Feedback Avoidance Behavior in the organization is very common but existing research on its formation mechanism is not very clear. Based on the view of Conservation of Resource Theory, we focus on relationship between Perceptions of Organizational Politics and Feedback Avoidance Behavior. The empirical research is based on 290 samples, according to research group of political perception significantly enhanced feedback avoidance; employees’ emotional intelligence reversely adjusts the influence of the Impression Management on Feedback Avoidance Behavior. At the same time, Impression Management Motive plays an intermediary role. To some extent, the results will enrich and deepen the existing research of POP and FAB; there will be implications for management practice.
We often find this kind of phenomenon, in the enterprise when the employee performance is poor, they try to avoid communicating with leader, such as “arranging themselves go out to avoid regulators”, “when encountering the managers choose another route to avoid meeting him” or “asking for leaving or finding a reason to stay at home to avoid the negative news of administrators” and so on. These behaviors are feedback avoidance behavior (FAB). Some studies have found that feedback avoidance can seriously impair performance or even external performance [
Based on the theory of resource preservation [
Based on characteristic of the human social environment in China, the management practices of many organizations produce the phenomenon such as power standard, Guan-xi [
H1: Employee’s perception of organizational politics significantly improves feedback avoidance behavior.
Influenced by the peculiarly implicit culture in China, employees in political atmosphere tend to manage others’ impression of self-presentation [
H2: Impression management motive plays an intermediary role in the employee’s organizational political consciousness and feedback avoidance behavior.
In 1990, Salovey, a psychologist at Yale university and Mayer, a psychologist at the university of New Hampshire firstly proposed the Emotional Intelligence (EI), it is defined as the ability to percept, assess, manage and control themselves or others’ emotions [
H3: Employees’ emotional intelligence negatively mediates the relationship between the management motivation and the feedback avoidance behavior.
The theoretical model is as
The samples in this study are from random sample. The recipients are employees who have subordinate relationships in the enterprises. The questionnaire has indicated that it is only used for research, and we commit that it is completely confidential without disclosing any employee’s personal privacy. A total of 302 copies of questionnaires were collected and the blank and at last, 290 copies of valid questionnaires were obtained. We selected 7 control variables of samples’ information. The details of information are as
Characteristics | value | Frequency (N = 290) | Frequency (%) | Characteristics | value | Frequency (N = 290) | Frequency (%) |
---|---|---|---|---|---|---|---|
Gender | male | 158 | 54.5 | years of working | Less than 2 years | 182 | 62.8 |
female | 132 | 45.5 | 2 to 5 years | 68 | 23.4 | ||
Age | Youger than 21 | 34 | 11.7 | 6 - 10 | 30 | 10.4 | |
21 - 30 | 234 | 80.7 | More than ten years | 10 | 3.4 | ||
31 - 40 | 20 | 6.9 | type of enterprise | State-owned enterprises | 90 | 31.0 | |
41 - 50 | 2 | 0.7 | The private sector | 104 | 35.9 | ||
Older than 50 | 0 | 0.0 | other | 96 | 33.1 | ||
Schooling | Junior high and below | 10 | 3.5 | scale of enterprise | Less than 100 people | 88 | 30.3 |
High school or junior college | 60 | 20.7 | |||||
Undergraduate course | 74 | 25.5 | 100 - 500 people | 76 | 26.2 | ||
Master and above | 146 | 50.3 | |||||
Position | Ordinary employees | 176 | 60.7 | 500 - 1000 people | 48 | 16.6 | |
Primary management | 76 | 26.2 | |||||
Middle manager | 30 | 10.3 | More than 1000 people | 78 | 26.9 | ||
Top management | 8 | 2.8 |
Each variable measuring tool are Likert scale, respondents according to employees’ feeling of POP, FAB, IMM and EI make their choices from “1―totally agree” to “7―completely disagree”.
This study adopted the scales which come from mature scales developed by scholars. In order to meet effective principle, before the formal investigation, the researchers invited English experts translated in double-blind and two-way on foreign scale, and then we modified this scale. After the questionnaire design, the experts and workers were invited to conduct the pre-test, finally the questionnaire was determined by comprehensive suggestions.
1) POP: the domestic scholars Ma Chao, et al. developed the 16 items of the questionnaire, such as “managers communicate with subordinates to improve their image”, “within the company, I should be carefully considered with which people can’t resist”, (1 is completely agree, 7 is completely disagree) the results of the survey of Cronbach Alpha is 0.914.
2) FAB: We use the scale which Moss et al. compiled by the 6 projects [
3) IMM: the internal consistency of the survey results is 0.849.
4) EI: the Wong and Law developed 16 items of the questionnaire, such as “I can well understand my emotions”, “I can always judge their mood from a friend’s behavior” (1 is completely agree, 7 is completely disagree). Cronbach Alpha is 0.904.
In addition, in the measurement, the main control variables are gender, age, level of education, job level, working years, type of enterprise and the enterprise scale. Among them, the men is “1”, women is “2”. There are five levels of age. There are four levels of education, position and working years. The type of enterprise is divided into three categories. Enterprise scale is divided into 4 categories.
This study used spss 20.0 to describe the descriptive statistics of the data, the alpha reliability analysis of the scale, and the correlation analysis between variables. At the same time, the main effect, the mediation effect and the regulation effect are examined. Due to the variable measurement using self-report scale, items were filled out by the same person. We use Harman single factor analysis of each variable to analyze the problem of common method bias. According to the results of the first element which is not rotated explains only about 24.49% of all measurement variance, there is no problem of common method biases.
The scales used in this study are all mature variable measurement scales. Therefore, these scales have good content validity. Generally speaking, the criterion of good performance of the scale is the factor loading is more than 0.5, and the main factor explains that the total variation is greater than 50%. The results of the KMO index and Bartlett spherical test are shown in the
The test results shows that EI, POP, IMM, FAB scale’s KMO index is above 0.7, they achieved the level of significance, so the scale is suitable for factor analysis.
The correlation analysis of the valid data was obtained through SPSS20.0, and the data of
In order to accurately determine the causal relationship between independent variable and the strength of the relationships, in this article, we test the causal
variables | Bartlett spherical test | explaination | |||
---|---|---|---|---|---|
KMO | The approximate chi-square | df | Sig. | Total variance | |
FAB | 0.86 | 1593.05 | 91 | 0.000 | 71.55% |
POP | 0.92 | 1248.52 | 55 | 0.001 | 54.50% |
IMM | 0.85 | 1089.77 | 66 | 0.002 | 65.68% |
EI | 0.88 | 1083.51 | 15 | 0.003 | 75.24% |
Mean | S.D. | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|
1. gender | 1.45 | 0.50 | |||||||||||
2. age | 1.97 | 0.46 | 0.04 | ||||||||||
3. schooling | 3.23 | 0.90 | 0.02 | 0.35** | |||||||||
4. position | 1.55 | 0.79 | −0.03 | 0.17* | 0.11 | ||||||||
5. years of working | 1.54 | 0.82 | −0.02 | 0.42** | −0.29** | 0.31** | |||||||
6. type of enterprise | 2.02 | 0.80 | 0.05 | −0.15 | −0.34** | −0.15 | 0.10 | ||||||
7. scale of enterprise | 2.40 | 1.18 | 0.04 | 0.13 | 0.307** | 0.12 | −0.01 | −0.26** | |||||
8. POP | 3.15 | 1.14 | 0.187* | 0.13 | 0.08 | 0.05 | 0.00 | −0.02 | 0.20* | ||||
9. IMM | 2.38 | 0.89 | 0.05 | 0.24** | −0.05 | 0.07 | 0.23** | −0.01 | 0.09 | 0.43** | |||
10. FAB | 3.41 | 1.31 | 0.19* | 0.31** | 0.06 | −0.03 | 0.18* | 0.04 | 0.21* | 0.72** | 0.59** | ||
11. EI | 2.43 | 0.82 | 0.38** | 0.05 | −0.09 | −0.05 | 0.03 | 0.04 | 0.04 | 0.42** | 0.30** | 0.40** |
Note: through double-tailed test, *indicates that the correlation is significant at 0.05 level; **indicates that the correlation is significant at 0.01.
relationship between the variables through the regression model. In the process of inspection, we control seven possible interference variables, and on this basis, the strength of the causal relationship between the variables was studied. The details are as
From the M3 of
For testing the intermediary role of IMM, we also use the regression equation to do further inspection, on the basis of previous studies (Baronr et al., 1986), can be through four steps. The results is as
As can be seen from the M3 in
Variable Step 1 (control variable) | FAB | ||||
---|---|---|---|---|---|
M1 | M2 | M3 | M4 | M5 | |
gender | |||||
age | 0.16*(0.20) | 0.05(0.21) | 0.14*(0.17) | 0.08(0.18) | 0.07(0.17) |
schooling | 0.30**(0.29) | 0.26(0.28) | 0.17*(0.24) | 0.16(0.24) | 0.18(0.23) |
position | −0.06(0.15) | −0.01(0.15) | −0.02(0.13) | 0.04(0.13) | −0.02(0.12) |
years of working | −0.10(0.14) | −0.09 (0.13) | −0.11(0.12) | −0.10(0.11) | −0.08(0.11) |
type of enterprise | 0.07(0.17) | 0.08(0.16) | 0.02(0.14) | 0.03(0.14) | 0.05(0.13) |
scale of enterprise | 0.09(0.14) | 0.09 (0.13) | 0.09 (0.11) | 0.09(0.11) | 0.11(0.11) |
variable | 0.22**(0.09) | 0.20*(0.09) | 0.17*(0.08) | 0.16(0.08) | 0.17(0.07) |
Step 2 (main effect) | |||||
EI | 0.31***(0.13) | 0.16*(0.12) | 0.17*(0.09) | ||
IMM | 0.54***(0.10) | 0.49***(0.10) | 045***(0.09) | ||
Step 3 (regulation effect) | |||||
EI * IMM | −0.24***(0.07) | ||||
VIF | ≤1.8 | ≤1.8 | ≤1.8 | ≤1.8 | ≤1.8 |
R2 | 0.18 | 0.26 | 0.45 | 0.47 | 0.53 |
ΔR2 | 0.14*** | 0.22*** | 0.41*** | 0.43*** | 0.48*** |
F | 4.41*** | 6.08*** | 13.61*** | 13.01*** | 14.41*** |
Note: the values in the table are normalized regression coefficients, and the brackets are standard error. *P < 0.05, **P < 0.01, ***P < 0.001.
variable | M6:IMM | M7:FAB | M8:FAB |
---|---|---|---|
Step 1 (control variable) | |||
gender | −0.13(0.13) | 0.05(0.15) | 0.06(0.13) |
age | 0.17(0.19) | 0.02(0.20) | 0.14(0.19) |
schooling | −0.13(0.10) | −0.03(0.11) | 0.01(0.10) |
position | −0.01(0.09) | −0.14(0.10) | −0.13(0.09) |
years of working | 0.13(0.11) | 0.13(0.12) | 0.09(0.11) |
type of enterprise | −0.03(0.09) | 0.06(0.10) | 0.07(0.09) |
scale of enterprise | 0.02(0.06) | 0.09(0.07) | 0.08(0.06) |
Step 2 (independent variable) | |||
POP | 0.42***(0.06) | 0.68***(0.07) | 0.55***(0.07) |
Step 3 (mediation variable) | |||
IMM | 0.30***(0.08) | ||
F | 5.89*** | 25.71*** | 30.56*** |
R2 | 0.26 | 0.60 | 0.67 |
ΔR2 | 0.21*** | 0.58*** | 0.65*** |
df | 279 | 279 | 278 |
Note: the values in the table are normalized regression coefficients, and the brackets are standard error. *P < 0.05, **P < 0.01, ***P < 0.001.
positive effect of perception of organizational political on feedback avoidance behavior is significant (r = 0.68, P < 0.001). When the IMM and POP in equation at the same time, positive effect of POP is still significantly (see M8, r = 0.55, P < 0.001), and the role of IMM is also significant (r = 0.30, P < 0.001). At the same time, the third step of the regression coefficient is less than the second step (r3 < r2), it shows that IMM plays partial Intermediary role between POP and FAB. H2 is supported.
This article discussed the relationship between organizational political consciousness and feedback circumvention, the analysis supports the POP has positive effect to the FAB, enriching the research of FAB. It shows that the atmosphere in the organization can lead to FAB. At the same time, the emotional intelligence of the employees decreases the generation of feedback avoidance behaviors. According to related research findings, feedback avoidance behavior has a significant negative effect on performance. At the same time, this paper finds that impression management motivation plays an intermediary role in POP and FAB. This paper explains the mechanism of perception of organizational politics on feedback avoidance behavior. The explanation is that when POP makes employees feel that their resources are at stake, the employees will directly act out the feedback avoidance behavior through the impression management motivation.
At the same time, this paper finds that emotional intelligence has positive effect on the feedback avoidance behavior, but as a regulation variable, the regulation effect of the IMM and FAB is negative. The findings reveal the boundary conditions where POP plays a role in FAB, and employees with high emotional intelligence may avoid feedback to superiors in order to preserve their resources. But when employees manage their own impression because of the organization’s long-term development, high emotional intelligence tends to feedback to employees and superior communication, so as to make benefits to the entire organization rather than individual behavior.
This study found that in the random samples, there are serious POP, so companies can adopt more appropriate management methods, create harmonious and friendly corporate atmosphere. The results suggest that the enterprise should pay attention to cultivate trust among the members of the organization and maintain it, encourage support staff feedback behavior. We should also focus on measuring the impression management motive and emotional intelligence of employees and maintaining the sustainable development of enterprises.
The analysis supports the POP has positive effect to the FAB, explains the mechanism of perception of organizational politics on feedback avoidance behavior and the regulation effect of EI in the IMM and FAB is negative. This study has the following shortcomings: firstly, the limitations of the scale. The scale of this research are mostly come from foreign countries, future research can design scale according to the situation of employees in China. Secondly, this paper uses a cross-sectional study design; this design can only reflect the correlation in certain time point between variables. Thirdly, IMM and POP in the study aren’t divided into several dimensions, such as the difference of impression management motive between positive and negative two aspects. Future studies can refine these two constructs to clarify the relationship.
Lin, R. and Sun, B. (2018) Perceptions of Organizational Politics Influences on Feedback Avoidance Behavior: The Effect of Impression Management Motive and Emotional Intelligence. Journal of Service Science and Management, 11, 26-35. https://doi.org/10.4236/jssm.2018.111003