Abstract
Purpose
This paper aims to investigate whether relational agency fosters relational people management using evidence from micro and small enterprises in Uganda, an African developing country. Specifically, the paper examines whether the individual relational agency dimensions (shared learning, mutual cooperation, collective efficacy and interaction enablement) also affect relational people management.
Design/methodology/approach
A cross-sectional survey design using a quantitative approach was used in this study. Data were collected from 241 micro and small enterprises in Uganda using a structured questionnaire and were analysed using the Statistical Package for Social Scientists.
Findings
The results indicate that relational agency is positively and significantly associated with relational people management. Findings further indicated that collective efficacy, mutual cooperation, shared learning and interaction enablement individually matter in relational people management.
Originality/value
To the best of the authors’ knowledge, this study may be among the first to demonstrate that relational agency and its individual dimensions (interaction enablement, shared learning, mutual cooperation and collective efficacy) foster relational people management in the context of micro and small enterprises of Uganda, an African developing country. Consequently, this study contributes to both theory and literature via the cultural historical activity theory, hence, adding to the scant existing literature on relational agency and relational people management.
Keywords
Citation
Nalweyiso, G., Mafabi, S., Kagaari, J., Munene, J., Ntayi, J. and Abaho, E. (2022), "Relational agency and relational people management: evidence from Uganda’s micro and small enterprises", Asia Pacific Journal of Innovation and Entrepreneurship, Vol. 16 No. 1, pp. 51-68. https://doi.org/10.1108/APJIE-01-2022-0004
Publisher
:Emerald Publishing Limited
Copyright © 2022, Grace Nalweyiso, Samuel Mafabi, James Kagaari, John Munene, Joseph Ntayi and Ernest Abaho.
License
Published in Asia Pacific Journal of Innovation and Entrepreneurship. Published by Emerald Publishing Limited. This article is published under the Creative Commons Attribution (CC BY 4.0) licence. Anyone may reproduce, distribute, translate and create derivative works of this article (for both commercial and non-commercial purposes), subject to full attribution to the original publication and authors. The full terms of this licence maybe seen at http://creativecommons.org/licences/by/4.0/legalcode
1. Introduction
Individuals spend a considerable amount of time in the workplace, making it necessary to nurture positive relationships at work (Debray and Spencer-Oatey, 2022). In micro and small enterprises, owner-managers and employees work closely with one another to undertake tasks. This implies that the quality of interpersonal relationships has a tremendous impact on the overall performance of these enterprises (Beqiri and Aziri, 2021). According to Baluku et al. (2016) and Nalweyiso et al. (2022), nurturing positive interpersonal relationships in the workplace contributes to the success and survival of enterprises. Owner-managers and employees depict positive interpersonal relationships in the form of having confidence in others, extending social credit, establishing friendly ties and portraying relational competencies (Mascarenhas et al., 2010; Shier et al., 2018). Relational people management involves mechanisms used by employees and managers to nurture and retain positive relationships among people for purposes of undertaking tasks. This is portrayed in the form of assistance both at work and in their personal lives, as well as creating a friendly work atmosphere (Pandita et al., 2017). It is also manifested as social support, trust building in relationships at the workplace (Shier et al., 2018) and conflict resolution skills (Benitez, 2018). These interpersonal relationships are considered a vital source of knowledge upon which enterprises can thrive (Basyouni and Parkinson, 2022). Ozer and Zhang (2021) found that positive interpersonal relationships at work enable people to generate ideas. Caldwell (2021) noted that during the COVID-19 pandemic, people in higher education relied more on good workplace relationships with colleagues. Another study found that colleagues who support one another are more likely to exhibit engagement behaviors in their workplaces (ter Hoeven and van Zoonen, 2020). Furthermore, a study on employees with ailments indicated that positive interpersonal relationships with colleagues demonstrated in the form of: social support and friendships, improved their health, well-being and retention at work (Holland and Collins, 2020). Similarly, Hanafin et al. (2022) found that positive co-worker relationships led to high levels of job satisfaction among nurses. According to Xiao-Ying et al. (2022), positive workplace relationships enable employees to engage in proactive behaviors. In addition, employees on leave revealed that they looked forward to returning to work to see their colleagues, given their good interpersonal relationships (Tjulin and MacEachen, 2016).
Despite the significance of having positive workplace relationships, the practices that promote them are under studied (Kandade et al., 2019). Less research attention has been given to the nurturing of positive workplace relationships (Debray and Spencer-Oatey, 2022). Specifically, there is a dearth of research focusing on the antecedents that foster relational people management, mostly in the context of micro and small enterprises (Harney and Alkhalaf, 2021; McGrath et al., 2017). Against that backdrop, scholars of workplace relationships have called upon the use of a broad range of theories to study the concept, specifically in the context of micro and small enterprises (Heaphy et al., 2018). Consequently, this paper is premised on the cultural historical activity theory (CHAT), where relational agency is used to explain relational people management in the micro and small enterprises of Uganda, an African developing country. Research has indicated that micro and small enterprises substantially contribute to the development of economies worldwide (Ali et al., 2019). In developing countries such as Uganda, they make up about 75% of the national gross domestic product (GDP) and use the country’s largest population of workers (Uganda Business Impact Survey, 2020). Despite such contributions, the failure rate of these enterprises remains alarming (Aketch et al., 2017). Research has shown that enterprises that survive and are successful nurture positive workplace relationships (Cuéllar-molina et al., 2019). Therefore, this paper contributes to the relational people management conceptual model proposed by Nalweyiso et al. (2022), who also called for statistical testing.
While the dimensions underlying relational agency are empirically underdeveloped, in this study, we draw on existing literature (Ben-Harush and Orland-Barak, 2019; Edwards, 2010) to advance shared learning (Leicher and Mulder, 2016), collective efficacy (Bandura, 2006), mutual cooperation and interaction enablement (Anderson and West, 1998) as relational agency’s key attributes. Few studies have explored the individual roles of these dimensions, as applied to this paper to relational people management in Ugandan micro and small enterprises. The authors also note that majority of the prior studies on relational agency (Ben-Harush and Orland-Barak, 2019; Edwards, 2007, 2009, 2010, 2017; Keeffe, 2017) focused on settings such as schools, communities, child care services, health care and higher education. Therefore, we argue that; it is quite timely to examine the role of relational agency and its individual dimensions in relational people management in the context of Ugandan micro and small enterprises.
Thus, the need to try to fill the above gaps triggered this study. The purpose of this study is twofold. First, we aim to provide an explanation of how relational agency fosters relational people management. Second, we examine whether the individual relational agency dimensions as used in this study matter in relational people management. A quantitative survey of 241 micro and small enterprises was used to gather evidence from Uganda. The findings indicate that relational agency and relational people management are positively and significantly associated. The results also show that the individual dimensions of relational agency used in this study, matter in relational people management.
This study’s findings contribute to the present literature on relational people management (Harney and Alkhalaf, 2021; Heaphy et al., 2018; Mallet and Wapshott, 2014; McGrath et al., 2017; Nalweyiso et al., 2022) by indicating, perhaps for the first time, that relational agency is positively and significantly associated with relational people management using evidence from Uganda. This study further contributes to the current literature by examining the role of the individual dimensions of relational agency in relational people management.
The rest of the paper is organized as follows. The next section is the literature review and the presentation of the theoretical foundation. This is followed by the methodology, results and discussion. Finally, the conclusion, implications, limitations of the study and areas for further research are presented.
2. Literature review
2.1 Theoretical foundation
This paper adopts Engestrom’s (1987) CHAT as the theoretical lens for fostering relational people management in micro and small enterprises. According to CHAT, human activity is a joint effort mirrored through agency. The activity system comprises of several individuals who cooperate to realize a mutual objective. The actors in the activity system no longer act as individuals but as agents who are interdependent (Engestrom, 1987). They have confidence in their combined abilities, constantly share information and respect everyone’s perceptions. From these group discussions, a shared solution that focuses on the object is derived (Bandura, 2000; Edwards, 2010; Engestrom, 1987). The theory is illustrated as an object-oriented collective activity system that is culturally mediated. It consists of: the subjects, rules, community, division of labor, mediating artifacts, the object and its subsequent outcomes. These components may switch positions from time to time depending on the dynamism within the activity system. Hence, the new model of activity theory focuses on object-oriented and artifact-mediated collective activity system as its unit of analysis (Engestrom, 1987).
Within the activity system, are multiple individuals whose combined efforts enable accomplishment of the object. This implies that human activity goes beyond individual actions to portray mutual representation. Individual actions are executed within a social framework called a “society” or “community” (Engeström, 1999). This is because in collective activity joint efforts, far exceed the sum of individual contributions (Engeström, 1999). This collective endeavor is a clear reflection of human agency also termed as “human activity,” which is relational in nature and characterizes the activity system (Engestrom, 1987). In the activity system, various individuals engage in discussions in the form of heated debates. These portray support and inconsistencies or contradictions as each individual puts their view forward. Such dialogues are ultimately aimed at a mutual response toward the object (Engeström, 2001b). These manifestations enable positive relationships to be nurtured in the workplace.
2.2 Hypotheses development
2.2.1 Relational agency and relational people management.
Relational agency is conceptualized as the synergy that emerges from collective activity when undertaking joint tasks (Bandura, 2000; Burkitt, 2016; Edwards, 2010). Individuals discover that the ability to overcome complex problems is embedded in collective efforts; hence, they need to cooperate with one another. In addition, the concept entails a conviction in collective capabilities to obtain the desired results (Bandura, 2000). It is also operationalized in terms of collective learning, in which individuals align their own interpretations with others’ understandings from which collective competence emerges (Edwards, 2010). These collective encounters are perceived as the glue that maintains relationships (Goldstein, 1999). During the COVID-19 pandemic, organizations embraced remote work, joint meetings and virtual discussions which enabled people to assist one another and minimize conflicts (Jamsen et al., 2022). One study found that individuals are more motivated to work together in established worthwhile connections. Such stability enables relationships to thrive through trust building and the creation of subsequent bonds (Melamed and Simpson, 2016). For a school, the emphasis is on joint concerns of all parties rather than teachers only. Once all the stakeholders in a school cooperate and make sacrifices for the sake of joint endeavors, quality relationships based on trust and strong bonds are established (Jo, 2014). As individuals work together and align their own interpretations with others’ perspectives, they become aware of each other’s capabilities. Consequently, they come to understand who to approach for a specific kind of support. In one study, different professionals worked together with women to enable them to handle their life challenges such as domestic violence. It was found that women who benefited from collective ideas, extended support to other women who faced similar problems (Edwards and Mackenzie, 2008). In addition, during agency endeavors, individuals reached a certain level of realistic agreement through free and open exchanges. Such an atmosphere enabled trust to be built and friendly ties to be strengthened among individuals (Edwards, 2010). A study on small and medium enterprises (SMEs) indicated that when owner-managers encourage collaborative working; they put themselves in a position to nurture positive relationships through strong bonds (Cuéllar-molina et al., 2019). Nalweyiso et al. (2022) also found that when people work hand in hand, they create friendships, build trust, support one another and amicably resolve disagreements. Based on the foregoing debate, we hypothesize the following:
Relational agency is positively related to relational people management.
2.2.2 Collective efficacy and relational people management.
Collective efficacy entails people’s shared awareness of the potential of joint efforts to accomplish tasks (Bandura, 2006; Goddard, 2002; Goddard et al., 2000). When people have confidence in their joint efforts, they are likely to resolve misunderstandings among themselves amicably and assist one another (Dubrow et al., 2018). A study among teachers in Israel revealed that those with a shared belief in their collective capabilities were more likely to exhibit trust among faculty members (Schwabsky et al., 2019). It is also noted that when people have collective confidence in their joint capabilities, they tend to discuss private matters, feel at home with others and build trust worthy relationships (Vassilev et al., 2019). Therefore, high levels of collective efficacy among people at work enable members to extend their support to one another. Following the foregoing debates, we hypothesize the following:
Collective efficacy is positively related to relational people management.
2.2.3 Mutual cooperation and relational people management.
Mutual cooperation involves identifying individuals’ unique abilities and creating room for interdependence among them at work (Anderson and West, 1998). In situations of interactions premised on cooperation, individuals are in a position to improve their interpersonal competencies. Such mutual circumstances help individuals acknowledge that either party is affected by the other, and hence, they recognize the need to improve their relational skills (Jordan, 2020). Another study, indicated that cooperation among support staff in a university is vital for nurturing trustworthy relationships (Gibbs and Kharouf, 2020). For teams in which there is interdependence, it is important for members to handle conflicts and support each other (DeChurch et al., 2013). This is because, in such settings people are conversant with each other (Rico et al., 2009). As indicated, employees whose work is interdependent tend to portray relational conduct in the form of assistance (Janz et al., 1997). In situations of high job interdependence where the tasks and work outcomes of one individual are influenced by the performance of other people, there is a display of positive work behaviors such as conflict handling (Sahu, 2018). In addition, individuals who perform interdependent tasks are likely to extend support towards others. This is because they acknowledge that they need one another to achieve their independent targets (Allen et al., 2003). Similarly, a study among nurses during the COVID-19 pandemic, found that the interdependent nature of their work enabled co-workers to support one another in the workplace (Leon and Baskin, 2022). Therefore, we hypothesize the following:
Mutual cooperation is positively related to relational people management.
2.2.4 Shared learning and relational people management.
Shared learning entails individuals collectively reflecting on and sharing knowledge as they work (Leicher and Mulder, 2016). A study among high school students found that when they study in small groups, chances are high that they will portray good interpersonal competencies (Moradi et al., 2018). Furthermore, students who study collaboratively tend to assist one another (Gillies, 2003). A study among hospital doctors revealed that promoting participatory learning approaches is vital. When such professionals share their experiences, they support one another, from which collective competence emerges, vital for their work (Claret et al., 2020). Even in instances of self-regulated learning, such endeavors are collectively influenced. Through their contributions, individuals support one another and build trustworthy relationships (Littlejohn et al., 2012). To improve school performance by increasing instructional capacity, there is a need to consider aspects such as information and knowledge sharing. These become the foundation for developing mutual trust. In a school setting, such mutual trust is built among principals, teachers, colleagues and students (Adams, 2013). Therefore, we hypothesize the following:
Shared learning is positively related to relational people management.
2.2.5 Interaction enablement and relational people management.
Interaction enablement involves creating an atmosphere that allows individuals across all levels of work to associate with one another (Anderson and West, 1998). When people engage in various interactions in the workplace, trust in others is built. This is because these avenues give people an opportunity to nurture relationships with others (Cui et al., 2015). Similarly, in a study among MBA students, “troubles talk” interactions which entail conversing about challenges led to the establishment of close and trust worthy relationships (Debray and Spencer-Oatey, 2022). Another study on SMEs indicated, when owner-managers encourage interactions during work, they nurture positive relationships (Cuéllar-molina et al., 2019). These constructive interactions sprout and nurture productive relationships. In the workplace, it is vital to create an atmosphere where frequent interactions can thrive for the purpose of developing lasting interpersonal relationships (Reich and Hershcovis, 2011). In support of this, Heaphy and Dutton (2008) noted that relationships begin with and are retained from repeated interactions. For work groups, where individuals work together most of the time, shared interactions result in strong relationships manifested in the form of joint trust among members (Nahapiet and Ghoshal, 1998). Research has also indicated that regular physical interactions in the form of meetings create an opportunity for superiors to know how their subordinates are doing (Terkamo-Moisio et al., 2021). Therefore, we hypothesize the following:
Interaction enablement is positively related to relational people management.
3. Methodology
3.1 Research design, population and sample
A cross- sectional, questionnaire survey and correlational research design were used. This enabled the data to be collected and analyzed at a single point in time. A correlational design was chosen because the study involved examining the relationships between the study variables. As per Yamane’s (1973) sample determination guidelines, the study focused on a sample of 399 micro and small enterprises from Kampala and the other central region of Uganda. These two regions have the highest number of such enterprises (Uganda Bureau of Statistics – Report on the Census of Business Establishments, 2010/2011). To select the enterprises, a systematic random sampling technique was used (Neuman, 2007). Owner-managers and employees formed the unit of inquiry and a minimum of two respondents per enterprise was targeted. Useable questionnaires were received from 241 micro and small enterprises, which represented a response rate of 60%. Most enterprises that participated had been in existence for 10 years and above at 44% of the sample. In terms of size, the majority of the enterprises (75.5%) employed between 20 and 49 people, whereas 24.5% employed less than 20. Finally, in terms of location, a majority of the enterprises (51.9%) were located in Kampala, and 48.1% were found in the other central region.
3.2 Control for common methods bias
In this study, we controlled for common methods bias using procedural remedies as recommended by Podsakoff et al. (2003), to minimize the measurement error. First, the questionnaire items from previous scholars were adapted to suit the current study context. We used diverse response scale categories that included; the confirming scale, frequency scale, numbers scale and truth scale. Items from the different constructs were mixed up across the various response scale categories based on their verbal anchors. In addition, we used codes to represent variable titles and their respective measures to encourage objectivity. In other words, the names of the variables and dimensions did not appear in the questionnaire. Finally, the questionnaire for the endogenous variable was administered two weeks after that of the exogenous variables.
3.3 Questionnaire, measures and control variables
To collect data, we used a structured questionnaire anchored on a six-point Likert scale. A structured questionnaire is regarded as a suitable instrument for large samples (Sekaran, 2003). The six-point Likert scale was preferred because it reduces response biases associated with scales that have a mid-point (Dolnicar et al., 2011). We developed our questionnaire after reviewing the existing literature. All study variables were measured basing on those used in prior research. Relational people management was measured in terms of trust building (Larzelere and Huston, 1980), social support (Pierce et al., 1991), workplace friendship (Nielsen et al., 2000) and conflict resolution (De Dreu et al., 2001). Relational agency was measured as interaction enablement (Anderson and West, 1998), collective efficacy (Bandura, 2006; Goddard, 2002; Goddard et al., 2000), mutual cooperation (Anderson and West, 1998) and shared learning (Leicher and Mulder, 2016). We controlled for variables such as the location of the enterprise and enterprise size in relation to the number of employees. According to Bartov et al. (2000), failure to control for confounding factors may falsely lead to the rejection of hypotheses that could have been accepted.
3.4 Factor analysis, validity and reliability
The Kaiser–Meyer–Olkin (KMO) test was used to determine sample adequacy and Bartlett’s test to determine whether our data were suitable for factor analysis (Field, 2009). From the results (Tables 1 and 2), the data were suitable for factor analysis. To test for reliability, Cronbach’s alpha coefficient was used to determine the internal consistency of the research instrument when used repeatedly under the same conditions. For all study variables in this study, Cronbach’s alpha coefficient was determined and considered sufficient as follows: interaction enablement a = 0.788, mutual cooperation a = 0.841, collective efficacy a = 0.818, shared learning a = 0.904 and relational people management a = 0.945. Based on these results, the research instrument was considered reliable (Field, 2009).
For validity, we focused on content and construct validity. For content validity, the questionnaire was given to a panel of experts, and their responses were carefully incorporated. Construct validity was examined by carrying out convergent and discriminant validity (Blumberg et al., 2014). To ascertain convergent validity, we used communalities through principal component analysis to extract those items that highly converged to form all the variables under study. Items with factor loadings of 0.5 and above were considered appropriate (Field, 2009) (Tables 1 and 2). For discriminant validity (Tables 1 and 2), we used the rotated component matrix through principal component analysis as the extraction method and varimax with Kaiser normalization as the rotation method to identify the principal components. Factors with loadings of 0.5 and above and eigenvalues greater than 1.0 were retained (Field, 2009).
4. Results
4.1 Descriptive statistics
The descriptive statistics for the dependent and independent study variables are shown in Table 3. The mean for relational people management was 4.13, meaning that, on average, micro and small enterprises largely nurture positive interpersonal relationships among people at work. For the independent variables, the results revealed that the mean score for relational agency was 4.23. This means that; on average, micro and small enterprises largely embrace relational agency practices. The results further showed that the mean score for interaction enablement was 4.08. This implies that on average, micro and small enterprises generally enable interactions and this confirmed the median, which is very close at 4.00. The results further showed that the mean score for shared learning was 4.22. This suggests that; on average, micro and small enterprises mainly embrace shared learning practices and this confirmed the median, which is very close at 4.00. The results also indicated that the mean score for collective efficacy was 4.21. This means that; micro and small enterprises mainly embrace collective efficacy practices and this confirmed the median, which is very close at 4.00. Finally, the results further indicated that the mean score for mutual cooperation is 4.23 out of a maximum of 6. This means that; on average micro and small enterprises largely embrace mutual cooperation practices and this confirmed the median, which is very close at 4.00.
4.2 Correlation analysis and ordinary regression analysis results
We used the Pearson correlation coefficient to determine whether there are positive relationships between the study variables as hypothesized from the literature. On obtaining the bivariate correlation results between the independent and dependent variables (Table 4), an ordinary multiple regression analysis was run (Table 4). The predictive power of relational agency as a global independent variable was examined to confirm (H1).
The correlation results in Table 4 show that there is a significant positive relationship between relational agency and relational people management (r = 0.500, p < 0.01). This means that a positive change in relational agency is associated with a positive change in relational people management. The results also show a significant positive relationship between interaction enablement and relational people management (r = 0.450, p <0.01). This means that a positive change in interaction enablement is associated with a positive change in relational people management. In addition, the results indicate a significant positive relationship between shared learning and relational people management (r = 0.364, p < 0.01). This implies that a positive change in shared learning is associated with a positive change in relational people management. Furthermore, the results also indicate a significant positive relationship between collective efficacy and relational people management (r = 0.307, p < 0.01). This means that a positive change in collective efficacy is associated with a positive change in relational people management. Finally, the results show a significant positive relationship between mutual cooperation and relational people management (r = 0.317, p < 0.01). This suggests that a positive change in mutual cooperation is associated with a positive change in relational people management.
From the ordinary regression analysis (Table 4), we ascertained that relational agency contributed about 25.4% of the variation in relational people management in micro and small enterprises. This finding further confirms H1, implying that relational people management varies depending on relational agency practices.
4.3 Hierarchical regression analysis results
Relational agency has four dimensions, which are also the focus of this study. Hence, under the guidelines set by Aiken and West (1991), we carried out a hierarchical regression analysis to further confirm the hypotheses. This analysis is vital in assessing the individual contributions of predictors and in examining their incremental validity (Table 5). Field (2009); recommended a hierarchical regression as suitable for determining the individual contributions of predictor variables to the dependent variable.
In Table 5, Model 1 shows the baseline model with only the control variables, as used in this study. Based on the results, the control variables did not make a significant contribution to the variance in relational people management. This implies that our models are not sensitive to confounding factors and that they are highly plausible.
The results revealed that the unstandardized beta coefficient for collective efficacy is significant at p < 0.01 (Table 5). In Model 2, the results show that collective efficacy is a significant predictor, contributing about 9.6% of the variance in relational people management, further confirming H2 (Table 5). The findings also showed that the unstandardized beta coefficient for mutual cooperation was significant, at p < 0.01 (Table 5). The contribution of mutual cooperation towards relational people management was 5.1% (Table 5), further confirming H3. Similarly, for H4, the unstandardized beta coefficient for shared learning was significant, at p < 0.01 (Table 5). Shared learning contributed about 5.1% of the variation in relational people management (Table 6), further supporting H4. Regarding H5, the unstandardized beta coefficient for the interaction enablement was significant, at p < 0.01 (Table 5). Interaction enablement explained about 7.7% of the variance in relational people management (Table 5).
Therefore, collective efficacy, mutual cooperation, shared learning and interaction enablement are significant predictors of relational people management. Taken together, these relational agency dimensions explained 26.4% of the variance in relational people management among micro and small enterprises in Uganda (Table 5). Generally, the findings indicate that Model 5 in Table 5 is the most credible model. The incremental positive changes in the adjusted R2 in Models 1–5 in Table 5 suggest that a better-fitting model emerges as collective efficacy, mutual cooperation, shared learning and interaction enablement are introduced in the model.
We carried out additional analysis using one-way analysis of variance to determine if there are significant differences between enterprises that have been in existence for 10+ years versus less than 10 years (Table 6) in regards to relational people management. The results in Table 6 show that there were no significant differences between enterprises that had been in existence for 10 + years versus less than 10 years in relation to relational people management.
5. Discussion
Regarding H1, the findings revealed a positive and significant association between relational agency and relational people management. This means that micro and small enterprises where people work together are likely to nurture positive workplace relationships in the form of building trust and developing friendships at work. This finding is in agreement with Cuéllar-molina et al. (2019) and Nalweyiso et al. (2022), who found that working collaboratively results into positive workplace relationships through strong bonds. Such a finding further validates the CHAT which asserts that human activity as a collective endeavor is a clear reflection of human agency which is relational in nature characterizing the activity system (Engestrom, 1987).
Regarding H2, the results indicated a positive and significant association between collective efficacy and relational people management. Such a finding implies that micro and small enterprises, where people believe that together they can make the enterprise succeed, are likely to count on others for help and avoid fights about their differences. This is in agreement with Dubrow et al. (2018) who indicated that when people have confidence in their joint efforts, they are likely to resolve misunderstandings amicably and assist one another.
Concerning H3, the findings revealed a positive and significant association between mutual cooperation and relational people management. This finding suggests that micro and small enterprises whose employees depend on one another for information to carry out tasks are likely to have a spirit of concern for each other. The finding agrees with Leon and Baskin (2022), who found out that during the COVID-19 pandemic, the interdependent nature of the work of nurses enabled co-workers to support each other.
Regarding H4, the findings presented a positive and significant association between shared learning and relational people management, implying that micro and small enterprises where people willingly share knowledge with others are likely to trust each other. This may also mean that micro and small enterprises whose people share ideas openly are likely to develop friendships at work. These findings concur with Moradi et al. (2018), who found that when high school students study in small groups, chances are high that they will demonstrate good interpersonal competencies. The finding also provides empirical evidence for the assertion by Adams (2013) that aspects such as information and knowledge sharing are crucial for developing mutual trust.
Finally, concerning H5, the results showed a positive and significant association between interaction enablement and relational people management. Such a finding means that micro and small enterprises where people interact frequently can count on others in times of stress. This finding is in agreement with Terkamo-Moisio et al. (2021), who found that regular physical interactions in the form of meetings create an opportunity for superiors to know how their subordinates are doing.
6. Conclusion, implications, limitations and areas for further research
This paper examined the role of relational agency and its individual dimensions in fostering relational people management in Ugandan micro and small enterprises. The findings showed that relational agency and all four individual dimensions (collective efficacy, mutual cooperation, shared learning and interaction enablement) play a role in fostering relational people management. Thus, these findings increase the amount of empirical evidence on relational agency and relational people management, specifically from the setting of micro and small enterprises in Uganda.
The study has several implications. For research, this study provides the initial evidence on the role of relational agency and its dimensions in fostering relational people management in Ugandan micro and small enterprises. Consequently, the study contributes to the scant existing research on the practices that promote relational people management. Regarding theory, this study used CHAT to explain relational people management. Therefore, this paper answers the call to use various theories to study relational people management, particularly, in the context of micro and small enterprises. In terms of methodology, the study embraced a quantitative approach, hence responding to a call in the current literature to quantitatively test the preceding associations. In practice, owner-managers and employees in micro and small enterprises may use the results of this study to instill a culture of collaborative working. Specifically, they ought to focus on collective efficacy, mutual cooperation, shared learning and interaction enablement practices if they are to nurture positive workplace relationships, which ultimately contribute to the success and survival of enterprises.
The limitations of this study are discussed alongside the areas for further research. First, this study only focused on micro and small enterprises in Kampala and the other central region of Uganda. This may have affected the generalizability of the results. Perhaps, future studies could explore relational people management in other contexts beyond the scope of this study. Second, the predictor variables explained only 26.4% of the variance in relational people management. Future studies may consider looking at other factors, such as generalized reciprocity, generative leadership, positive emotions. Finally, the study used a quantitative methodological approach. Future studies should consider a mixed methodology, which may provide a comprehensive and holistic understanding of relational people management. However, the findings are applicable to related studies.
Rotated component matrix for relational agency
| Item | 1 | 2 | 3 | 4 |
|---|---|---|---|---|
| We check whether our activities produced the expected results | 0.730 | |||
| We talk about different ways in which we can reach our objectives | 0.620 | |||
| In this enterprise, employees with expert knowledge are willing to help others | 0.600 | |||
| We review our methods of work because of changes in the environment | 0.586 | |||
| We regularly discuss whether as an enterprise we are working effectively | 0.573 | |||
| In this enterprise, we exchange information to solve problems together | 0.728 | |||
| In this enterprise, most of the activities in one job are related to the activities of others | 0.646 | |||
| At work we foster an atmosphere of free cooperation amongst us | 0.642 | |||
| We try to work together to find solutions that meet our expectations | 0.595 | |||
| People here are confident that they can make the firm succeed | 0.573 | |||
| The opportunities in this business help ensure that the firm will succeed | 0.527 | |||
| At work, we keep in regular contact with each other | 0.764 | |||
| We keep in touch with each other | 0.718 | |||
| In this enterprise, we work as a team | 0.689 | |||
| In this enterprise we communicate frequently amongst ourselves | 0.617 | |||
| Eigen value | 2.604 | 2.595 | 2.347 | 2.198 |
| Percentage variance | 17.361 | 17.303 | 15.645 | 14.651 |
| Cumulative percentage | 17.361 | 34.664 | 50.309 | 64.960 |
KMO = 0.946; Bartlett test of Sphericity Approx. Chi-Square =1639.232, df = 105, Sig. = 0.000. Extraction method: Principal Component Analysis; rotation method: Varimax with Kaiser normalization. 1 = Shared learning; 2 = Mutual cooperation; 3 = Collective efficacy; 4 = Interaction enablement
Source: Primary data
Rotated component matrix for relational people management
| Item | 1 | 2 | 3 | 4 |
|---|---|---|---|---|
| In this enterprise, communication among people is encouraged | 0.607 | |||
| At my workplace, informal talk is allowed | 0.613 | |||
| In this enterprise, we formally share experiences, stories and jokes | 0.504 | |||
| In this enterprise, people work with others to solve problems | 0.567 | |||
| In this enterprise, we informally share experiences, stories and jokes | 0.530 | |||
| In this enterprise, there are opportunities to develop a spirit of togetherness | 0.560 | |||
| In this enterprise, people trust each other | 0.627 | |||
| People at work are encouraged to show a great deal of honesty | 0.538 | |||
| In this enterprise, people are given full responsibility for completion of a task | 0.543 | |||
| In this enterprise, people treat others justly even when there is opportunity to take advantage of them | 0.564 | |||
| At work, people trust each other’s behaviors | 0.552 | |||
| In this enterprise, we feel confident of people’s skills and abilities to do their work | 0.538 | |||
| In this enterprise, people give other’s honest feedback | 0.573 | |||
| In this enterprise, people have the willingness to bail each other out | 0.603 | |||
| In this enterprise, people stand in for each other when there is need | 0.542 | |||
| When we have a conflict at work, I insist that both parties give in a little | 0.611 | |||
| When we a conflict at work, I try to come up with a balanced solution | 0.508 | |||
| When I have a conflict at work, I resolve it | 0.543 | |||
| In case of a conflict at work, I avoid a fight about our differences | 0.501 | |||
| Eigen value | 4.704 | 2.151 | 2.086 | 1.675 |
| Percentage variance | 24.759 | 11.319 | 10.981 | 8.818 |
| Cumulative percentage | 24.759 | 36.079 | 47.060 | 55.878 |
KMO = 0.899; Bartlett test of Sphericity Approx. Chi-Square =1559.716, df = 171, Sig. = 0.000. Extraction method: Principal Component Analysis; rotation method: Varimax with Kaiser normalization. 1 = Workplace friendship; 2 = Trust building; 3 = Social support; 4 = Conflict resolution
Source: Primary data
Descriptive statistics
| Item | Interaction enablement |
Shared learning |
Collective efficacy |
Mutual cooperation |
Relational agency |
Relational people management |
|---|---|---|---|---|---|---|
| Mean | 4.08 | 4.22 | 4.21 | 4.23 | 4.23 | 4.13 |
| Median | 4.00 | 4.00 | 4.00 | 4.00 | 4.50 | 4.15 |
| Mode | 4.00 | 4.00 | 5.00 | 5.00 | 4.50 | 4.00 |
| SD | 1.10 | 1.04 | 1.07 | 1.11 | 0.90 | 0.61 |
| Variance | 1.22 | 1.09 | 1.15 | 1.24 | 0.81 | 0.37 |
| Minimum | 1.00 | 1.00 | 1.00 | 1.00 | 1.50 | 2.69 |
| Maximum | 6.00 | 6.00 | 6.00 | 6.00 | 6.00 | 5.77 |
Source: Primary data
Correlation analysis and ordinary regression analysis results
| Variables | 1 | 2 | 3 | 4 | 5 | 6 |
|---|---|---|---|---|---|---|
| Collective efficacy (1) | 1 | |||||
| Mutual cooperation (2) | 0.384** | 1 | ||||
| Shared learning (3) | 0.360** | 0.330** | 1 | |||
| Interaction enablement (4) | 0.384** | 0.345** | 0.348** | 1 | ||
| Relational agency (5) | 0.737** | 0.721** | 0.699** | 0.725** | 1 | |
| Relational People Management (6) | 0.307** | 0.317** | 0.364** | 0.450** | 0.500** | 1 |
**Correlation is significant at the 0.01 level (one-tailed). R square = 0.263; Adjusted R Square = 0.254; Sig = 0.000; dependent variable: Relational People Management
Hierarchical regression results
| Item | Model 1 | Model 2 | Model 3 | Model 4 | Model 5 |
|---|---|---|---|---|---|
| Constant | 4.472 | 3.653 | 3.240 | 2.864 | 2.545 |
| Control variables | |||||
| Location | −0.022 | −0.055 | −0.099 | −0.050 | −00.037 |
| Size | −0.084 | −0.074 | −0.055 | −0.094 | 0.101 |
| Independent variables | |||||
| Collective efficacy | 0.311** | 0.221** | 0.152** | 0.076 | |
| Mutual cooperation | 0.249** | 0.192** | 0.136** | ||
| Shared learning | 0.249** | 0.186** | |||
| Interaction enablement | 0.316** | ||||
| Model summary | |||||
| Model F | 0.930 | 9.112 | 10.744 | 12.136 | 15.351 |
| Adjusted R Square | −0.001 | 0.092 | 0.140 | 0.188 | 0.264 |
| F Change | 0.930 | 25.288 | 14.123 | 15.131 | 25.182 |
| R Square change | 0.008 | 0.096 | 0.051 | 0.051 | 0.077 |
| Durbin–Watson | 2.076 | ||||
**p < 0.01
Source: Primary data
One-way analysis of variance (ANOVA)
| Sum of squares | df | Mean square | F | Sig. | |
|---|---|---|---|---|---|
| Between groups | 11.106 | 12 | 0.925 | 1.828 | 0.054 |
| Within groups | 115.412 | 228 | 0.506 | ||
| Total | 126.518 | 240 |
Relational people management
Source: Primary data
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Further reading
Ehrhardt, K. and Sharif, M.M. (2019), “Career implications for high-quality work relationships: an SCCT test”, Journal of Managerial Psychology, Vol. 34 No. 7, pp. 474-490, doi: 10.1108/JMP-10-2018-0443.
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Kanu, A.M. (2015), “An investigation into the prevalence of HRM practices in SMEs: Sierra Leone an example”, Developing Country Studies, Vol. 5 No. 6, pp. 11-29.
Acknowledgements
The authors wish to extend gratitude to Makerere University Business School. This paper is part of a PhD study sponsored by Makerere University Business School. The listed co-authors are my supervisors. Also, the authors would like to appreciate the editor and the two anonymous reviewers for their constructive comments and guidance.