INTERNATIONAL JOURNAL OF RESEARCH AND SCIENTIFIC INNOVATION (IJRSI)
ISSN No. 2321-2705 | DOI: 10.51244/IJRSI |Volume XII Issue IX September 2025
Page 3607
Disaggregating Financial Management Practices and SME
Performance: Evidence from Agro-Processing Firms in Emerging
Markets
*
Kyakunzire Annet Mitchel., Sunday Arthur., Eton Marus., Eliab Byamukama Mpora
Kabale University, Uganda
DOI:
https://doi.org/10.51244/IJRSI.2025.120800326
Received: 01 Sep 2025; Accepted: 07 Sep 2025; Published: 11 October 2025
ABSTRACT
Small and medium enterprises are essential drivers of economic growth and employment in emerging markets
but often struggle with weak financial management practices. This study investigates the influence of financial
management strategies, financial reporting and analysis, inventory decisions, financing structures, and working
capital management on the performance of agro-processing enterprises in Uganda’s Ankole sub-region. A
quantitative cross-sectional survey was conducted with 192 formally registered enterprises. Structural equation
modeling was used to examine the relationships between financial management practices and business
performance. The results show that financial reporting and analysis, financial management strategies, and
financing structures have a significant positive impact on business performance. Inventory decisions and
working capital management showed no direct effect, although the effect of working capital management
became significant when firm age was considered. These findings highlight the need for targeted financial
training and policy support tailored to enterprise maturity and context.
Keywords: Financial Management Practices; Small and Medium Enterprises (SMEs); Business Performance;
Emerging Markets; Working Capital Management; Financial Reporting and Analysis; Financing Structure;
Investment Decisions; Structural Equation Modeling (SEM); Agro-processing.
INTRODUCTION
Small and medium-sized enterprises (SMEs) are widely acknowledged as key drivers of economic growth,
innovation, and employment, particularly in emerging markets (Gherghina, 2020). SMEs contribute significantly
to GDP and job creation, fostering economic diversification and social inclusion (Labeeque, A., & Sanaullah,
2019). However, despite their critical role, many SMEs in developing economies struggle with financial
constraints, inadequate management practices, and limited access to formal financial services, which collectively
hinder their growth and sustainability (Karadag, H., 2015).
Effective financial management practices, including the implementation of comprehensive financial
management strategies , rigorous financial reporting and analysis, strategic inventory decisions, diversified
financing sources, and sound working capital management—are essential for enhancing the operational
efficiency and performance of SMEs (Rahmah, R. A., & Peter, F. O., 2024). These practices enable SMEs to
optimize resource allocation, improve cash flow, and make informed strategic decisions, which are critical for
survival and growth in competitive and uncertain market environments (Nasimiyu, A. E. 2023).
However, the extent to which these financial management practices impact SME performance in emerging
markets remains inadequately understood. Emerging markets often feature institutional weaknesses, information
asymmetries, and financial market imperfections that may alter the traditional relationships observed in
developed economies (Wolmarans, H. P., & Meintjes, Q. 2015). Most SMEs in these contexts frequently rely
on informal financing sources and face challenges in adopting formal financial management tools, which may
affect the effectiveness of standard financial practices (Nguyen, B., & Canh, N. P., 2021).
INTERNATIONAL JOURNAL OF RESEARCH AND SCIENTIFIC INNOVATION (IJRSI)
ISSN No. 2321-2705 | DOI: 10.51244/IJRSI |Volume XII Issue IX September 2025
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Motivation
The motivation for this study stems from the pressing need to better understand how financial management
practices influence SME performance within the specific constraints of emerging economies. Despite the
recognized importance of financial management, many SMEs, particularly in sectors like agro-processing in
regions, remain underserved by formal financial institutions and often lack the capacity to implement robust
financial systems (Forkuoh, et al., 2015). This gap in knowledge limits the ability of policymakers, development
agencies, and financial institutions to design targeted interventions that enhance SME financial capabilities and,
consequently, their performance and contribution to economic development. Moreover, prior research often
treats financial management practices as a uniform concept, without disaggregating the distinct roles of various
components such as working capital management or financial reporting, nor considering contextual moderators
like firm age or sector-specific factors (Francisco, P. M., 2024). This study aims to address these limitations by
providing nuanced insights into how different financial management dimensions relate to SME performance,
thereby supporting more tailored capacity-building efforts and financial product development.
Understanding these dynamics is particularly critical in light of global trends emphasizing SME resilience and
sustainable growth in the post-pandemic economic recovery phase (World Bank, 2021). By investigating these
issues in emerging market contexts, this research contributes to bridging academic knowledge gaps and offers
practical guidance to strengthen SME ecosystems, fostering broader economic development and poverty
alleviation.
Therefore, this study examined the impact of financial management practices on SME performance in emerging
markets, focusing on contextual factors influencing effectiveness and providing insights for targeted
interventions and policy development.
Methods
This study employed a quantitative, cross-sectional research design to examine the impact of financial
management practices on the performance of small and medium enterprises (SMEs) in emerging markets.This
study utilized Structural Equation Modeling (SEM) to analyze the relationship between financial management
practices and the performance of small and SMEs in emerging markets.
Study Population
The target population comprised agro-processing SMEs operating in the Ankole sub-region of southwestern
Uganda. This population was selected due to the region’s economic reliance on agro-based industries and the
observable challenges SMEs face in adopting formal financial practices. A purposive sampling technique was
employed to select SMEs operating in the agro-processing sector within the Ankole sub-region, with eligibility
limited to firms that were formally registered, had been in operation for at least three years, and employed
between 5 and 100 people. Business owners or financial managers directly involved in financial decision-making
were targeted as key respondents. Based on Structural Equation Modeling (SEM) guidelines recommending a
minimum of 10 respondents per parameter, 192 structured questionnaires were distributed, and 192 valid
responses were retained for analysis after data cleaning, exceeding the threshold for SEM analysis. Primary data
were collected using a structured questionnaire adapted from existing validated instruments, incorporating
closed-ended Likert-scale items. The instrument focused on five latent constructs of financial management
practices; Financial management strategies (FMS), Financial Reporting and Analysis (FRA), Inventory
Decisions (ID), Financing Sources (FS), and Working Capital Management (WCM).
The dependent construct was Business Performance (BP). Each latent construct was measured by two or more
observed indicators (e.g., FRA1, FRA2 for FRA; BP1, BP2 for BP). Data collection was conducted in-person,
with research assistants providing clarification where needed. Each latent variable was measured using multiple
observed indicators (e.g., FRA1, FRA2 for FRA; BP1, BP2 for BP). Confirmatory Factor Analysis (CFA) was
first conducted to validate the measurement models, assessing reliability and construct validity. Model fit was
evaluated using indices including the Comparative Fit Index (CFI), Tucker-Lewis Index (TLI), Root Mean
Square Error of Approximation (RMSEA), and Standardized Root Mean Square Residual (SRMR).
INTERNATIONAL JOURNAL OF RESEARCH AND SCIENTIFIC INNOVATION (IJRSI)
ISSN No. 2321-2705 | DOI: 10.51244/IJRSI |Volume XII Issue IX September 2025
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The structural model specifying hypothesized causal relationships between financial management constructs and
SME performance was estimated using Maximum Likelihood Estimation in JASP software (version 0.19.30).
Convergent validity was assessed through Average Variance Extracted (AVE), while discriminant validity was
tested via the Heterotrait-Monotrait (HTMT) ratio.
RESULTS
Structural Model
Structural Model Analysis is the second part of SEM, following the Measurement Model (CFA). It focuses on
analyzing the relationships between latent variables (Mueller & Hancock, 2018). It is a regression between
unobserved variables. Unlike CFA, which does not differentiate between the dependent and independent
variables, the structural model does. In this Thesis, the proposed structural model consisted of two sets of latent
constructs, of which one was exogenous (independent), that is, financial management practices, and the other
endogenous (dependent), that is, performance (BP). Structural model analysis is presented below:
Model specification: The independent variable was financial management practices, which were made up of
latent variables FMS, FRA, ID, FS, and WCM (all these were maintained as they were during CFA). The
dependent variable was performance, which was made up of the latent variable BP. In the proposed model in
Figure 1, observed variables FMS1 and FMS2 relate to latent variable FMS; observed variables FRA1 and FRA2
relate to latent variable FRA; observed variables ID1 and ID2 relate to latent variable ID; observed variables
FS1 and FS2 relate to latent variable FS; Observed variables C1, C3, C6, C7 and C8 relate to latent variable
WCM; and observed variables BP1 and BP2 relate to latent variable BP. On the other hand, latent constructs
FMS, FRA, ID, FS, WCM (independent variables) relate to latent construct BP (dependent variable). The causal
relationship between an independent variable and a dependent variable is shown by a single arrow, whereas the
covariance between the independent variables is represented by two-headed arrows.as illustrated in the structural
model in Figure 1.
Figure1: Structural model with direct path coefficients
Model estimation: The model was estimated using the Maximum likelihood estimation method with the help of
Jeffrey's Amazing Statistics Program (JASP) version 0.19.30 software.
Model fit evaluation: The model was evaluated to assess how well it fitted to data using fit indices, Root Mean
Square Error of Approximation (RMSEA), Comparative Fit Index (CFI), Standardized Root Mean Square
Residual (SRMR), and model chi-square. The summary of fit indices for the model, in Figure 4.4, is as follows:
INTERNATIONAL JOURNAL OF RESEARCH AND SCIENTIFIC INNOVATION (IJRSI)
ISSN No. 2321-2705 | DOI: 10.51244/IJRSI |Volume XII Issue IX September 2025
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Chi-square (𝜒
2
) p-value < 0.001, RMSEA =0.117; CFI =0.819; SRMR =0.080 and TLI=0.746. Concerning the
threshold values indicated in Appendix B2.d, the proposed model is a good fit to the data.
Reliability and validity assessment:
a) Convergent validity: There was convergent validity as depicted by the values of AVE for all the latent
constructs since they were all greater than 0.5. That is, AVE for WCM= 0.654, FS=0.650, ID=0.523,
FRA= 0.715, BP=0.697, and FMS=0.551. Detailed values are in Appendix B2.d.
b) Discriminant validity: Discriminant validity is the degree to which two conceptually similar concepts are
distinct (Hair et al., 2010). Discriminant validity can be obtained if the Heterotrait-Monotrait Ratio of
Correlations (HTMT) value is below 0.90 (Ringle, et al., 2023). In this study, HTMT ratio was used to
test for discriminant validity concepts. It was revealed that there is good discriminant validity since all
the HTHT ratios were less than 0.90 . Therefore, the constructs being studied are truly distinct and not
simply measuring the same underlying concept.
Table. 1: Heterotrait-monotrait ratio
WCMS
FS
ID
FRA
BP
FMS
1.000
0.209
1.000
0.783
0.361
1.000
0.812
0.283
0.812
1.000
0.566
0.132
0.721
0.893
1.000
0.825
0.305
0.748
0.812
0.781
1.000
The CFA confirmed that all latent constructs—FMS, FRA, ID, FS, WCM, table 1, and BP—were measured
reliably and validly. Fit indices demonstrated excellent measurement model fit: CFI and TLI both equal to 1.00,
RMSEA at 0.000, and SRMR values near zero (e.g., SRMR = 6.428×10⁻⁹ for FRA).
Convergent validity was strong, with AVE values exceeding the recommended 0.50 threshold (FRA = 0.628,
BP = 0.569, WCM = 0.654, FS = 0.650, ID = 0.523, FMS = 0.551). These constructs explained a substantial
proportion of variance in their indicators; for example, FRA accounted for 63.4% of variance in FRA1 and
FRA2, and BP explained 56.9% of variance in BP1 and BP2, confirming reliable measurement of the financial
management constructs and performance outcomes.
The structural model relating financial management practices to SME performance was tested using Maximum
Likelihood Estimation. Fit indices were: χ² significant at p < 0.001 (expected with large samples), CFI = 0.819,
TLI = 0.746, RMSEA = 0.117, and SRMR = 0.080. While CFI and TLI were slightly below the ideal cutoff of
0.90, the model fit was deemed acceptable given the complexity of the model and sample size.
All latent variables demonstrated convergent validity with AVE values above 0.50. Discriminant validity was
supported, as all HTMT ratios were below 0.90, indicating conceptual distinctness among constructs such as
FMS, FRA, and WCM.
Path coefficients revealed positive associations between financial management practices and SME performance.
The strongest relationship was between FRA and performance, underscoring the critical role of effective
financial reporting in enhancing SME outcomes. WCM and FMS also positively influenced performance, though
moderately. ID and FS contributed positively but with smaller effect sizes.
Effect of Working Capital Management on Business Performance
The hypothesis that WCM does not influence BP among agro-processing SMEs in the Ankole sub-region was
supported by SEM results (path coefficient = -3.652, p = 0.834), indicating no significant association.
INTERNATIONAL JOURNAL OF RESEARCH AND SCIENTIFIC INNOVATION (IJRSI)
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Though counterintuitive given WCM’s recognized role in liquidity and operational efficiency, this finding aligns
with Positive Accounting Theory (Watts & Zimmerman, 1986), which highlights managerial preference for
internal financing due to the high information costs of external equity. In Ankole SMEs, internal financing
predominates, limiting the adoption of dynamic working capital strategies and thus WCM’s performance impact.
Qualitative insights supported this context: one SME owner reported improved cash flow management
preventing cash shortages despite no significant profit gains, while another noted reliance on informal capital
tracking due to limited access to formal finance.
Contrasting broader literature where WCM generally enhances performance (Sawarni et al., 2020; Wang et al.,
2020a), the insignificant effect here may stem from the micro-scale of SMEs, capital constraints, and reactive
rather than strategic capital practices (Akgün & Karataş, 2020). Non-linear WCM-performance relationships
reported elsewhere (Altaf & Ahmad, 2019; Laghari & Ye, 2019) also suggest that both under- and over-
investment in working capital can harm performance.
Importantly, when firm age was included as a moderator, WCM’s impact on performance became positive and
significant (see Table 1), indicating that as SMEs mature, working capital practices increasingly contribute to
improved business outcomes. This highlights the importance of firm lifecycle stage in interpreting the WCM-
performance relationship.
The Effect of Financing Structures on Business Performance
The study revealed a statistically significant positive relationship between financing structures and business
performance. Financing structure, defined by the balance among debt, equity, and internal funds, plays a crucial
role in enhancing profitability, growth, and sustainability of SMEs, although effects vary by financing type,
sector, and firm size.
Despite widespread challenges in accessing formal finance due to stringent collateral requirements and complex
procedures, many SMEs rely on informal financing such as trade credit and personal savings. While these
informal sources provide short-term liquidity, they often lack scale and duration to support substantial growth,
potentially explaining the weak linkage between working capital management and performance.
Efficient allocation and disciplined use of financial resources emerged as key determinants of business success.
Interviewees emphasized strategic financial planning and targeted fund deployment as mechanisms improving
operational efficiency and profitability, consistent with empirical findings linking financial efficiency to
enhanced SME outcomes (Abor et al., 2023; OECD, 2023).
Extant literature corroborates this nuanced impact: short-term debt and firm age may negatively affect
performance, whereas long-term debt and equity show neutral or positive effects depending on context (Li et al.,
2022; Parvin et al., 2020). Industry-specific financing preferences further complicate these dynamics, with debt-
heavy capital structures common in real estate and manufacturing, contrasted by equity reliance in technology
firms (Lei, 2025).
Governance factors, such as board size and ownership structure, also moderate financing effects (Ngatno et al.,
2021; Zhou et al., 2012). Collectively, findings suggest optimal financing structures depend on firm-specific
factors, and enhancing SME access to diverse, affordable financing combined with capacity-building in fund
management could substantially improve performance.
The Effect of Investment Decisions on Business Performance
Contrary to prevailing SME literature, investment decisions did not have a statistically significant impact on
business performance among agro-processing SMEs in Ankole. Typically, strategic investments, especially in
research and development (R&D), intangible assets, and capital infrastructure, are linked to improved
profitability and growth.
INTERNATIONAL JOURNAL OF RESEARCH AND SCIENTIFIC INNOVATION (IJRSI)
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This divergence appears due to sector-specific constraints, limited resources, and reactive rather than strategic
investment behaviors. Qualitative data showed SMEs often invest primarily for survival, focusing on repairs or
stock replacement instead of innovation or market upgrades. A lack of market research prior to investments
further exacerbates inefficiencies, resulting in poor returns and reluctance to invest in the future.
Global studies consistently demonstrate the positive impact of targeted investments on SME performance (He
& Estébanez, 2023; Ali et al., 2024). The alignment of investment and financing strategies, investment in
intangible assets, and consideration of firm and macroeconomic conditions are critical for success (Abanis et al.,
2022; Seo & Kim, 2020; Adongo et al., 2020).
Psychological and behavioral factors also influence investment effectiveness (Purwidianti et al., 2024a), while
industry-specific evidence highlights the importance of matching investment horizons with financing terms
(Bello & Sensini, 2020). These findings suggest enhancing SMEs’ strategic capacity for investment planning
and market analysis could unlock performance benefits currently unrealized in Ankole.
The Effect of Financial Reporting and Analysis on Business Performance
The study confirmed a statistically significant positive effect of FRA on SME business performance. Reliable
financial information enables better planning, control, and strategic decision-making, thereby improving
profitability and overall outcomes.
Qualitative responses indicated that even locally adapted, simplified financial reporting practices enhanced cost
management, investment decisions, and external credibility. Respondents emphasized that routine financial
reports helped identify inefficiencies and guided profit-oriented decisions, echoing findings by Amoako et al.
(2023) that basic financial reporting improves transparency and accountability.
Extensive literature supports these results. High-quality financial reporting facilitates not only financial
performance but also stakeholder trust, strategic planning, and sustainability initiatives (Bhagavath & Sasirekha,
2025; McMahon & Davies, 1994; Oncioiu et al., 2020). The quality of financial analysis is influenced by data
availability, digital tools, and an innovation culture, all of which enhance decision-making (Gupta et al., 2024;
Huang et al., 2022).
Moreover, financial reporting impacts extend beyond profitability, affecting non-financial performance
dimensions such as environmental and governance reporting (Crous et al., 2021; Galama & Scholtens, 2021).
Mediation effects of profitability and the moderating role of digital transformation further nuance this
relationship (Sumantri et al., 2024).
Overall, these findings reinforce the critical role of FRA as an indispensable tool for SME growth and
sustainability, highlighting the need for capacity-building to improve financial literacy and reporting quality in
emerging market contexts.
CONCLUSION
This study assessed the impact of financial management practices on SME performance in emerging markets,
focusing on agro-processing firms in Uganda’s Ankole sub-region. Using SEM, the study examined five
constructs, FMS, FRA, ID, FS, and WCM, in relation to business performance. FRA showed the strongest
positive association, underscoring the importance of consistent and reliable financial reporting. FMS and FS also
had positive but smaller effects. WCM and ID showed no significant direct impact, likely due to resource
limitations and informal practices among smaller or early-stage firms. However, firm age moderated the effect
of WCM, indicating its increasing relevance as SMEs mature.
These results highlight the differentiated impact of financial practices and the influence of contextual factors
such as firm lifecycle. Policy and development interventions should prioritize strengthening FRA and FS
capabilities while promoting financial planning aligned to firm maturity. Support structures must reflect sector-
specific constraints and the realities of informal financial behaviors.
INTERNATIONAL JOURNAL OF RESEARCH AND SCIENTIFIC INNOVATION (IJRSI)
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Future research should adopt longitudinal designs to explore changes over time, investigate digital financial
tools’ role in enhancing management capacity, and examine behavioral or institutional factors influencing
practice adoption. These insights will guide more tailored interventions to improve SME resilience,
competitiveness, and long-term sustainability in emerging economies.
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