Original Research

The role of affective commitment in promoting knowledge sharing in Zimbabwean higher education

Audrey Dumbura, Serife Eyupoglu

Received: 08 May 2024; Accepted: 19 Feb. 2025; Published: 12 Apr. 2025

Copyright: © 2025. The Author(s). Licensee: AOSIS.
This is an Open Access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Purpose: This study explores the effect of affective commitment on knowledge-sharing behaviour (KSB), highlighting the role of positive and negative affect (emotions) in shaping this relationship in higher educational institutions. A robust knowledge-sharing environment fosters decent work encouraging institutional members to collaborate and share knowledge for mutual success.

Design/methodology/approach: The study employed a cross-sectional design, with cluster sampling encompassing five universities in Zimbabwe. Data were collected via an electronic questionnaire distributed to academic staff, ensuring convenience and minimising response bias. A cover page provided a debriefing on the study’s purpose.

Findings/results: Statistical findings show a significant relationship between affect and knowledge sharing. They also affirm a positive correlation between high affective commitment and elevated KSB.

Practical implications: The study advises practitioners and managers of higher educational institutions to foster KSB through sustainable decent work, which encompasses worker rights, better working conditions and increased skill development. Encouraging emotional bonds, staff welfare and recognition of knowledge as intellectual capital are crucial for organisational success.

Originality/value: The study seeks to enhance KSB literature by adding affect and affective commitment as new variables. Additionally, it explores the impact of affective commitment on knowledge sharing within higher educational institutions, particularly in the context of Zimbabwe, a non-Western, sub-Saharan country, thereby laying a foundation for future research that examines cultural differences in similar variables.

Keywords: positive affect; negative affect; affective commitment; knowledge sharing; decent work; sustainable education; cognitive behavioural theory; higher educational institutions.

Introduction

International development policy and practice between 2015 and 2030 will be directed by the Sustainable Development Goals (SDGs), which were taken up by the United Nations General Assembly (UNGA) in 2015. The tenets of the SDGs state that social, economic and environmental sustainability challenges should all be given equal weight. The eighth SDG focuses on equitable compensation for equal labour of equal value, decent work for all men and women, and full and worthwhile employment, including youth and anyone with disabilities. Decent work, which encourages sustained economic growth, increased productivity and technological innovation, is the primary theme of this study. The three dimensions of decent work show a human-centric approach to productivity that is pivotal in reaching organisational goals on a base level and, in turn, global goals. It is particularly noticeable in personnel knowledge management, which values each employee’s unique knowledge resources and elevates them to the status of an important part of the company’s intellectual capital. This strengthens the positions held by personnel and increases their chances of receiving decent treatment at work (Podgórny, 2018). As a guiding factor for achieving objectives and sustainability, knowledge management and, specifically, knowledge sharing serve as a critical tool and assets (Goswami & Agrawal, 2023). In addition, workers are more inclined to impart information in a suitable setting that provides decent work (Motta et al., 2023). Therefore, the interrelationship of decent work and knowledge sharing is pivotal in reaching the global goal.

Witherspoon et al. (2013) stated that knowledge sharing is an elementary unit for the success of organisations and is crucial to their very survival. Considering how crucial knowledge sharing is, it is essential, therefore, to explore the elements that impact knowledge-sharing behaviours (KSBs). These elements consist of individual traits of the knowledge holders, the organisational climate and the group characteristics within the organisations. Several empirical studies have been conducted on personal characteristics such as demographics (Amin et al., 2011; Boateng et al., 2015), personality traits (Akbar et al., 2023; Cabera et al., 2006), common vision, self-efficacy, loyalty, trust (Le et al., 2023; Zeng et al., 2014) and organisational commitment (Fayda-Kinik, 2022; Yesil, 2014). However, a shortcoming within the literature is identified regarding the relationship between affective commitment (a critical element of organisational commitment) and knowledge sharing. Organisational commitment results in knowledge sharing within the institution (Ng, 2022; Tennakoon et al., 2022). It can be in the forms of affective, persistent and normative dedication. The delicate process of knowledge sharing requires the engagement of the participants. Therefore, the emphasis in knowledge management research has turned towards people-centric topics, such as affective commitment (Cabrera et al., 2006).

Knowledge-sharing activities are shown to have cognitive, social, physical and emotional dimensions. In knowledge organisations, the risk of non-recognition and stealing of intellectual capital is highly likely. In this sense, knowledge sharing is considered to be a risky behaviour. Several variables that influence risk-taking behaviour are mediated by emotions and not mental processes, such as the underlying sentiment, the time between decisions and results, and the vivid manner in which the result is imagined in the mind (Loewenstein et al., 2001). Emotions, or ‘affect’, are pivotal in interpersonal interactions among employees that foster knowledge-sharing habits. People also try to keep up connections by controlling other people’s perceptions or emotions (Turnley & Bolino, 2001). Hence, it is important to look at the elements influencing the decision-making process regarding knowledge sharing.

In today’s globalised and diversified landscape, higher education has evolved into an international arena where knowledge is a cornerstone of institutional competitiveness. Knowledge sharing enables higher educational institutions to stay relevant, adapt to emerging trends and address complex challenges collaboratively. Moreover, cultivating a robust knowledge-sharing environment is instrumental in fostering ‘decent work’ principles within these institutions. This, in turn, leads to a more supportive and inclusive workplace culture where individuals feel valued, respected and empowered, thus contributing to overall well-being and sustainable organisational growth. Also, when employees experience decent work conditions, they are more inclined to feel engaged and committed to their organisation, fostering a greater readiness to engage in knowledge-sharing activities and collaborate with colleagues for mutual success.

In light of the above, this study seeks to better understand the effect of affective commitment on knowledge sharing, as well as the role of positive and negative affect in shaping the affective commitment–knowledge-sharing relationship. Recognising the critical implications of this relationship in achieving both organisational objectives and broader global sustainability targets, this study seeks to examine the key variables influencing these interactions. Higher education institutions, as the epitome of knowledge organisations, make them an ideal choice for addressing gaps in the literature. Furthermore, whereas previous studies have mostly concentrated on Western countries, this study looks at higher educational institutions in Zimbabwe, a sub-Saharan African nation that has not received enough attention in the existing body of research. Finally, this study attempts to understand the affective commitment, knowledge sharing and positive and negative affect nexus, drawing on cognitive behavioural theory. Consequently, the findings of this study are expected to contribute to the literature on knowledge sharing in higher educational institutions in sub-Saharan Africa by shedding light on the crucial role that affective commitment plays in facilitating knowledge sharing, as well as the influential role of affect in shaping this relationship. This area has been relatively underexplored in academic research.

The following sections will include a review of the body of literature on the variables of this study, a presentation of the hypotheses, specifics of the methodology used and a discussion of the results. The study’s limitations, acknowledgements and the importance of the findings are finally examined, along with potential directions for further research.

Literature review and hypothesis development

Investigating the causes of knowledge sharing is crucial because it reveals elements that favourably influence people’s intents and actions, which are necessary for long-term organisational development and financial success (Witherspoon et al., 2013). Subsequently, this review will define knowledge sharing and its importance for the success of an organisation, especially in promoting creativity and teamwork. The article then looks at the affective dimensions and how they influence KSB, including the roles of positive affect, negative affect and affective commitment. It draws attention to important research gaps and the limited investigation of these dynamics in non-Western contexts, particularly in sub-Saharan Africa. To provide a foundation for understanding the complex interactions among these variables, the review concludes by outlining the hypotheses and presenting the theoretical model supporting this investigation.

Knowledge sharing

Knowledge sharing is the transfer of task insight and data to an individual, enabling one to collaborate, find solutions, generate novel concepts or carry out rules or guidelines (Santos et al., 2015). Business people must comprehend the factors and mechanisms that motivate individuals to express their invaluable information to others to encourage KSB (Razak et al., 2016). While sharing knowledge improves organisational performance, very few businesses have succeeded in putting the approach into practice. Concerning the implementation of successful plans, organisations may fail because of improper knowledge sharing among colleagues (Lekhawipat et al., 2018).

Sharing knowledge is essential to developing an innovative culture in organisations (Kumar et al., 2024). According to Obermayer and Toth (2020), knowledge sharing, a process essential to an organisation’s optimal goal fulfilment, involves focusing on three important areas: individual, organisational and technology. Trust (Hosen et al., 2023), reciprocal relationships (Aldaheri, 2023), the intention to share information (Zenk, 2022) and emotions (Luqman et al., 2023) are among the individual dimensions. The organisational dimension consists of affective commitment (Karim, 2023), organisational structure (Lee, 2023) and managerial support (Le, 2024). All information and communications technology (ICT) is included in the technological component (Abdelwhab et al., 2019). The main focus of this study is on two of the above-stated variables of knowledge sharing, namely affect (emotions) and affective commitment, which will be discussed next.

Affect

According to Watson et al. (1988), the two primary dimensions of affect are positive affect (PA) and negative affect (NA). The Positive and Negative Affect Schedule (PANAS) quantifies these aspects, which are essential to comprehending emotional events. The emotions listed in the above scale will be used in this study.

Positive affect

Positive affect is described as the tendency of an individual to feel enthusiastic, awake or dynamic. Higher positive affect is the condition of being more energised and focusing on enjoying life (Watson et al., 1988). The cognitive benefits of positive affect are considered in the context of impacts on social interaction, which demonstrates that positive affect promotes interpersonal understanding, sharing and assistance. Studies have been conducted regarding how psychological factors influence individuals’ emotional experiences, which consequently affect their readiness to share knowledge and their ability to do their jobs. Chan et al. (2023) found that in strategic decision-making contexts, both positive and negative emotions, particularly excitement and anxiety have a favourable impact on information-sharing intentions and group knowledge sharing. Organisational knowledge sharing is greatly impacted by trust, which fosters long-term competitive advantage (Capestro et al., 2024). Comfort as an emotion, especially when provided by the organisation, can boost workers’ readiness to share knowledge and encourage employee knowledge sharing (Wang, 2016). Pride and empathy positively impact the intention to share knowledge, willingness and behaviour (Van Den Hooff et al., 2012). Akgün et al. (2017) asserted that the emotions of employees are barriers to knowledge sharing. While considering surprise, joy and interest, Savolainen (2015) concluded that contextual elements that influence knowledge sharing include emotions. Pride, joy, interest, surprise, excitement, comfort and empathy have been concentrated on in the literature, overshadowing the larger array of other positive emotions that could have an impact on knowledge exchange; therefore, the aim of this study is to include all the emotions from PANAS:

H1: There is a positive relationship between positive affect and KSB.

Negative affect

Negative affect is a state of distress and disillusion. People with higher negative affect express anger, disgust, guilt and fear (Berkowitz, 1990). Aversion to sharing knowledge is not always facilitated by negative emotions. Strong risk aversion and concern about sharing knowledge can result from unfavourable past experiences. Furthermore, obstacles may arise from perfectionism, a fear of making mistakes or a fear of looking foolish (Tsui et al., 2009). Results from a study on the efficiency of cross-cultural communication, cultural acuity and information exchange by Presbitero and Attar (2018) indicate that anxiety is strongly and adversely associated with knowledge sharing. Team arousal, where team members’ anxiety levels are high, together with stress, has been isolated as a determinant in the withholding of knowledge within organisations (Wang & Chang, 2018). Conversely, environments where negative emotions are freely expressed during knowledge-sharing activities, namely in-person or online brainstorming, as well as project management, have been shown to better facilitate knowledge sharing (Van Den Hooff et al., 2012):

H2: There is a relationship between negative affect and KSB.

Affective commitment

According to organisational behaviour literature, affective commitment can be described as a person’s identification, emotional connection and participation in the organisation and its objectives (Meyer et al., 1997). A shared sense of accountability for both achievements and setbacks fosters affective connections among team members in collaborative initiatives, which greatly improves the sharing of tacit knowledge (Nguyen, 2024). Affective commitment is considered to be the most prominent measurement in predicting an extensive range of employee behavioural outcomes such as reduced absenteeism, decreased employee turnover, organisational citizen behaviour and knowledge sharing (Herold, 2006). Earlier studies have discussed the impact of affective commitment on knowledge sharing. Ahmad et al. (2019) found that knowledge sharing is favourably correlated with employee recognition and emotional connection, and trust is a strong and constructive mediator between affective commitment and knowledge sharing. Academic job characteristics influence KSB by encouraging affective commitment (Karim, 2023). In addition, Fait et al. (2023) identified a positive relationship between affective commitment and knowledge sharing. Personnel who have higher affective commitment score higher in KSBs, which in turn favours institutional psychological ownership (Li et al., 2015). Acknowledgement and appreciation of personnel’s organisational affective commitment motivate knowledge sharing (Ahmad et al., 2019). Curado et al. (2019), in Portuguese small and medium enterprises, identified a significantly positive correlation between affective commitment and knowledge sharing.

According to the above-stated research, affective commitment typically and largely amplifies the exchange of knowledge within organisations. The company culture, therefore, must provide a safe emotional environment, in addition to other decent work aspects, which leads to employees sharing information:

H3: There is a relationship between affective commitment and KSB.

The grand theory underpinning this study is cognitive behavioural theory. According to Hupp et al. (2008), cognitive behaviour is used to represent covert behaviour inclusive of emotions, thoughts and images. There are three propositions within the cognitive-behavioural framework: overt, covert and the environment (Dobson & Dozois, 2021). The principal objective of cognitive behavioural theory is examining how particular thoughts generate specific feelings, which subsequently lead to specific behavioural reactions. The cognitive behavioural framework, according to Kendall (2006), highlights the patterns provided by the environment that influence personal information gathering and actions thereafter. Apart from external factors, an individual’s emotions and ideas are thought to have a distinct impact on behaviour. Behaviour is the result of intricate interactions between individual and environmental influences (McGuire, 1995). However, in the cognitive behavioural framework, the individual is characterised regarding interactions between cognitive, affective and behavioural characteristics rather than solely regarding characteristics of classic personality theories. Thus, this research aims to look at the numerous aspects of cognitive behavioural theory to explain the interaction of the different variables. Firstly, the relationship that exists between an employee and their workplace leads to and maintains affective commitment towards the organisation. Secondly, the different emotions (positive and negative affect) influence the controlled processing in the decision-making processes within the workplace. Lastly, the KSB may or may not materialise owing to the interaction of these variables.

Research model

The ultimate research purpose is to analyse the relationships between the variables as indicated in the following Figure 1 illustrating the interrelationships of the hypotheses posed for this research.

FIGURE 1: Theoretical model.

Methodology

This study’s quantitative research methodology is consistent with the examination of well-established constructs including affective commitment, negative affect and positive affect (Barnard & Pendock, 2013).

Sample and procedures

This study’s target population consisted of all 13 927 full-time academic faculty members in Zimbabwe. With a population of 13 927 and a 5% margin of error, the Yamane’s (1967) calculation yielded a sample size of 389 people; hence, a sample of 400 was employed (Sharma, 2020). Only five of Zimbabwe’s 30 universities – a mix of state and private institutions – are globally accredited, and those were the subject of this investigation. A questionnaire was distributed electronically to the academic staff (respondents) at their convenience minimising response bias. A cover page was attached to the questionnaire to provide adequate debriefing regarding the aim of the study and to indicate that answering the questionnaire would serve as informed consent. A total of 315 academic staff out of the 400 who were sent the questionnaire completed the survey. The final sample size was 302 after excluding the surveys with missing data. The respondents’ demographic profile showed that 57.1% of them were men and 42.9% were women. Most of the respondents were aged between 45 years and 54 years (54.1%), 21.5% of the respondents were aged between 35 years and 44 years and 15.85% of the respondents were aged between 55 years and 64 years. When asked what degree of schooling they had completed most recently, 3.3% said tertiary/university, and 96.7% said postgraduate. For comprehensive sample information, see Table 1.

Measurement scales

A self-administered questionnaire that consisted of four sub-parts that measure socio-demographic data, PANAS, Knowledge-Sharing Behavior Scale (KSBS) and Affective Commitment Scale was employed. A socio-demographic questionnaire was distributed to obtain participants’ characteristics, namely age, gender, level of education, marital status, university affiliation and nationality.

Affective commitment was measured using the Affective Commitment Scale (Allen & Meyer, 1990), an 8-item questionnaire on the level of the perceived relationship of an employee towards an organisation. A 5-point Likert scale was used to measure the responses ranging from 1 = strongly agree to 5 = strongly disagree. The items include (1) I would be very happy to spend the rest of my career with this organisation. This specific scale was chosen because studies that have utilised it have found that it generates a single factor with high reliability (Merrit, 2012).

KSB was measured using the Knowledge-Sharing Behavior Scale (Yi, 2009). A 28-item questionnaire with 4 dimensions: (1) written contributions – I submit documents and reports, (2) organisational communications – Propose problem-solving suggestions in team meetings, (3) personal interactions – Engage in long-term coaching relationships with junior employees and (4) community of practices – Meet with community members to work to encourage excellence in community’s practice. The scoring is a five-point frequency response ranging from 1 = strongly agree to 5 = strongly disagree. Oliveira et al. (2015) while studying alternative methods of measuring KSB, the KSBS is the most reliable when measuring both tacit and explicit knowledge sharing. It was therefore selected as the best choice for this study.

Affect was measured using the PANAS (Watson et al., 1988). This is a 20-item self-report measure including Positive Affectivity (PA, 10 items) and Negative Affectivity (NA, 10 items). The scale utilises a self-report Likert format ranging from 1 = strongly agree to 5 = strongly disagree. Items include (1) Interested and (11) Irritable. Individuals who score highly on PA are considered to have higher positive affect and those that score highly on NA are considered to have higher negative affect. According to Crawford and Henry (2004), the PANAS was developed to measure the affect in various circumstances, such as present, over the past day, week or year, in general (on average). This scale can evaluate current affect, dispositional or trait affect, emotional fluctuations over time, or emotional responses to events. The choice to use PANAS was because it is among the most widely utilised scales to measure mood or emotion.

Analytical strategy

The data obtained were analysed through the Statistical Package for Social Sciences, v. 26 (SPSS) and Analysis of Moment Structures, v.26 (AMOS). To determine whether the research model was appropriate for testing the hypotheses, we employed structural equation modelling (SEM) via AMOS. Through comparing the routes between the individual interactions concerning other factors, the method, which focuses on a confirmatory factor analysis (CFA) standpoint, assesses the distinctiveness of the scales and measures the validity and reliability of the model (Schumacker, 2004). Firstly, the control variables were excluded from this analysis step as they did not meet the study’s pertinent significance level (Savalei, 2006).

Ethical considerations

Ethical clearance to conduct this study was obtained from the Near East University Scientific Research Ethics Committee (No. YDÜ/SB/2020/850).

Results

Common method variance

Before assessing the validity of the standard sample, an exploratory factor analysis (EFA) was carried out to assess retention of affective commitment, affect and KSB, ensuring the Kaiser–Meyer–Olkin test surpassed 0.70 (0.958) and Bartlett’s test exhibited a p-value below 0.01 (0.000) (Jöreskog, 2007). According to Hair et al. (2020), items with a cross-loading of 0.40 or higher should be kept in the study for interpretation purposes. Common method variance (CMV) may be an issue in some self-report studies, and to combat this, pointing out potential biases and implementing controls are essential (Chang et al. 2020). It is vital therefore that we did this process to amplify the strength of the measurement constructs. Using exploratory factor analysis (EFA), extracting affect, affective commitment and knowledge-sharing variables, one component was rated at less than half of the variance, that is, 42.85% of the total. Using AMOS, we conducted the common latent component test and found 1.8% < 3%. Therefore, using both methods we discovered that CMV had no significant influence on the study findings.

Construct validity

The scale’s validity and reliability were tested. The unique quality of the research variables and model fit were tested using two confirmatory factor analyses. The models both contained all four variables (AC, PA, NA and KSB) and were placed in unique groups, then second-order groups, and run. Each factor’s factor loadings were examined for significance, and items that did not meet the goodness-of-fit requirements were eliminated (Hair et al., 2014). Consequently, a four-factor model was studied, retaining KSB (4 items), affective commitment (4 items), positive affect (8 items), and negative affect (6 items). Table 2 lists the CFA items that were retained along with their item range.

By using AMOS to conduct confirmatory factor analysis (CFA), which examined the measurement models, factor loadings were assessed for every item during the CFA, and one item that had insufficient factor loading (< 0.50) was excluded. The hypothesised model’s overall goodness-of-fit was evaluated using a variety of model-fit metrics, such as root mean square error of approximation (RMSEA), Tucker–Lewis index (TLI), standardised root mean square residual (SRMR), goodness-of-fit index (GFI), comparative fit index (CFI) and Chi-square mean (CMIN)/degrees of freedom (df). Interestingly, every value was within widely acknowledged bounds (Bentler, 1990; Hu & Bentler, 1998; Schermelleh-Engel et al., 2003; Ullman, 2001).

The indices listed in Table 3 demonstrate how well the four-factor model comprising of positive affect, negative affect and KSB and affective commitment fit the data. The results show a good model fit. Probability = 0.000 (acceptable if the value is insignificant) (Bagozzi & Yi, 2012). CMIN/df = 1.838 (acceptable if < 2) (Ullman, 2001). Goodness-of-fit index = 0.899 (acceptable, slightly below the recommended > 90; Hair et al., 2010). Comparative fit index = 0.963 (acceptable > 0.90; Bentler, 1990). Tucker–Lewis index = 0.958 (acceptable > 0.90 Bentler, 1990). Standardised root mean square residual = 0.0341 (acceptable < 0.08; Hu & Bentler, 1998). Root mean square error of approximation = 0.053 (acceptable < 0.08; Hu & Bentler, 1998). The alternative model, which treated positive affect, negative affect and second-order factors, did not yield significant variances, that is, PCMIN/df = 1.830 and CFI = 0.963.

Table 4 explains the model validity measures as provided by Gaskin and Lim (2016). We executed the models in AMOS, achieving results of standardised regression and covariances (Sürücü & Maslakci, 2020), then subsequently employed the use of James Gaskin’s statistical tools to assess the discriminant and convergent validity of the components concerning vital indicators, namely maximum shared variance (MSV), average variance extracted (AVE) and composite reliability (CR).

The findings showed the validity of the model. AVE values were greater than 0.50, demonstrating convergent validity. CR values were higher than 0.70 showing good reliability. Maximum shared variance values were higher than AVE values therefore, discriminant validity was adequate. In addition, AVE values were higher than the squared correlation between constructs therefore, discriminant validity was strong. All of these findings corroborate the model’s adherence to Hu and Bentler’s (1999) stringent requirements for convergent validity, reliability and discriminant validity (AVE > 0.50, CR > 0.70 and MSV < AVE).

Descriptive statistics

Table 5 presents descriptive statistics that include the study variables’ means, standard deviations and correlations. The interpretation of the positive and negative correlation degrees was to interpret positive values as an increase in the corresponding variable and negative values as a decrease in its quantity. Positive affect and KSB were found to have a strong and statistically significant positive correlation (r = 0.746, p < 0.001), which offers strong support for Hypothesis 1 (H1). This result implies that a higher inclination for peers to share knowledge is linked to an increase in positive affect. There was a large and statistically significant adverse correlation between KSB and negative affect (r = −0.713, p < 0.001), providing strong support for Hypothesis 2 (H2). This finding illustrates a relationship between a rise in negative affect and a decreased propensity for peers to share knowledge. Substantial support for Hypothesis 3 (H3) was obtained when it was discovered that affective commitment and KSB had a statistically significant positive association (r = 0.780, p < 0.001). This finding depicts a relationship between increased affective commitment and peers’ propensity to share knowledge.

Hypothesis testing

With the use of SPSS regression analysis, we tested hypotheses 1, 2 and 3. H1: There is a relationship between positive affect and KSB. The dependent variable KSB was regressed on predicting variable PA to test hypothesis H1. PA significantly predicted KSB, F (1, 300) = 377.519, p < 0.001, which indicates that PA can play a significant role in shaping KSB (b = 0.847, p < 0.001). These results direct the positive affect of the KSB. Moreover, the R² = 557 depicts that the model explains 55.7% of the variance in KSB.

H2: There is a relationship between negative affect and KSB. The evidence suggests that negative affect has a significant impact on information-sharing practices and also looks into the connection between negative affect and KSB. Regressing the dependent variable, KSB, on the predictor, negative affect (NA), tests the hypothesis (H2). The derived F-statistic (F [1, 300] = 310.726, p < 0.001) indicates that KSB is significantly predicted by negative affect, which depicts NA playing a significant role in shaping KSB (b = −0.761, p < 0.001). These results show that KSB and negative affect are negatively correlated. Additionally, the R² value of 0.509 signifies that the model accounts for 50.9% of the variance in KSB. This substantial explanatory power underscores the considerable influence of negative affect in elucidating the observed variation in KSB.

Lastly, H3: There is a relationship between affective commitment and KSB. The hypothesis tests if affective commitment has a significant impact on KSB. The dependent variable KSB was regressed on predicting variable AC to test hypothesis H1. Affective commitment significantly predicted KSB, F (1, 300) = 465.531, p < 0.001, and this indicates that AC can have a significant impact on shaping KSB (b = 0.740, p < 0.001). Moreover, the R² = 0.608 indicates that the model explains 60.8% of the variance in KSB. Based on the results, we conclude a significant relationship between affective commitment and KSB. Table 6 illustrates the summary of the findings.

Discussion

Based on cognitive behavioural theory, this study explores the effect of affect and affective commitment on KSB. Hypotheses 1 to 3 were validated. This study found significant relationships between positive affect, negative affect and KSB. In particular, the study shows that more negatively affectively inclined workers tend to share less knowledge with others. On the contrary, a positive correlation is observed concerning positive affectivity, and this correlation is complex because of the interaction between security, risk and trust factors. This emphasises how important it is for organisations to think beyond only the physical health of their workforce. An all-encompassing strategy is indicated, one that includes careful assessment, assistance and the creation of a setting that supports psychological sustainability in the workplace.

This study emphasises how crucial affecive commitment is to encouraging KSB in higher educational settings. The findings show that affective commitment encourages information exchange among co-workers because people feel their growth and the organisation’s progress are complementary. People who have high affective commitment also typically have high degrees of engagement and devotion to their organisations. Meyer et al. (1989) highlighted the connection between these practices and enhanced performance and outcomes inside the company. It plays a crucial role in fostering innovation and creativity, which subsequently supports the development of long-lasting business procedures. In addition, Gupta (2015) emphasised that these positive emotions account for effective leadership styles, personal development and enhanced team performance. This supports our results in that positive affect should be conserved in human resource management practices. This consideration, while encouraging knowledge-sharing practices, subsequently encourages innovation, mentorship and overall organisational success. One of the keystones for enhancing resilience in cooperatives is the unique member connection, in which members function as both owners and users. This unique relationship aligns organisational design more closely with member requirements, delivering a major competitive advantage (Briscoe & Ward, 2000). Moreover, Byrne et al. (2012) showed that knowledge from relationship marketing literature, as opposed to cooperative-specific literature, provides deeper insight into the dynamics of the credit organisation–member relationship.

Theoretical implications

Firstly, this study contributes to the theoretical conversation by including affect and affective commitment to the framework of knowledge sharing. Through merging insights from psychology, organisational behaviour and knowledge management, the study offers a comprehensive framework. While prior research focused on the antecedents of affective commitment (Cownie, 2019; Gao-Urhahn et al., 2016; Jayasingam et al., 2016; Jussila et al., 2012), this study diverges by emphasising the behavioural and psychological characteristics of human capital for the benefit of management.

Secondly, this study is ground-breaking as it is the first research to look at an array of both negative and positive affect (interest, excitement, strength, enthusiasm, alertness, feeling inspired, activeness, determination, distress, feeling upset, irritability, jitteriness, nervousness and fear). Previous research has predominantly concentrated on specific emotions in the context of organisational performance, specifically examining distinct emotions such as pride and empathy (Van Den Hooff et al., 2012), pride and anxiety (Luqman et al., 2023), and enthusiasm and anxiety (Chan et al., 2023). This divergence from earlier studies represents a distinctive addition to the academic discourse regarding the dynamics of knowledge-sharing practices.

Conclusively, our research makes a distinctive contribution to the KSB literature not only by adding affect and affective commitment as variables but also by contextualising it within a non-Western, specifically sub-Saharan Africa, milieu. Our investigation concentrates on academic colleagues within the higher education sector in Zimbabwe, an area largely devoid of pertinent scholarly enquiry. This deliberate focus addresses a notable gap in the existing literature, establishing our study as a foundational reference for future research seeking cultural differentiation in the exploration of similar variables within diverse contexts.

Practical implications

The evidence from this study lays the groundwork for understanding the interconnected aspects of attitude, behaviour and cognition in the context of KSB. These results hold considerable practical implications for academicians, practitioners and Human Resource (HR) managers.

For practitioners and HR managers, top management is advised to establish social and collaborative platforms within the organisation that facilitate KSB. Acknowledging and respecting employees’ feelings are crucial in creating a conducive environment for knowledge exchange. Effective teams and groups should be formed to encourage learning and knowledge sharing. Technical knowledge ought to be recorded and structured schedules should be implemented for employees to engage in learning and sharing activities. On-the-job training, accompanied by technical handouts, can enhance employees’ knowledge and skills. Recognising the pivotal role of HR managers, special incentives should be provided to them for transferring to the workforce technical and domain-specific information, as suggested by Whicker and Andrews (2004). Furthermore, efforts to strengthen affective commitment between employees and the organisational structure are recommended.

Limitations

Despite providing valuable insights, this study has limitations. Firstly, the study explored the direct relationships between the variables. However, future research may examine the mediating and moderating effect of the effect on the relationship between affective commitment and knowledge sharing. Secondly, we propose that this study be repeated in other economic sectors.

Conclusion

In conclusion, this study advances the discourse on KSB by investigating affect and affective commitment within Zimbabwe’s higher education sector. Demonstrating a positive link between affective commitment and KSBs, our study pioneers the exploration of affect as a contributing variable in organisational knowledge-sharing dynamics. These results have important theoretical and practical ramifications, especially for non-Western contexts. Drawing from cognitive-behavioural theory, our findings emphasise the crucial influence of emotions on decision-making in knowledg-sharing contexts. Practical implications for practitioners include the establishment of social platforms and structured training, with cultural differentiation considered in the African context. This research not only expands theoretical frameworks but also lays the groundwork for future investigations into affective commitment and KSBs in diverse organisational and cultural settings.

Acknowledgements

This article is partially based on A.D.’s doctoral dissertation, entitled ‘Affect and Affective Commitment, Antecedents to Knowledge Creation and Knowledge-Sharing? A Study of University Personnel’, towards the degree of Doctor of Philosophy in Innovation and Knowledge Management in the Innovation and Knowledge Management Department, Near East University, Cyprus, with supervisor Professor S. Eyupoglu.

The authors declare that they have no financial or personal relationships that may have inappropriately influenced them in writing this article.

A.D. and S.E. conceptualised the study and contributed to the study methodology; A.D. contributed to the data collection, analysis and writing – original draft preparation; S.E. contributed to the writing – review and editing and supervision. A.D. and S.E. read and agreed to the published version of the manuscript.

This research received no specific grant from any funding agency in the public, commercial or not-for-profit sectors.

The data that support the findings of this study are available from the corresponding author, A.D. upon reasonable request.

The views and opinions expressed in this article are those of the authors and are the product of professional research. They do not necessarily reflect the official policy or position of any affiliated institution, funder, agency or that of the publisher. The authors are responsible for this study’s results, findings and content.

References