This study aims to verify the relationship between organisational culture consent and job satisfaction among creative talents using data from China and to provide professionals with insights into the factors to be considered for shaping culture functions, improving job satisfaction and retaining creative talents of innovative organisations.
Related theories of enterprise management are studied to form a logical theoretical system and explain the effect of organisational culture consent on job satisfaction for creative talents. Organisational culture consent is quantified and subsequently examined with job satisfaction based on the data from 2512 respondents who were a part of a survey conducted across 28 companies. The relationship is measured through correlation and regression analyses.
The respondents were found to have a moderate level of job satisfaction. Clan organisation culture was dominant in both the present and preferred cultures for innovative and non-innovative companies; however, organisational culture consent was significantly related to job satisfaction only for creative talents and not for general workers.
A clear and dynamic organisational culture needs to be created to boost creative employees’ flexible aspirations. Diversity of employees should be taken into account to better formulate a reasonable compensation, promotion and motivation mechanism.
This study addresses the research gap in the field of job satisfaction in China by providing a method to quantify organisational culture consent based on data collected by the Organisational Culture Assessment Instrument and to analyse its relationship with job satisfaction among creative talents.
With technology becoming one of the core competitive advantages today (Gao,
This study explores the organisational culture consent through the difference between extant and preferred organisational cultures and investigates its relationship with job satisfaction. Based on a theoretical review and qualitative analysis of the issues, this study proposes relationship hypotheses between organisational culture consent and job satisfaction among creative talents and verifies them with empirical results. The findings underscore the need for managers to pay more attention to the link between organisational culture consent and job satisfaction of creative talents and take necessary measures to retain talent and promote innovation production.
This article is organised as follows: Section 2 reviews relevant theories of organisational culture consent and job satisfaction and briefly examines the relationship between them. Section 3 presents the hypotheses of this study. Using field survey data, this section provides a statistical analysis of the organisational culture and job satisfaction of innovative and non-innovative companies in Nanjing, China. Sections 4 and 5 discuss the findings regarding the relationship between the degree of alignment of perceived and preferred organisational culture and job satisfaction.
Organisational culture consent is the key to measure the success of organisational culture. Improving employee identity is the focus and the main challenge in corporate culture construction. Lee (
Creative talents are generally considered as the core of sustainable innovation development. Previous studies suggested that creative talents can produce innovative output (Wonglimpiyarat,
Creative talents are highly mobile (Shearmur,
Job satisfaction is the extent of contentment an employee obtains from their job, and comprises both affective and cognitive components (Weiss & Cropanzano,
There are two basic ways to measure job satisfaction: the single overall assessment method and the comprehensive scoring method. Single overall assessment involves the responses of an employee regarding their feelings about and towards their job. Comprehensive scoring divides job satisfaction into multiple dimensions in investigating job satisfaction. Investigation includes guided interviews, impressions, structured questionnaires and unstructured questionnaires. In practice, questionnaires are the most convenient and frequently used method. Compiled by Weiss, Dawis and England (
As creative development is currently part of the national development strategy of China, retaining creative employees and enhancing their working enthusiasm has been the subject of intense discussion. Scholars in South Africa found numerous significant relationships between job satisfaction and organisational commitment in innovative companies (Lumley et al.,
There is a strong interaction between organisational culture consent and job satisfaction. Previous empirical studies on job choices suggest that perceived organisational values influence an organisation’s attractiveness, especially to job seekers (Cable & Judge,
The apparatus used to assess organisational culture can also be used to assess organisational culture consent by having respondents complete the questionnaire twice, based on their perceptions and preferences and then comparing the responses (Liu,
The OCAI is a self-reported survey comprising six questions and can be administrated electronically (James-Parks,
The extant literature has established the fact that organisational culture is related to job satisfaction in various work settings. Studies also indicate that dissonance between perceived and preferred organisational culture can influence job satisfaction for employees, especially for creative talents. To verify whether the noted difference in organisational culture consent can predict job satisfaction and to examine whether the relation only exists in the context of creative talents, two hypotheses are proposed:
This study comprised employees of 28 companies in Nanjing as its sample: 14 from the List of Top 50 Innovative Enterprises in Nanjing (Nanjing Municipal Science and Technology Bureau,
This study aimed to quantify the difference between cognised organisational culture and individual preference (IP) for further discerning the correlation between this difference and job satisfaction. As noted above, the OCAI was adopted to assess both perceived and preferred organisational culture within the sample companies. To assess the difference, respondents were first asked to assign a value for each alternative of a question based on their perception of their company’s organisational culture; subsequently, they were asked to assign a value to the same alternatives based on their own preferences. The difference between extant and preferred organisational culture was used as the independent variable, and job satisfaction constituted the dependent variable. As suggested by Kamalanabhan, Sai and Mayuri (
The difference (Diff) between IP and cognised culture (CC) can be described as the sum of the absolute values of the difference between the average results of the options, as shown in
After quantifying the difference, the Pearson correlation analysis was used to reveal the relation between the difference and job satisfaction. One-stage least squares (OLS) regression analysis was adopted to confirm the relation and check whether the difference can be used as a predictor of job satisfaction. Demographic variables were also used as selection variables to run conditional regression tests to examine their contingent effects. Statistical Product and Service Solutions (SPSS) 22.0 was used in this study for data analysis.
The survey data indicated that employee ideas mostly corresponded with those of the company, but some minor differences remained in each respective type. This difference is demonstrated in
Organisational culture cognition difference of creative talents.
Organisational culture cognition difference of general workers.
Descriptive statistics.
Variable | CT |
GW |
||
---|---|---|---|---|
CC | IP | CC | IP | |
Clan | 29.58 | 30.85 | 30.42 | 30.99 |
Adhocracy | 22.45 | 23.32 | 22.35 | 23.16 |
Market | 23.12 | 21.8 | 23.01 | 21.67 |
Hierarchy | 24.84 | 24.03 | 24.23 | 24.18 |
JSA | 2.8673 | - | 2.822 | - |
Diff | 20.244 | - | 18.1812 | - |
Total count | 1105 | - | 1407 | - |
Age 20–30 (%) | 66.43 | - | 57.14 | - |
Age 30–40 (%) | 26.52 | - | 31.98 | - |
Age 40–50 (%) | 4.71 | - | 7.89 | - |
Other ages (%) | 2.35 | - | 2.99 | - |
Male (%) | 62.53 | - | 64.82 | - |
Female (%) | 37.47 | - | 35.18 | - |
College degree (%) | 44.98 | - | 49.68 | - |
Bachelor’s degree (%) | 41.18 | - | 33.90 | - |
Master’s degree (%) | 3.53 | - | 5.12 | - |
PhD (%) | 0.54 | - | 0.85 | - |
Other degrees (%) | 9.77 | - | 10.45 | - |
IP, individual preference; CC, cognised culture; CT, creative talents; GW, general workers; JSA, average job satisfaction.
Pearson correlation analysis was conducted to reveal the relationship between the differences in the perception of organisational culture types and job satisfaction.
Pearson correlations result.
Variable | Category | JSA | Diff | Age | Gender | Education | Corporation | |
---|---|---|---|---|---|---|---|---|
CT | Pearson correlation | 1 | −0.106 |
−0.077 |
−0.162 |
0.070 |
0.006 | |
Sig. two-tailed | - | 0 | 0.011 | 0 | 0.02 | 0.849 | ||
1105 | 1105 | 1105 | 1105 | 1105 | 1105 | |||
GW | Pearson correlation | 1 | −0.021 | −0.131 |
−0.211 |
0.059 | −0.057 | |
Sig. two-tailed | - | 0.643 | 0.004 | 0 | 0.203 | 0.22 | ||
1407 | 1407 | 1407 | 1407 | 1407 | 1407 |
CT, creative talents; GW, general workers; Sig., significance; JSA, average job satisfaction; Diff, difference.
, Correlation is significant at the 0.05 level (two-tailed);
, Correlation is significant at the 0.01 level (two-tailed).
One-stage least squares regression analysis was conducted to verify the fact that the difference and other control variables could be used as predictors of job satisfaction. As
Linear regression result of creative talents and general workers.
Variable | JSA | Coefficient | Standard error | 95% confidence | Interval | Sig. | |||
---|---|---|---|---|---|---|---|---|---|
CT | Diff | −0.004 | 0.001 | −3.547 | 0 | −0.249 | −0.076 | ||
Constant | 2.958 | 0.038 | 78.005 | 0 | 3.103 | 4.321 | |||
0.011 | - | - | - | - | - | - | |||
Akaike crit. (AIC) | 123.306 | - | - | - | - | - | - | ||
Number of observations | - | - | - | - | 1105 | - | - | ||
Bayesian crit. (BIC) | - | - | - | - | 134.62 | - | - | ||
GW | DIFF | −0.001 | 0.002 | −0.464 | 0.643 | −0.249 | −0.076 | - | |
Constant | 2.84 | 0.059 | 47.769 | 0 | 3.103 | 4.321 | |||
0 | - | - | - | - | - | - | |||
Akaike crit. (AIC) | 123.306 | - | - | - | - | - | - | ||
Number of observations | - | - | - | 1407 | - | - | - | ||
Bayesian crit. (BIC) | - | - | - | 134.62 | - | - | - |
CT, creative talents; GW, general workers; Sig., significance; JSA, average job satisfaction; Diff, difference; crit., criteria.
,
,
,
In summary, the results indicate that employees of the sampled companies evaluated their job satisfaction at an upper middle level. The results also show that clan organisation culture was dominant. The findings support the fact that the difference between cognised or extant organisational culture cognition and preferred organisational culture is negatively correlated to job satisfaction. The higher the level of difference, the lower the organisational culture consent and job satisfaction. As this relationship is only significant for creative talents, H1 and H2 are verified.
To further explore whether the control variables would affect the relation between organisational culture consent and job satisfaction in the regression model for creative talents, the study takes the basic personal information results as selection variables to build conditional regression models. By building these conditional regression models, this study aims to examine the impact of every alternative of the mentioned control variables.
Conditional regression result of creative talents (age).
Model | Variable | Unstandardised coefficients |
Standardised coefficients: Beta | Sig. | ||
---|---|---|---|---|---|---|
Standard error | ||||||
A1 |
(Constant) | 3.018 | 0.047 | - | 64.679 | 0 |
Diff | −0.004 | 0.002 | −0.102 | −2.781 | 0.006 | |
A2 |
(Constant) | 2.828 | 0.073 | - | 38.564 | 0 |
Diff | −0.003 | 0.002 | −0.09 | −1.547 | 0.123 | |
A3 |
(Constant) | 2.493 | 0.164 | - | 15.219 | 0 |
Diff | 0 | 0.006 | 0.011 | 0.074 | 0.941 | |
A4 |
(Constant) | 3.518 | 0.199 | - | 17.711 | 0 |
Diff | −0.024 | 0.008 | −0.538 | −3.126 | 0.005 |
Note: A1–4 dependent variable: JSA.
Sig., significance; Diff, difference.
, Selecting only cases for which age = 1;
, Selecting only cases for which age = 2;
, Selecting only cases for which age = 3;
, Selecting only cases for which age = 4.
Conditional regression result of creative talents (gender).
Model | Variable | Unstandardised coefficients |
Standardised coefficients: Beta | Sig. | ||
---|---|---|---|---|---|---|
Standard error | ||||||
G1 |
Constant | 3.08 | 0.045 | - | 67.805 | 0 |
Diff | −0.005 | 0.001 | −0.12 | −3.177 | 0.002 | |
G2 |
Constant | 2.762 | 0.066 | - | 41.813 | 0 |
Diff | −0.005 | 0.002 | −0.096 | −1.961 | 0.051 |
Note: Dependent variable: JSA.
Sig., significance; Diff, difference.
, Selecting only cases for which gender = 2;
, Selecting only cases for which gender = 2.
From
Conditional regression result of creative talents (educational level).
Model | Variable | Unstandardised coefficients |
Standardised coefficients: Beta | Sig. | ||
---|---|---|---|---|---|---|
Standard error | ||||||
E1 |
Constant | 2.933 | 0.057 | - | 51.218 | 0 |
Diff | −0.002 | 0.002 | −0.039 | −0.87 | 0.385 | |
E2 |
Constant | 2.951 | 0.059 | - | 50.352 | 0 |
Diff | −0.008 | 0.002 | −0.183 | −3.967 | 0 | |
E3 |
Constant | 2.668 | 0.198 | - | 13.451 | 0 |
Diff | −0.01 | 0.006 | −0.272 | −1.723 | 0.093 | |
E4 |
Constant | 1.405 | 0.858 | - | 1.636 | 0.177 |
Diff | 0.086 | 0.116 | 0.35 | 0.746 | 0.497 | |
E5 |
Constant | 3.309 | 0.099 | - | 33.5 | 0 |
Diff | −0.002 | 0.003 | −0.062 | −0.644 | 0.521 |
Note: Dependent variable: JSA.
Sig., significance; Diff, difference.
, Selecting only cases for which education = 1;
, Selecting only cases for which education = 2;
, Selecting only cases for which education = 3;
, Selecting only cases for which education = 4;
, Selecting only cases for which education = 5.
Conditional regression result of creative talents (corporation classification).
Model | Variable | Unstandardised coefficients |
Standardised coefficients: Beta | Sig. | ||
---|---|---|---|---|---|---|
Standard error | ||||||
C1 |
(Constant) | 2.758 | 0.244 | - | 11.316 | 0 |
Diff | 0 | 0.008 | 0.002 | 0.013 | 0.99 | |
C2 |
(Constant) | 2.895 | 0.184 | - | 15.762 | 0 |
Diff | −0.008 | 0.006 | −0.16 | −1.306 | 0.196 | |
C3 |
(Constant) | 3.267 | 0.126 | - | 25.886 | 0 |
Diff | −0.013 | 0.003 | −0.397 | −3.966 | 0 | |
C4 |
(Constant) | 2.995 | 0.09 | - | 33.431 | 0 |
Diff | −0.004 | 0.003 | −0.112 | −1.384 | 0.169 | |
C5 |
(Constant) | 2.957 | 0.088 | - | 33.703 | 0 |
Diff | 0.001 | 0.003 | 0.017 | 0.242 | 0.809 | |
C6 |
(Constant) | 2.684 | 0.118 | - | 22.773 | 0 |
Diff | 0.002 | 0.004 | 0.048 | 0.505 | 0.615 | |
C7 |
(Constant) | 2.73 | 0.119 | - | 22.986 | 0 |
Diff | −0.005 | 0.004 | −0.123 | −1.25 | 0.214 | |
C8 |
(Constant) | 3.012 | 0.07 | - | 42.793 | 0 |
Diff | −0.005 | 0.002 | −0.106 | −1.938 | 0.054 |
Note: Dependent variable: JSA.
Sig., significance; Diff, difference.
, Selecting only cases for which corporation = 1;
, Selecting only cases for which corporation = 2;
, Selecting only cases for which corporation = 3;
, Selecting only cases for which corporation = 4;
, Selecting only cases for which corporation = 5;
, Selecting only cases for which corporation = 6;
, Selecting only cases for which corporation = 7;
, Selecting only cases for which corporation = 8.
The results of this study show that employees in Nanjing are generally satisfied with their work. Clan culture was the dominant organisational culture type. Hierarchy culture is the second dominant type, which indicates that employees are used to a well-structured institutional system. Market culture is also influential for creative talents, suggesting that innovative industries are open to changes and are highly competitive. This study found no drastic difference between the cognised and preferred organisational culture. However, deeper scrutiny reveals some differences, and creative talents have less consent for organisational culture than GW. This may be because creative talents have more practical skills and innovative minds, which help them be more individualistic. Their skill set and capability make creative talents more competitive in their careers; thus, they are not as keen as GW to blend in an organisation. They could rely on their ideas to become self-dependent entrepreneurs (Audretsch & Belitski,
The results of this study validate its hypotheses. Subsequently, management personnel can use these results as a reference for future management practice. Firstly, companies in innovative industries need to improve both the physical environment and organisational culture of their employees to enhance their job satisfaction. Secondly, these companies need to create a clear and appropriate organisational culture, which is dynamic to the companies’ context. Constantly tailoring the culture to the aspirations of employees is vital to its efficacy, as it actively shapes an innovative organisational culture that will encourage bold and creative behaviour among employees. Thirdly, the characteristic diversity of creative employees should not be neglected. As employees have different backgrounds, their evaluation of organisational culture and job satisfaction may vary. Accordingly, managers should be aware of such diversity, conduct training and counselling for different groups, listen to all opinions and adjust the current organisational culture accordingly to improve employees’ sense of identity and form a more tolerant atmosphere. Fourthly, the results of this study can help formulate a reasonable compensation, promotion and motivation mechanism. Compensation is extremely important to employees and reflects their value to the company. While salary is an important factor in determining job satisfaction, the relationship between remuneration and job satisfaction is not determined by an employee’s total income. Promotion will bring positive changes in management power, social status, job content and remuneration. Providing fair promotion opportunities and self-development programmes can have a positive impact on employees’ job satisfaction.
By examining organisational culture and job satisfaction in innovative and general companies, this study develops and tests a method of quantifying the difference between extant and preferred organisational culture and the impact of this difference on job satisfaction. The findings are expected to help Chinese innovative companies attract and retain creative talents. The results suggest that there is a gap between extant and preferred organisational culture within the sampled companies, and it impacts job satisfaction in the form of organisational culture consent. While Chinese innovative companies, employers and employees are becoming more aware of the concept and presence of organisational culture, its importance and capabilities are way beyond what is currently comprehended. The findings can help managers address this oversight, realise the importance of creative talents’ organisational culture consent and pay greater attention to organisational culture improvement. Identifying the influence of organisational culture consents on job satisfaction is a good start for innovative companies in China to better treat and support creative talents. If provided with a more dynamic and tolerant cultural environment, creative talents may have higher organisational culture consent, which encourages them to stay in their jobs and work more efficiently. Such a virtuous cycle is a good foundation for sustainable innovative development.
This study has two limitations. Firstly, quantifying the difference between extant and preferred organisational culture constitutes the foundation of this study as it allows the analysis to move beyond theoretical discussion. However, the data collected from the sampled companies showed differences that are not particularly prominent. This could be because the survey was disseminated by the company’s human resources manager, and this ‘top-down’ procedure resulted in anonymity concerns among the sampled employees. Secondly, this study added only demographic variables as control variables. Further influencing factors, such as work stress and personality traits, can be added for multiple comparisons and correlation analyses.
The authors thank Editage (
The authors declare that they have no financial or personal relationships that may have inappropriately influenced them in writing this article.
L.Z. came up with the idea and methods, dispatched the survey, analysed the results and drafted the manuscript. Y.W. helped in composing the survey and drafted part of the literature review.
This article followed all ethical standards for research without direct contact with human or animal subjects.
This research received no specific grant from any funding agency in the public, commercial or not-for-profit sectors.
The data that support the findings of this study are available from the corresponding author, L.Z., upon reasonable request.
The views and opinions expressed in this article are those of the authors and do not necessarily reflect the official policy or position of any affiliated agency of the authors.