Sage Journals: Discover world-class research

Abstract

Innovation is the effective weapon for enterprises to face complicated dynamic environment, and to obtain long-term competitive advantages. Organization innovative climate can promote enterprises’ innovative capability and performance through affecting individual staff attitude, motivation and innovative activities. Therefore, by evaluating organization innovative climate of enterprises with scientific methods, weak points can be discovered and adjusted, so promotion of organization innovative climate is the essence of maintaining enterprises’ innovative energy. Based on domestic and overseas scholars’ research, this paper illustrates new quantitative evaluation method: enterprises’ organization innovative climate on the basis of intuitionistic fuzzy number. Indicators are scored through newly constructed evaluation indicator system. Scores of enterprises’ organization innovative climate are obtained through the calculation of intuitionistic fuzzy number. This model which is more scientific and completed, avoids the awareness of much evaluation information. And it enriched enterprises’ organization innovative climate evaluation theory and methods. At last, the feasibility and practicability of the approach introduced are proved through empirical analysis.

Keywords

Intuitionistic fuzzy number organizational innovative climate evaluation

Get full access to this article

View all access options for this article.

References

Sun

, et al., Open innovation model selection from the perspective of organization capability, Science Research Management37(11) (2016), 35–42.

Bharadwaj

A.S.

, A resource-based perspective on information technology capability and firm performance: An empirical investigation, MIS Quarterly24(1) (2000), 169–196.

Markus

and Frese

, Innovation is not enough: Climates for initiative and psychological safety, Process Innovations, and Firm Performance, Journal of Organizational Behavior24(1) (2003), 45–68.

Oldham

G.R.

and Cummings

, Employee creativity: Personal and contextual factors at work, The Academy of Management Journal39(3) (1996), 607–634.

Edmondson

, Psychological safety and learning behavior in work teams, Administrative Science Quarterly44(2) (1999), 350–383.

West

M.A.

, Sparkling fountains or stagnant ponds: An integrative model of creativity and innovation implementation in work groups, Applied Psychology51(3) (2002), 355–387.

West

M.A.

and Anderson

N.R.

, Innovation in top management teams, Journal of Applied Psychology81(6) (1996), 680–693.

Siegel

S.M.

and Kaemmerer

W.F.

, Measuring the perceived support for innovation in organizations, Journal of Applied Psychology63(5) (1978), 553–562.

Ekvall

, Organizational climate for creativity and innovation, European Journal of Work and Organizational Psychology5(1) (1996), 105–123.

10.

Amabile

T.M.

, et al., Assessing the work environment for creativity, The Academy of Management Journal39(5) (1996), 1154–1184.

11.

Chen

, A review of major instruments assessing climate for creativity and innovation, China Soft Science (7) (2006), 86–95.

12.

Zheng

, Jin

and Ma

, The measurement of organizational innovation climate and its moderating effect in the relationship between employees’ innovation ability and innovation performance, Acta Psychologica Sinica41(12) (2009), 1203–1214.

13.

Sun

, Wang

and Shi

, Empirical study on the difference of different of types of enterprise’s organizational climate for innovation in China’s context, Nankai Business Review11(2) (2008), 42–49.

14.

Liu

, Shi

and Zhang

, A research of innovative climate: Definition, classification and scale development, Studies in Science of Science27(2) (2009), 289–294.

15.

Ren

and He

, The construction of fuzzy synthetic evaluation model for organization innovative climate, Statistics & Decision8(4) (2013), 52–54.

16.

and Chen

, Intuitionistic fuzzy aera set and its application in pattern recognition, Fuzzy Systems and Mathematics29(1) (2015), 134–141.

17.

Guo

and Lv

, The research of intuitionistic fuzzy number, Fuzzy Systems and Mathematics27(5) (2013), 11–20.

18.

Wang

, Li

and Pu

, Defermination for priority ratings of customer requirements based on group multi-granularity linguistic information in product planning, China Mechanical Engineering23(8) (2012), 980–986.

19.

Chen

and Tan

, Handling multicriteria fuzzy decision-making problems based on vague set theory, Fuzzy Sets and Systems67(2) (1994), 163–172.

20.

Wang

and Li

, Intuitionistic random multi-criteria decision-making approach based on score functions, Control and Decision25(9) (2010), 1299–1306.

21.

Víctor

, Pérez-García

, et al., Applied mathematics and nonlinear sciences in the war on cancer, Applied Mathematics and Nonlinear Sciences1(2) (2016), 423–436.

Research on the evaluation of enterprise’s organization innovative climate based on intuitionistic fuzzy number

Abstract

Keywords

Get full access to this article

References