Decoding Factors Influencing Knowledge Sharing Among Indonesian Scholars

: This study examines the determinant factors of knowledge-sharing intention and behaviour among academics in Indonesia. Academics need to compete and excel in global competition amidst obstacles such as qualification, competency, and working culture. The study integrated the Theory of Planned Behavior, Social Capital Theory, and perceived cost. A questionnaire was distributed online to academics, and 239 respondents were obtained. Data analysis was undertaken by using SEM-PLS. The result found that all the variables examined were determined to be significant, except commitment, extrinsic reward, and facilitating condition. The importance of social networks, trust, self-efficacy, management support, social media use, and perceived cost among academics. The result can help management better understand how to create a knowledge-sharing environment in the institution, significantly higher education institutions with open and distance learning systems.


INTRODUCTION
Higher education institutions are the centre of knowledge.Higher education's input and output is the knowledge generated from academics, which makes it different from other organisations (Afshar Jalili & Ghaleh, 2020;Pedro et al., 2020).Knowledge is a power of competitive edge; an organisation should focus on information efficiency and knowledge creation (Farooq & Vij, 2019).The responsibility of higher education institutions is to create and disseminate knowledge (Afshar Jalili & Ghaleh, 2020).A knowledge management approach can facilitate the transition toward a knowledge-based economy, improving the 411 education program that is implicated in the university's overall performance (Afshar Jalili & Ghaleh, 2020;Rehman & Iqbal, 2020).Higher education institutions are regarded as places for academics to share their ideas and knowledge.Sharing knowledge fosters innovative work behaviour (Kim & Park, 2017).Thus, to maximise intellectual capital and compete in the global market, higher education must now use knowledge sharing to benefit students and society (Azeem et al., 2021;Mahdi et al., 2019).
Knowledge sharing is a reciprocal interaction that requires both the giver and the taker of knowledge.Consequently, it involves gathering and imparting knowledge to others (Akram et al., 2020).However, one complex knowledge management process could be improved sharing (Tirana & Tjakraatmadja, 2019).Many academics assume their knowledge is valuable, so it cannot be shared (Fauzi, Nya-Ling et al., 2018).A study by (Butt & Ahmad, 2019) found that individual, interpersonal, and corporate factors influenced knowledge sharing.A study by (Nguyen et al., 2022) found that conflict, job insecurity, and cynicism raise the possibility of individuals hiding their knowledge.To encourage knowledge-sharing, the study of (Al-Kurdi et al., 2020) discovered that the organisational setting of academics has a potent impact on their knowledge-sharing practices.Transformational leadership could also reduce the effect of conflict and support creating a favourable working environment (Nguyen et al., 2022).Thus, it is crucial to have an enhanced understanding of the value of knowledge sharing for acceleration and effectiveness in decision-making.
This study investigates the factors behind the knowledge-sharing intention and knowledge-sharing behaviour by integrating Planned Behavior and Social Capital Theory.Integrating those theories allows for a deeper comprehension of factors determining knowledge sharing between academics.The theory of Planned behaviour has been extensively used in the social and behavioural sciences.Three types of consideration guide human behaviour: beliefs of the behaviour's most likely effect (attitude), beliefs of how others expect their behaviour (subjective norm), and beliefs about the availability of facilitate that support the performance of behaviour (perceived behavioural control) (Bosnjak et al., 2020).Meanwhile, social capital theory is subject to social structures and relationships (Abbasi et al., 2021).Based on this theory, social capital subsists between individual and their connection, standards, networks, and organisational structures that collaborate for economic, social, and psychological advantages (Gannon & Roberts, 2020).The networking of organisations supports initiating and preserving the relationship, motivates individuals to join in activities that benefit each party, and offers chances for the development of communal capital (Birasnav et al., 2019).That theory can be used to understand the individual's behaviour and interaction with the community (Fauzi, Tan Nya-Ling et al., 2019).Therefore, the current study will identify the influencing factors of academics' knowledge-sharing intention, including attitude (i.e.commitment, social network, trust, extrinsic reward, and self-efficacy), subjective norm (i.e.management support), perceived behavioural control (i.e.facilitating condition and social media) and perceived cost.
Novelty.Based on the previous explanation, several studies have researched the crucial factors influencing knowledge-sharing intention and behaviour in an academic environment.The study will address several novelties.First, previous studies integrated the theories of TPB and SCT.This study adds extrinsic reward and self-efficacy as variables influencing knowledge-sharing attitudes.Extrinsic rewards are included to recognise the pragmatic aspect of knowledge sharing.At the same time, self-efficacy is included to recognise scholars' confidence in their capacity for knowledge sharing.Adding these variables will enrich understanding knowledge-sharing attitudes influenced by internal and external factors.Second, the subject of this study is academics in open and distance higher education in Indonesia.Most previous study subjects were academics in a country or at a university.There remains a need to discover knowledge-sharing factors in academic environments with distance learning as the modus for learning.The academics are assigned in different areas, either in headquarters or 39 areas in Indonesia.This condition led to different environments becoming interesting to explore.The academics are spread throughout Indonesia, with diverse characteristics and challenges such as individual competency and capability, working environment, and geographic location.It is critical to comprehend knowledge sharing in this organisation to boost knowledge-sharing practices to the advantage of academics and institutions.
The key focus of this study is to scrutinise factors determining Indonesian academics in knowledge sharing.The research question is: What factors influence knowledge-sharing intention and knowledge-sharing behaviour among academics in Indonesia?The subject of this study is academics at Universitas Terbuka (UT).The result of this study can be an important suggestion for management in proposing a knowledge-sharing strategy for their academics to advance knowledge-sharing practices in academic communities.These ultimately will benefit academic career development as well as increase organisational competitiveness.

THEORETICAL REVIEW
This study applied the theory of planned behaviour (TPB) and the social capital theory (SCT), widely used as the primary interplay elements that could influence academics' knowledge-sharing behaviour.This study also added perceived cost as a variable.
Social Capital Theory.Social capital is essential to company success and competitive advantage (Berraies et al., 2020).Social capital theory is any resource from an individual or group owned and acquired from strong relational networks (Donate et al., 2019).It stands for the networks and conventions that influence group behaviour (Berraies et al., 2020).A previous study found that trust and social networks positively impacted knowledge-sharing attitudes (Fauzi, Nya-Ling et al., 2018, 2019;Fauzi, Tan Nya-Ling et al., 2019).
Hypothesis Development.The study outlines 14 hypotheses.The following provides more details on the respective hypothesis.
Commitment.Commitment is the mental connection between the individual and their organisation (H.M. Aziz et al., 2021).Commitment towards academics' job will equip management to plan and manage programs related to knowledge sharing.Academics will put in the effort and time to participate in knowledge-sharing programs (Fauzi, Nya-Ling et al., 2019).The committed academic will be able to encounter the competition (Fauzi, Tan, et al., 2019).The previous study by (Luo et al., 2021) discovered that commitment significantly influences knowledge-sharing intention.Thus, this study intends the first hypothesis as follows: H1: Commitment has positively influenced attitudes toward knowledge sharing.
Social Network.The relationships between academics and non-academics within or outside higher education institutions are social networks (Fauzi, Nya-Ling et al., 2018).When academics collaborate with their network, inside or outside their institutions, it will increase new ideas and knowledge that will benefit their institution, students, and community (Fauzi, Nya-Ling et al., 2019).Previous studies (Almurqin et al., 2020;Chedid et al., 2020;Fauzi, Nya-Ling et al., 2018, 2019Fauzi, Tan Nya-Ling et al., 2019) found that the attitude toward knowledge sharing has been affected by positive and significant by social network.Thus, this study intends the second hypothesis as follows: H2: Social networks have positively influenced attitudes towards knowledge sharing.

Trust.
Trust is an essential variable of SCT.People will share their knowledge with people they trust (Fauzi, Nya-Ling et al., 2019).Previous studies (Fauzi, Nya-Ling, et al., 2018;2019;Fauzi, Tan Nya-Ling, et al., 2019;Hosen et al., 2020) found a strong connection between trust and attitude on knowledge sharing.With trust, the positive behaviour of knowledge sharing, such as increasing productivity, increasing self-awareness, and creating work-life balance, will be performed (Fauzi, Nya-Ling, et al., 2018).Therefore, this study intends the third hypothesis as follows: H3: Trust has positively influenced attitudes towards knowledge sharing.
Extrinsic Reward.The material rewards that staff members of an organisation could get for sharing their knowledge with other colleagues (Nguyen & Malik, 2020).The extrinsic rewards are akin to financial benefits such as salary, bonuses, commission, and promotion (Mikelsone et al., 2022;Nguyen & Malik, 2020).The organisation is to reward rewards knowledge-sharing through behaviour to ensure the knowledge remains in remission (Halisah et al., 2021).The study of (Jusoh & Alfawareh, 2020) found extrinsic reward as a crucial factor for knowledge sharing in all contexts of the organisation.Thus, the authors argue that those benefits motivate academics to share knowledge.Therefore, this study intends the fourth hypothesis as follows: H4: Extrinsic reward has positively influenced attitudes towards knowledge sharing.
Self-Efficacy.Self-efficacy means the belief that a person can achieve objectives in a particular manner (Syabarrudin et al., 2020).Academics with strong self-efficacy in knowledge sharing tend to take instruction in any format because they are confident they will succeed with their current knowledge (Mustika et al., 2022).Based on (Mafabi et al., 2017), one must possess a particular ability to engage in specific activities.Some previous studies found that self-efficacy positively and significantly impacts knowledge sharing (Arain et al., 2020;Bai et al., 2019;Mustika et al., 2022).Thus, the fifth hypothesis of this study is proposed as: H5: Self-efficacy has positively influenced attitudes towards knowledge sharing.
Management Support.Extensive support from management will motivate academics to share their knowledge with others.In higher education institutions, the management decides policy, rules, and regulations (Fauzi, Tan et al., 2019).Management might continuously promote knowledge sharing among staff members and offer necessary support (Rahoo et al., 2022).The kind of support can be in direct participation in the knowledgesharing program and activity and give academics appreciation for their work and effort (Fauzi, Tan, et al., 2018).The previous study (Chedid et al., 2022;Fauzi, Nya-Ling, et al., 2018, 2019;Fauzi, Tan Nya-Ling, et al., 2019) found that management support positively influenced subjective norms that led to knowledge sharing.Thus, the sixth hypothesis of this study is proposed as: H6: Management support has positively influenced subjective norms towards knowledge sharing.
It is a facilitating condition.Facilitating conditions is necessary to make a task easier (Sulaiman et al., 2022).Facilitating conditions are tools and a supportive atmosphere that can encourage and improve knowledge sharing.In this context, it includes the availability of hardware and software that support knowledge sharing (Fauzi, Nya-Ling et al., 2019;Fauzi, Tan Nya-Ling et al., 2019).The availability of those facilities will help academics share knowledge.Thus, the seventh hypothesis of this study is proposed as:

H7:
The facilitating condition has positively influenced perceived behavioural control towards knowledge sharing.Social Media Use.In the digital era, social media is part of the daily habit of communicating, socialising, and sharing thoughts.Social media is an easy and fast tool for sharing knowledge that academics can use (Fauzi, Nya-Ling et al., 2018).Social media is a powerful tool for those who do not have a background in information and technology but can afford many facilities to share their knowledge (N.E. A. Aziz et al., 2022).Networking can be done through social media, but it relies on their familiarity with it.The previous studies (Fauzi, Nya-Ling, et al., 2018, 2019;Fauzi, Tan Nya-Ling, et al., 2019;Hosen et al., 2020) found a significant influence of social media towards perceived behavioural control.Thereby, the eighth hypothesis of this study is proposed as: H8: Social media use has positively influenced perceived behavioural control towards knowledge sharing.
Attitude.Attitude positively influences individual intention (Ajzen et al., 2018).According to (Mousa et al., 2019), attitude is to what extent an individual has a favourable or bad knowledge-sharing evaluation.In academics, the favourable or lousy evaluation of knowledge-sharing behaviour is according to their beliefs in sharing (Jameel et al., 2021).The study of (Chedid et al. 2020;Fauzi, Nya-Ling et al., 2018, 2019Fauzi, Tan Nya-Ling et al., 2019;Hosen et al., 2020;Javaid et al., 2020;Rahman et al., 2018) proved the importance of attitude on knowledge sharing intention.The academic's positive attitude will increase their willingness to share their knowledge.Thus, the ninth hypothesis of this study is intended as: H9: Attitude has positively influenced knowledge-sharing intention.
Subjective Norm.Individual behaviour depends on how others perceive their behaviour (Ajzen et al., 2018).Subjective norms specify appropriate knowledge-sharing conduct (Obrenovic et al., 2022).In higher education, when the surrounding people think that knowledge sharing is good behaviour, academics would do that.In this study, the subjective norm is regarded as the perception of the rector, dean, director, and study program head that knowledge sharing is their encouragement.Previous studies by (Chedid et al. 2020;Fauzi, Nya-Ling et al., 2018, 2019Fauzi, Tan Nya-Ling et al., 2019Fullwood & Rowley, 2017;Hosen et al., 2020) have demonstrated that the intention to share knowledge is substantially subject to the subjective norm.Thus, the tenth hypothesis of this study is proposed as: H10: Subjective norm has positively influenced the intention of knowledge sharing.
They perceived Behavioral Control.Perceived behavioural control in knowledgesharing is the individual's perception of their capacity to perform knowledge-sharing behaviours (Fauzi, Nya-Ling, et al., 2018).It expresses how academics think they have the tools, abilities, and opportunities to accomplish a task.Perceived Behavioral Control encourages academic intentions by motivating people to take on tasks they see as having the potential for success (Fauzi, Nya-Ling et al., 2019).Previous studies by (Fauzi, Nya-Ling, et al., 20182019Fauzi Tan Nya-Ling et al., 2019) demonstrated a strong correlation between perceived behavioural control and knowledge sharing.Thus, the eleventh hypothesis of this study is proposed as: H11: Perceived behavioural control has positively influenced knowledge-sharing intention.
Perceived Cost.Academics' knowledge is their asset.Academics control their knowledge and whether it is shared (Fauzi, Nya-Ling et al., 2018).Then academics might think that knowledge sharing could waste their time and money, as previously proved (Fauzi, Nya-Ling et al., 2018;2019).In this study context, perceived cost is seen as contrary to (Fauzi, Nya-Ling, et al., 2018;2019) because the institutions will provide financial support.As academics, they must share knowledge.Perceived cost is seen as how academics put their time and effort as cost for knowledge sharing.So, the twelve hypotheses of this study are proposed as follows: H12: Perceived cost has positively influenced knowledge-sharing intention.Knowledge Sharing Intention.Previous studies (Chedid et al., 2020;Fauzi, Nya-Ling et al., 2018, 2019;Fauzi, Tan Nya-Ling et al., 2019) found positive and robust effects on knowledge-sharing intention and behaviour.Therefore, the thirteenth hypothesis of this study is proposed as: H13: Knowledge-sharing intention has positively influenced knowledge-sharing behaviour.
In addition to increasing intention, perceived behavioural control also directly impacts behaviour.When the intention to share is constant, then creating behaviour to do knowledge sharing (Fauzi, Nya-Ling, et al., 2019).Previous studies by (Fauzi, Nya-Ling, et al., 2018, 2019;Hosen et al., 2020) showed that perceived behavioural control positively and strongly impacts knowledge-sharing behaviour.Thus, the fourteenth hypothesis of this study is proposed as follows: H14: Perceived behavioural control has positively influenced knowledge-sharing behaviour.

Figure 1. Research Framework
Source: Author's construct As stated in the explanation above, the following Error!Reference source not found.is the framework of this present work.This present study developed 14 hypotheses, consisting of five constructs that influence attitudes, one that influences subjective norms, and two that influence perceived behavioural control.Based on TPB, attitudes, subjective norms, and perceived behavioural control influence knowledge-sharing intention, leading to knowledge-sharing behaviour.Perceived behavioural control also influences knowledgesharing behaviour.Last, perceived cost influences knowledge-sharing intention.

METHODS
Research Design.In this study, two types of research approaches quantitative and qualitative were combined in a process known as a mixed method (Melão & Reis, 2020).The sequential explanatory design approach was used in this procedure.Unproven theories were explained by gathering and examining quantitative evidence and then applying the qualitative method.Interviews with chosen informants yielded qualitative data (Muhdar et al., 2023).
Measurement.A theoretical model was applied to investigate knowledge sharing among academicians.We gathered primary data through an online questionnaire because it was the quickest and most efficient to get the responses.The developed questionnaire consisted of some questionnaire items.The items of commitment, social network, trust, management support, facilitating condition, social media use, attitude, subjective norm, perceived behavioural control, perceived cost, knowledge-sharing intention, and knowledge-sharing behaviour were acquired (Fauzi, Nya-Ling, et al., 2019).At the same time, the items of extrinsic rewards and self-efficacy were acquired from (Nguyen & Malik, 2020).
Data.This study collected primary data from academicians at Universitas Terbuka all over Indonesia using online questionnaires as the fastest and most efficient tool for responding and interviewing to validate the quantitative result.Online questionnaires were distributed from May 8, 2023 to June 3, 2023.Every item was assessed utilising a six-point quantitative rating scale, varying from strongly disagree (one) to agree (six).The questionnaire was delivered in Bahasa Indonesia.There were 239 valid responses by June 3, 2023, from 714 e-mails and WhatsApp Groups, with a response rate of 33.473 per cent.The characteristics of the sample by gender, education, function, length of work, faculty, and location can be seen in Table 1: 54.393 per cent of respondents were female, 77.406 per cent of respondents were master's degree, 46.862 per cent respondents were assistant professor (lektor), 35.565 per cent respondents came from Faculty of Law, Social, and Political Sciences, and 33.891 per cent respondents has been working for 1 to 5 years.

RESULTS
To assess and validate the theoretical model, the gathered data was scrutinised utilising Structural Equation Modeling (SEM) using Partial Least Square (PLS).Previous studies (Berraies et al., 2020;Fauzi, Tan et al., 2020;Fauzi, Nya-Ling, et al., 2018) used SEM to measure the structural model.PLS analysis comprises two steps: the measurement model and the structural model.The structural model was used to examine the hypotheses and construct testing, while the measurement model evaluated validity and reliability (Franque et al., 2021).
Measurement Model.The outer model was assessed using metrics such as convergence validity, construct validity, construct reliability, average variance extracted (AVE), discriminant validity, and cross-loading.The results are shown in Table 2. Convergent validity assessed the degree of interdependence among two measures of the same concept.An outer loading value of 0.700 or higher is considered highly satisfactory.However, an outer loading of 0.500 or higher is considered practically significant (J.F. Hair et al., 2019).From Table 2, all items or indicators of outer loading values are higher than 0.600, which means they are valid.It took two times of iterations to get this result by eliminating TR3 (trust).So, according to the validity of outer loading, the selected item or indicator is valid in convergent validity.All values of Cronbach's Alpha in Table 2 are more than 0.700, which indicates a reliable scale.The Composite Reliability (CR) result from Table 2 is more than 0.700, indicating good internal consistency.
Moreover, Average Variance Extracted (AVE) values greater than 0.500 were used to test the convergent validity.This indicates that these indicators elucidate more than half of their variance.The concept satisfies all conditions and can be applied to the assessment of the theoretical model.
The discriminant validity was examined using the Fornell-Larcker Criterion, Cross Loading Criterion, and Heterotrait-Monotrait Ratio of Correlation.The result of the Fornell-Larcker Criterion has been fulfilled by discriminant validity from the square root of AVE for each latent variable beyond the correlation between that latent variable and any other latent variable (J.F. Hair et al., 2019).There was also the fulfilment of the Cross-Loading Criterion (Purwanto & Sudargini, 2021), which is that any indicator variable's correlation with another latent variable should not be more significant than the indicator variable alone.Last, (J.Hair & Alamer, 2022) proposed that if the HTMT value is less than 0.900, it indicates established discriminant validity between a particular pair of reflective constructs.All the value of HTMT is lower than 0.900.The result of the measurement model proves the models' statistical distinctness and potential application in evaluating the structural model.These findings include strong internal consistency, reliability indicators, discriminant validity, and convergence validity.
Structural Model.A structural model was assessed to verify the hypotheses and construct.Figure 2 presents the research model result.The model explains 24.700 per cent of the variance in the attitude of knowledge sharing.Some variables are significant in determining attitude: social network, trust, and self-efficacy, thus supporting hypotheses 2, 3, and 5 (H2, H3, and H5).The remaining variables are insignificant in determining attitude: commitment and extrinsic reward, thus not supporting hypotheses 1 and 4 (H1 and H4).
The model explains 21.100 per cent of the variance in the subjective norm of knowledge sharing.Management support is statistically significant in determining subjective norms, thus supporting hypothesis 6 (H6).
The model explains 31.500 per cent of the variance in the perceived behavioural control of knowledge sharing.Social media use is statistically significant in determining perceived behavioural control, thus supporting hypothesis 8 (H8).Otherwise, the facilitating condition is insignificant in determining perceived behavioural control, thus not supporting hypothesis 7 (H7).The model explains 41.600 per cent of the variance in knowledge-sharing intention.The attitude, subjective norm, perceived behavioural control, and perceived cost are statistically significant in determining knowledge-sharing behaviour, thus supporting hypothesis 9 (H9), hypothesis 10 (H10), hypothesis 11 (H11), and hypothesis 13 (H13).
The model explains 59.700 per cent of the variance in knowledge-sharing behaviour.Knowledge-sharing intention and perceived behavioural control are statistically significant in determining knowledge-sharing behaviour, thus supporting hypotheses 12 (H12) and 14 (H14).
The most robust relationships, respectively, were knowledge-sharing intention on knowledge-sharing behaviour, social media use on perceived behavioural control, management support on the subjective norm, and subjective norm on knowledge-sharing intention.

DISCUSSION
According to data processing results, the determinant factor of knowledge sharing between academics in Indonesia has been appropriately addressed.The research model developed can effectively explain the significant role of several factors in knowledgesharing behaviour among academics in Indonesia.Fourteen hypotheses have been developed.The hypothesis result can be seen in Table 3.Of 14 hypotheses, 11 are significant, and three are not significant.Knowledge-sharing intention is the most robust explanatory variable of knowledge-sharing behaviour, followed by perceived behavioural control and perceived cost.The knowledge-sharing intention is explained by subjective norm as the strongest predictor, followed by perceived behavioural control, perceived cost, and attitude.Subjective norm is explained by management support.Perceived behavioural control is explained by social media use.Surprisingly, commitment and extrinsic reward do not explain attitude, and facilitating conditions do not explain perceived behavioural control.The following will discuss specifically each hypothesis.
The effect of commitment on attitude.The results show that commitment (H1) does not affect attitude.The commitment in this current study was related to how academics committed to the organisation, such as excitement to spend their career in the organisation, discuss their organisation with others, and a sense of belonging regarding the organisation's problems.Commitment is related to connecting with an organisation (H.M. Aziz et al., 2021) through loyalty, dedication, and identification with its goals and values.There are some possible explanations regarding the result.First, there needs to be more excitement regarding implementing knowledge sharing for organisations due to the nature of academic work and organisational culture.Academics may prioritise other things than sharing knowledge, such as personal interest, distance education management, and student admission.Second, academics are unwilling to share their knowledge because it is valuable.The competitive situation in an organisation might be the motivation to hide their knowledge.The last possible factor is academic workload and time constraints in organisational environments.It is suggested for management to nurture a collaborative culture in the organisation.Working together on the project, sharing ideas, and giving feedback in a group will encourage academics to share their knowledge and expertise with their colleagues.The result needs to be consistent with the study of (Luo et al., 2021), which found that commitment has a positive and significant impact towards the attitude of knowledge sharing.However, those studies focus on virtual communities in China, which tend to have the same interests to share.In contrast, knowledge sharing among academics in open and distance higher education is more complex, and more effort is needed to increase the excitement of knowledge sharing.
The effect of social networks on attitude.Social networks connect academics and non-academics inside or outside the organisation (Fauzi, Nya-Ling et al., 2018).Social networks (H2) positively and significantly impact the attitude toward knowledge sharing.It means academics believe that social networks are helpful for access to resources and information.The result suggests that academics use social networks to grab and disseminate new knowledge.Through social networks, academics can also update the valuable development of their field.Social networks can encourage academics to convey their knowledge, discuss, collaborate, and produce new knowledge by getting support and reinforcement from their networks.This result is consistent with the study of (Almurqin et al., 2020Chedid et al., 2020;Fauzi, Nya-Ling et al., 2018, 2019;Fauzi, Tan Nya-Ling et al., 2019).However, those studies focus on the public universities in Saudi Arabia, public universities in Portuguese, and public and private universities in Malaysia.This study focuses on open and distance higher education in Indonesia, where social networks are critical for learning activities.This study proves that social networks are essential for knowledge sharing, which can directly and indirectly improve the quality of learning activities.
The effect of trust on attitude.Trust (H3) has a positive and significant impact on the attitude of knowledge sharing.It shows that trust plays a central role in shaping attitudes by fostering open communication, mediating constructive responses and support, and mitigating the fear of knowledge loss.Academics will be more interested in sharing their knowledge with trusted others and, more importantly, for confidential information that will be misused if academics share with anyone (Hosen et al., 2020).The result suggests maintaining open communication between academics by acting with integrity, honesty, and regard for other people's viewpoints.The result is consistent with (Fauzi, Nya-Ling, et al., 2018, 2019;Fauzi, Tan Nya-Ling, et al., 2019;Hosen et al., 2020).Still, trust has become a crucial factor that affects attitudes toward knowledge sharing.In the context of UT, with academics spread all over Indonesia, trust becomes a catalyst that accelerates knowledge sharing.
The effect of extrinsic rewards on attitude.Surprisingly, extrinsic reward (H4) does not affect attitude toward knowledge sharing extrinsic reward in this context regarding salary, bonus, and promotion.Extrinsic rewards may not be the main reason for academics to share their knowledge, but they must share their knowledge.There are many 'other rewards' given by organisations so that academics feel the rewards for sharing knowledge are ordinary and do not motivate them to share knowledge.Academics also need time and effort to share knowledge and other primary responsibilities, reducing the urge to be involved in knowledge-sharing activities.As knowledge sharing is the key to competitive advantage, the result suggests that management evaluate the strategy and focus on knowledge sharing.This result is inconsistent because extrinsic rewards are less effective than predicted (Jusoh & Alfawareh, 2020).Other than using extrinsic rewards to motivate academics to share knowledge, it might be considered to focus on intrinsic motivation and investing in the professional development of academics.
The effect of self-efficacy on attitude.Self-efficacy (H5) is found to have a positive and significant impact on an attitude of knowledge sharing.Self-efficacy is akin to the academic's conviction of their ability to accomplish tasks and achieve goals.This confidence enhances academics' keenness to share their knowledge with others because they deem themselves to have valuable insight.Besides that, the belief in their communication skill to articulate their ideas clearly, engage in discussions, and deliver complex concepts effectively will increase their self-efficacy in knowledge sharing attitude.The result suggests maintaining a collaborative culture and improving the capacity and capability of academics in their field.It is aligned with previous studies on sharing (Arain et al., 2020;Bai et al., 2019;Mustika et al., 2022), which assess managers and subordinates in different organisational contexts.In this study.The same positive result is found in the academic environment between academics.
The effect of management support on subjective norm.Management support characterises subjective norms.The statistical result shows that management support (H6) significantly influences subjective norms.It means the perception and expectation of management, in this context, rector/dean/director/program head, will shape how academics act.Management has a role in influencing academic perceptions and attitudes towards sharing knowledge and encouraging the sharing of organisational values.The result suggests that management's leadership in endorsing and supporting knowledge-sharing initiatives and becoming role models are seen as a signal that knowledge is valued and expected behaviour.The result is aligned with studies of (Chedid et al. 2022;Fauzi, Nya-Ling et al., 2018, 2019Fauzi, Tan Nya-Ling et al., 2019).It is suggested that academics agree to share their knowledge and insert the knowledge-sharing activity in each academic and administrative process (Chedid et al., 2020;Fauzi, Nya-Ling et al., 2018).
The effect of facilitating condition on perceived behavioural control.Facilitating conditions are not significant on perceived behavioural control (H7).In this context, facilitating conditions are related to accessibility to hardware and software.The use of both may be determined by perceived ease of use or familiarity with the technology.Instead of optimising that software, academics use their time to learn more about how to use the software.Different academic ages will also influence how fast they learn.
Additionally, changes and updates of both also overwhelm academics to use.The result suggests that in developing hardware or software, it is also essential to increase the user's capability in this context of academics to optimise that hardware and software.Hardware and software are not only for digitalising data but also help academics increase their knowledge-sharing productivity.The result needs to be consistent with the earlier studies of (Fauzi, Nya-Ling, et al., 2019;Fauzi, Tan Nya-Ling, et al., 2019).This does not mean facilitating is unimportant; instead, achieving what has been planned takes more time and effort.
The effect of social media on perceived behavioural control.In contrast to the facilitating conditions, social media use has a positive and significant impact towards perceived behavioural control (H8).Social media allows academics to expand the opportunities to interact with people, facilitate idea exchange, collaborate, and share knowledge.Nowadays, using social media for those things in platforms such as Facebook, Twitter, Instagram, and TikTok is easier, faster, and reaches a larger audience than conventional methods.Social media also can be used to stay updated on information related to their fields.Lastly, social media can be a platform to get feedback, validate, and recognise academics' contributions to knowledge sharing.The result suggests that knowledge sharing is more accessible when the tools are used daily.It is consistent with earlier studies (Fauzi, Nya-Ling et al., 2018, 2019;Fauzi, Tan Nya-Ling et al., 2019;Hosen et al., 2020).The barrier of knowledge sharing in open and distance higher education with academics across Indonesia can be solved using social media.
The effect of attitude on knowledge sharing intention.Attitude has a statistically significant and positive influence on knowledge-sharing intention (H9).A positive attitude encourages academics to share knowledge sharing.The role of social networks, trust, and self-efficacy has increased the effect of attitude on knowledge sharing.Academics perceive knowledge sharing as an essential and valuable activity contributing to knowledge development, career growth, and academic achievement.They recognise the benefits of knowledge sharing, such as initiating collaboration, cultivating innovation, and enhancing the quality of research.Besides that, academics have been aware that knowledge sharing is an integral part of their academic identity and responsibility.This result suggests the crucial role of attitude in shaping academics' intentions to engage in knowledge-sharing activities.The result is consistent with (Chedid et al. 2020;Fauzi, Nya-Ling et al., 2018, 2019;Fauzi, Tan Nya-Ling et al., 2019;Hosen et al., 2020;Javaid et al., 2020;Rahman et al., 2018).The positive attitude toward knowledge-sharing has increased knowledge-sharing intention among academics in higher education.
The effect of subjective norm on knowledge sharing intention.The statistical result showed that subjective norms significantly and positively influence knowledge-sharing intention (H10).The expectation of surroundings, such as peers, colleagues, and supervisors regarding knowledge sharing, influence academics.It encourages academics to align their intentions with social expectations.Additionally, peers', colleagues', and supervisors' behaviour becomes a reference point for academics to share knowledge.A good environment supports academics in knowledge sharing.This result is aligned with earlier studies of (Chedid et al., 2020;Fauzi, Nya-Ling, et al., 2018, 2019;Fauzi, Tan Nya-Ling, et al., 2019;Fullwood & Rowley, 2017;Hosen et al., 2020).Creating academic groups to share their knowledge or progress of work in a specific schedule will increase the pressure and intention to share the knowledge.
The effect of perceived behavioural control on knowledge sharing intention.Perceived behavioural control positively and significantly impacts knowledge-sharing intention (H11).Academics have a sense of competence and capability to overcome obstacles and challenges associated with knowledge sharing.Moreover, academics also have access to requisite resources that make them feel empowered to perform knowledge sharing.It means that the belief in their ability will have a beneficial impact on knowledge-sharing intention.This result is aligned with the previous studies of (Fauzi, Nya-Ling et al., 2018, 2019;and Fauzi, Tan Nya-Ling et al., 2019).Academics need to affirm themselves when facing challenges to boost their intention of knowledge sharing.
The effect of perceived cost on knowledge sharing intention.Perceived cost positively and significantly impacts knowledge-sharing intention (H12).Academics have been aware of spending their time and effort sharing knowledge, such as sharing knowledge with peers and colleagues.Academics believe that shared knowledge will give more significant benefits and can open new opportunities for individual career development or organisational reputations.The result of the prediction contrasts with the result of (Fauzi, Nya-Ling, et al., 2018, 2019), where time and effort become a barrier to sharing knowledge.The result shows the academics' dedication to their work.
The effect of knowledge sharing intention on knowledge sharing behaviour.Knowledge-sharing behaviour is predicted by knowledge-sharing intention (H13).Knowledge-sharing intentions become the strongest predictor of knowledge-sharing behaviour.This means that the theory of planned behaviour can predict behaviour in the context of knowledge sharing in higher education institutions.As mentioned by (Fauzi, Nya-Ling, et al., 2018), the individual factor (such as commitment, social network, trust, extrinsic reward, and self-efficacy), organisational support (such as management support), and technological support (such as facilitating condition and social media use) become the variables' predictor of academics' knowledge sharing intention.The result is consistent with (Chedid et al. 2020;Fauzi, Nya-Ling et al., 2018, 2019Fauzi, Tan Nya-Ling et al., 2019), who found the same finding but in a different context.
The effect of perceived behavioural control on knowledge sharing behaviour.Perceived behavioural control becomes the predictor of knowledge-sharing behaviour (H14).The result is aligned with earlier studies (Fauzi, Nya-Ling, et al., 2018, 2019;Hosen et al., 2020).Academics are more potentially engrossed in knowledge-sharing behaviour when they apprehend themselves and can manage it.Academics who feel confident in sharing knowledge effectively are likelier to participate in such behaviour.
Theoretical Implications.This study presents a combinative model of the theory of planned behaviour and social capital theory that explores knowledge-sharing behaviour.The results support the significance of the additional variable from (Arain et al., 2020Bai et al., 2019;Fauzi, Tan Nya-Ling et al., 2019;Jusoh & Alfawareh, 2020Mustika et al., 2019) in academic behaviour to knowledge sharing.As a result, this foundational contribution makes it possible to use models in new research contexts.
Practical Implications.Our results enlighten management and help us better understand factors to optimise academic knowledge-sharing behaviour.Increasing organisational competitiveness by evaluating and implementing advanced steps to optimise these factors is essential.For example, social networks, trust, and self-efficacy were predictors of attitudes towards knowledge sharing.Thus, organisations should collaborate with other institutions that can be initiated by study programs, faculty, or top management.Academics can also participate in associations to hear and communicate updates regarding their disciplines and join conferences or seminars.These activities can boost academics' social network, trust, and confidence.
Management support is a predictor of subjective norms towards knowledge sharing.Thus, management needs to be transparent and fair by communicating policies and procedures related to knowledge sharing and hearing the problems of academics.Moreover, the academics in UT are across Indonesia, so it is essential to support a knowledge-sharing environment for academics in headquarters or the UT area.The role of management as a leader is to give academics support and examples, which will also encourage academics toward knowledge sharing.Extrinsic rewards are found to be insignificant in the attitude toward knowledge sharing.One of the reasons is that academics can obtain many other rewards besides extrinsic rewards from knowledge sharing.This situation might reduce the motivation of academics toward knowledge sharing.Thus, it is also crucial for management to build an atmosphere that encourages academics to do knowledge sharing by firstly increasing their awareness of knowledge sharing and formulating new strategies to boost that and, for example, creating small communities in study programs that regularly report research progress as a trigger for knowledge sharing.Last, social media use has been discovered to predict perceived behavioural control.Millennials and Gen Z are active in social media.The increasing number of those generations as academics can strengthen institutions in circulating knowledge through social media as the easiest and fastest tool for knowledge sharing.Those generations can also collaborate with previous generations to increase the number of academics who share knowledge.

CONCLUSION
Based on the evidence presented, factors that influence knowledge-sharing behaviour are knowledge-sharing intention and perceived behavioural control.Attitude, subjective norm, perceived behavioural control, and perceived cost positively impact knowledgesharing intention.The empirical results also show that attitude is influenced by social networks, trust, and self-efficacy; the subjective norm is influenced by management support; and perceived behavioural control is influenced by social media use.To increase knowledge sharing culture among academics, management should evaluate current strategies by paying attention to social networks, trust, self-efficacy, management support and social media.Management should ensure that collaboration with other institutions runs well, give more opportunities for academics to join any academic forum, and encourage academics to share their knowledge on any social media platform.
This study only included academics of an open and distance higher education institution in Indonesia.Future research could include non-open and distance higher education institutions with different backgrounds.Future research can also focus on organisational factors and transformational leadership, which are limited in this study and need to be explored.

ACKNOWLEDGEMENT
We thank LPPM Universitas Terbuka for funding this research.

Table 2 .
Measurement Model

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Hypothesis Result