C target pathway in China by 2030, J. Clean. 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Steelmak, 46, pp. 609-617, (2019); Hasanbeigi A., Arens M., Cardenas J.C.R., Price L., Triolo R., Comparison of carbon dioxide emissions intensity of steel production in China, Germany, Mexico, and the United States, Resour. Conserv. Recycl, 113, pp. 127-139, (2016); Xuan Y., Yue Q., Forecast of steel demand and the availability of depreciated steel scrap in China, Resour. Conserv. Recycl, 109, pp. 1-12, (2016); Juntueng S., Towprayoon S., Chiarakorn S., Energy and carbon dioxide intensity of Thailand’s steel industry and greenhouse gas emission projection toward the year 2050, Resour. Conserv. Recycl, 87, pp. 46-56, (2014)	F. Wei; College of Economics and Management, Shanghai Polytechnic University, Shanghai, 201209, China; email: ffwei@sspu.edu.cn		Multidisciplinary Digital Publishing Institute (MDPI)						20711050				English	Sustainability	Article	Final	All Open Access; Gold Open Access	Scopus	2-s2.0-85194356625
	Pakkar M.S.	Pakkar, Mohammad Sadegh (56181914500)	56181914500	An integrated approach based on DEA and AHP	2015	Computational Management Science	12	1		153	169	16	17	10.1007/s10287-014-0207-9	https://www.scopus.com/inward/record.uri?eid=2-s2.0-84939876833&doi=10.1007%2fs10287-014-0207-9&partnerID=40&md5=e5beed45ab67a850a281c044c3fe90f7	Laurentian University, Sudbury, P3E 2C6, ON, Canada	Pakkar M.S., Laurentian University, Sudbury, P3E 2C6, ON, Canada	This research proposes a theoretical framework to assess the performance of Decision Making Units (DMUs) by integrating the Data Envelopment Analysis (DEA) and Analytic Hierarchy Process (AHP) methodologies. According to this, we consider two sets of weights of inputs and outputs under hierarchical structures of data. The first set of weights, represents the best attainable level of efficiency for each DMU in comparison to other DMUs. This level of efficiency can be less than or equal to that of obtaining from a traditional DEA model. The second set of weights reflects the priority weights of inputs and outputs for all DMUs, using AHP, in the DEA framework. We assess the performance of each DMU in terms of the relative closeness to the priority weights of inputs and outputs. For this purpose, we develop a parametric distance model to measure the deviations between the two sets of weights. Increasing the value of a parameter in a defined range of efficiency loss, we explore how much the deviations can be improved to achieve the desired goals of the decision maker. This may result in various ranking positions for each DMU in comparison to the other DMUs. To highlight the usefulness of the proposed approach, a case study for assessing the financial performance of eight listed companies in the steel industry of China is carried out. © 2014, Springer-Verlag Berlin Heidelberg.	Analytic hierarchy process; Data envelopment analysis; Distance model; Hierarchical structures of data; Performance								Azadeh A., Ghaderi S.F., Izadbakhsh H., Integration of DEA and AHP with computer simulation for railway system improvement and optimization, Appl Math Comput, 195, 2, pp. 775-785, (2008); Cai Y., Wu W., Synthetic financial evaluation by a method of combining DEA with AHP, Intern Trans Operat Res, 8, 5, pp. 603-609, (2001); Charnes A., Cooper W.W., Rhodes E., Measuring the efficiency of decision making units, Europ J Operat Res, 2, 6, pp. 429-444, (1978); Chen T.Y., Measuring firm performance with DEA and prior information in Taiwan’s banks, Appl Econ Lett, 9, 3, pp. 201-204, (2002); Cooper W.W., Seiford L.M., Zhu J., Handbook on data envelopment analysis, (2004); Entani T., Ichihashi H., Tanaka H., Evaluation method based on interval AHP and DEA, Cent Europ J Operat Res, 12, 1, pp. 25-34, (2004); Ertay T., Ruan D., Tuzkaya U.R., Integrating data envelopment analysis and analytic hierarchy for the facility layout design in manufacturing systems, Inf Sci, 176, 3, pp. 237-262, (2006); Feng Y., Lu H., Bi K., An AHP/DEA method for measurement of the efficiency of R&D management activities in universities, Intern Trans Operat Res, 11, 2, pp. 181-191, (2004); Ho C.B., Oh K.B., Selecting internet company stocks using a combined DEA and AHP approach, Intern J Syst Sci, 41, 3, pp. 325-336, (2010); Hong-yi L., Chu Z., Di Z., Stock investment value analysis model based on AHP and gray relational degree, Manag Sci Eng, 4, 4, pp. 1-6, (2010); Jablonsky J., Measuring the efficiency of production units by AHP models, Math Comp Model, 46, 7, pp. 1091-1098, (2007); Jyoti B., Deshmukh S.G., Evaluating performance of national R&D organizations using integrated DEA–AHP technique, Intern J Product Perform Manag, 57, 5, pp. 370-388, (2008); Kao C., A linear formulation of the two-level DEA model, Omega, 36, 6, pp. 958-962, (2008); Kim T., Extended topics in the integration of data envelopment analysis and the analytic hierarchy process in decision making, (2000); Kong W., Fu T., Assessing the performance of business colleges in Taiwan using data envelopment analysis and student based value-added performance indicators, Omega, 40, 5, pp. 541-549, (2012); 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	Alavi S.; Aghakhani H.	Alavi, Somaieh (36138808500); Aghakhani, Hamid (57226291672)	36138808500; 57226291672	Identifying the effect of green human resource management practices on lean-agile (LEAGILE) and prioritizing its practices	2023	International Journal of Productivity and Performance Management	72	3		599	624	25	46	10.1108/IJPPM-05-2020-0232	https://www.scopus.com/inward/record.uri?eid=2-s2.0-85111075002&doi=10.1108%2fIJPPM-05-2020-0232&partnerID=40&md5=c5d66f534e551ab3c3ff5179316d460e	Shahid Ashrafi Esfahani University, Isfahan, Iran; Islamic Azad University Najafabad Branch, Najafabad, Iran	Alavi S., Shahid Ashrafi Esfahani University, Isfahan, Iran; Aghakhani H., Islamic Azad University Najafabad Branch, Najafabad, Iran	Purpose: The present study attempted to identify, measure and prioritize key green human resource management (GHRM) practices to achieve the lean-agile mindset in the steel industry. Design/methodology/approach: Following an in-depth review of the literature, this study identifies GHRM practices. Then, the effect of green HRM practices on the lean-agile mindset was evaluated using structural equation modeling (SEM). In the next step, using the fuzzy analytic hierarchy process (FAHP), prioritization of practices that have significant effects on lean-agile mindset were discussed. Findings: The present study introduced eight GHRM practices. The results of SEM showed a significant and positive effect of all GHRM practices on lean-agile mindset. Prioritization of GHRM practices by the FAHP was defined as green reward management, green education and development, green performance evaluation, green discipline management, green employment, green safety and health management, green selection and green career design. Research limitations/implications: The present study suffers from some limitations. First, the research was conducted at a temporal section. Second, this research has been conducted in a particular industry. Practical implications: The present study encourages human resource managers to increase their efforts to achieve green employees and put employee greenery in their strategic goals. Social implications: Successful implementation of GHRM programs has positive consequences at the individual, organizational and community levels. Implementation of the identified actions increases employee vitality at the individual level. At the organizational level, the work environment of environmentally friendly organizations is also more attractive to job seekers. Finally, at the social and extra-organizational level, a green lifestyle is spread in the community, which will lead to a healthy and green environment. Originality/value: Emphasizing environmental principles on the one hand and creating the lean-agile mindset on the other are effective factors on maintaining the competitive advantage of industries. In this regard, the present study presented two innovations in HRM literature: (1) assessing the effect of GHRM practices on lean-agile mindset and (2) prioritizing GHRM practices based on the lean-agile mindset. © 2021, Emerald Publishing Limited.	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SHS Web of Conferences, (2018); Walters D., Helman D., Performance management: value drivers and strategic value builders, Strategic Capability Response Analysis, pp. 75-98, (2020); Wang E., Jiang W., Mao S., Job autonomy and turnover intention among social workers in China: roles of work-to-family enrichment, job satisfaction and type of sector, Journal of Social Service Research, 46, 6, pp. 1-15, (2020); Wijesooriya W., Jayarathana S., The effect of financial and non-financial rewards on employee performance, 5th HRM Student Research Symposium, (2018); Yohannessen K., Pinto-Galleguillos D., Parra-Giordano D., Agost A., Valdes M., Smith L.M., Galen K., Arain A., Rojas F., Neitzel R.L., Health assessment of electronic waste workers in Chile: participant characterization, International Journal of Environmental Research and Public Health, 16, 3, (2019)	S. Alavi; Shahid Ashrafi Esfahani University, Isfahan, Iran; email: somayeh_alavi61@yahoo.com		Emerald Publishing						17410401				English	Int. J. Product. Perform. Manage.	Article	Final		Scopus	2-s2.0-85111075002
	Kumar R.; Tiwari S.; Kansara S.	Kumar, Rupesh (57216141130); Tiwari, Saurabh (55538178200); Kansara, Surendra (57201475289)	57216141130; 55538178200; 57201475289	Barriers Prioritization of the Indian Steel Industry Supply Chain: Applying AHP and Fuzzy AHP Method	2021	Vision							6	10.1177/09722629211065687	https://www.scopus.com/inward/record.uri?eid=2-s2.0-85121827743&doi=10.1177%2f09722629211065687&partnerID=40&md5=e81a2afe5c57022e56192a19a7c8bb0a	School of Business, University of Petroleum and Energy Studies (UPES), Uttarakhand, Dehradun, India; Symbiosis Institute of Operations Management (SIOM), Constituent of Symbiosis International (Deemed University), Maharashtra, Pune, India	Kumar R., School of Business, University of Petroleum and Energy Studies (UPES), Uttarakhand, Dehradun, India; Tiwari S., School of Business, University of Petroleum and Energy Studies (UPES), Uttarakhand, Dehradun, India; Kansara S., Symbiosis Institute of Operations Management (SIOM), Constituent of Symbiosis International (Deemed University), Maharashtra, Pune, India	This study seeks to identify possible key barriers in the supply chain of the Indian steel industry. Each of these hindrances has a significance in serving the store network and refining the economy of India. The study is a mix of theoretical and useful structures, which would zero in on those critical barriers in the steel supply chain. It includes a theoretical examination of the barriers in the Indian steel industry and ranking of these barriers using multicriteria methods, that is, analytical hierarchical process (AHP) and fuzzy analytical hierarchical process (FAHP) approaches. The main finding is the identification of key barriers in the Indian steel industry supply chain and prioritizing them according to the severity of their impact. Eleven potential key barriers have been considered in the study for analysis. There can be more barriers in the Indian steel industry. This study exposes the application of both methods, that is, AHP and FAHP, for ranking identified barriers. © 2021 Management Development Institute.	AHP; FAHP; Multicriteria Methods; Steel Industry; Supply Chain								Ayhan M.B., A fuzzy AHP approach for supplier selection problem: A case study in a gear motor company, International Journal of Managing Value and Supply Chains, 4, 3, pp. 11-23, (2013); Backman J., Kyllonen V., Helaakoski H., Methods and tools of improving steel manufacturing processes: Current state and future methods, IFAC-PapersOnLine, 52, 13, pp. 1174-1179, (2019); Buckley J.J., Fuzzy hierarchical analysis, Fuzzy Sets Systems, 17, 1, pp. 233-247, (1985); Burange L.G., Yamini S., Competitiveness of the firms in Indian iron and steel industry, (2010); Chang D.-Y., Applications of the extent analysis method on fuzzy AHP, European Journal of Operational Research, 95, 3, pp. 649-655, (1996); Chatterjee A., Transition of the Indian steel industry into the twenty-first century, Ironmaking & Steelmaking, 36, 7, pp. 491-499, (2009); Chen Y., Huang P., Bi-negotiation integrated AHP in suppliers selection, Benchmarking: An International Journal, 14, 5, pp. 575-593, (2007); Dheeraj B.K., Babu V.C., Madhuri K., Patnaik D., Narayana G.V.V.S., Kumar G., Gayathri V.R.P., India’s steel vision: Macro logistics base, (2006); Firoz A.S., Opportunities and challenges of the Indian steel industry: In the context of future growth, Asian Steel Watch, 4, pp. 24-39, (2017); Ghosh S., Iron and steel industry in India: Past, present and future, (2005); Govindan K., Murugesan P., Selection of third-party reverse logistics provider using fuzzy extent analysis, Benchmarking: An International Journal, 18, 1, pp. 149-167, (2011); Jena N., Seth N., Investigating the perceptions of Indian employees on logistics network and logistics cost on Indian steel sector, Asia Pacific Journal of Marketing and Logistics, 28, 3, pp. 565-574, (2016); Kumar R., Kansara S., Information technology barriers in Indian sugar supply chain: An AHP and fuzzy AHP approach, Benchmarking: An International Journal, 25, 7, pp. 1978-1991, (2018); Kumar S.P., Naidu B.V., An analysis of Indian steel industry, Journal of International Academic Research for Multidisciplinary, 1, 3, pp. 110-119, (2013); Lin J., Liu M., Hao J., Jiang S., A multi-objective optimization approach for integrated production planning under interval uncertainties in the steel industry, Computers & Operations Research, 72, pp. 189-203, (2016); Marciniak Z., Duncan J.L., Hu S.J., Mechanics of sheet metal forming, (2002); Mehdiyev N., Lahann J., Emrich A., Enke D., Fettke P., Loos P., Time series classification using deep learning for process planning: A case from the process industry, Procedia Computer Science, 114, pp. 242-249, (2017); Mitra R., Sebastian D.V.J., Efficiency in the Indian iron and steel industry, Journal of Advances in Management Research, 11, 1, pp. 2-16, (2014); Morfeldt J., Nijs W., Silveira S., The impact of climate targets on future steel production: An analysis based on a global energy system model, Journal of Cleaner Production, 103, pp. 469-482, (2015); Muthuraman B., Steel steals the show, (2006); Pal P., Gupta H., Kapur D., Carbon mitigation potential of Indian steel industry, Mitigation and Adaptation Strategies for Global Change, 21, pp. 391-402, (2016); Popli G.S., Popli R., Research paper on investment opportunities in the steel sector of India on the concept of Make in India, (2015); Ray P., Navulla D., Financial obstacles and disputes faced by steel industries of India, International Journal of Research in Commerce, Economics & Management, 6, 5, pp. 99-103, (2016); Ray S., Pal M.K., Trend in total factor productivity growth in Indian iron and steel industries under a liberalized trade regime: An empirical analysis with adjustment for capacity utilization, Journal of Applied Business and Economics, 11, 3, (2010); Saaty T.L., The analytic hierarchy process, (1980); Saaty T.L., Homogeneity and clustering in AHP ensures the validity of the scale, European Journal of Operational Research, 72, 3, pp. 598-601, (1994); Saaty T.L., Vargas L.G., Uncertainty and rank order in the analytic hierarchy process, European Journal of Operational Research, 32, 1, pp. 107-117, (1987); Scarsi R., Recovering supply chain cost efficiency through original logistics solutions: A case in the steel industry, Supply Chain Forum: An International Journal, 8, 1, pp. 74-82, (2007); Schuler D.A., Corporate political strategy and foreign competition, The Academy of Management Journal, 39, 3, pp. 720-737, (1996); Sobaszek L., Gola A., Swic A., Predictive scheduling as a part of intelligent job scheduling system, International Conference on Intelligent Systems in Production Engineering and Maintenance, pp. 358-367, (2017); Vadde S., Srinivas G., The Indian steel sector: Development and potential, Zenith International Journal of Multidisciplinary Research, 2, 1, pp. 177-186, (2012); Domestic steel production expecting a revival, (2020); The white book of steel, (2012)	R. Kumar; School of Business, University of Petroleum and Energy Studies (UPES), Dehradun, Uttarakhand, India; email: rupesh.kumar@ddn.upes.ac.in		Sage Publications India Pvt. Ltd						09722629				English	Vision	Article	Article in press		Scopus	2-s2.0-85121827743
	Jaiswal R.K.; Lohani A.K.; Galkate R.V.	Jaiswal, R.K. (38461222000); Lohani, A.K. (6602080269); Galkate, R.V. (11239480600)	38461222000; 6602080269; 11239480600	Decision support for scenario analysis in a complex water resource project	2021	Journal of Applied Water Engineering and Research	9	1		52	68	16	2	10.1080/23249676.2020.1844604	https://www.scopus.com/inward/record.uri?eid=2-s2.0-85096332138&doi=10.1080%2f23249676.2020.1844604&partnerID=40&md5=4bf0c85c2335d9c2dd71371c2be99cf3	National Institute of Hydrology, CIHRC, Bhopal, India; National Institute of Hydrology, Surface Water, Roorkee, India	Jaiswal R.K., National Institute of Hydrology, CIHRC, Bhopal, India; Lohani A.K., National Institute of Hydrology, Surface Water, Roorkee, India; Galkate R.V., National Institute of Hydrology, CIHRC, Bhopal, India	Multi-criteria decision support (MCDS) was developed and demonstrated for a complex reservoir system for a comprehensive assessment of performance for a complex reservoir system. A management model for the Tandula complex system in India was developed in MIKE HYDRO Basin. This system has three interconnected reservoirs, three irrigation commands, and one industrial user. The results from simulations were analyzed in multi-criteria decision support using an economic and six performance indicators to get a comprehensive performance index for the system. The results of the analysis confirmed that the yearly deficit of the Tandula command maybe about 6.36 MCM with 88% reliability under the present efficiency of 51% and no groundwater use (SCN-1). The comprehensive performance index for scenario SCN-1 was 0.13 which can be increased to 0.86 by increasing efficiencies and consumptive use. Abbreviations: AHP: Analytical hierarchical process; ANN: Artificial Neural Network; BSP: Bhilai Steel Plant; CEA: Cost effectiveness analysis; DAPP: Dynamic adaptive policy pathways; DS: Decision scaling; GW: Groundwater; Ha: Hectare; MORDM: Many objective robust decision making; MOVA: Many-objective visual analytics; MCDA: Multi Criteria Decision Analysis; MCM: Million cubic meter; MCDA: Multi-criteria decision analysis; NB-DSS: Nile Basin Decision Support System; ROA: Real options analysis; RRV: Reliability, resilience, vulnerability; RDM: Robust decision making; WEAP: Water Evaluation and Planning; SCN: Scenario; VIDEO Visually interactive decision-making and design using evolutionary multi-objective optimization. © 2020 IAHR and WCCE.	analytical hierarchal process; consumptive use; crop yield; irrigation planning; performance indicator; Reservoir operation								Adeloye A.J., Soundharajan B.-S., Mohammed S., Harmonisation of reliability performance indices for planning and operational evaluation of water supply reservoirs, Water Resour Manag, 31, pp. 1013-1029, (2017); Belton V., Stewart T.J., Multiple Criteria Decision Analysis: an Integrated Approach, (2002); Ben-Haim Y., Info-gap Decision Theory: decisions Under Severe Uncertainty, (2006); Biswas B., Aquifer Mapping and Management Plan (Durg block, Durg district, Chhattisgarh), (2017); Bouman B.A.M., Kropff M.J., Tuong T.P., Et al., Oryza 2000: modeling Lowland Rice, (2001); Bryant B.P., Lempert R.J., Thinking inside the box: A participatory, computer-assisted approach to scenario discovery, Technol Forecast Soc Change, 77, pp. 34-49, (2010); Cai X., McKinney D.C., Lasdon L.S., A framework for sustainability analysis in water resources management and application to the Syr Darya Basin, Water Resour Res, 38, pp. 21-1-21-14, (2002); Chang F.-J., Chen L., Chang L.-C., Optimizing the reservoir operating rule curves by genetic algorithms, Hydrol Process, 19, pp. 2277-2289, (2005); Collins M.G., Steiner F.R., Rushman M.J., Land-use suitability analysis in the United States: historical development and promising technological achievements, Environ Manage, 28, pp. 611-621, (2001); Crowe K.A., Parker W.H., Using portfolio theory to guide reforestation and restoration under climate change scenarios, Clim Change, 89, pp. 355-370, (2008); Dong Z., Pan Z., An P., Et al., A novel method for quantitatively evaluating agricultural vulnerability to climate change, Ecol Indic, 48, pp. 49-54, (2015); Dorini G., Kapelan Z., Azapagic A., Managing uncertainty in multiple-criteria decision making related to sustainability assessment, Clean Technol Environ Policy, 13, pp. 133-139, (2011); Ehsani N., Fekete B.M., Vorosmarty C.J., Tessler Z.D., A neural network based general reservoir operation scheme, Stoch Environ Res Risk Assess,