1 Introduction

1.1 Research Background

Amid rapid change and global competition, employee innovation is crucial for organizational growth and adaptability (Amabile, 1996). Active Management by Exception (MBEA), a form of transactional leadership, involves proactively monitoring performance and addressing deviations. Though often seen as limiting autonomy and creativity, this study suggests MBEA can promote innovation by enhancing instrumental organizational support—a key psychological mechanism^[1].

1.2 Research Significance.

This study offers a refined view of transactional leadership by highlighting the constructive role of active management by exception in promoting innovation. It expands leadership theory by emphasizing the value of performance monitoring in specific contexts. By introducing instrumental organizational support as a mediator, it deepens the understanding of perceived organizational support and its behavioral outcomes. Integrating social exchange and resource conservation theories, the study provides a strong framework for explaining how leadership affects innovation through resource-based mechanisms^[2].

From a managerial standpoint, this research helps organizations recognize that not all forms of transactional leadership are detrimental to innovation. Proactive problem-solving and timely intervention, when paired with tangible resource support, may serve as effective tools for promoting employee creativity. The findings can guide managers in adopting supportive yet structured leadership behaviors and in designing systems that enhance employees’ access to instrumental resources^[3].

1.3 Research Questions and Objectives

To explore the underlying mechanism through which active management by exception influences innovation, this study addresses the following research questions:

RQ1: Does active management by exception positively influence employee innovative behavior?

RQ2: Does instrumental organizational support mediate the relationship between active management by exception and innovative behavior?

RQ3: If so, what is the nature of the mediation—partial or full?

Accordingly, the study aims to:

Develop a theoretical model incorporating active management by exception, instrumental organizational support, and employee innovative behavior;Empirically test the proposed relationships using data collected from employees in multiple industries;Derive theoretical insights and managerial implications based on the findings.

1.4 Research Design and Structure

This study adopts a theory-driven empirical approach. First, based on a comprehensive literature review, hypotheses are formulated and a conceptual model is developed. Next, a survey is conducted to collect data from frontline employees, and the data are analyzed using structural equation modeling (SEM) to test the proposed hypotheses. Finally, the results are interpreted and implications for both theory and practice are discussed^[4].

2.Literature Review and Hypotheses

2.1 Active Management by Exception

Active Management by Exception (MBEA) is a core component of transactional leadership. It refers to a leader’s proactive efforts to monitor subordinates’ behavior and performance, identifying potential problems or deviations from expected standards, and taking corrective action in a timely manner (Bass & Avolio, 1995). Unlike passive management, which reacts after problems arise, MBEA focuses on anticipating risks and

2.2 Employee Innovative Behavior

Employee innovative behavior refers to the intentional generation, promotion, and implementation of new ideas within a work role or organization (Scott & Bruce, 1994). The process is typically divided into three phases: problem recognition, idea generation and advocacy, and idea implementation^[5].

2.3 Instrumental Organizational Support

Instrumental organizational support refers specifically to the concrete assistance and resources provided by the organization to help employees accomplish their tasks, including access to information, tools, training, time flexibility, and managerial assistance (Rhoades & Eisenberger, 2002). It plays a crucial role in enabling employees to engage in high-resource-demanding behaviors such as innovation.

This study draws upon two primary theoretical frameworks: Social Exchange Theory (SET) and Conservation of Resources Theory (COR).

Social Exchange Theory (Blau, 1964) posits that relationships in organizations are formed through reciprocal exchanges. When employees perceive that leaders or organizations invest resources or care into their well-being, they are likely to reciprocate with positive work behaviors, such as loyalty, commitment, and innovation.

2.4 Theoretical Foundation

Conservation of Resources Theory (Hobfoll, 1989) suggests that individuals strive to obtain, retain, and protect valuable resources. Since innovative behavior often requires significant cognitive and emotional investment, employees are more likely to engage in such behavior when they feel adequately resourced and supported.

Based on the above literature and theoretical framework, the following hypotheses are proposed:

H1: Active management by exception positively influences employee innovative behavior.

Proactive feedback, problem-solving, and performance correction from leaders can stimulate employee awareness of improvement opportunities and support innovation.

H2: Active management by exception positively influences instrumental organizational support.

2.5 Hypotheses Development

When leaders engage actively with employee performance issues, employees are more likely to perceive that the organization is providing tangible help and resources.

H3: Instrumental organizational support positively influences employee innovative behavior.

Instrumental support reduces the risk and cost associated with innovation, and enhances employees’ confidence and motivation to innovate.

H4: Instrumental organizational support mediates the relationship between active management by exception and employee innovative behavior.

Leadership behavior enhances perceived support, which in turn fosters innovation, forming a “leader behavior → support perception → innovative behavior” pathway.

2.6 Conceptual Framework

A visual representation of the proposed theoretical model is shown below:

3. Research Methodology

3.1 Overview of Research Design

This study adopts a quantitative research method to empirically test the theoretical model proposed in Chapter 2, which examines how Active Management by Exception (MBEA) influences Employee Innovative Behavior (EIB) through the mediating role of Instrumental Organizational Support (IOS). The research process involves four main stages:

1.Selection of established measurement scales and questionnaire development;

2.Pilot testing and revision of questionnaire items for clarity and localization;

3.Formal data collection through online and offline survey distribution;

4.Data analysis using statistical tools to verify the hypotheses and model fit.

3.2 Variable Measurement and Scale Sources

The core variables in this study include one independent variable (MBEA), one mediating variable (IOS), and one dependent variable (EIB), along with several control variables. All constructs are measured using five-point Likert scales (1 = strongly disagree, 5 = strongly agree), based on validated instruments.

3.2.1 Active Management by Exception (MBEA)

This variable captures the extent to which employees perceive their leaders proactively monitor and address performance deviations. Sample items include:

“My supervisor pays close attention to potential problems before they occur.”

“My manager intervenes before mistakes become serious.”

3.2.2 Instrumental Organizational Support (IOS)

IOS refers to employees’ perception of tangible assistance and resources from the organization. It is adapted from the original POS scale and focused on task-related support. Sample items include:

“I can obtain the resources I need from the organization to accomplish my tasks.”

“When I encounter problems, the organization provides practical help.”

3.2.3 Employee Innovative Behavior (EIB)

EIB reflects employees' tendency to generate, promote, and implement new ideas. This study adopts supervisor ratings to reduce common method bias. Sample items:

“This employee often suggests new ways to improve work processes.”

“He/she takes action to implement new ideas.”

3.2.4 Control Variables

To account for demographic and contextual differences, the following control variables are included:

Gender (male = 1, female = 0)；Age (categorical: ≤25, 26–35, ≥36)；Education level (associate and below, bachelor, master and above)；Industry type (manufacturing, IT, healthcare, etc.)；Work tenure (in years, continuous variable)

3.3 Questionnaire Design and Pilot Testing

3.3.1 Structure of the Questionnaire

The structured questionnaire consists of five sections:

1. Research introduction and confidentiality statement；
2. Demographic information
3. MBEA scale items；
4. IOS scale items；
5. EIB scale items (self or supervisor-rated).

3.3.2 Pilot Test Procedure

A pilot test was conducted with 30 respondents from various industries. Feedback was collected regarding clarity, translation accuracy, and cultural relevance. Revisions were made to improve readability and avoid ambiguous or overly academic phrasing

3.4 Sampling and Data Collection

3.4.1 Sampling Method

The study adopted a purposive sampling approach supplemented by snowball sampling, leveraging professional contacts and HR personnel to access participants. Data were collected from employees in eastern China across sectors including manufacturing, IT, healthcare, and public institutions.

3.4.2 Sample Characteristics

A total of 354 responses were collected, with 320 valid responses retained after screening. Demographic breakdown:

3.5 Data Analysis Techniques

Data were analyzed using SPSS 26.0 and AMOS 24.0 in the following steps:

3.5.1 Reliability Analysis.

Cronbach’s alpha was computed for each scale; values > 0.70 indicated good internal consistency.

3.5.2 Validity Testing.

Confirmatory Factor Analysis (CFA) was conducted to assess construct validity;Model fit indicators included CFI, TLI, RMSEA, AVE, and CR.

3.5.3 Correlation Analysis.

Pearson correlation coefficients were used to examine basic relationships among variables and assess multicollinearity.

3.5.4 Structural Equation Modeling (SEM).SEM was employed to test the hypothesized path relationships;Both direct and indirect effects were modeled and compared.

3.5.5 Mediation Testing

Bootstrap method with 5,000 resamples was used to estimate indirect effects;

A 95% confidence interval not including zero indicates significant mediation.

4.Results and Analysis

4.1 Data Preprocessing and Descriptive Statistics

Prior to formal analysis, the 320 valid responses were screened and processed as follows:

Reverse-coded items were recoded appropriately;Missing values (<1%) were handled using mean imputation;Skewness and kurtosis values for all variables were within ±1.5, indicating approximate normality.

4.1.1 Descriptive Statistics

All variables exhibit moderately high means and acceptable dispersion, indicating generally positive perceptions of leadership behavior, organizational support, and employee innovation in the sample.

4.2 Reliability and Validity Analysis

4.2.1 Reliability

Cronbach’s alpha values for all scales exceeded 0.80, indicating high internal consistency:

4.2.2 Validity (Confirmatory Factor Analysis)A three-factor model was tested using AMOS. Model fit and construct validity were assessed using standard indices:

Results confirm good model fit and satisfactory convergent validity and composite reliability for all latent constructs.

Pearson correlation coefficients among the core variables are shown below:

** p < 0.01

All variables are significantly positively correlated, supporting the hypothesized relationships and justifying further SEM analysis.

A structural equation model was constructed with MBEA as the independent variable, IOS as the mediator, and EIB as the dependent variable. Three main paths were examined:

MBEA → IOS；IOS → EIB；MBEA → EIB

4.4.1 Model Fit

The structural model fits the data well based on commonly accepted criteria.

4.4.2 Path Coefficients

All paths are statistically significant, indicating that instrumental organizational support partially mediates the relationship between active management by exception and employee innovation.

The Bootstrap method (5,000 resamples) was used to test the significance of the indirect effect:

The confidence interval does not contain zero, confirming a significant partial mediation effect of IOS.

This chapter empirically tested the proposed research model. Key findings include:

Active management by exception significantly promotes employee innovative behavior;

Instrumental organizational support enhances innovation and acts as a psychological and resource-based bridge;

IOS plays a partial mediating role between leadership behavior and employee innovation, confirming the theoretical model.

These results lay a solid foundation for the final discussion and practical implications in the next chapter.

5.Discussion and Conclusion

Grounded in Social Exchange Theory and Conservation of Resources Theory, this study constructed and tested a mediation model in which Active Management by Exception (MBEA) influences Employee Innovative Behavior (EIB) through Instrumental Organizational Support (IOS). The main findings are as follows:

MBEA has a significant positive effect on employee innovative behavior.

Contrary to traditional views that transactional leadership suppresses innovation, this study reveals that when leaders demonstrate timely intervention and performance monitoring, they communicate clear expectations and convey trust, thereby stimulating employees’ willingness to innovate.

Instrumental organizational support positively influences employee innovation.

When employees perceive tangible resources and assistance—such as tools, information, and time flexibility—they are more likely to engage in innovation, as the perceived costs and risks of innovation are reduced.

IOS partially mediates the relationship between MBEA and EIB.

Leaders who engage in active exception management enhance employees’ perceptions of organizational support, which in turn increases innovative behavior. The indirect effect was statistically validated via structural equation modeling and Bootstrap mediation testing.

Despite its contributions, this study has several limitations:

(1) Cross-sectional design

As a cross-sectional study, causal inferences are limited. Future studies could adopt longitudinal or experimental designs to capture dynamic changes and strengthen causal conclusions.

(2) Potential common method bias

Although supervisor ratings were used for EIB, most data were self-reported. Future research should incorporate multi-source or time-lagged data to reduce method bias.

(3) Lack of moderating variables

This study focused on a mediation model. Future research could explore moderators such as innovation climate, psychological empowerment, or individual innovation self-efficacy to develop a moderated mediation model.

(4) Limited industry generalizability

The sample was concentrated in manufacturing and technology sectors. Broader samples from finance, education, or public administration would improve external validity and generalizability.

This study demonstrates that active management by exception—a typically underappreciated leadership style—can, when paired with instrumental organizational support, meaningfully promote employee innovation. The findings challenge the simplistic dichotomy between transformational and transactional leadership, offering a more nuanced understanding of how leadership behaviors can enable innovation through resource-based mechanisms. Future research can expand this work by examining these dynamics in varied organizational and cultural settings.

References

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[3]Yukl, G. (2013). Leadership in organizations(8th ed.). Pearson Education.

[4]Zhou, J., & George, J. M. (2001). When job dissatisfaction leads to creativity: Encouraging the expression of voice. Academy of Management Journal, 44(4), 682–696.

[5]Graen, G. B., & Uhl-Bien, M. (1995). Relationship-based approach to leadership: Development of leader–member exchange (Graen & Uhl-Bien, 1995) (LMX) theory. The Leadership Quarterly, 6(2), 219–247.