Motivate or suppress: The dual effects of leader bottom-line mentality on employee innovation behavior

doi:10.21203/rs.3.rs-5283142/v1

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Research Article

Motivate or suppress: The dual effects of leader bottom-line mentality on employee innovation behavior

https://doi.org/10.21203/rs.3.rs-5283142/v1

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Background

In the VUCA era, employee innovation behavior is critical to a enterprise success. In China's high power distance and collectivist culture, employee innovation behavior is often influenced by leadership authority, leading to a division between proactive and reactive innovation behavior, with each having a different effect on innovation performance. Innovation is influenced not only by leadership type but also by leadership mindset. As a unidimensional approach focused on bottom-line profits while neglecting other important factors, leader bottom-line mentality (LBLM) and its effect on employee innovation behavior, especially on proactive and reactive innovation, has yet to be thoroughly explored. Understanding this dual influence can help balance short-term profit goals with long-term innovation development.

Methods

This study employed a two-stage survey method, conducting a questionnaire survey with employees from 13 innovation-driven enterprises, ultimately collecting 351 valid responses. Using SPSS and MPLUS software, the data were analyzed through reliability and validity tests, confirmatory factor analysis, descriptive statistics, and linear regression to validate the proposed research hypotheses.

Results

the study finds that LBLM has a significantly negative effect on employee proactive innovation behavior but a positive effect on reactive innovation behavior. Moreover, employees' willingness to take risks mediates the relationship between LBLM and employee innovation behavior. At the same time, intrinsic work values negatively moderate the relationship between LBLM and Willingness to take risks, enhancing proactive innovation behavior and reducing reactive innovation behavior. On the other hand, extrinsic work values positively moderate the relationship, enhancing reactive innovation behavior and reducing proactive innovation behavior.

Conclusion

As a unidimensional mentality, LBLM has a double-edged effect on employee innovation behavior: it positively predicts reactive innovation behavior while negatively predicting proactive innovation behavior. However, this effect is moderated by work values; intrinsic work values weaken the double-edged effect, whereas extrinsic work values enhance its influence.

Leader bottom-line mentality

Willingness to take risks

Work values

Proactive innovation behavior

Reactive innovation behavior

In the VUCA era, innovation is a key factor for the survival and development of enterprises [1]. Since employees are the core driving force of organizational innovation, effectively motivating their innovation behavior is crucial to the success of enterprise innovation [2]. In a society like China, characterized by high power distance and a collectivist orientation, employee innovation behavior are often influenced by organizational and leadership authority, which tends to lead to obedience to authority. Furthermore, a common phenomenon in Chinese enterprises is "policy-driven" innovation, where enterprises, in response to national policy requirements, often require employees to innovate in unsuitable fields or positions, leading to poor innovation outcomes. For example, Huawei once responded to the national new energy strategy by investing substantial resources in developing solar cell technology. Although this aligned with policy directions, some projects did not achieve expected commercial success due to insufficient market demand and limited technological applications. This policy-driven innovation, though aligned with national strategies, did not fully match the enterprise core business, resulting in resource waste and low innovation efficiency. In this context, some scholars have pointed out that employee innovation behavior in the Chinese organizational environment can be divided into two distinct forms: proactive innovation behavior and reactive innovation behavior [3]. Proactive innovation behavior refers to employee voluntary innovation efforts, driven by intrinsic motivation, where they are willing to take risks that may arise during the innovation process. This behavior is considered extra-role behavior, encouraging employees to actively explore unknown areas, thus enhancing innovation performance [4]. In contrast, reactive innovation behavior occurs under the pressure of performance expectations or leadership authority, where employees are forced to innovate. This is considered in-role behavior, which often leads to inefficiencies and resource waste, negatively impacting innovation performance [5]. Although reactive innovation behavior is prevalent in Chinese enterprises, existing research primarily focuses on proactive innovation behavior, neglecting the presence and effect of reactive innovation behavior. Studying the different mechanisms of these two forms of innovation is crucial for fully understanding innovation phenomena in Chinese enterprises. To enhance overall innovation performance, enterprises need to not only motivate employee proactive innovation behavior but also deeply explore and manage reactive innovation behavior to optimize innovation management strategies and maximize innovation performance.

Employee innovation behavior is closely related to leadership, which serves as a critical situational factor [6–8]. Although previous research has explored the effect of different leadership styles on employee innovation behavior, focusing solely on leadership styles does not fully reveal the mechanisms by which leadership influences innovation. A leader thinking model is also a key factor influencing employee attitudes and behavior [9]. Among these, leader bottom-line mentality (LBLM), a unidimensional thinking model focused on ensuring organizational bottom-line goals (such as financial performance), often neglects other important aspects of the organization [10]. This mentality at the individual level may lead to a series of negative outcomes, such as increasing employee social inhibition behavior, unethical behavior, knowledge hiding, and silence [10–12], while also reducing employee performance [13]. However, some studies have shown that LBLM can lead to positive outcomes, such as improving employees' service quality, work focus, and task performance [11, 14]. Although extensive research has explored the effects of LBLM on employees, the relationship between this mentality and employee innovation behavior remains underexplored, especially in the context of China. This gap limits our theoretical understanding and ability to assess whether LBLM has a negative or positive effect on employee innovation behavior, thereby preventing organizations from drawing practical insights for innovation management. Given these theoretical gaps and practical needs, it is crucial to investigate the mechanisms through which LBLM influences employee innovation behavior, particularly with regard to the differentiated mechanism on proactive innovation behavior and reactive innovation behavior in the Chinese context.

The effect of leadership on employee innovation behavior is not merely a direct result; it involves a more complex process of psychological and behavioral evolution process [15]. According to the "Stimulus-Organism-Response" (SOR) model, the pathway from leadership to employee innovation behavior requires the mediation of psychological factors such as cognition, emotion, and motivation [16]. Existing research suggests that leaders with a strong bottom-line mentality are primarily focused on ensuring the achievement of bottom-line goals and tend to avoid high-risk decisions, resulting in a lower willingness to take risks. Within the framework of social information processing theory, leaders, as key sources of social information, convey their attitudes, expectations, and standards to employees, providing employees with corresponding information cues [17], thereby influencing their risk perception and behavioral choices. When employees receive risk-averse signals from their leaders, they are likely to reduce their own willingness to take risks. Willingness to take risks (WTR), as an important intrinsic motivation and proximal intention for innovation behavior, plays a critical role in the innovation process. Dewett [18] argues that WTR is a key factor in stimulating employee innovation behavior, especially in proactive innovation behavior. In this form of innovation behavior, employees are required to make risky decisions in highly uncertain situations and bear potential failures. In contrast, reactive innovation behavior typically occurs within the framework of tasks assigned by the organization, involving relatively lower risk [5]. Thus, it can be inferred that the risk-averse tendency of LBLM may suppress employees' WTR, thereby reducing the occurrence of proactive innovation behavior, while indirectly promoting the emergence of reactive innovation. Therefore, employees' willingness to take risks may serve as an important mediating variable in the relationship between LBLM and employee innovation behavior.

Individual intrinsic motivation at work is often influenced by one’s understanding of the value or significance of the job, which is shaped by work values [19, 20]. As a core component of self-concept, work values are defined as the outcomes individuals hope to achieve through work [21], representing people’s expectations of their job [22]. Work values are often divided into two dimensions: intrinsic and extrinsic. Intrinsic work values emphasize non-material rewards, focusing on psychological satisfaction, such as recognition from others and self-contribution, while extrinsic work values emphasize material rewards, such as salary and promotion [23].Employees with strong intrinsic work values often pursue autonomy, growth, and creativity at work and are inclined to take risks in innovation [24]. For these employees, innovation—especially related to organizational change and continuous development—is seen as part of their job. Thus, even if LBLM attempts to limit innovation by conveying risk-averse signals, employees with strong intrinsic values will still maintain high levels of innovation motivation and be willing to take corresponding risks [25]. These employees exhibit a high degree of openness and responsibility toward organizational innovation, and they are unlikely to abandon proactive innovation even in the face of conservative leadership. In contrast, employees with extrinsic work values are more focused on the external rewards their work brings, such as financial benefits and promotions [23]. They tend to view work as a tool to fulfill material needs and lack intrinsic motivation for innovation. For these employees, innovation is often perceived as “extra work”. LBLM strengthens their tendency to avoid risks, as innovation that diverges from bottom-line goals may consume organizational resources and increase uncertainty regarding their personal financial benefits. These employees believe that achieving bottom-line goals is more likely to ensure their economic interests, leading them to follow leadership directives and avoid risky innovation. As a result, LBLM further reduces the likelihood of these employees engaging in proactive innovation, encouraging them instead to engage in safer, reactive innovation activities. In this way, work values, by moderating WTR, ultimately influence the differential effect of LBLM on employee innovation behavior.

In summary, this paper will explore the differentiated effect of LBLM on employee innovation behavior by distinguishing between proactive and reactive innovation behavior within the specific organizational context of China. This approach not only helps deepen our understanding of the complexity of innovation but also provides a new research perspective for enterprises to optimize their innovation management strategies.

Theoretical analysis and hypotheses

LBLM and employee innovation behavior

In Western research, employee innovation behavior is often viewed as an individual's proactive and voluntary behavior [26]. However, this mainstream innovation theory falls short when explaining the widespread phenomenon of "reactive" innovation behavior in the Chinese context. Specifically, in the context of "state-driven" innovation, various industries have witnessed a surge of innovation activities driven by policies and regulations, but these innovations often fail to achieve the expected performance. As a result, scholars have classified employee innovation behavior in Chinese organizations into proactive innovation behavior and reactive innovation behavior [3]. Proactive innovation behavior refers to employees voluntarily and actively engaging in innovation activities, bravely facing potential challenges during the innovation process [27]. This type of innovation is characterized by spontaneity, proactivity, and risk-taking. In contrast, reactive innovation behavior refers to innovation that employees undertake involuntarily under external pressure or organizational innovation targets [3], which is marked by non-identification, reactive responses, and obligation. Proactive innovation behavior extends beyond an employee's job scope, often considered "extra-role" behavior, with core traits of spontaneity, autonomy, and voluntariness. Employees engage in proactive innovation typically out of a high level of commitment to the organization, curiosity about the innovation task, and a strong passion for their work, showcasing a willingness to take risks that surpass organizational expectations [3; 28]. However, under the influence of strong LBLM, employees tend to recognize that ensuring the achievement of the organization's bottom-line goals is the optimal choice within their job scope [29]. Since bottom-line goals often compete with other priorities for resources [30], employees are likely to be cautious about engaging in innovation activities unrelated to these goals. LBLM encourages employees to focus on achieving bottom-line objectives, and taking proactive risks to explore innovations unrelated to these goals might be seen as an unreasonable use of organizational resources. As a result, employees’ investment in innovation may be inhibited unless the innovation aligns with the bottom-line goal or when employees must creatively solve problems to complete complex and uncertain tasks [31]. Therefore, this study proposes the following hypothesis:

H₁

LBLM negatively predicts employee proactive innovation behavior.

H₂

LBLM positively predicts employee reactive innovation behavior.

The mediating effect of WTR

Willingness to take risks (WTR) refers to an individual's intrinsic psychological motivation to accept high risks, potential losses, and possible negative outcomes in order to achieve favorable results for the organization, such as improving innovation performance or capturing market opportunities [32]. Leaders with a strong bottom-line mentality often focus on ensuring the achievement of bottom-line goals and tend to have a heightened awareness of risk avoidance. For matters beyond the bottom-line goals, these leaders often adopt a cautious or evasive attitude, exhibiting a lower willingness to take risks.

According to social information processing theory, leaders, as one of the critical sources of social information within an organization, convey clear messages through their attitudes, expectations, and standards [17]. When employees perceive that their leaders are focused on ensuring the bottom-line goals and avoiding risks, they recognize that the organization does not encourage behaviors beyond these goals and may even penalize such actions. As a result, employees are likely to allocate their primary resources toward achieving the bottom-line goals, naturally reducing their willingness to take risks in other areas. Risk aversion plays a significant role in innovation behavior. On the one hand, risk aversion suppresses employee proactive innovation behavior because proactive innovation is a high-risk activity with many uncertainties, and its outcomes are often unpredictable [33]. Proactive innovation typically requires employees to make risky decisions, which conflicts with the tendencies of risk-averse individuals. On the other hand, risk aversion may encourage reactive innovation behavior. Reactive innovation behavior involves tasks explicitly defined by the organization or leader, where employees are expected to follow established procedures or instructions, face relatively low risks, and experience more predictable benefits [28]. Therefore, by reducing employees' WTR, LBLM may inhibit proactive innovation behavior while encouraging reactive innovation behavior. Therefore, this study proposes the following hypotheses:

H₃

WTR plays a mediating role between LBLM and employee proactive innovation;

H₄

WTR plays a mediating role between LBLM and employee reactive innovation;

The moderating effect of work values

Work values, as the embodiment of employees' values in the workplace, represent the intrinsic needs and qualities employees seek in their work. They define employees' overall motivation at work and guide their choices and evaluations of work-related behaviors and events, significantly influencing their attitudes, judgments, and actions [34]. Work values are generally divided into intrinsic work values and extrinsic work values. Intrinsic work values refer to the importance employees place on non-material factors that allow for self-expression at work, such as job diversity, autonomy, and creativity. In contrast, extrinsic work values focus on the material or instrumental rewards employees receive from their jobs, such as salary, promotion opportunities, and status [23]. Employees with high levels of intrinsic work values tend to strongly identify with their work, value personal development opportunities, and seek autonomy, responsibility, a sense of achievement, and challenging work tasks. These employees are more likely to take proactive risks, even when leaders emphasize the importance of bottom-line goals or when the organization penalizes actions that go beyond these goals. As the level of intrinsic work values increases, the willingness to change the organization, the sense of responsibility at work, and the spirit of risk-taking become more pronounced [22, 35]. For instance, employees with high intrinsic work values may prefer roles that allow them to make independent decisions about their work content, even if this comes with lower job security.

In contrast, employees with high extrinsic work values are more concerned with the tangible rewards that work provides. They understand that respecting and adhering to the leader's bottom-line goals is the most effective way to maximize their benefits. Taking risks or using organizational resources to pursue actions beyond the bottom-line goals is seen as an impractical choice. For these employees, the desire to change the organization is often outweighed by considerations of tangible rewards, which in turn lowers their WTR.

Thus, work values play a crucial moderating role in the relationship between LBLM and employee innovation behavior. The differences between intrinsic and extrinsic work values significantly influence employees' WTR and their propensity to innovate.

H₅

Intrinsic work values moderate the relationship between LBLM and WTR, weakening its negative effect. When employees have high intrinsic work values, the inhibitory effect of LBLM on WTR is reduced.

H₆

Extrinsic work values moderate the relationship between LBLM and WTR, strengthening its negative effect. When employees have high extrinsic work values, the inhibitory effect of LBLM on WTR is enhanced.

Based on the above analysis and proposed hypotheses, this study posits that LBLM indirectly influences employee innovation behavior (including proactive and reactive innovation behaviors) through the pathway of WTR, and this influence is moderated by employees' work values (intrinsic and extrinsic work values). Specifically, a high level of intrinsic work values can moderate the negative effect of LBLM on WTR, thereby enhancing proactive innovation behavior while weakening reactive innovation behavior. Conversely, a high level of extrinsic work values can strengthen the negative effect of LBLM on WTR, thereby diminishing proactive innovation behavior while promoting reactive innovation behavior. Therefore, this study proposes the following integrated hypotheses:

H₇

Intrinsic work values moderate the mediating role of WTR in the relationship between LBLM and employee innovation behavior (both proactive and reactive). Specifically, under high intrinsic work values, the negative effect of LBLM on proactive innovation behavior and the positive effect on reactive innovation behavior will be suppressed.

H₈

Extrinsic work values moderate the mediating role of WTR in the relationship between LBLM and employee innovation behavior (both proactive and reactive). Specifically, under high extrinsic work values, the negative effect of LBLM on proactive innovation behavior and the positive effect on reactive innovation behavior will be enhanced.

Based on the above, the theoretical research model of this article is derived, as shown in Fig. 1.

Research process and samples

Considering the availability and authenticity of the data, this study used the convenient sampling method to conduct a questionnaire survey among employees of 13 companies engaged in innovative activities, covering high-tech services, electronic information technology, biology and medicine, and telecommunications. To ensure the accuracy of the data, specific control methods were used in the design of the scale, questionnaire distribution, and collection process in this study. With the help of a market research company, the questionnaire was distributed and collected on site. Before completing the questionnaire, the respondents were told that the research data were only used for academic research to ease their concerns. In addition, to reduce the effect of common method bias and improve the reliability of the research results, this study adopted a two-stage survey method. In the first stage, a total of 460 questionnaires were distributed; these included LBLM, WTR, work values (intrinsic and extrinsic work values), and demographic information. When completing the questionnaires, employees were asked to sign their name in the upper left corner of the questionnaire to facilitate coding for the second phase of the survey. After excluding invalid questionnaires with irregular filling and missing data, 412 valid questionnaires were obtained, for an effective recovery rate of 89.57%. The second survey was conducted two months later, and 412 questionnaires were returned to the employees who had completed and were coded in the first phase; these questionnaires mainly measured employee innovation (proactive and reactive innovation). After excluding the situations of resigned employees and invalid questionnaires with regularity and missing data, 351 effective questionnaires were obtained, for an effective recovery rate of 85.19%. The details are shown in Table 1.

Table 1

Sample distribution
Variables	Details	Frequency	Ratio
Gender	male	233	66.38%
Gender	female	118	33.62%
Age	18–25	39	11.11%
	26–35	163	46.44%
	36–45	117	33.33%
	≥ 45	32	9.12%
Education	master	86	24.50%
	bachelor	178	50.71%
	≤college degree	87	24.79%
Work tenure	≥ 3years	139	39.60%
	1-3years	167	47.58%
	< 1year	45	12.82%

Measurements

Leader bottom-line mentality (LBLM). This article uses a scale developed by Greenbaum et al. [10] to measure LBLM; these items were originally created to reflect respondents' assessment of BLM. The respondents indicated how strongly they agreed that their leader (a) "is solely concerned with meeting the bottom line"; (b) "only cares about the business"; (c) "treats the bottom line as more important than anything else"; and (d) "cares more about profits than employee well-being". Its Cronbach's α is 0.813.

Willingness to take risks (WTR). The WTR was measured with a scale developed by Dewett [36] consisting of 8 items, such as (a) "When I think of a good way to improve the way I accomplish my work, I will risk potential failure to try it out"; (b) "I will take a risk and try something new if I have an idea that might improve my work, regardless of how I might be evaluated"; (c) "I will take informed risks at work in order to get the best results, even though my efforts might fail"; (d) "I am willing to go out on a limb at work and risk failure when I have a good idea that could help me become more successful"; (e) "I don’t think twice about taking calculated risks in my job if I think they will make me more productive, regardless of whether or not my efforts will be successful"; (f) "Even if failure is a possibility, I will take informed risks on the job if I think they will help me reach my goals"; (g) "When I think of a way to increase the quality of my work, I will take a risk and pursue the idea even though it might not pan out"; and (h) "In an effort to improve my performance, I am willing to take calculated risks with my work, even if they may not prove successful". Its Cronbach's α is 0.871.

Work Values. The measurement of intrinsic and extrinsic work values was based on the research of Chang, Choi, & Kim [37]. The intrinsic work values scale included the following 7 items: (a) "opportunities to learn new technology and knowledge"; (b) "the R&D project itself"; (c) "autonomy in performing tasks"; (d) "possibilities for expressing and realizing my full capability"; (e) "opportunities to achieve something valuable"; (f) "opportunities to participate in decision-making"; and (g) "participation in professional/academic conferences or seminars". Its Cronbach's α is 0.859. Extrinsic work values were measured by the following 5 items: (a) "salary"; (b) "fringe benefits (e.g., pension, insurance, paid leave)"; (c) "social reputation of my job"; (d) "status at the laboratory or the company"; and (e) "satisfaction of my family regarding my job". Its Cronbach's α is 0.865.

Employee innovation behavior. Proactive innovation behavior mainly draws on the research results of Frese et al. [31], with a total of 7 items, including (a) " I actively attack problems"; (b)" Whenever something goes wrong, I search for a solution immediately"; (c) " Whenever there is a chance to get actively involved, I take it"; (d) " I take initiative immediately even when others don’t"; (e) " I use opportunities quickly in order to attain my goals"; (f) " Usually, I do more than I am asked to do"; (g) "I am particularly good at realizing ideas", etc., with the Cronbach's α is 0.846; The measurement of reactive innovation behavior mainly draws on the research results of Zhao et al. [38], with a total of 5 items, including (a)"Innovation is just about completing established tasks"; (b) "Utilizing loopholes in innovation rules and perfunctory innovation"; (c) "To achieve and recognize innovative achievements, one has to change their creative ideas to comply with social norms and industry paradigms"; (d) "Innovation should cater to the preferences of leaders and execute their innovative instructions like a machine"; (e) "Engaging in innovative work under high pressure and strict reward and punishment systems", etc., with the Cronbach's α is 0.834.

The above scales are all measured by a 5-point Likert scale (1 not important, 5 very important).

Confirmatory factor analysis

This study used Mplus 7.0 to conduct confirmatory factor analysis, and the fitted values of each model are shown in Table 2. According to Table 2, compared with other competitive models, the six-factor model has the best fit (χ²/df = 2.017, RMSEA = 0.058, NNFI = 0.931, CFI = 0.928, IFI = 0.910); at the same time, all the fitting indicators of the model have reached the standards recognized by the academic community. Therefore, there is good discriminant validity among the variables in this study, which can be used for the next step of testing the correlation between variables.

Table 2

The results of confirmatory factor analysis
Models	χ²/ df	RMSEA	NNFI	CFI	IFI
LBLM; WTR; IWV; EWV; PIB; RIB	2.017	0.058	0.931	0.928	0.910
LBLM; WTR; IWV; EWV; PIB + RIB	2.311	0.134	0.902	0.911	0.902
LBLM; WTR; IWV; EWV + PIB + RIB	2.572	0.199	0.853	0.849	0.848
LBLM; WTR; IWV + EWV + PIB + RIB	3.176	0.204	0.807	0.812	0.810
LBLM; WTR + EWV + PIB + RIB	3.520	0.238	0.733	0.721	0.732
LBLM + WTR + IWV + EWV + PIB + RIB	4.532	0.273	0.474	0.469	0.470
Note. LBLM = leader bottom-line mentality; WTR = willingness to take risks; IWV = intrinsic work values; EWV = extrinsic work values; PIB = proactive innovation behavior, RIB = reactive innovation behavior

Although data were collected at two time points, considering that LBLM, WTR, work values (intrinsic and extrinsic work values), and employee innovation behavior (proactive and reactive innovation behaviors) were all reported by employees themselves, there may still be a risk of common method bias. Therefore, this study conducted a Harman single-factor test. The results showed that the variance explained by the first common factor was 23.63%, which was below the critical value of 40%, indicating that the problem of common method bias was not serious. To enhance the rigor and credibility of the research results, a common method factor was added to the six-factor model to further test for common method bias. Unfortunately, the seven-factor model could not be fitted with Mplus 7.0 software. This means that the factor structure with common method factors did not significantly change in fitting degree, indicating that there is no serious problem of common method bias in this study.

Descriptive statistics

The means, standard deviations, and correlation coefficients between the main variables in this study are shown in Table 3. According to Table 3, LBLM has a significant negative correlation with proactive innovation (r=-0.195, P < 0.01), a positive correlation with reactive innovation (r = 0.249, P < 0.01), and a negative correlation with WTR (r=-0.438, P < 0.01); At the same time, WTR is positively correlated with proactive innovation (r = 0.383, P < 0.01), and negatively correlated with reactive innovation (r=-0.137, P < 0.05). These correlations are consistent with theoretical expectations; therefore, the research hypotheses of this study are preliminarily supported.

Table 3

The results of descriptive statistics
Variables	M	SD	SEX	EDU	WT	LBLM	WTR	IWV	EWV	PIB	RIB
SEX	0.662	0.720	1.000
EDU	2.405	1.150	0.069	1.000
WT	2.269	0.951	0.077	0.054	1.000
LBLM	3.986	0.652	0.104^*	0.066	-0.017	1.000
WTR	2.878	0.695	-0.094	0.061	0.033	-0.438^**	1.000
IWV	3.413	0.702	-0.078	0.084	0.019	0.218^**	0.088	1.000
EWV	3.641	0.597	0.044	-0.065	0.026	0.126^*	0.144^*	-0.029	1.000
PIB	3.756	0.640	0.009	0.073	-0.014	-0.195^**	0.383^**	0.308^**	-0.352^**	1.000
RIB	2.942	0.585	0.072	0.023	0.055	0.249^**	-0.137^*	-0.141^*	0.268^**	0.062	1.000

Hypothesis testing

This study validated Hypothesis 1 through linear regression analysis, and the results are shown in Table 4. In Table 4, as shown in M₁ that after controlling for relevant variables, LBLM negatively predicts employee proactive innovation (β=-0.206, P < 0.01). As shown in M₃, LBLM positively predicts employee reactive innovation (β = 0.477, P < 0.01). In view of this, it can be inferred that Hypothesis 1 and Hypothesis 2 are supported.

According to M₅, the negative effect of LBLM on WTR is significant (β=-0.385, P < 0.01); according to M₂, WTR has a significant positive effect on employee proactive innovation (β = 0.411, P < 0.01); and compared to M₁, LBLM still has a significant effect on employee proactive innovation (β=-0.286, P < 0.01), indicating that WTR plays a mediating role between LBLM and proactive innovation, thus supporting Hypothesis 3. Moreover, according to M₄, it can be inferred that WTR has a negative effect on reactive innovation (β=-0.293, P < 0.01), and compared with that of M₃, the effect of LBLM on employee reactive innovation is still significant (β = 0.322, P < 0.01), indicating that WTR also plays a mediating role between LBLM and reactive innovation, thus supporting Hypothesis 4.

To further verify the mediating role of WTR, the data were computed using the process method in SPSS and sampled 5000 times to examine its significance. The results indicated that after controlling for relevant variables, the indirect effect of LBLM on proactive innovation through WTR was − 0.108, with a 95% CI of [0.022, 0.074], excluding 0; the indirect effect of LBLM on reactive innovation through WTR was 0.069, with a 95% CI of [0.019, 0.108], excluding 0. Therefore, Hypotheses 2 and 3 are once again supported.

This study further tested Hypotheses 5 and 6 based on the moderating effect test method. To avoid multicollinearity, LBLM and work values (internal and extrinsic work values) were centralized. The results are shown in Table 4. Table 4 shows that after controlling for relevant variables, M₇ had a significant negative correlation with the interaction term (LBLM* IWV) and WTR (β=-0.189, P < 0.01). According to M₉, there was a significant positive correlation between the interaction item (LBLM* EWV) and WTR (β = 0.136, P < 0.05).

To further clarify the direction and magnitude of the moderating effect, this study used the mean plus or minus one standard deviation as the benchmark to separate high and low levels of employee work values (intrinsic and extrinsic work values). The simple slope test results are shown in Fig. 2 and Fig. 3. Figure 2 shows that when employees have low levels of intrinsic values, the negative effect of LBLM on WTR is significant; when employees have a high level of intrinsic values, the negative correlation between LBLM and WTR decreases. Therefore, Hypothesis 5 is supported. Furthermore, as shown in Fig. 3, when employees have a high level of extrinsic values, the negative effect of LBLM on WTR is significant; when employees have low levels of extrinsic values, the negative correlation between LBLM and WTR decreases. Therefore, Hypothesis 6 is supported.

Table 4

The results of test analysis
Variables	PIB		RIB		WTR
Variables	M₁	M₂	M₃	M₄	M₅	M₆	M₇	M₈	M₉
SEX	0.047	-0.006	-0.027	0.033	-0.038	-0.004	0.017	-0.024	0.046
EDU	0.042	0.034	0.025	-0.002	0.036	0.021	0.050	0.063	0.042
WT	0.059	0.006	-0.019	0.035	0.013	0.041	0.044	0.039	0.038
LBLM	-0.206^**	-0.286^**	0.477^**	0.322^**	-0.385^**	-0.243^**	-0.352^**	-0.271^**	-0.306^**
WTR		0.411^**		-0.293^**
IWV						0.162^*	0.144^*
EWV								-0.218^**	-0.148^*
LBLM* IWV							-0.189^**
LBLM* EWV									0.136^*
R²	0.193	0.622	0.727	0.074	0.290	0.288	0.577	0.593	0.681
△R²	0.190	0.597	0.701	0.067	0.274	0.249	0.508	0.529	0.647
F	4.996	6.322	7.870	6.943	5.442	10.255	8.734	8.044	5.588
Note. P < 0.05; *P < 0.01

The moderated mediation effect was tested using the path analysis method proposed by Edward and Lambert [39], and the results are shown in Table 5. The indirect effect of LBLM on proactive innovation behavior was not significant under high intrinsic work values (β=-0.021, 95% CI=[-0.162, 0.027]), but was significant under low intrinsic work values (β = 0.068, 95% CI=[0.022, 0.046]). The indirect effect of LBLM on reactive innovation behavior was also not significant under high intrinsic work values (β = 0.009, 95% CI=[-0.017, 0.069]), but was significant under low intrinsic work values (β = 0.059, 95% CI=[0.014, 0.045]). Hence, Hypothesis 7 was supported. The indirect effect of LBLM on proactive innovation behavior was significant under high extrinsic work values (β=-0.071, 95% CI=[-0.032, -0.016]), but not significant under low extrinsic work values (β = 0.011, 95% CI=[-0.012, 0.029]). The indirect effect of LBLM on reactive innovation behavior was also significant under high extrinsic work values (β=-0.255, 95% CI=[-0.043, -0.003]), but not significant under low extrinsic work values (β = 0.013, 95% CI=[-0.025, 0.054]). Thus, Hypothesis 8 was supported.

Table 5

The results of moderated path analysis
Variables	LBLM—WTR—PIB		LBLM—WTR—RIB
Variables	Indirect effect	95%CI(BCB)	Indirect effect	95%CI(BCB)
Higher IWV (+ 1 SD)	-0.021	[-0.162, 0.027]	0.009	[-0.017, 0.069]
Lower IWV (-1 SD)	0.068	[0.022, 0.046]	0.059	[0.014, 0.045]
Diff	0.093	[0.015, 0.253]	0.128	[0.008, 0.073]
Higher EWV (+ 1 SD)	-0.071	[-0.032, -0.016]	-0.255	[-0.043, -0.003]
Lower EWV (-1 SD)	0.011	[-0.012, 0.029]	0.013	[-0.025, 0.054]
Diff	0.048	[-0.026, -0.012]	0.083	[-0.043, -0.003]

Conclusion

First, LBLM negatively predicts employee proactive innovation behavior and positively predicts employee reactive innovation behavior. This implies that, compared to proactive innovation, LBLM is more likely to encourage employees to engage in reactive innovation. As a primary source of social information, the leader's attitudes and behaviors convey clear expectation signals to employees, influencing their perceptions and actions. Under the influence of LBLM, employees recognize the importance of ensuring bottom-line goals (such as profits or financial metrics) and tend to passively accept tasks assigned by the organization, including those related to bottom-line-oriented innovation activities. At the same time, employees avoid the uncertainty and risk associated with proactive innovation behaviors and refrain from engaging in other innovation efforts that may compete with bottom-line goals, in order to avoid organizational disapproval or even punishment.

Second, WTR mediates the relationship between LBLM and employee innovation behavior (both proactive and reactive innovation behaviors). Influenced by LBLM, employees gradually realize that risk-taking behaviors beyond the bottom-line goals may not be accepted by the organization and might even result in negative consequences. As a result, they become more conservative, and their willingness to take risks decreases. Given that risk-taking willingness is a key factor driving innovation activities [40], when WTR diminishes, they are more inclined to perform tasks assigned by the organization within the scope of their established roles, engaging in low-risk, reactive innovation rather than actively taking risks to pursue high-risk and more uncertain innovation activities.

Third, work value orientation (both intrinsic and extrinsic work values) effectively moderates the effect of LBLM on employee innovation behavior through the path of WTR. When intrinsic work values are high, employees tend to pursue autonomy, growth, and creativity, and are more open to organizational change [41]. This value orientation weakens the negative effect of LBLM on WTR, thereby enhancing proactive innovation behavior and reducing reactive innovation behavior. In contrast, when extrinsic work values are high, employees place more emphasis on economic rewards and material benefits, leading to more conservative behavior, which amplifies the negative effect of LBLM on WTR. This situation promotes reactive innovation while suppressing proactive innovation.

Theoretical contributions

First, this study enriches the research on LBLM and its outcome variables, expanding the content and depth of this field. The existing literature has not yet directly explored the relationship between LBLM and employee innovation behavior. This study delves into the effect of LBLM on employee innovation behavior from the perspective of employees' intrinsic motivation, responding to scholars' calls to "explore the relationship between LBLM and other outcome variables (beyond work performance and employees' ethical behavior)" [42].

Second, it broadens the study of employee innovation behavior. On one hand, it challenges the traditional view of equating employee innovation behavior with proactive innovation [43], and, considering the unique organizational context in China, distinguishes between proactive innovation behavior and reactive innovation behavior, analyzing the differential effects of LBLM on these two forms of innovation behavior. On the other hand, this study selects LBLM as a typical leadership mindset as the independent variable, examining its mechanism of influence on employee innovation behavior, providing a new perspective to promote innovation and further enriching the antecedent research on employee innovation behavior.

Third, the study explores the moderating role of work values and clarifies the boundary conditions of how LBLM influences employee innovation behavior. Through empirical research, the study confirms that intrinsic work values can effectively moderate the negative effect of LBLM on WTR, while extrinsic work values amplify this negative effect, thereby indirectly influencing employee innovation behavior. This provides new evidence for a deeper understanding of the dynamic process by which LBLM affects employee innovation behavior.

Practical implications

First, organizations should take measures to suppress the negative effects of LBLM. First, when recruiting managers, they avoid allowing candidates with certain traits, such as Machiavellianism and narcissism, to enter the organization because managers with the above traits are prone to bottom-line thinking patterns [13]. Second, scientific goal management training courses should be designed and held to allow management to learn comprehensive goal management and goal balancing to avoid giving too much attention to financial performance indicators and neglecting other important goals, such as social responsibility and employee welfare. Furthermore, we should open channels of expression and establish smooth channels for suggestions so that employees can promptly and effectively report to superiors when they encounter injustice.

Second, leaders should stimulate employees' willingness to take risks through proactive behavioral strategies. First, they should clearly communicate the organization's strategy and goals, ensuring that employees have a clear understanding of their job responsibilities and role expectations while recognizing their own importance. Second, leaders should provide appropriate empowerment by granting employees autonomy, encouraging self-management and a sense of responsibility in their work, which in turn motivates them to take on innovative tasks. Finally, by incorporating flexibility and humanistic care into management, leaders can enhance employees' psychological safety through trust and support, thereby increasing their WTR.

Third, employees' tendency towards extrinsic work values should be weakened, and their motivation towards intrinsic work values should be enhanced. First, when selecting and recruiting, organizations need to focus on the work values of employees and select outstanding talent with strong intrinsic work values rather than a utilitarian orientation. Second, to strengthen the development of corporate culture at the value concept level, enterprises should attach importance to the role of two dimensions of work values, focus on the education of work values within the enterprise, guide employees to make choices and evaluations of current work values, and form the concepts and beliefs that resonate with the organization, leadership, and employees necessary for the development of the enterprise. Furthermore, managers can integrate intervention training on work values into enterprise training, internalizing work values to enhance employee confidence and automatically promoting the emergence of technological innovation and invention in the enterprise.

Limitations and directions

The first limitation is that due to the conditions of the survey, the cross-sectional survey data of this study restricted strict causal inference and failed to effectively reveal the dynamic effect between LBLM, WTR, work values and employee innovation behavior. In future research, multitime longitudinal data can be used to further verify the dynamic causal relationships between variables. The second limitation is that this study used self-reported data from employees, which may lead to common method bias. Although this study used procedural and statistical control to control common method bias within a reasonable range, to obtain more accurate conclusions, future research may consider using multisource data such as leader–subordinate paired data for further exploration. Third, this study divides work values into two dimensions, intrinsic work values and extrinsic work values, which cannot fully and deeply reflect the moderating effect of work values because work values are also divided into different dimensions and contents, such as three dimensions (internal, extrinsic, and social reward dimensions) [44] and four dimensions (internal, extrinsic, social, and reputation dimensions) [45]. The moderating effect of work values may vary under different dimensions and contents, which can be explored in future research to enrich the study of work values.

Ethics approval and consent to participate

All procedures followed were in accordance with the ethical standards of the responsible committee of human experimentation (institutional and national) and with the Helsinki Declaration of 1975, as revised in 2000. Written informed consent was obtained from all the participants for being included in the study. The research project was approved by the Academic and Ethics Committee of Zhejiang Financial College.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.

Funding

This research was funded by Zhejiang Province Philosophy and Social Sciences Planning Project, grant number 24NDJC280YBM.

Author Contribution

Shiwen Luo has made contributions to the Conceptualization, Formal analysis, Investigation, Data curation and Writing original draft preparation. David Yoon Kin Tong has made contributions to the Methodology, Formal analysis, Resources, and Writing review and editing. All authors reviewed the manuscript.

Acknowledgements

We thank all the participants to take part in the study.

Data Availability

The data that support the fndings of this study are available from the corresponding author upon request.

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No competing interests reported.

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Motivate or suppress: The dual effects of leader bottom-line mentality on employee innovation behavior

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Abstract

Background

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Introduction

Theoretical analysis and hypotheses

LBLM and employee innovation behavior

The mediating effect of WTR

The moderating effect of work values

Method

Research process and samples

Measurements

Results

Confirmatory factor analysis

Descriptive statistics

Hypothesis testing

Conclusion and insights

Conclusion

Theoretical contributions

Practical implications

Limitations and directions

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Funding

Author Contribution

Acknowledgements

Data Availability

References

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