Combined with the relevant theories and frameworks, this study constructs evaluation indicator and index system of organization quality specificity immune evolution ability. On the basis, this study uses the intuitively fuzzy multi-attribute decision making method based on evidential reasoning to carry out empirical analysis of organizational quality specificity immune evolution ability, empirical analysis data derive from the research objects of relevant experts, typical and representative large-sized manufacturing enterprises. The empirical analysis results indicate that the intuitively fuzzy multi-attribute decision making method based on evidential reasoning considers subjective and objective factors, which integrates the intuitively fuzzy information and gives out the corresponding decision according to the evaluation value. It is also useful, effective, feasible and operable to take the intuitively fuzzy multi-attribute decision making method based on evidential reasoning to evaluate, select and make decision choice on the best and optimal partner and investee object in multi-attribute group decision making according to organization quality specificity immune evolution ability, and give out orders of all partners and investees. The research methods and results can further improve the organization quality specificity immune efficiency, identify organization quality problems and defects, improve organization quality performance, and maintain organization health, which also provide new decision-making method for the multi-attribute groups of organization quality specificity immune evolution ability.
NairA., Meta-analysis of the relationship between quality management practices and firm performance-Implications for quality management theory development, Journal of Operations Management24(6) (2015), 948–975.
2.
ChooA.S., LindermanK.W. and SchroederR.G., Method and context perspectives on learning and knowledge creation in quality management, Journal of Operations Management25(4) (2007), 918–931.
3.
FlynnB.B., SchroederR.G. and SakakibaraS., The impact of quality management practices on performance and competitive advantage, Decision Sciences26(5) (1995), 659–691.
4.
LiB.B., JiangY. and NanA., An empirical study on the relationship between quality management practice and enterprise performance in the post industrial era, Technology Progress and Countermeasures (4) (2014), 74–79.
5.
SzmidtE. and KacprzykJ., Entropy for intuitionistic fuzzy sets, Fuzzy Sets and Systems118(3) (2001), 112–122.
6.
ChenG., ZhaoY. and SuB., Raw material inventory optimization for MTO enterprises under price fluctuations, Journal of Discrete Mathematical Sciences and Cryptography20(1) (2017), 255–270.
7.
HuberG.P., Organization learning: the contributing processes and the literature, Organization Science2(1) (1991), 88–115.
8.
WeiG.W., Some induced geometric aggregation operators with intuitionistic fuzzy information and their application to group decision making, Applied Soft Computing10 (2010), 423–431.
9.
ChengH., Chinese economic growth has shifted from “speed age” to “quality age”, Macro Quality Research (4) (2014), 1–12.
10.
KaynakH. and HartleyJ.L., A replication and extension of quality management into the supply chain, Journal of Operations Management26(4) (2008), 468–489.
11.
KaynakH., The relationship between total quality management practices and their effects on firm performance, Journal of Operations Management21(4) (2003), 405–435.
12.
XuH., JiC.L., LiJ., et al., Research on the mechanism of risk response of technology-SMEs based on the organizational immunization perspective, Management World (2) (2011), 142–154.
13.
ZhaoJ.B., The mechanism of the impact of organizational cognition on immune behavior and organizational health - A case study of A enterprise, Economic Management35(12) (2013), 54–64.
14.
JiangJ., LiX., XingL.N. and ChenY.W., System risk analysis and evaluation based on fuzzy evidence reasoning, System Engineering Theory and Practice33(2) (2013), 529–537.
15.
WalshJ.P. and UngsonG.R., Organizational memory, Academy of Management Review16(1) (1991), 57–91.
16.
HoughJ.R. and WhiteM.A., Scanning actions and environmental dynamism: Gathering information for strategic decision making, Management Decision42(6) (2004), 781–793.
17.
WuJ., Study on the mechanism of emergency response ability of safety production based on the theory of immune genetic evolution, Harbin Engineering University, (2013).
18.
ZadehL.A., Fuzzy sets, Information and Control8(3) (1965), 338–353.
19.
HuL.F., ChuJ.T. and LiQ., An evidential reasoning method of multi-attribute decision making based on projection, Control and Decision30(2) (2015), 261–265.
20.
ShiL.P. and LiuQ., Evaluation of the maturity of enterprise quality management, Statistics and Decision52(3) (2015), 183–185.
21.
ShiL.P. and LiuQ., Quality defect management ability evaluation of enterprises based on projection pursuit and optimal segmentation-Explanatory framework of medical analogy and metaphor thought, Journal of Applied Sciences13(10) (2013), 1833–1837.
22.
ShiL.P., LiuQ. and TangS.L., The path of quality performance improvement based on the perspective of tissue-specific immunity-An Empirical Analysis of projection pursuit and forced entry method, Nankai Management Review15(6) (2012), 123–134.
23.
ShiL.P., LiuQ. and TengY., The path to improve the quality performance based on OSI-PP-Enter: A theoretical framework and empirical analysis, Journal of Management Engineering29(3) (2015), 152–163.
24.
ShiL.P., LiuQ., WuK.J. and DuZ.W., Function mechanism of the consistency of the building elements of quality specific immunity on quality performance-based on the empirical analysis of PP, fit method and hierarchical regression analysis, Industrial Engineering and Management18(3) (2013), 84–91.
25.
ShiL.P., LiuQ., JiaY.N. and YuX.Q., Quality performance improvement path optimization based on Projection Pursuit-RAGA-NK-GERT-The explanation framework of the organization quality specific immunity and product life cycle as the leading logic, Operational Research and Management24(4) (2015), 188–197.
26.
ShiL.P., LiuQ., JiaY.N. and YuX.Q., Research on the relationship between network strength, TQM practice and organizational learning-Expand the potential path of triggering organizational learning, Management Review26(5) (2014), 48–60.
27.
VaizM.E. and AltinayZ., Reaching out merits of information technology: Conflict management in schools, Eurasia Journal of Mathematics Science and Technology Education13(7) (2017), 2979–2992.
28.
ZhangM.J. and WangY.M., Mixed evidence reasoning uncertainty decision method based on the extended principle, Control and Decision30(4) (2015), 670–676.
29.
JiangP., SuQ. and DangJ.X., Quality management practices and firmperformance influencemechanismof different types of empirical research, China Soft Science (7) (2009), 134–143.
30.
LeightonP., Meta-regulation in practice: Beyond the normative views of morality and rationality, Journal of Management & Organization23(6SI) (2017), 907–908.
31.
LvP. and WangY.H., Organizational immune behavior and Research mechanism, Journal of Management6(5) (2009), 607–614.
32.
LvP. and WangY.H., Research on enterprise adaptability based on organizational immune perspective, Scientific Research Management29(1) (2008), 164–171.
33.
LvP. and WangY.H., The construction and operation mechanism of the organization immune system - A case study of Dayawan nuclear power plant, Science and Technology Management28(5) (2007), 151–156.
34.
LvP., An empirical study of the influence mechanism of organizational immune behavior on organizational performance, Science and Science and Technology Management32(7) (2011), 15–23.
35.
SunP.S., Study on the relationship between quality management and quality performance of supply chain from the perspective of immune system, Jilin: Doctoral Dissertation of Jilin University, 2012.
36.
LiuQ., DuanL.J., YangW., WangS. and ShiL.P., Relationships among prerequisite variables, organizational quality immunity and health, International Journal of Simulation: Systems, Science and Technology17(14) (2016), 16.1–16.6.
37.
LiuQ., ShiL.P. and SuY., Identify the factors affecting team quality defect management-An empirical analysis based on the perspective of metaphor analogy medical, Modern Finance and Economics (11) (2015), 71–84.
38.
LiuQ., ShiL.P. and SuY., The factors influencing of the quality defect management and function mechanism of the quality defect management on quality performance: research status and trends, Technology and Economy34(7) (2015), 92–99.
39.
LiuQ., ShiL.P., ChenW. and SuY., Identification of influence factors of team quality defect management and the extraction of micro and macro fuzzy rules based on the SYT-FR-CA: Theoretical framework based on the leading logic of medical immunity and medical evidence, Industrial Engineering and Management21(3) (2016), 110–117.
40.
LiQ.X., SunP.S. and JingF.H., Research on supply chain quality management model based on the perspectives of immunity, Commercial Research (7) (2010), 72–76.
41.
ZhangQ.X., The role of quality management practices in enterprise innovation performance: The mediating effect of innovative mental models, Zhejiang: Doctoral Dissertation of Zhejiang University, 2012.
42.
DaftR.L., SormunenJ. and ParksD., Chief executive scanning, environmental characteristics, and company performance: an empirical study, Strategic Management Journal9(2) (1988), 123–139.
43.
BealR.M., Competing Effectively: Environmental Scanning, Competitive Strategy, and Organizational Performance in Small Manufacturing Firms, Journal of Small Business Management38(1) (2000), 27–47.
44.
RuiS. and VossC.A., Quality management re-visited: a reflective review and agenda for future research, Journal of Operations Management20(1) (2002), 91–109.
RahmanS.U. and BullockP., Soft TQM, hard TQM, and organisational performance relationships: An empirical investigation, Omega33(1) (2005), 73–83.
47.
JefferisT.C. and TheronL.C., Promoting resilience among Sesotho-speaking adolescent girls: Lessons for South African teachers, South African Journal of Education37(3) (2017), 1391–1402.
48.
GaoW., FarahaniM.R., AslamA. and HosamaniS., Distance learning techniques for ontology similarity measuring and ontology mapping, Cluster Computing-The Journal of Networks Software Tools and Applications20(2SI) (2017), 959–968.
49.
XiongW. and FengX.B., An empirical study on the relationship between quality management practices and performance based on enterprise characteristic variables, Journal of Zhejiang University (Humanities and Social Sciences Edition) (11) (2011), 1–13.
50.
DaiW.F., ZhongQ.Y. and HeD.D., Intuitionistic fuzzy multiple attribute group decision making method based on evidence reasoning, Operations Research and Management Science26(9) (2017), 1–6.
51.
FengX.B. and ChenL.Q., Research on relationships among quality management practice, organizational learning and enterprise performance, Management Review28(1) (2016), 31–41.
52.
ZhangX.H., Effect of quality management practices on organizational performance: From the perspective of market oriented, Zhejiang: Master Degree Thesis of Zhejiang University, 2015.
53.
QiaoX.J. and LiY.J., Risk analysis model of sudden events based on fuzzy evidence reasoning, System Engineering Theory and Practice35(10) (2015), 2657–2666.
54.
GuoX.S., Research on the impact of quality management practice on project quality performance in construction enterprises, Chongqing: Chongqing University Master Degree Thesis, 2016.
55.
PanX.W. and WangN., Research on the path and the way to enhance the immune response of enterprise quality, Journal of Chongqing Jiaotong University (Social Science Edition)15(4) (2015), 57–60.
56.
ZhangY. J., MaP.J., SuX.H., ZhangC.P., Interval intuitionistic fuzzy multiple attribute decision-making under the condition of attribute weight uncertainty, Automation Journal38(2) (2012), 220–228.
57.
JiangY., An Empirical Study on the relationship between quality management practice and enterprise performance in manufacturing enterprise, Chongqing: Chongqing University Master Degree Thesis, 2013.
58.
QinY., LouY., ZhaoY. and ZhangJ., Research on relationship between tourism income and economic growth based on meta-analysis, Applied Mathematics & Nonlinear Sciences3(2018), 105–114.
59.
QinY., LuoY., LuJ., YinL. and YuX., Simulation analysis of resource-based city development based on system dynamics: A case study of Panzhihua, Applied Mathematics & Nonlinear Sciences3(1) (2018), 115–126.
60.
XieY., GeS., JiangS., LiuZ., ChenL., WangL., ChenJ., QinL. and PengW., Study on biomolecules in extractives of Camellia oleifera fruit shell by GC-MS, Saudi Journal of Biological Sciences25(2) (2018), 234–236.
61.
LiuZ., FengJ. and WangJ., Effects of the sharing economy on sequential innovation products, Complexity (2019), 3089641.
