Restricted accessResearch articleFirst published online 2025-5
Enhanced EDAS framework for quality evaluation of cultural industry development under the background of digital economy based on SVNNCSM and SVNNCFSM techniques
With the advent of digital economy era, the high-quality development of cultural industry has received people's attention. How to take advantage of the favorable opportunities of rapid development of the digital economy to further promote the innovative development of cultural industry is an important problem that needs to be solved in development process of Chinese cultural industries. The quality evaluation of cultural industry development in the context of the digital economy is MAGDM. The single-valued neutrosophic sets (SVNSs) is useful tool to cope with uncertain information during the quality evaluation of cultural industry development in the context of the digital economy. In this paper, the single-valued neutrosophic number EDAS (SVNN-EDAS) model based on single-valued neutrosophic number cosine similarity measure (SVNNCSM) and SVNN cosine function similarity measure (SVNNCFSM) is formed to cope with the MAGDM. The CRITIC model is administrated to obtain the weight numbers in light with the SVNNCSM and SVNNCFSM under SVNSs. Finally, numerical example and different comparative analysis for quality evaluation of cultural industry development in the context of the digital economy is administrated to validate SVNN-EDAS model. The main contributions of this study are formed: (1) the CRITIC model is formed to obtain the weight numbers in light with SVNNCSM and SVNNCFSM; (2) the SVNN-EDAS model is formed in light with SVNNCSM and SVNNCFSM under SVNNs; (3) Finally, numerical example and comparative analysis for quality evaluation of cultural industry development in the context of the digital economy is administrated to validate SVNN-EDAS model.
HutchinsBRoweD. From broadcast scarcity to digital plenitude the changing dynamics of the media sport content economy. Telev New Media2009; 10: 354–370.
2.
LeeJY. Contesting the digital economy and culture: digital technologies and the transformation of popular music in Korea. Inter-Asia Cult Stud2009; 10: 489–506.
3.
HoltF. The economy of live music in the digital age. Eur Cult Stud2010; 13: 243–261.
4.
LazovicVDurickovicT. The digital economy in developing countries - challenges and opportunities. In: 37th International convention on information and communication technology, electronics and microelectronics (MIPRO), Ieee, Opatija, CROATIA. Opatija, Croatia: IEEE; 2014, pp.1580–1585.
5.
YouZTZhongMGaoQ, et al.The impact of digital economy on residents’ health: based on the perspective of population ageing. Front Public Health2021; 9: 14.
6.
KviatA. Post-digital prosumption and the sharing economy of space: the pay-per-minute cafe. J Consum Cult2022; 22: 801–822.
7.
LiXYLiangXPYuT, et al.Research on the integration of cultural tourism industry driven by digital economy in the context of COVID-19-based on the data of 31 Chinese provinces. Front Public Health2022; 10: 10.
8.
StraughanERBissellD. Curious encounters: the social consolations of digital platform work in the gig economy. Urban Geogr2022; 43: 1309–1327.
9.
FangZHuangLZhangH. Analyzing the impact of geographic environment differences on the dual backwardness of rural economy and information in the perspective of digital poverty. Sustainability2023; 15: 11.
10.
HeJLPengJZengG. The spatiality of the creative digital economy: local amenities to the spatial agglomeration of creative e-freelancers in China. J Knowl Econ2023; 14: 4608–4629.
11.
JiangXXWangXRenJ,et al.Digital economy, agglomeration, and entrepreneurship in Chinese cities. Manag Decis Econ2023; 44: 359–370.
12.
JordanTRichterichA. Researching the digital economy and the creative economy: free gaming shards and commercialised making at the intersection of digitality and creativity. Eur J Cult Stud2023; 26: 354–370.
13.
OttoEISalkaJHBlokA. How app companies use github: on modes of valuation in the digital attention economy. J Cult Econ2023; 16: 242–259.
14.
StambolievEChristiaensT. Digital working lives: workers autonomy and the gig economy. J Cult Econ2023; 16: 923–925.
15.
WangLYHuHQWangXZ, et al.The synergistic evolution of resilience and efficiency in the digital economy and its path identification: evidence from China. Systems2023; 11: 26.
16.
WangRHWangQJShiRB, et al.How the digital economy enables regional sustainable development using big data analytics. Sustainability2023; 15: 16.
17.
XiongMZZhangFZhangHJ,et al.Digital economy, credit expansion, and modernization of industrial structure in China. Fin Res Lett2023; 58: 9.
18.
ZhongXJCaoZYPengB,et al.Study on the coupling and coordination relationship between the digital economy and green development: evidence from guangdong province in China. Front Environ Sci2023; 11: 10.
19.
JiwasiddiASchlagweinDCahalaneM, et al.Digital nomadism as a new part of the visitor economy: the case of the “digital nomad capital” Chiang Mai, Thailand. Inf Syst J2024: 43.
20.
XiaLBaghaieSSajadiSM. The digital economy: challenges and opportunities in the new era of technology and electronic communications. Ain Shams Eng J2024; 15: 8.
21.
YaoFGSongYWangXM. How the digital economy empowers the structural upgrading of cultural industries-an analysis based on the spatial durbin model. Sustainability2023; 15: 17.
22.
ZhangRZLiZJXiaoCQ,et al.New engines of economic growth: how digital currencies lead the way to growth in the era of digital economy. Econ Anal Policy2023; 80: 1597–1617.
23.
ZhengZYZhuYMWangY, et al.Spatio-temporal heterogeneity of the coupling between digital economy and green total factor productivity and its influencing factors in China. Environ Sci Pollut Research2023; 30: 82326–82340.
24.
PoonCSYipRCP. The cultural shift of the construction industry of Hong Kong under the influence of sustainable development. In: 6th International conference on tall buildings/Mini symposium on sustainable cities/Mini symposium on planning, design and socio-economic aspects of tall residential living environment, World Scientific Publ Co Pte Ltd, Hong Kong, PEOPLES R CHINA. Ube, Japan: World Scientific; 2005, pp.987–992.
25.
WangQH. The municipal group in central China and the development of its cultural industry clusters. In: 4th International conference on innovation and management, Wuhan Univ Technology Press, Ube, JAPAN. Ube, Japan: Wuhan University Technology Press; 2007, pp.356–361.
26.
WangYZhengLX. Development research of cultural creative industry based on the intangible cultural heritage in Hangzhou. In: 9th IEEE international conference on computer-aided industrial design and conceptual design, Ieee, Kunming, PEOPLES R CHINA. Kunming, Peoples of China: IEEE; 2008, pp.1293-+.
27.
XieCYZhaoXHuangL,et al.Assessment of coordinated development of digital technology and cultural industries in sustainable environment: Evidence from provincial level data in mainland china, Economic Research-Ekonomska Istrazivanja, (2022) 16.
28.
XieZQZhangYFangZQ. The space-time evolution of the coupling and coordinated development of public cultural services and cultural industries: a case study of 31 regions in China. Sustainability2022; 14: 16.
29.
XuJYWangJXLiuQY, et al.Retracted: the influence of culture and art management on the healthy development of cultural economy industry under the background of sustainable ecological environment (retracted article). J Environ Pub Health2022; 2022: 7.
30.
YanJLiZH. Retracted: the integrated development of tourism and cultural and creative industries based on smart city cloud service information system (retracted article). Mob Inf Syst2022; 2022: 10.
31.
YangTT. Influence of the coordinated development mechanism of tourism and digital cultural industry on alleviating tourists’ psychological anxiety. Psychiatr Danub2022; 34: S505–S506.
32.
ZeilerXMukherjeeS. Video game development in India: a cultural and creative industry embracing regional cultural heritage(s). Games Cult2022; 17: 509–527.
33.
ZemiteIKundaIJudrupaI. The role of the cultural and creative industries in sustainable development of small cities in Latvia. Sustainability2022; 14: 22.
34.
ZengHYangL. The innovation and development path of cultural and creative industries in anhui province, China: nvivo12-based policy text analysis. Comput Intell Neurosci2022; 2022: 11.
35.
ZhangRPuLJ. Evaluation of the competitiveness and sustainable development of eco-cultural tourism fusion industry. J Environ Protect Ecol2022; 23: 243–250.
36.
ChangCCPaiCJLoHW. Sustainable development evaluation of cultural and creative industries using a neutrosophic-based dematel-topsis approach. Int J Inf Technol Decis Mak2024; 23(03): 1367–1400.
37.
FanTFuTXuQ,et al.Retraction: research on the purification of environmental pollution by biomaterials and its treatment methods in the development of rural cultural and creative industries (retraction of vol 2022, art no 1594081, 2022). Bioinorg Chem Appl2023; 2023: 1.
38.
GaoYTurkinaEVan AsscheA. The nexus between the cultural and creative industries and the sustainable development goals: a network perspective. Reg Stud2023: 58(04).
39.
JiCYXuG. Digital development of cultural and creative industries under the security of 5 g mobile and communication. Wirel Pers Comm2023: 15. https://doi.org/10.1007/s11277-023-10498-x
40.
KongYL. Real-time processing system and internet of things application in the cultural tourism industry development. Soft Computing2023; 27: 10347–10357.
41.
SokólAPangsy-KaniaSBieganskaJ. Do cultural industries have an impact on sustainable development in eu countries?J Clean Prod2023; 428: 12.
42.
YangHXueDQLiHL, et al.Interaction between the cultural and entertainment industry and urban development in xi'an: a case study. Land2023; 12: 21.
43.
YaoHAXuPPFuHW,et al.Promoting sustainable development in the construction industry: the impact of contractors’ cultural preferences on green construction performance. Environ Imp Assess Rev2023; 103: 11.
44.
YuZNYuJ. Evaluation of the coordinated development between Chinese cultural industry and scientific & technological innovation. Plos One2023; 18: 23.
45.
HuG. Modified edas method for spherical fuzzy multiple attribute group decision making and applications to English classroom teaching quality evaluation. J Intell Fuzzy Syst2023; 45: 2799–2811.
46.
GaoP. Vikor method for intuitionistic fuzzy multi-attribute group decision-making and its application to teaching quality evaluation of college English. J Intell Fuzzy Syst2022; 42: 5189–5197.
47.
DouW. Madm framework based on the triangular pythagorean fuzzy sets and applications to college public English teaching quality evaluation. J Intell Fuzzy Syst2023; 45: 4395–4414.
48.
RongX. Triangular pythagorean fuzzy Bonferroni mean operators in multiple attribute decision making and applications to college English smart classroom teaching quality evaluation. J Intell Fuzzy Syst2023; 45: 2871–2886.
49.
WeiL. An integrated decision-making framework for blended teaching quality evaluation in college English courses based on the double-valued neutrosophic sets. J Intell Fuzzy Syst2023; 45: 3259–3266.
KarunanithiKHanCLeeCJ, et al.Identification of a hemodynamic parameter for assessing treatment outcome of edas in moyamoya disease. J Biomech2015; 48: 304–309.
52.
Keshavarz GhorabaeeMZavadskasEKOlfatL,et al.Multi-criteria inventory classification using a new method of evaluation based on distance from average solution (edas). Informatica2015; 26: 435–451.
53.
MallickRPramanikSGiriBC. Neutrosophic magdm based on critic-edas strategy using geometric aggregation operator. Yugosl J Oper Res2023; 33: 683–698.
54.
MallickRPramanikS. Trnn- edas strategy for madm with entropy weight under trapezoidal neutrosophic number environment. In: SmarandacheFAbdel-BassetM (eds) Neutrosophic operational research: methods and applications. Cham: Springer International Publishing, 2021, pp.575–592.
55.
YeJ. Similarity measures of intuitionistic fuzzy sets based on cosine function for the decision making of mechanical design schemes. J Intell Fuzzy Syst2016; 30: 151–158.
56.
PengJJWangJQWangJ, et al.Simplified neutrosophic sets and their applications in multi-criteria group decision-making problems. Int J Syst Sci2016; 47: 2342–2358.
57.
YeJ. Improved cosine similarity measures of simplified neutrosophic sets for medical diagnoses. Artif Intell Med2015; 63: 171–179.
58.
DiakoulakiDMavrotasGPapayannakisL. Determining objective weights in multiple criteria problems: the critic method. Comput Oper Res1995; 22: 763–770.
59.
ZavadskasEKBausysRStanujkicD,et al.Selection of lead-zinc flotation circuit design by applying waspas method with single-valued neutrosophic set. Acta Montan Slovac2016; 21: 85–92.
BiswasPPramanikSGiriBC. Neutrosophic topsis with group decision making. In: KahramanCOtayİ (eds) Fuzzy multi-criteria decision-making using neutrosophic sets. Cham: Springer International Publishing, 2019, pp.543–585.
62.
BolturkEKarasanA. Prioritization of investment alternatives for a hospital by using neutrosophic codas method. J Mul-Valued Log Soft Comput2019; 33: 381–396.
63.
LiYHLiuPDChenYB. Some single valued neutrosophic number heronian mean operators and their application in multiple attribute group decision making. Informatica2016; 27: 85–110.
64.
ErogluHSahinR. A neutrosophic vikor method-based decision-making with an improved distance measure and score function: case study of selection for renewable energy alternatives. Cognit Comput2020; 12: 1338–1355.
65.
SalabunWUrbaniakK. A new coefficient of rankings similarity in decision-making problems. In: 20th Annual international conference on computational science (ICCS), springer international publishing ag, Amsterdam, NETHERLANDS. Amsterdam, Netherlands: IEEE; 2020, pp.632–645.
66.
SałabunWWątróbskiJShekhovtsovA. Are mcda methods benchmarkable? A comparative study of topsis, vikor, copras, and promethee ii methods. Symmetry2020; 12: 1549.
67.
YuanY. Enhanced edas technique for colleges business English teaching quality evaluation based on euclid distance and cosine similarity measure. J Intell Fuzzy Syst2024; 46: 75–89.
68.
TverskyAKahnemanD. Prospect theory: an analysis of decision under risk. Econometrica1979; 47: 263–291.
JiangZWeiGChenX. Edas method based on cumulative prospect theory for multiple attribute group decision-making under picture fuzzy environment. J Intell Fuzzy Syst2022; 42: 1723–1735.
71.
SuYZhaoMWWeiC,et al.Pt-todim method for probabilistic linguistic magdm and application to industrial control system security supplier selection. Int J Fuzzy Syst2022; 24: 202–215.
72.
LinYWangYMChenSQ. Hesitant fuzzy multiattribute matching decision making based on regret theory with uncertain weights. Int J Fuzzy Sys2017; 19: 955–966.
73.
RenHPGaoYXYangTH. A novel regret theory-based decision-making method combined with the intuitionistic fuzzy Canberra distance. Discret Dyn Nat Soc2020; 2020: 9.
74.
JiaXWangXFZhuYF, et al.A two-sided matching decision-making approach based on regret theory under intuitionistic fuzzy environment. J Intell Fuzzy Syst2021; 40: 11491–11508.
75.
TianXLXuZSGuJ,et al.A consensus process based on regret theory with probabilistic linguistic term sets and its application in venture capital. Inf Sci2021; 562: 347–369.
76.
ZhangGQDongYCXuYF. Consistency and consensus measures for linguistic preference relations based on distribution assessments. Inf Fusion2014; 17: 46–55.
77.
DongYCLiCCXuYF,et al.Consensus-based group decision making under multi-granular unbalanced 2-tuple linguistic preference relations. Group Decis Negot2015; 24: 217–242.
78.
WuZBXuJP. Managing consistency and consensus in group decision making with hesitant fuzzy linguistic preference relations. Omega-Int J Manag Sci2016; 65: 28–40.
79.
LiaoHCLiZMZengXJ,et al.A comparison of distinct consensus measures for group decision making with intuitionistic fuzzy preference relations. I J Comput Intell Syst2017; 10: 456–469.
80.
JinFFGargHPeiLD, et al.Multiplicative consistency adjustment model and data envelopment analysis-driven decision-making process with probabilistic hesitant fuzzy preference relations. Int J Fuzzy Syst2020; 22: 2319–2332.
81.
MengFYChenSMZhangSL. Group decision making based on acceptable consistency analysis of interval linguistic hesitant fuzzy preference relations. Inf Sci2020; 530: 66–84.
