Open AccessHow Does Organisational Politics Impact Innovative Work Behaviour? The Mediating Role of Knowledge Sharing
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To understand the mechanism of innovative work behaviour (IWB) in China’s higher education. With a total of 495 valid responses from six universities in China, this study utilised Amos26 for data analysis. The structural equation model indicates that organisational politics (OP) significantly influences academics’ knowledge sharing behaviour (KSB) (β = -0.220, p < 0.000) and IWB (β = -0.126, p < 0.005). The mediating effect of knowledge sharing is confirmed (β = -0.193, p < 0.003). This study confirms the detrimental effect of OP on KSB and IWB within Chinese high education institutions. Consequently, to foster innovation among academics, management should consider controlling OP within the organisational environment. Standardising the supervision and management of executive power, ensuring that administrative power operates transparently. Additionally, delineating between OP and non-OP behaviours will mitigate the negative impact of OP on innovation.1. Introduction
Innovation is a crucial factor in ensuring the survival and growth of organisations, serving as a catalyst for productivity enhancement, elevation of living standards, and advancement of social development and transformation (Dutta et al., 2022). Innovation is a pivotal driver for China’s economic transformation and attaining high-quality development (Jiang et al., 2020). However, this requires substantial innovative outcomes and creative talents.
Meanwhile, in many countries, higher education institutions (HEIs) have been recognised as critical stakeholders in innovation (Smith, 2007). Based on innovation in teaching, learning, and research, academics nurture innovative talents and address the shortage of technical expertise. Simultaneously, they offer theoretical and practical guidance, aiding companies in problem-solving and driving corporate innovation (Smith, 2007). Universities leverage the knowledge spillover effect, develop human capital and innovation, and contribute to societal transformation (Al-Mansoori & Koç, 2019).
The current challenges faced by China include a need for more technical personnel in critical fields and insufficient innovation in HEIs (Lou & Wu., 2017). How to address these issues has been a topic of discussion. Ministry of Education of the People’s Republic of China. (2018) has proposed the construction of innovative teachers, recognising the pivotal role of innovative academics in the innovation of HEIs. As a result, encouraging innovation among academics in HEIs has become critical to China’s innovation-driven transformation.
Since the 1960s, scholars have been focusing on innovation research, with a gradual shift toward studying individual IWB after 2000. This shift is attributed to recognising that individuals are the foundation for generating new ideas and fostering innovation. To enhance innovation, a deeper understanding of organisational factors influencing individual IWB is crucial (Bos-Nehles et al., 2017). If an organisation lacks the means to motivate staff members to participate in IWB, its innovative capabilities may be constrained. Moreover, current scholarly research on IWB predominantly concentrates on the private sector within Western cultural contexts. More emphasis needs to be placed on the effect of organisational factors on IWB in the eastern public sector.
In the discourse concerning the impact mechanisms of organisational factors on IWB, scholars have predominantly focused on formal, legitimate, and positive factors. In their efforts to deepen the understanding of the mechanisms of IWB, researchers have predominantly discussed the influence of positive factors on employee IWB, such as organisational justice and organisational support. In contrast, research on informal and negative factors is comparatively limited. Understanding non-formal, negative factors is crucial for organisational development because these elements are an inherent requirement for a comprehensive comprehension of organisational operations and management mechanisms. Due to the inherent limitations of resources, OP is inevitable within organisations. OP significantly influences individual behaviour, and psychology predicts employee behaviour. However, owing to the unethical nature of OP, it is generally disliked. China, emblematic of a collectivist culture, places significant importance on organisations and individuals. Mainly influenced by traditional Chinese culture, where "Guanxi" implies that the acquisition of resources within an organisation can transcend formal procedures and systems, the prevalence of OP utilising informal power within a relationship-centric organisational environment may lead to unfair resource distribution, potentially impacting the psychology and behaviour of employees.
Furthermore, HEIs are knowledge-centric and prioritise knowledge as one of the most crucial resources in the academic environment. The exchange of knowledge among academics is vital for the success of universities (Akosile & Olatokun, 2020). KSB enhances employees’ knowledge storage, enabling them to generate new ideas and solve problems, thereby implementing IWB (Phung et al., 2019). Building on IWB, academics are vital in generating and distributing knowledge for society and students. However, within the context of OP, even when employees engage in KS, they may not receive fair treatment and rewards from the organisation due to the manipulation of resource allocation through OP. OP can lead academics to develop a diminished perception of the organisation and their colleagues, subsequently reducing their positive contributions to the organisation and having a detrimental impact on KS and IWB. Therefore, as a response to OP, academics’ positive extra-role behaviours, such as KS and IWB, tend to decrease. Additionally, the reduction in KS within the organisation limits academics’ access to new knowledge, constrains new ideas, and resolves related issues, thereby reducing the likelihood of employees engaging in IWB. Scholars have investigated how OP affects employees’ KS. However, most research has been centred on the private sector in Western cultural contexts, with limited exploration in the public sector, especially in knowledge-intensive HEIs within eastern cultural backgrounds. Considering the inevitability of OP in HEIs and the significance of academics’ KS, it is imperative to explore the relationship between OP, KS, and IWB in public sectors in eastern cultural contexts.
In addition, Chinese HEIs encounter challenges such as inadequate innovation output and a scarcity of talented individuals. However, the essence of fostering innovation output and nurturing creative talent within HEIs lies in university academics’ IWB. Therefore, it is crucial to investigate the underlying mechanisms that drive IWB. Considering the organisational context of Chinese HEIs, this study identifies two indispensable factors, OP and KS, to examine their influence on the IWB exhibited by university academics. Moreover, this study investigates the mediating role played by KS in shaping the relationship between OP and IWB.
The study is organised as follows: Section 2 provides a detailed review and develops hypotheses; Section 3 introduces the methodology; Section 4 summarises the results; and Section 5 discusses the related research. Section 6 summarises the conclusion. Sections 6 and 7 summarise the implications, limitations, and future research directions.
2. Literature Review and Hypothesis Development
Knowledge-intensive organisations seek creative and innovative solutions to complex problems through their employees’ knowledge, creativity, and innovative participation (Malik, 2022). Due to the scarcity of resources, OP is inevitable and necessary for individual success (Kacmar & Baron, 1999). However, limited research comprehensively explores the effect of OP and KS on IWB in knowledge-intensive organisations. Therefore, this study focuses primarily on the integrated mechanisms of OP, KS, and IWB in HEIs. In addition, the propositions of the current study are grounded in the logical and theoretical foundations of Resource Conservation Theory (COR) and Social Exchange Theory (SET).
When internal resources within an organisation are limited, informal OP is employed as a means of resource acquisition (Burns, 1961). However, a prominent drawback in current OP research is the need for measurement consistency (Jafariani et al., 2012). Therefore, establishing a comprehensive definition is the initial step in researching OP. Building upon this definition, further exploration of pertinent studies concerning OP can be undertaken (Ferris et al., 2013).
The macro-level political studies focus on distributing and utilising public authority and involve various power structures. Micro- OP is the illegal use of formal power by organisational members. Simultaneously, drawing on earlier scholarly debates on OP, it can be established that it is characterised by illegitimacy, immorality, and self-interest. For instance, Burns (1961) emphasised the moral illegality nature of OP behaviour within organisations. OP is a social influence process that involves strategically planned behaviour to maximise one’s interests, either at the expense of others or in line with others’ interests (Ferris et al., 2013).
Therefore, synthesising these perspectives, OP primarily involves discussions on unethical, illegal, and unrecognised (not sanctioned by procedures, authority, or public consensus) clandestine manoeuvres of administrative power to maximise self-interest. In this process, these power manoeuvres may align with others’ interests or come at the cost of sacrificing others’ interests. OP is the spectre of manipulating grey power outside the organisation’s formal institutions and procedures.
Furthermore, research on OP encompasses various sub-concepts such as OP behaviour (OPB), political skills, political will, and OP tactics, as well as perceived organisational politics (POP). However, political will, political skills, or political tactics are crucial factors influencing the implementation and success of OPB. Hence, OP-related research primarily focuses on two aspects: OPB and POP. In understanding the relationship between OPB and POP, Vigoda & Cohen (2002) assert that there is a distinction between the concepts of OPB and POP and explore the influence of OPB on POP. Therefore, following the chronological order, OPB should precede POP. Members engage in the illegitimate exercise of power to gain resources (such as OPB) within the organisation, leading employees to form judgments and perceptions (such as POP) about the intensity of OP (whether resource allocation follows legitimate procedures and systems or involves clandestine operations through illegitimate, unethical, and informal political behaviour). POP occurs when an organisational member’s selfish behaviour characterises the workplace and is the subjective assessment of how much coworkers’ and supervisors’ selfish behaviour characterises the workplace (Ferris et al., 2000). Thus, POP is the outcome of OPB (Ferris et al., 2019), which is a particular sequence of a person’s psychological reactions.
An operational definition of POP offered in this paper posits that POP is a 3-dimensional variable: general political behaviour, which encompasses the actions of people who act selfishly in order to achieve desired results; go along to get ahead, which is the inaction of people in order to achieve desired results; and pay and promotion policies, whereby the organisation exhibits political behaviour through the policies it implements (Kacmar & Carlson, 1997).
A framework for evaluating and integrating new experiences and information is provided by knowledge, which is thought of as a fluid mixture of framed experience, values, background knowledge, and expert insights (Bolisani & Bratianu, 2018). Knowledge is identified as the most crucial resource in modern organisations, and its replication by competitors is challenging (Raj Adhikari, 2010).
In HEIs, creating new knowledge by studying existing knowledge has long been regarded as a core practice, with knowledge exchange being fundamental (Mutahar et al., 2022). However, in knowledge-intensive HEIs, knowledge is a crucial asset for university academics. They create knowledge through research and disseminate it to students through teaching activities and collaborations with industry (Al-Kurdi et al., 2020). Therefore, not all academics may be equally inclined to share their knowledge (Fauzi, 2023). Hence, university knowledge management and sharing have emerged (Al-Kurdi et al., 2020). However, many institutions, including research-oriented universities, still underestimate the importance of KM, resulting in a slow uptake of KM initiatives and activities within their organisations (Tan, 2016). Furthermore, while KS has been widely discussed in for-profit organisations, it is crucial to consider knowledge’s pivotal role in HEIs (Mutahar et al., 2022). Nevertheless, research on KS in knowledge-intensive organisations like HEIs remains limited (Al-Kurdi et al., 2018).
Despite its importance, a consistent definition of knowledge sharing has yet to be found. Due to different backgrounds and perspectives, scholars have provided varying definitions of knowledge sharing, making it a topic of ongoing debate between academia and practitioners (Al-Kurdi et al., 2018). In some studies, KS may encompass the intention, capability, and behaviour of sharing knowledge. Because organisations can analyse and quantify behaviour and integrate it into performance evaluation systems, this study primarily focuses on KSB. Based on the background of this study within HEIs, the current research adopts the operational definition of KSB as interactions among academics from HEIs, entailing the exchange of knowledge, information, and experiences concerning teaching and research, which is proposed by Rahman et al. (2021).
IWB is considered a determinant factor influencing organisational competitiveness and survival. Foundational to high-performance organisations, IWB is instrumental in exploring opportunities, identifying problems, translating ideas into tangible outcomes, and integrating these outcomes into organisational practices. However, scant attention has been devoted to understanding the individual and organisational factors influencing individual innovation. Therefore, identifying relevant factors impacting IWB is crucial (Kör, 2016; van Assen & Caniëls, 2022). Furthermore, most researchers focus on how positive organisational factors influence IWB. Particularly, emphasis is placed on positive organisational elements like organisational support, learning organisational culture, green talent management, etc. Among numerous organisational factors, OP is a paradoxical entity that elicits strong reactions to both positive and negative outcomes. Consequently, it has been a central theme in systematic investigations, encompassing various topics within organisational science (Ferris et al., 2019). In particular, the relationship between OP and innovation has received extensive research attention. Chen et al. (2022) found that POP was negatively related to innovative behaviour in Chinese industries. Limited research has considered this relationship in the educational sector.
Furthermore, the conservation of resource theory, posits that individuals exert maximum effort to acquire, protect, and maintain their existing resources. They perceive losses as threats and adjust accordingly based on the external environment. However, when OP occurs in the work environment, employees may perceive the organisation as rife with deception and self-interest. Consequently, they tend to conserve their resources to cope with the pressure of resource loss caused by OP. This conservation may involve preserving resources and decreasing resource investment in innovation, thereby diminishing IWB. H1: OP has a significant negative impact IWB.
In the era of the knowledge economy, knowledge management plays a vital role in promoting organisation and stabilising an economy. KS is the core and most complicated part of knowledge management. KS is essential because it can help organisations realise the best management practices and reduce redundant learning efforts and futile duplication of labour (Hansen, 2002). Even if KS has many benefits, however, the triggering factors for knowledge sharing are unclear (Tohidinia & Mosakhani, 2010).
OP is an essential organisational factor. Researchers emphasise that in the context of OP, employees are willing to engage in negative behaviours. KS is influenced by motivation and perception (Hameed et al., 2019). OP destroys trust and decreases organisation members’ related KSB. For instance, Kaur & Kang (2023) predicted that OP would increase employees’ knowledge of hiding behaviour in banks in India. Chen et al. (2022) found that OP is positively related to knowledge-sharing hostility among employees and supervisors from various Chinese industries. However, previous studies also revealed that OP positively predicts KS, and employees are more inclined to participate in KS if they perceive their organisational climate to be political. For instance, Rodriguez et al. (2021) and Rodriguez et al. (2024) investigated employees in a Brazilian cultural context and found that POP facilitates KS. Thus, does OP promote or facilitate KS? The relationship between OP and knowledge sharing is unclear and can be investigated further in different sectors.
Furthermore, the COR theory provides the theoretical basis for the current research propositions. According to the COR theory, people are motivated to protect their current resources and acquire new resources. When an organisation acts in a way that gains resources at the expense of others, the individual will work negatively, such as by hiding knowledge rather than sharing knowledge.
Therefore, based on COR and the empirical research above, this study predicts that individuals who perceive OP may decrease KSB in universities. The following research hypotheses are proposed in this study. H2: OP has a significant negative impact on KSB.
Innovation is crucial to businesses’ growth and enhancing an organisation’s capability (Kraśnicka et al., 2018). KS is a crucial component of corporate growth (Almulhim, 2020). Knowledge helps identify and exploit opportunities and benefits for organisational innovation (Kaya & Patton, 2011). KS enhances employee capacities, fosters creativity, and promotes modernisation (Almulhim, 2020). Therefore, KS affects the emergence of IWB directly and indirectly (Vandavasi et al., 2020).
Numerous studies have also shown the connection between KS and IWB. For instance, Kim & Park (2017) revealed that KS encourages employees to engage in IWB. In addition, the positive effect of KS on IWB was confirmed by Derin et al. (2022) among 495 employees in Turkey, by Sudibjo & Prameswari (2021) among 260 school teachers in Indonesia, and by Vandavasi et al. (2020) among the management team and individuals in the Taiwan hotel industry, etc.
SET can support the following propositions on a logical and theoretical basis: According to SET, people quickly broaden their knowledge domains through knowledge sharing, the interchange of critical information, and improvements in their problem-solving skills and IWBs (Kmieciak, 2020). Therefore, when a person receives knowledge from other people based on reciprocity norms, they may be encouraged to reward the knowledge sharer with a material or immaterial return; it can even be a behavioural reward. Thus, the knowledge receiver engages in extra-role behaviours such as IWB to benefit the knowledge sharer and organisation. In addition, the above research also emphasises the critical role of KS in improving individual IWB. This study predicts that individuals who received KS may engage in IWB at Chinese public universities. Therefore, based on the previous studies, this study proposes a hypothesis. H3: KSB has a significant positive impact on IWB.
To explore the mechanism through which OP influences innovation, researchers have investigated the impact of OP on innovation. For instance, Omer & Hassan (2018) discussed the negative correlation between POP and creative propensity. Researchers further explore relevant mediating and moderating factors to deepen their understanding of this mechanism. Chen et al. (2022) introduced knowledge-sharing hostility as a mediating variable, while Agarwal (2016) discussed the moderating impact of locus of control and the mediating impact of work engagement. However, when OP is present in the organisation, academics’ downbeat POP, where resources are allocated through informal political means rather than fair procedural rules, leads to reduced reciprocation towards the organisation. This reduction may result in decreased KS and IWB.
Furthermore, according to COR, OP diminishes academics’ KS, preventing them from acquiring additional knowledge to compensate for existing problems. OP reduces the likelihood of KS solving problems encountered in their work and diminishes IWB further. Therefore, OP is posited to decrease KS, leading to employees responding with less IWB due to the scarcity of KS. This establishes OP as a mediating factor in the relationship between KSB and IWB. Based on the literature mentioned above, research gaps, and theoretical foundations, the following research hypotheses are proposed. Figure 1 presents the diagrammatic representation. H4: KSB can mediate the relationship between OP and IWB.
3. Methodology
To elucidate the mechanisms influencing IWB among university academics, this study conducted a questionnaire survey across six universities in China. The pertinent data primarily originated from the Chinese Ministry of Education and relevant university websites, necessitating stratified sampling techniques for data collection. A random sample of respondents was contacted to confirm the completion of the questionnaire and to clarify and answer some questions. Six hundred questionnaires were distributed to academics, accompanied by explicit instructions on distributing and completing the surveys. Before data collection, the researchers obtained ethics permission from the Ethics Committee and guaranteed anonymity and confidentiality.
The final dataset comprised 541 collected questionnaires. Following data cleansing procedures, 495 valid questionnaires were used for subsequent data analysis. Among the 495 respondents, there were 197 males and 298 females, excluding administrative personnel from the universities. The participants represented various academic ranks, encompassing assistants, lecturers, associate professors, and professors. This sampling approach was designed to ensure the broad applicability and representativeness of the research findings, providing a comprehensive understanding of the characteristics and influencing factors of IWB among university academics.
The study mostly used a five-point Likert scale (1 being strongly disagree and 5 being strongly agree) to validate the research’s hypotheses. The POP scale was adapted from Kacmar & Carlson (1997), the KSB scale was adapted from Rahman et al. (2021), and the IWB scale was adapted from Ibus et al. (2020). A back-translation method was utilised to translate the questionnaire into Chinese to minimise variations across different versions of the questionnaire. The reliability coefficients for the scales were 0.86, 0.9, and 0.9, respectively. The final questionnaire for this study comprised 28 items.
4. Results
The systematic error in data that results from employing a standard procedure for data collection or measurement in a study is known as common method bias. In other words, it reflects a situation where the data collection method exaggerates the correlations between variables. Common sources of method bias arise when predictor variables are obtained from the same source, and other biases can stem from the context of the measurement items, the context of the measurement tool, or the context in which the measurement is obtained (Podsakoff et al., 2003).
Researchers employ strategies to mitigate common method bias, such as utilising multiple data collection methods, applying statistical techniques (e.g., Harman’s single-factor test), and incorporating procedural remedies in the research design. This study employed procedural remedies during the data collection, including ensuring participants’ answers remained anonymous and confidential. This was done to minimise the possibility of bias, encouraging participants to provide truthful answers rather than responses they perceive as socially acceptable.
Additionally, statistical methods were used to find if common method bias was present. Harman’s single-factor test results show that common method bias has no discernible impact on the study’s data. The factor loading explaining the total variance is 33.591%, less than the 50% threshold standard (Podsakoff et al., 2003).
Of the 495 participants, 197 were males and 298 were females, excluding school administrative personnel. The participants included assistants (19%), lecturers (48.3%), associate professors (26.7%), and professors (6.1%). The mean, standard deviation, minimum, and maximum values for the pertinent constructs are shown in Table 1.
Mean | Std. Deviation | Minimum | Maximum | |
POP | 2.922 | 0.764 | 1.00 | 5.00 |
KSB | 3.697 | 0.793 | 1.00 | 5.00 |
IWB | 3.741 | 0.739 | 1.00 | 5.00 |
This study adopts relevant scales in different cultural contexts and revalidates scales previously verified for reliability in prior research. The reliability values of Cronbach’s alpha for the scales measuring IWB, KSB, and POP are displayed in Table 2. Every measurement result is reliable, with Cronbach’s alpha values higher than 0.8. This validates the scales’ dependability and shows that they are appropriate for application to research (Pallant, 2020).
Variables | Number of Items | Cronbach’s Alpha Reliability |
OP | 11 | 0.887 |
KSB | 8 | 0.906 |
IWB | 9 | 0.916 |
Confirmatory Factor Analysis (CFA) examines the connections between corresponding indicators and latent variables. In structural equation modelling (SEM), CFA is employed to assess the extent to which a specified measurement model, consisting of latent constructs and observed indicators, fits the observed data. It aids in validating the measurement model (Harrington, 2009). CFA assesses the measurement model using a set of fit indices. Figure 2 shows the CFA model, and Table 3 presents the goodness-of-fit indices for the final model. The CFA results indicate an excellent fit for the measurement model. The ChiSq/df is 2.168, below the threshold of 3 (Marsh & Hocevar, 1985). Furthermore, the CFI value is 0.954, exceeding the recommended threshold of 0.9 (Bentler, 1990), indicating a well-fitting model. The RMSEA yields a value of 0.049, below the threshold of 0.08 (Browne & Cudeck, 1992). The standardised root mean square residual (SRMR) is 0.054, below the threshold of 0.08 (Shi et al., 2018).
Additionally, CFA results indicate that the variables form a reasonable structure. The factor loadings for the POP range from 0.52 to 0.79, for the KSB from 0.52 to 0.87, and for the IWB from 0.56 to 0.86, demonstrating the validity of the variable structure (Kim & Mueller, 1978). Convergent validity meets the criteria if average variance explained (AVE) values exceed 0.5. The AVE value of GPB is lower than 0.452. However, if AVE is less than 0.5 and composite reliability is greater than 0.6, the convergent validity remains sufficient (Fornell & Larcker, 1981). When composite reliability (CR) values for the most factors are more significant than 0.7, the consistency of reliability among the items is confirmed (Bagozzi & Yi, 1988). Table 4 presents the measurement model’s results, including factor loadings, CR, and AVE. Moreover, Table 5 shows the construct correlations where the AVE square root is larger than the correlations with other variables and exceeds 0.7. This implies that discriminant validity is satisfactory (Fornell & Larcker, 1981).
Indices | Final Measurement Model |
χ2/df | 2.168 |
CFI | .954 |
GFI | .903 |
TLI | .948 |
RMSEA | .049 |
SRMR | .054 |
Construct | Items | Factor Loading | CR | AVE |
OP | GPB | 0.526 | 0.832 | 0.624 |
GGA | 0.792 | |||
PPP | 0.704 | |||
General Political Behaviour | GPB1 | 0.832 | 0.613 | 0.452 |
GPB2 | 0.811 | |||
Go Along to Get Ahead | GGA1 | 0.802 | 0.867 | 0.570 |
GGA2 | 0.639 | |||
GGA3 | 0.666 | |||
GGA4 | 0.827 | |||
GGA5 | 0.818 | |||
Pay and Promotion Policies | PPP1 | 0.727 | 0.876 | 0.640 |
PPP2 | 0.842 | |||
PPP3 | 0.838 | |||
PPP4 | 0.788 | |||
KSB | KSB1 | 0.833 | 0.908 | 0.557 |
KSB2 | 0.868 | |||
KSB3 | 0.858 | |||
KSB4 | 0.699 | |||
KSB5 | 0.519 | |||
KSB6 | 0.688 | |||
KSB7 | 0.695 | |||
KSB8 | 0.745 | |||
IWB | IWB1 | 0.652 | 0.917 | 0.556 |
IWB2 | 0.564 | |||
IWB3 | 0.574 | |||
IWB4 | 0.795 | |||
IWB5 | 0.751 | |||
IWB6 | 0.817 | |||
IWB7 | 0.859 | |||
IWB8 | 0.816 | |||
IWB9 | 0.817 |
Variable | POP | KSB | IWB |
POP | 0.790 | ||
KSB | -0.22 | 0.746 | |
IWB | -0.276 | 0.711 | 0.746 |
SEM analysis used Amos 26 to test this study’s hypotheses. The status of the hypotheses is detailed in Table 6. The final SEM model is illustrated in Figure 3. The SEM results indicate that OP significantly negatively impacts academics’ IWB (β = -0.126; p < 0.005). OP also has a significant negative impact on KSB (β = -0.220; p < 0.000). Moreover, KSB significantly and positively impacts academics’ IWB (β = 0.683; p < 0.000).
Hypothesis | Hypothesis Path | Path Coefficient | S.E. | C.R. | P-value | Final Remarks |
H1 | IWBs<--- POP | -0.126 | 0.057 | -2.84 | 0.005 | Supported |
H2 | KSB <--- POP | -0.220 | 0.08 | -3.723 | *** | Supported |
H3 | IWB <--- KSB | 0.683 | 0.058 | 11.12 | *** | Supported |
To test the mediating effect of KSB, this study employed bootstrapping, a non-parametric resampling technique, using the bootstrap method available in Amos 26. Bootstrap resampling is a method that does not assume a normal distribution, involves iterative sampling and estimating from the dataset, and provides a more accurate test of indirect effects (Preacher & Hayes, 2008). When invoked by the bootstrap to conduct statistical significance tests, extremely large numbers of resamples are required. It takes an enormous number of resamples to perform statistical significance tests using the bootstrap (Fan, 2003). In this study, 5000 bootstrap resamples were utilised with a confidence interval level of 95%. The results of the analysis support the mediating role of KSB between POP and IWB. POP has a significant indirect effect on academics’ IWB by reducing KSB. The key findings related to the mediation hypothesis are presented in Table 7.
Hypotheses | Hypotheses Path | Indirect Estimate | S.E. | Bias | Lower | Upper | P-value | Final Remarks |
H4 | IWB<---KSB<---POP | -0.193 | 0.076 | -0.007 | -0.367 | -0.069 | 0.003 | Accepted |
5. Discussion
This study investigates how OP affect Chinese university academics’ IWB practices. The primary hypotheses of this study are as follows: POP among academics will significantly influence IWB (H1), POP among academics will significantly impact KSB (H2), KSB among academics will significantly influence IWB (H3), and KSB mediates the relationship between POP and IWB (H4). The proposed model demonstrated a good fit in the CFA stage.
The results of the SEM confirm that academics’ POP reduced positive work behaviours, decreased KSB with colleagues, and diminished IWB. However, KSB has a positive impact on academics’ IWB. These findings align with the perspectives of previous researchers (Akram et al., 2020; Chen et al., 2022).
Furthermore, due to the negative impact of OP on academics’ KSB, academics in the organisation reduce their access to helpful information. This limitation hinders academics from solving relevant problems through new knowledge and ideas, resulting in a corresponding decrease in IWB. This study suggests that OP explains approximately 13% of the variance in academics’ IWB. About 22% of the variance in academics’ KSB is attributed to OP, and approximately 68% of the variance in academics’ IWB is influenced by KSB. The positive impact of KS on IWB underscores its importance as a factor in enhancing academics’ IWB. The negative impact of OP highlights its significance as a deterrent to the proactive behaviour of Chinese university academics.
The significant regression paths provide the foundation for testing the mediation between the dependent and independent variables, as presented in Table 7. Finally, with an indirect estimate of 19.3% and p = 0.003, the mediation of KSB in the relationship between POP and IWB (H4) is deemed acceptable. The mediation path from OP to KSB and IWB suggests that KSB acts as a mediating effect between the relationship between OP and academics’ IWB.
6. Conclusions
The primary objective of this study is to apply organisational behaviour theories and methods, integrate organisational and individual factors, elucidate the impact of OP and KS on the IWB of academics in Chinese HEIs. Consequently, the study successfully captures the perspectives of personnel and organisational factors influencing academics’ IWB. Based on the above analysis, this study posits that while KSB has a positive and significant impact on academics’ IWB, OP exerts a negative and significant influence on both academics’ KSB and IWB. Additionally, KSB serves as a mediator in the relationship between POP and academics’ IWB. In other words, beyond directly affecting academics’ KSB and IWB negatively, POP further impacts academics’ IWB by reducing KSB. Therefore, KS is an essential factor in encouraging academics to be involved in IWB and cannot be triggered automatically, and the organisational environment should be improved to encourage KS. In addition, individual behaviour is influenced by societal values and norms and how individuals perceive their environment and process information (Chiu, 1995). In the context of China’s collectivist and paternalistic cultural background, organisations hold significant importance for individuals. They provide social engagement activities for individuals and facilitate developing and maintaining relationships among employees and between the organisation and its employees (Chandra, 2012). Therefore, organisations should regulate power and related procedures to reduce the occurrence of OP and weaken the negative impact of OP.
7. Contributions and Implications
This study contributes both theoretically and practically to the IWB. Theoretically, it introduces a mediation analysis, demonstrating the mediating role of KS between OP and academics’ IWB. This represents how OP, by reducing KS, further diminishes the IWB of university academics. It enhances understanding of how OP affects IWB, specifying its impact on Chinese university academics’ IWB.
On a practical level, the study proposes several managerial recommendations.
Firstly, it highlights the role of OP in academic’ IWB. Particularly in Chinese HEIs, the detrimental effects of OP warrant managerial attention. Therefore, the study suggests that managers should pay special attention to OP, delineate the boundaries between political and non-political behaviours, and mitigate the negative impact of OP on academic innovation. This, in turn, would foster a conducive environment where academics are more inclined to engage in IWB, ultimately elevating the innovation levels within HEIs.
Furthermore, the study underscores the contribution of KSB to academics’ IWB, acting as a mediator in the relationship between OP and IWB. Thus, OP directly affects IWB negatively and exacerbates its negative impact through its adverse effect on KSB. Therefore, management should, on the one hand, control political behaviour within the organisation, ensuring that organisational power operates transparently and minimises the adverse effects of OP. On the other hand, it is crucial to encourage academics to engage in regular knowledge exchange and sharing, fostering a collaborative and trust-based work environment. This approach positions ethical conduct against self-serving OPB, promoting KSB, and implementing IWB.
8. Study Limitations and Future Research Suggestions
Despite researchers strengthening the directional hypotheses through the lenses of COR and SET, the cross-sectional design restricts in-depth exploration of specific causal relationships between variables. Future research should undertake longitudinal studies to establish more robust causal relationships among the research variables.
Furthermore, knowledge sharing is the only mediator in this study. Other factors may mediate the relationship between OP and knowledge sharing. In particular, the relationship between OP and KS is inconsistent. The previous study predicted the positive effects of OP and KS (Rodriguez et al., 2024). However, this study found a negative relationship between OP and KS. Thus, the mechanism between OP and KS can be explored further.
Additionally, in terms of research variables, future studies may explore the impact of different forms of OP and the boundary effects of related mechanisms, warranting a more thorough investigation, and the effects of OP and KS on academics’ IWB in the contexts of other organisations be investigated.
The data used to support the research findings are available from the corresponding author upon.
The authors declare no conflicts of interest.
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