Exploring the Moderating Effect of Business Demographics on Financial Management Practices and Business Performance

Exploring the Moderating Effect of Business Demographics on Financial Management Practices and Business Performance

Logeswary Sooriyakumaran

Trincomalee campus, Eastern University Sri Lanka

DOI: https://dx.doi.org/10.47772/IJRISS.2025.90600024

Received: 30 May 2025; Accepted: 03 June 2025; Published: 26 June 2025

ABSTRACT

This study investigates the moderating role of demographic profiles—specifically business age, education level, and gender—on the relationship between financial management practices (FMP) and business performance (BP) among SMEs in the Northern Province of Sri Lanka. The study employs multi-group analysis in structural equation modelling (SEM) through AMOS 24, prepares categorical data using SPSS 26, conducts moderation analysis using z-scores and nested model comparisons, and evaluates the impact of these demographic factors on the relationship between FMP and BP. Results indicate that business age and education level significantly moderate this relationship, while gender shows limited moderating influence. These results suggest that older firms, through accumulated experience and resource efficiency, leverage FMPs more effectively to improve business performance, while younger firms face relatively higher costs in adopting such practices. The findings support policy and training initiatives tailored by firm age and education to enhance financial capability and SME growth.

Keywords: Financial management practices, democrafic profile, business performance, multigroup analysis

INTRODUCTION

Small and medium-sized enterprises (SMEs) play a vital role in contemporary global economies by contributing significantly to innovation, employment generation, and economic diversification (Ayyagari, Demirgüç-Kunt, & Maksimovic, 2011). In Sri Lanka, the SME sector is particularly important due to the country’s diverse geographical, cultural, and economic landscape. This diversity necessitates targeted development strategies to unlock regional potential and foster inclusive growth.

Despite SME’s accounting for approximately 90% of all business entities in Sri Lanka (Ministry of Industry and Commerce, 2020), the sector has yet to fully realise its development targets. Policymakers have consistently prioritised SME development, recognising its strategic importance for economic stability and resilience (Nishantha, 2019). However, critical challenges related to capacity, financial management practices, and access to markets continue to hinder performance outcomes.

This research expands on earlier work by the main researcher (Sooriyakumaran et al., 2022) by looking at how factors like gender, education level, and the age of a business affect the link between financial management practices and business performance. By deepening the understanding of these moderating factors, the study aims to provide more nuanced insights that can guide targeted interventions and capacity-building strategies within Sri Lanka’s SME sector.

Problem Identification

Small and medium enterprises (SMEs) face persistent performance challenges primarily due to limited knowledge of financial management practices (FMPs) and an increasingly uncertain commercial environment (Karadag, 2015). Financial mismanagement, inadequate strategic planning, and constrained access to capital have been identified as key factors that hinder SME growth and sustainability.

Business demographics are increasingly recognised as pivotal determinants of organisational performance. One key demographic factor—the age of the enterprise—has been found to significantly influence its growth trajectory and operational resilience. Empirical studies suggest that younger firms are generally more susceptible to early failure, whereas older, more established businesses tend to demonstrate greater stability and adaptive capacity (Hui et al., 2013; Mann & Sager, 2007). The longevity of an enterprise often correlates with enhanced financial discipline and more consistent adoption of effective financial management practices (Nyamao et al., 2013). This suggests that business maturity more strategic responses to market and operational challenges. Consequently, analysing the influence of business demographics the heterogeneity of financial behaviour and performance outcomes across SMEs.

Additionally, the educational background of individuals involved in financial decision-making has a measurable impact on SME performance. Kalaipriya (2021) demonstrated that higher education levels among financial practitioners lead to more informed and strategic financial practices, resulting in improved business outcomes.

This study seeks to examine the financial management practices of SMEs and their impact on business performance while exploring how demographic factors—such as gender, education level, and business age—moderate this relationship. Understanding these interactions will enable the formulation of targeted recommendations to strengthen the SME sector and guide policy interventions more effectively.

Research Question

The following central research question guides this study:

To what extent do demographic factors—specifically the business age, gender, and education level of respondents—moderate the relationship between financial management practices and the performance of SMEs in the Northern Province of Sri Lanka?

This question seeks to explore the extent to which selected demographic characteristics influence the relationship between financial management practices (FMPs) and business performance. Understanding these moderating effects is essential for designing more targeted and effective financial interventions and support mechanisms for small and medium-sized enterprises (SMEs), tailored to the demographic profiles of their operators.

Research Objectives

The overarching aim of this research is to analyse the moderating effects of demographic variables on the relationship between financial management practices and the performance of SME’s in the Northern Province of Sri Lanka. In pursuit of this aim, the study sets out the following specific objectives:

1. The study aims to investigate how demographic factors, specifically business age, gender, and education level, moderate the relationship between financial management practices and SME performance.
   This objective seeks to find out how factors like business age, gender, and education level affect the connection between financial management practices and performance results, based on findings from the researcher’s previous work (Sooriyakumaran et al., 2022a).
2. The objective is to provide evidence-based recommendations that SMEs, policymakers, and supporting institutions can use to enhance their financial management practices through demographically informed strategies. This includes policy- and practice-orientated guidance designed to improve the financial resilience and operational efficiency of SMEs, taking into account demographic diversity as a strategic factor in intervention design.

The significance of the Study

Small and Medium Enterprises (SMEs) contribute significantly to the Sri Lankan economy, accounting for approximately 45% of domestic employment and 52% of the Gross Domestic Product (Ramanayake, 2019). Given their substantial contribution, which surpasses regional averages, it is critical to investigate the factors influencing their performance and growth potential. Understanding SME performance is particularly important, as poor outcomes in this sector could adversely affect the broader economy.

Recent evidence suggests that approximately 25% of Sri Lankan small and medium-sized enterprises (SMEs) have ceased operations within the past four years (2018 -2022), with ineffective financial management practices identified as a primary contributing factor (Department of Census and Statistics, 2023). Many studies have looked at how financial management practices (FMPs) affect the performance of small and medium-sized enterprises (SMEs) in Sri Lanka. While these research studies offer useful information about the role of FMPs in influencing business outcomes, they often overlook the potential influence of contextual variables. Notably, the moderating role of business demographic factors—such as firm age, size, and ownership structure—has been underexplored in the existing literature (Rathnasiri, 2014, 2015; Madurapperuma, Thilakerathne, & Manawadu, 2016). In response to this gap, Sooriyakumaran (2022b) recently proposed a conceptual framework positing that demographic characteristics may moderate the relationship between FMPs and SME performance. Building upon this proposition, the present study aims to assess the extent empirically to which demographic variables influence this dynamic, thereby contributing to a more nuanced understanding of SME financial performance determinants.

Accordingly, the present research aims to examine how demographic factors moderate the relationship between financial management practices and SME performance in Sri Lanka, providing evidence-based recommendations to entrepreneurs to sustain business success. Focusing on SMEs in the Northern Province is essential to obtain insights that contribute to the national economy, especially given the region’s unique post-conflict context.

This study draws on contemporary financial management theories, including equity theory and pecking order theory, to analyse SMEs’ financial practices and performance in the Northern Province. By doing so, it addresses both empirical and theoretical gaps in the local context.

Hence, this research clearly identifies the moderating effects of demographic factors on the relationship between financial management practices and business performance among SMEs in the Northern Province’s post-war environment. The findings aim to support rapid economic recovery in the region and contribute to increasing the Northern Province’s GDP share within Sri Lanka.

LITERATURE REVIEW

Modern Financial Management Theories

Emery et al. (1991, as cited in Wundengba, 2020) identified several foundational financial management theories that underpin decision-making processes in contemporary business contexts. These include agency theory, pecking order theory, and equity theory. Wundengba (2020) observed that small and medium-sized enterprises (SMEs), particularly in developing economies, increasingly rely on such theoretical frameworks to shape their financial management practices.

Equity theory emphasises fairness in the distribution of financial resources among stakeholders. The International Accounting Standards Board’s (IASB) 2010 Conceptual Framework integrates four core equity theories: proprietary theory, entity theory, enterprise theory, and residual equity theory (Mourik, 2014). The relevance and application of these theories vary according to the enterprise’s structural, economic, and accounting contexts.

Pecking order theory, in particular, has been widely adopted to explain financing preferences and decision-making hierarchies among SMEs across multiple countries, including Uganda (Abanis et al., 2013), Kenya (Kinyua & Mungai, 2018), Sri Lanka’s Gamoaga district (Uduwaka & Dedunu, 2019), and Nigeria (Folajinmi & Peter, 2020). Additionally, elements of residual equity theory and proprietary theory have been applied in the Kenyan context by Kanyuga (2017) and Musando (2013), respectively. Despite this growing body of international research, theoretical applications in Sri Lanka remain underexplored, indicating a significant gap in the literature. This study seeks to address this void by examining the relevance and applicability of modern financial management theories within the Sri Lankan SME sector.

Moderating Effects of Demographic Attributes

Moderation occurs when the relationship between two variables changes depending on the presence of a third variable (Pritha, 2021). This third variable can be qualitative or quantitative and affects the direction or strength of the relationship between independent and dependent variables.

Business Age as a Moderator

Researchers have identified business age as a significant moderator in the relationship between financial management practices and performance (Nketsiah, 2015, 2018a). Research by Ntim, Evans, and Anthony (2014) demonstrates that firm age influences the adoption of formal accounting and control systems. Contrarily, Wijekumara (2019) found firm age to have an insignificant positive effect on formal accounting adoption among SMEs in Anuradhapura.

Education Level as a Moderator

Financial literacy, often proxied by education level, is the capacity to manage finances effectively and contributes to economic development (Kalaipriya, 2021). Several studies have examined education level as a moderating factor. Kalaipriya (2021) found that financial literacy moderated the relationship between risk aversion and investment intentions. Sindani (2019) identified education as a moderator between accounts receivable management and SME growth in Kenya. However, mixed findings exist, with Owusu et al. (2019) reporting contradictory results.

Gender as a Moderator

The moderating role of gender has also been investigated. Hoque and Awang (2019) found gender and education levels moderated the relationship between entrepreneurial marketing and financial performance. This finding aligns with Aren and Aydemir (2015) but contrasts with Ansar et al. (2019). Some studies (Lachance, 2014; Leila, 2011, as cited in Ansar et al., 2019) indicate men have greater financial knowledge, while others, like Lusardi (2015, as cited in Ansar et al., 2019), suggest women outperform men in financial management.

Hypotheses Development

Based on evidence from Hall (1995, as cited in Nketsiah, 2018a), Nketsiah (2015, 2018a), and Mann and Sager (2007) firm age is hypothesised as a significant moderator. Ali and Isak (2019) demonstrated that education level and gender moderate the relationship between entrepreneurial marketing and financial performance, with education being significant but not gender. Other studies (Owusu et al., 2019; Sucuahi, 2013 : Hoque & Awang, 2019) have yielded mixed results, leading us to propose the following hypotheses:

H1: SME age has a significant moderating effect on the relationship between financial management practices and SME performance in the Northern Province of Sri Lanka.

H2: Educational level has a significant moderating effect on the relationship between financial management practices and business performance of SMEs in the Northern Province of Sri Lanka.

H3: Gender has a significant moderating effect on the relationship between financial management practices and business performance of SMEs in the Northern Province of Sri Lanka.

Scope and Contribution of the Current Study

Previous studies focused on limited populations within Sri Lanka’s Northern Province, leaving many areas unexplored (Kengatharan et al., 2017; Kalaipriya, 2020; Kengatharan, 2020). This study expands the scope by including all SMEs registered under Divisional Secretariat divisions in the province, building upon Sooriyakumaran’s (2022) research, which examined a narrower segment.

METHODOLOGY

This study uses a quantitative research design to look at how financial management practices (FMP) relate to business performance (BP) in small and medium-sized enterprises (SMEs) in the Northern Province of Sri Lanka, especially considering the impact of certain business demographic factors. The research is explanatory in nature and employs hypothesis testing to validate a conceptual model developed based on theoretical and empirical literature.

Data Sources

The study employs both primary and secondary data sources to ensure a comprehensive analysis.

Primary data were collected through a structured questionnaire administered to SME owners, managers, or accounting assistants who are directly involved in financial management practices and contribute to decision-making processes within their respective enterprises. The questionnaire covered various aspects of financial management, business performance indicators, and demographic attributes, such as business age, education level of decision-makers, and gender.

Secondary data were obtained from scholarly journal articles, published reports specific to the Northern Province, and other relevant government and institutional publications. These sources provided contextual background and theoretical foundations and supported the validation of the research framework.

Sampling Technique and Sample Size

A stratified random sampling method was employed to ensure fair representation of small and medium-sized enterprises (SMEs) from all areas within the Northern Province. The stratification was based on the number of registered SMEs in each Divisional Secretariat (DS) division, thereby ensuring proportional representation across the region. The target population for this study was 24,316 SMEs, which is considered large, particularly in the Sri Lankan context. Therefore, we determined the sample size using the general guidelines for Structural Equation Modelling (SEM) in AMOS, in conjunction with Yamane’s (1967, as cited in Adam, 2021) and Slovene’s (1960, as cited in Adam, 2021) formulas. Based on these methods, a total of 450 respondents were selected, which is deemed statistically adequate for conducting SEM and other multivariate analyses.

Data Collection Instrument

The questionnaire used for primary data collection comprised both closed-ended and scaled questions based on existing literature and validated constructs. The instrument was pre-tested and refined to ensure reliability and clarity. It included sections on financial management practices, business performance metrics, and demographic characteristics of the respondents and businesses.

Data Analysis Techniques

The analysis of data involved both descriptive and inferential statistical techniques, using SPSS and AMOS software packages. The specific analytical techniques included:

Descriptive Statistics: To summarise respondent demographics, business characteristics, and the central tendencies of key variables.

Multiple Group Analysis (MGA): To examine the moderating effects of business age, education level, and gender on the relationship between FMP and business performance. MGA allowed for a comparison of path coefficients across subgroups to determine the significance of moderating variables.\

Ethical Considerations

Participation in the study was voluntary, and informed consent was obtained from all respondents. Confidentiality of individual and business information was assured, and data were used solely for academic purposes.

Analysis of data

Demographic Characteristics of Respondents

In this study, the unit of analysis comprises the SME owners, managers, or accounting assistants responsible for financial management practices and supporting business decision-making. Respondents varied across several demographic dimensions, including gender, age, education level, marital status, and their role within the business. Additional business characteristics were also recorded, such as the type of business, years of operation, number of employees, and annual turnover.

Table 1 provides a summary of the respondents’ demographic and business profiles. Of the total sample, 74% were male and 26% were female. This finding reflects an improvement in female participation in SME management in the Northern Province, aligning with the observations of Kengatharan and Yogendrarajah (2017), who noted a 19% female contribution during their 2017 study. The increase indicates a positive trend in women’s engagement in entrepreneurial activities.

Regarding educational attainment, the data reveal that over 50% of respondents possessed a degree or a professional qualification, while 41% held a G.C.E. Advanced Level (A/L) qualification, and 8% had a G.C.E. Ordinary Level (O/L) certificate. These results suggest that a substantial proportion of SME managers or decision-makers are relatively well-educated and are therefore more likely to be competent in managing financial activities. This finding is consistent with the conclusions of Rathnasiri (2014), who also reported a high percentage of educated SME respondents.

In terms of business experience, 49% of respondents had operated their businesses for more than 10 years. This finding corroborates the empirical results of Nketsiah (2018) and Tharmini and Lakshan (2021), who suggested that business longevity enhances the likelihood of adopting structured financial management practices. Similarly, Kengatharan and Yogendrarajah (2017) asserted that experience plays a crucial role in improving financial recordkeeping and overall business performance.

Table 1: Demographic Characteristics of Respondents

(Source: Survey Data 2020)

Moderator Analysis and Findings

Multi-group analysis in structural equation modelling (SEM) is another form of moderation analysis using categorical variables or grouping variables. This process is straightforward in AMOS as the grouping variable. In this data set, moderate variables of business age and education data were entered as ordinal (e.g., within a given range) and gender was entered as a grouping variable as male and female. Hence, business age and education moderating variables (demographic profiles) had to be converted into categorical ones by using SPSS 26. Then did the moderator analysis by using AMOS 24.

Moderating tests for the Research Model

The main goal of moderation analysis is to see if the strength or direction of the relationship between an independent variable and a dependent variable changes based on a third variable, called the moderator (Baron & Kenny, 1986, as cited in Memon et al., 2019). In this study, the moderating effects of business age, education level, and gender were investigated using multi-group analysis (MGA).

To assess the magnitude of these moderating effects, effect size (f²) values were calculated using online statistical tools provided by Gaskin (http://statwiki.kolobkreations.com, as cited in Memon et al., 2019). The effect size indicates the extent to which the inclusion of a moderator contributes to the change in the coefficient of determination (R²) in the model.

The sample was divided into two subgroups for each moderator variable (business age, education level, and gender), following the requirements for multi-group analysis. According to Bollen (1989), achieving approximately equal group sizes is crucial to control for confounding influences and to maintain the robustness of the test statistics. Therefore, each moderator variable was dichotomised based on the collected data to ensure balanced group sizes and satisfy MGA’s assumptions.

Figure 1 illustrates the structural path model used for testing the moderation effects. The moderation tests were used on the proposed relationships in this model to see if the model’s parameters were significantly different between the groups.

Figure 1 Modelling the Moderator for Latent Construct

Invariance Test

This study aimed to check how certain categories, like business age, education level, and gender, affect the structural model by performing configural and metric invariance tests.

All model fit indices indicate an excellent fit for both business age groups, education level and gender groups. Specifically, CMIN/DF was below 3, CFI values were close to 1, RMSEA values were below the 0.06 threshold, and PClose values exceeded 0.05, confirming configural invariance (Hair et al., 2010; Hoque & Awang, 2019; Awang et al., 2017).

Hypothesis tests for moderating effects for latent constructs

The analysis of hypothesis 1, which is the significant moderation effect of business age on the relationship between financial management practices and business performance of SMEs in the Northern Province of Sri Lanka, was conducted with the support of divided group data of business age.

The moderation effect on the links between financial management practices (MAR, FRPA, AIS, WCM, ID, and FIN) and business performance was tested by using AMOS. These relationships were looked at individually for each group and then compared using their regression weights and critical ratios to see the differences between the groups, as shown in Table 2, with the help of James Gaskin’s Excel sheets from the stats tool package (2012).

Table 2 Path wise moderation effect of Business age group difference

The overall moderation effect due to the variation in the business age context was tested on all the relevant structural paths and was found significant at the 0.01 and 0.05 levels (z scores greater than +/- 2.33 and +/- 1.645, respectively) on paths between ID and BP, AIS and BP, WCM and BP, and finally FMP and BP (Table 8). The z-score was 1.8 in the relationship between investment decisions and business performance, which was greater than or equal to the critical value of 1.645. Thus, it is significant at the 0.05 level. If the z-score falls within +/- 1.645 of the normal distribution, researchers accept the alternative hypothesis.

In conclusion, as per H1, firm’s age played the role of moderator on the relationships between FMP and BP (Nketsiah, 2018a; Hui et al., 2013).

Further, when researchers conducted the moderation test for each group of business age on the relationship between financial management practices and business performance of SMEs with nested model comparison, the following results were identified and strengthened the above result.

Table 3: Moderation Test of Business age

As presented in Table 3, the chi-square value and degrees of freedom for the unconstrained model in the high business age group were 1229.799 and 886, respectively, whereas the constrained model yielded a chi-square value of 1264.829 with 887 degrees of freedom. Following the guidelines proposed by Awang et al (2015) and Hair et al. (2010), a difference in chi-square values exceeding 3.84 with one degree of freedom indicates a significant moderating effect along the path of interest. In this instance, the chi-square difference is 35.03, which is substantially greater than the critical threshold, suggesting a strong moderating effect of business age in the high group.

Furthermore, the same moderation analysis was conducted for the low business age group, and the results, presented in Table 3, also demonstrated a significant moderating effect. These findings collectively indicate that business age significantly moderates the relationship between the model variables in both high and low business age groups.

Table 4; Nested model comparison of business age

The result of multiple group analysis to test the business age nested model comparison is in the above table. It shows the significant value of p is at 0.000 and reinforces the acceptance of H1.

In line with Hypothesis 1 (H1), the age of a firm appears to moderate the relationship between financial management practices (FMPs) and business performance (BP). This finding supports earlier studies by Nketsiah (2018), Amaradiwakara and Gunatilake (2017), and Hui et al. (2013), which showed that older businesses—usually those that have been around for more than ten years—are generally better at managing working capital, accounting information systems (AIS), and making investment decisions. This advantage may be attributed to their accumulated experience and resource availability, which facilitate more effective implementation of FMPs. Mayuran (personal communication, December. 22.2024) further argues that younger firms often face greater challenges in executing these practices efficiently due to higher associated costs and limited operational maturity. Nonetheless, when younger firms adopt sound financial practices, it enhances their chances of continuity and long-term success. These insights point out the value of firm age as a contextual factor shaping financial decision-making and performance outcomes.

The moderating effect of education level on the relationship between financial management practices and business performance is examined.

The moderating influence of education level on the relationship between financial management practices (FMPs) and business performance (BP) was tested using the unstandardised regression weights from AMOS 24 and the critical ratio differences between parameters. Table 5 was derived using James Gaskin’s Stats Tools Package Excel utility (2012).

Table 5: Path wise moderation effect of education level group difference

The z-score analysis in Table 5 demonstrates that education levels significantly moderate the relationships between certain FMP components and BP. The threshold for statistical significance in z-scores was ±1.282 for the 10% and ±2.326 for the 1% levels, respectively (Field, 2018).

The relationship between Accounting Information Systems (AIS) and BP (z = -1.320) is significant at the 10% level. This suggests that the effectiveness of AIS on BP varies depending on respondents’ education levels.

A stronger moderation effect is observed in the relationship between Working Capital Management (WCM) and BP (z = -2.419), significant at the 1% level.

The overall link between FMP and BP shows a highly significant moderation effect (z = 6.250), indicating that education level substantially shapes the impact of FMPs on SME performance.

These findings align with previous research that has emphasised the critical role of financial literacy and education in shaping SME success. Owusu et al. (2019), for example, found that financial literacy moderated the impact of financial resources on SME growth in Ghana. Similarly, Sucuahi (2013), Fatoki (2014), and Adomako and Danso (2014) confirmed that educational background influences financial decision-making and firm outcomes.

The significance of these moderating effects was further validated using model comparison techniques.

As both education level groups showed significant chi-square differences (> 3.84) with df = 1, the moderation hypothesis was supported for each subgroup

Table 6: Moderation Test of Education Level

The moderation test is significant since the difference in chi-square value between the constrained and unconstrained models was higher than 3.84 with 1 degree of freedom, which is 3.84. In Table 6, the difference in Chi-Square value is 128.625, which is higher than 3.84, and while the difference in degrees of freedom is 887-886 = 1, Hence, the moderation test result shows a significant effect in the education level I group. And moreover, this analysis was conducted on the education level II group also and identified significant effect.

Table 7: Nested model comparison of business age

The calculated Δχ²/Δdf value is 503.547 divided by 102, resulting in 4.937 (p < .01), which indicates a statistically significant difference between the two education groups. This evidence supports the acceptance of  H2, asserting that education level moderates the effect of FMPs on BP.

These results have important implications for both policy and practice, underscoring the need to enhance financial literacy and education among SME owners and managers to ensure more effective financial decision-making and sustainable business growth.

Qualitative insights gathered through interviews with Velnamby and Anushanthan (personal communication, December 20, 2024) offer further support for these findings. Both experts highlighted that higher levels of education among SME owners or managers contribute to a more strategic alignment of financial management practices (FMPs) with the firm’s specific needs and resource constraints. They noted that education not only enhances the ability to implement appropriate financial controls but also minimises avoidable expenditures associated with inefficient or misaligned financial systems. This suggests that education plays a pivotal role in optimising FMPs and improving overall business efficiency.

Table 8 presents the path-wise moderation effects based on gender group differences. According to the z-scores and p-values, the results indicate no statistically significant gender-based moderation in the relationships between several constructs and business performance (BP). Specifically, individual decision-making (ID), accounting information systems (AIS), market orientation (MAR), and financial infrastructure (FIN) did not show significant differences across gender groups. The relationship between BP and working capital management (WCM) was significant only among female respondents (p = .011), while the relationship between BP and financial resource planning and availability (FRPA) was significant only among male respondents (p = .178). However, the z-scores for FRPA (-1.368) and FIN (-1.443) were higher than the level for being somewhat significant (p < .10), suggesting that gender might influence these specific areas.

Even though we thought gender would play a role in how financial management practices (FMPs) affect business performance, the results showed otherwise, leading to the rejection of Hypothesis 3 (H3). This outcome suggests that gender, in this context, does not exert a statistically significant influence on how FMPs affect business outcomes. This finding is consistent with prior research by Hoque, Awang, and Ansar et al. (2019), who argue that gender-based differences in financial behaviour and decision-making are not universally observed and may vary depending on sociocultural and organisational contexts. These results imply that other demographic or structural factors may play a more critical role in shaping financial practices than gender alone.

Table 8: Path wise moderation effect of gender group difference

Multi-group Analysis: Gender-Based Model Testing

The structural invariance test further assessed moderation across gender groups. Table 17 shows the results for the male group, where the difference in chi-square values between the restricted model (χ² = 1427.154, df = 887) and the unrestricted model (χ² = 1340.538, df = 886) was 86.616. Since this difference exceeds the critical value of 3.84 at 1 degree of freedom, the moderation effect was deemed statistically significant for males.

Table 9: Moderation Test of gender

In the same way, Table 9 shows a significant moderation effect for females, with a chi-square difference of 59.736 constrained model χ² = 1244.413, unconstrained model χ² = 1184.677 ; df difference = 1). These findings confirm that both male and female subgroups exhibit significant internal moderation effects.

However, the nested model comparison in Table 10 did not support overall gender moderation. The chi-square difference for the structural weights model was Δχ² = 103.179 with p = .114, which is above the threshold for significance. Other model fit measures (ΔNFI = .010, ΔIFI = .011, ΔTLI = –.002) also back up the finding that there is no significant difference based on gender in the overall structural model.

Table 10: Nested model comparison of gender

Statistical evidence from the Northern Provincial Statistics (2024) indicates that literacy rates in the region are uniformly high, with all districts reporting rates above 85%, irrespective of gender. This high level of literacy might help ensure that both men and women have similar knowledge about financial management, which is why there are no major differences between genders in how they use financial management practices and their effects on business performance.

Consequently, Hypothesis 3 (H3), which posited a significant moderating effect of gender on the relationship between financial management practices (FMPs) and business performance (BP), was rejected. However, the analysis did reveal marginal gender-based effects in specific relationships—particularly between financial reporting and analysis (FRPA), financial information (FIN), and BP. This subtle variation may be explained by behavioural differences traditionally associated with gender. For instance, women are often observed to exhibit stronger financial discipline, more structured planning, and greater risk aversion—factors that can positively influence financial decision-making and performance outcomes (Hill & Asarta, 2016). These findings suggest that, while gender may not broadly moderate the FMP–BP relationship, it can influence specific financial behaviours that warrant further investigation.

CONCLUSION

This study confirms that financial management practices (FMPs) are very important for improving business performance (BP) in small and medium-sized enterprises (SMEs), especially when looking at different demographic factors. While the findings indicate that both male and female participants reported meaningful internal impacts of FMPs, gender did not significantly moderate the overall relationship between FMPs and BP. This aligns with prior research suggesting that gender-based financial behaviour may not be universally influential across different organisational settings (Hoque & Awang, 2019; Ansar et al., 2019). However, small differences based on gender were seen in certain areas—especially in how financial resource planning and availability (FRPA) and financial infrastructure (FIN) relate to BP—where female participants showed stronger connections. These patterns may reflect broader behavioural and socialised differences in financial literacy and risk management among women (Hill & Asarta, 2016).

In contrast, business age and educational attainment were found to be significant moderators of the FMP–BP relationship. Older firms demonstrated a higher capacity to implement structured financial strategies, likely due to accumulated experience and resource availability (Hui et al., 2013; Nyamao et al., 2013). Similarly, higher educational attainment among SME decision-makers enhanced the alignment of financial practices with organisational goals, thereby reducing inefficiencies and reinforcing financial discipline (Mayuran, 2022; Velnamby & Anushanthan, personal communication, December 20, 2024).

Despite growing awareness of their importance, FMPs remain insufficiently integrated into the operational strategies of many SMEs in Sri Lanka. This gap can be attributed to financial constraints, lack of managerial expertise, limited institutional support, and poor awareness regarding the tangible benefits of sound financial governance (Sooriyakumaran et al., 2022a). Yet, effective use of FMPs contributes significantly to financial transparency, informed decision-making, and long-term sustainability. The evidence thus points to the need for SME owners, managers, and financial personnel to embed financial planning and control mechanisms into their strategic and day-to-day operations.

Moreover, this study points to the need for well-targeted policy interventions. Practical recommendations drawn from interviews with SME development experts (Nimalathasan & Mayuran, personal communication, January 6 & 8, 2025) include: (1) organising awareness-building workshops via the Institute of Chartered Accountants of Sri Lanka (ICASL) in collaboration with academic and industry professionals; (2) introducing tax incentives through the Inland Revenue Department for SMEs, demonstrating verifiable adoption of best financial practices; and (3) allocating government- or donor-funded development projects preferentially to SMEs recognised by Chambers of Commerce or relevant authorities for financial transparency and performance.

Given that this study only examined a limited range of demographic moderators—namely, business age, educational attainment, and gender—future research should explore additional variables such as leadership styles, regulatory compliance, adherence to accounting standards, and digital financial literacy. These factors may provide further insight into how demographic and organisational dynamics interact with FMPs to influence SME performance.

In summary, strengthening the adoption of FMPs within SMEs necessitates a holistic approach involving government agencies, policymakers, and SME-support institutions. Better training programs, financial support, and a supportive regulatory environment will be essential for improving the financial skills of SMEs, helping them become more resilient, and ensuring they continue to contribute to fair and inclusive economic growth.

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