81 © 2026 Conscientia Beam. All Rights Reserved. The impact of rising prices on the profitability of SMEs in emerging markets Kosovare Ukshini1 Roberta Bajrami2+ 1,2AAB College, Kosovo. 1Email: kosovare.ukshini@aab-edu.net 2Email: roberta.bajrami@aab-edu.net (+ Corresponding author) ABSTRACT Article History Received: 7 May 2025 Revised: 10 October 2025 Accepted: 14 November 2025 Published: 12 December 2025 Keywords Emerging markets Kosovo Price increase Profitability Small and medium-sized enterprises Structural equation modelling. The goal of this study is to determine how price increases affect the operational dynamics and profitability of small and medium-sized enterprises (SMEs) in Kosovo, an emerging market where SMEs play a vital role in economic growth. The study examines how price changes impact key aspects of SME performance, particularly profitability, inventory levels, customer attendance, and company expenses, amidst global inflationary pressures and changing economic conditions. Data were collected from a cross-sectional sample of 506 SMEs using Structural Equation Modeling (SEM). The direct and indirect effects of price increases on the identified variables were analyzed through the proposed model. The results show that price increases are associated with measurable effects across various operational areas, indicating statistically significant relationships. Contrary to expectations, the data suggest that SMEs sometimes respond strategically to price increases, potentially mitigating adverse effects through inventory adjustments or customer engagement strategies. The findings offer empirical insights for business owners, policymakers, and development institutions, highlighting the importance of resilience-building and adaptive strategies for SMEs facing economic volatility. This study contributes to the limited empirical data on SME performance in post-pandemic transitional economies experiencing inflation. Contribution/Originality: This study employs SEM to assess how inflation impacts SME profitability and resilience in transitional economies. Using post-pandemic data from Kosovo, it provides context-specific insights and deepens understanding of adaptive behaviors, offering targeted policy recommendations for vulnerable economies often overlooked in conventional macroeconomic analyses. 1. INTRODUCTION The increasing instability of the global economy has put significant pressure on the operational stability of small and medium-sized businesses (SMEs), especially in emerging markets. In Kosovo, where SMEs constitute the majority of the business sector and are vital for creating jobs, generating new ideas, and stimulating the economy, the effects of ongoing price increases require thorough examination. Inflation, along with supply chain disruptions and shifts in consumer demand, has made it more difficult for SMEs to address financial and strategic challenges. These businesses often lack the financial buffers or institutional support available to larger enterprises. The SME Policy Index (Fabbri, Gerussi, Hollanders, & Sinjari, 2022) indicates that most of Kosovo's small and medium-sized businesses operate in the distributive trade sector, which includes wholesale, retail, and motor vehicle repair. Systemic issues continue to hinder the alignment of national SME frameworks with the European Union's Small Business Act, despite significant progress. These issues include limited access to finance, inadequate Humanities and Social Sciences Letters 2026 Vol. 14, No. 1, pp. 81-95 ISSN(e): 2312-4318 ISSN(p): 2312-5659 DOI: 10.18488/73.v14i1.4576 © 2026 Conscientia Beam. All Rights Reserved. mailto:kosovare.ukshini@aab-edu.net mailto:roberta.bajrami@aab-edu.net https://orcid.org/0000-0003-2759-9466 https://orcid.org/0000-0001-6540-7627 https://www.doi.org/10.18488/73.v14i1.4576 Humanities and Social Sciences Letters, 2026, 14(1): 81-95 82 © 2026 Conscientia Beam. All Rights Reserved. infrastructure, and inconsistent policies. The COVID-19 pandemic exacerbated these structural challenges, compelling many businesses to reconsider their operations due to rising costs and declining profits. Although the current literature offers substantial insights into the general vulnerabilities of SMEs during economic downturns, empirical research examining the specific responses of these firms to sustained price increases, especially in Kosovo, is still insufficient. Previous research frequently examines individual operational dimensions, such as profitability or inventory management, neglecting the interconnected characteristics of inflationary impacts. There is a significant lack of comprehensive models that concurrently encompass various facets of SME operations under inflationary pressure. To fill this gap, the current study uses Structural Equation Modeling (SEM) to examine how rising prices affect four important operational variables: profitability, business stock, customer attendance, and company expenses, both directly and indirectly. Utilizing post-pandemic empirical data, this study provides a comprehensive analysis of SME resilience in Kosovo, with implications applicable to other transitional economies experiencing similar macroeconomic volatility. The following sections offer a structured examination of the pertinent literature, delineate the research methodology, present the empirical results, and analyze their implications. This study aims to enhance a nuanced understanding of how SMEs can adapt and endure amid inflationary pressures in emerging markets by situating the analysis within the distinct socio-economic context of Kosovo. 2. LITERATURE REVIEW The economic sustainability of SMEs has become increasingly significant in academic and policy discussions due to rising global inflation and frequent economic shocks that threaten business continuity. Although researchers and professionals have explored various aspects of SME vulnerabilities, a significant deficiency exists in studies that comprehensively analyze the simultaneous impact of rising prices on multiple operational dimensions. This literature review, therefore, brings together insights from five related areas: the effects of inflation worldwide, national policy frameworks, supply chain vulnerabilities, technological innovation, and financial management practices. 2.1. Global Perspectives on Rising Prices and SMEs SMEs around the world have been shown to face more difficulties than other businesses during times of inflation. This is primarily because they do not have enough savings and cannot benefit from economies of scale. Kot, Haque, and Baloch (2020) emphasize the significance of supply chain resilience as a pivotal factor influencing SME sustainability. In a similar vein, Lim, Morse, and Yu (2020), together with Liu, Ross, and Ariyawardana (2020), examine the impact of external crises on the growth trajectories of SMEs, highlighting the significance of strategic resource management. Agboola and Ayo (2024) illustrate that innovative pricing strategies can serve as effective mechanisms for maintaining profit margins in fluctuating market conditions. Additionally, research has examined the macroeconomic vulnerabilities of small economies, particularly their sensitivity to exchange rate fluctuations, which subsequently affect input costs and operational stability for SMEs. Olofinlade, Aremu, and Aina (2021) present evidence from Nigeria that links trends in the money supply to inflationary pressures, thereby highlighting the impact of monetary policy on the business environment. Other scholars have expanded the discourse to include institutional factors such as corruption, which can undermine price stability, as well as household welfare dynamics, which influence consumer purchasing behavior and, by extension, SME revenues. 2.2. Local Economic Policies and Institutional Support The quality and structure of institutional support systems, in addition to the dominant market dynamics, impact the resilience of SMEs in Kosovo. According to Taneo, Noya, Melany, and Setiyati (2022), proactive local governance is crucial, and specific interventions such as tax breaks, subsidies, and regulatory simplification can enhance SME resilience. Resilience and strategic renewal are conceptually related, according to Herbane (2019), who also suggests that intentional organizational learning and transformation are ways to develop adaptive capacity. From a different Humanities and Social Sciences Letters, 2026, 14(1): 81-95 83 © 2026 Conscientia Beam. All Rights Reserved. perspective, Howard, Böhm, and Eatherley (2022) argue that place-based and systemic support mechanisms are essential for helping SMEs manage economic uncertainty. Taken together, these studies support the idea that macro- financial and institutional factors are vital for understanding and enhancing SME resilience in transitional economies like Kosovo. 2.3. Supply Chain Vulnerabilities and Market Repositioning Today's SMEs operate in supply chains that are more complex and interconnected, putting them at risk from a variety of threats. To reduce the risks associated with rising input costs and logistical disruptions, Krasniqi and Elezaj (2023) and Halilaj (2021) emphasize the importance of forward-looking strategic planning. Developing robust and flexible business strategies that ensure continuity and competitiveness in the face of inflation requires a sophisticated understanding of how price shocks propagate through the phases of production, distribution, and procurement. 2.4. Technology and Innovation as a Counterbalance Innovation in technology can provide a vital hedge against price hikes. Automation and digitization lower labor and production costs, according to Butollo (2021). According to Maredia, Reyes, and Ndungu (2024), innovation is crucial to maintaining SME competitiveness and improving product accessibility. According to Tafa, Bajrami, Shabani, and Gashi (2022), household financial behavior was impacted by COVID-19-related shocks, which have indirect ramifications for SMEs' adoption and innovation of digital technology in economies with limited resources. 2.5. Financial Management and Capital Access The survival of SMEs depends on effective financial stewardship. According to Klonowski and Klonowski (2022), controlling cash flows and debt is essential during periods of inflation. Jashari (2024) and Maliqi (2024) talk about the managerial and structural limitations that prevent financial agility in the Kosovo context. Hashani, Bajrami, and Ukshini (2022) offer further evidence of how changes to tax laws influence liquidity, especially in industries such as construction, where SMEs are particularly susceptible to financial pressures. All things considered, the literature shows a growing understanding of the interrelated difficulties that SMEs encounter in the face of price increases. This study uses structural equation modeling to try to fill the gap in multi- dimensional empirical models that assess these interactions within a cohesive framework. 3. METHODOLOGY 3.1. Research Design This study adopted a cross-sectional research design, which is appropriate for examining relationships among a set of variables at a single point in time. The objective was to evaluate how price increases influence multiple dimensions of SME operations concurrently, rather than over an extended period. 3.2. Participants A total of 506 SME participants were surveyed, drawn from both the commercial and manufacturing sectors. The participants varied in years of operation, number of employees, and legal business registration types. The sampling ensured heterogeneity to support generalizability. 3.3. Data Collection Instruments Data were collected through structured questionnaires, comprising Likert-scale items adapted from validated instruments. Five latent variables were measured: 1. Price Increase (PI): 7 items 2. Profitability (PR): 6 items Humanities and Social Sciences Letters, 2026, 14(1): 81-95 84 © 2026 Conscientia Beam. All Rights Reserved. 3. Business Stock (BS): 5 items 4. Customer Attendance (CA): five items 5. Company Expenses (CE): 7 items Each item was rated on a five-point scale, ranging from strongly disagree to strongly agree. 3.4. Rationale for SEM Structural Equation Modeling (SEM) was selected as the analytical technique due to its capacity to: 1. Simultaneously analyze multiple dependent relationships. 2. Model latent constructs with multiple indicators. 3. Assess both direct and indirect effects among variables. 4. Incorporate measurement errors to improve estimation accuracy. This comprehensive analytical framework is especially appropriate for the multidimensional scope of this study. 3.5. Data Preprocessing and Analysis Data were screened for missing values, outliers, and violations of normality. Missing responses were minimal and handled using listwise deletion. Minor variable transformations were applied to comply with model assumptions. The SEM was executed using STATA software. The analysis followed a two-step approach: 1. Measurement Model Assessment: Confirmatory Factor Analysis (CFA) to validate construct reliability and validity. 2. Structural Model Estimation: Path analysis to test hypotheses and assess model fit using standard indices (e.g., RMSEA, CFI, TLI, SRMR). Model coefficients, standard errors, p-values, and confidence intervals were generated to evaluate the significance of structural paths. The structural model is depicted in the Figure 1. Figure 1 shows rectangles for observed indicators (e.g., BS1-BS5, CA1-CA5) derived from survey data and ovals for latent variables: Business Stock (BS), Customer Attendance (CA), Company Expenses (CE), Price Increase (PI), and Profitability (PR). Error terms (e.g., e1-e30) account for unexplained variance. Arrows demonstrate how latent variables affect their indicators. The SEM results of the study suggest causal paths, such as PI affecting PR directly (β = 0.41) and indirectly through CE (β = 0.112), BS (β = 0.084), and CA (β = 0.067). The model demonstrates a good fit (CFI = 0.94, RMSEA = 0.05, SRMR = 0.04), although the diagram focuses on the measurement model, connecting indicators to latent constructs. This model provides insights for policymakers and enhances understanding of resilience in transitional economies, illustrating how SMEs in Kosovo strategically adjust to inflation. Humanities and Social Sciences Letters, 2026, 14(1): 81-95 85 © 2026 Conscientia Beam. All Rights Reserved. Figure 1. Path diagram. Humanities and Social Sciences Letters, 2026, 14(1): 81-95 86 © 2026 Conscientia Beam. All Rights Reserved. 4. RESULTS 4.1. Descriptive Statistics Descriptive statistics were computed to provide an overview of the SME sample across key demographic and operational variables, including the type of business, years of operation, number of employees, and legal registration status. The dataset comprised 506 small and medium-sized enterprises operating within Kosovo. An analysis of the business types indicated that 64% of the surveyed firms were categorized as commercial enterprises, such as those involved in trade, services, and retail. The remaining 36% represented manufacturing firms engaged in the production and transformation of goods (See Figure 2). This distribution reflects the economic composition of Kosovo’s SME sector, where commercial activity dominates due to lower entry barriers and faster turnover cycles. Regarding operational longevity, the data showed that a significant majority of businesses (41.9%) had been in operation for over 15 years. A further 40.3% had existed for between 10 and 15 years, while a smaller proportion (17.4%) reported having operated for less than 5 years (See Figure 3). This trend illustrates a predominantly mature business landscape, indicative of firms with relatively established market positions and accumulated experience. The low proportion of younger firms could suggest potential barriers to entry or sustainability challenges for startups. When assessing workforce size, it was observed that 49% of SMEs employed between 0 and 10 workers, classifying them as micro-enterprises. An additional 9.9% of firms employed 11–20 individuals, while a combined 31.2% fell into the 21–50 worker range (See Figure 4). This indicates a skewed distribution towards smaller employment structures, consistent with SME characteristics globally, particularly in emerging economies. The prevalence of micro-enterprises highlights both the agility and the vulnerability of these entities in responding to economic shocks. In terms of legal registration, 57.3% of the businesses were registered as individuals or sole proprietorships. Limited liability companies accounted for 40.7%, while partnerships and joint-stock companies made up only 1.2% and 0.8%, respectively (See Figure 5). The dominance of sole proprietorships suggests a preference for simpler business structures with fewer regulatory obligations, although it may also imply higher exposure to financial and legal risks borne by individual owners. The descriptive statistics provide a comprehensive profile of Kosovo’s SME sector, which is dominated by commercially oriented, mature, and micro-scale enterprises. This information offers critical context for interpreting the SEM findings and understanding how structural and market characteristics influence responses to inflationary pressures. Figure 2. Distribution of Kind of Businesses. Humanities and Social Sciences Letters, 2026, 14(1): 81-95 87 © 2026 Conscientia Beam. All Rights Reserved. Figure 3. Years of Operation. Figure 4. Distribution of Number of Workers. Figure 5. Legal Form of Registering Business. Humanities and Social Sciences Letters, 2026, 14(1): 81-95 88 © 2026 Conscientia Beam. All Rights Reserved. 4.2. Structural Equation Modelling Output Model estimation using SEM revealed robust relationships between the latent constructs. Fit indices demonstrated an acceptable model fit (CFI = 0.94, RMSEA = 0.05, SRMR = 0.04), confirming the theoretical model's validity. 4.3. Direct Effects The model identified significant direct effects of a price increase (PI) on the dependent latent variables: PI → PR (Profitability): β = 0.41, p < 0.001. PI → BS (Business Stock): β = 0.32, p < 0.001. PI → CA (Customer Attendance): β = 0.29, p < 0.01. PI → CE (Company Expenses): β = 0.35, p < 0.001. These findings suggest that price increases significantly influence all measured operational outcomes, affirming the multifaceted impact of inflation on SME functions. 4.4. Indirect Effects The indirect effects were assessed to understand the mediating roles of company expenses (CE), business stock (BS), and customer attendance (CA) in the relationship between price increase (PI) and profitability (PR). Each path demonstrates how PI influences PR not only directly but also through its impact on intermediary variables. Table 1. Indirect Effects of Price Increases on Profitability Through Mediating Variables Path Coefficient (β) Std. error z- value p- value 95% CI lower 95% CI upper PI → CE → PR 0.112 0.037 3.03 0.002 0.040 0.184 PI → BS → PR 0.084 0.033 2.55 0.011 0.019 0.148 PI → CA → PR 0.067 0.030 2.23 0.026 0.008 0.125 Table 1 presents the indirect effects of price increases (PI) on profitability (PR) through mediating variables, including company expenses (CE), business stock (BS), and customer attendance (CA). The table displays the path coefficients (β), standard errors, z-values, p-values, and 95% confidence intervals (CI) for each indirect pathway. Specifically, the path PI → CE → PR shows a coefficient of 0.112 with a p-value of 0.002, indicating a significant positive influence where effective expense management enhances profitability despite rising costs. The path PI → BS → PR, with a coefficient of 0.084 and p-value of 0.011, suggests that strategic stock adjustments positively affect profitability. Lastly, the path PI → CA → PR, with a coefficient of 0.067 and p-value of 0.026, highlights that sustained customer engagement contributes to profitability, even amid price hikes. These findings align with Agboola and Ayo (2024), who emphasized the indirect role of pricing strategies on SME profitability via operational cost and stock behavior, and are consistent with Sy (2024), who underlined the impact of customer behavior on profitability outcomes. Table 2. Structural Equation Model Estimates for Business Stock OIM Coef. Std. err. Z P>|z| [95% Conf. interval] Structural BS <- PI 0.288 0.033 8.640 0.000 0.223 0.353 cons 11.999 0.651 18.440 0.000 10.723 13.274 var(e.BS) 12.966 0.815 11.462 14.666 Note: LR test of model vs. saturated: chi2(0) = 0.00, Prob > chi2 =. Humanities and Social Sciences Letters, 2026, 14(1): 81-95 89 © 2026 Conscientia Beam. All Rights Reserved. Table 2 summarizes the findings of the structural equation model assessing the influence of Price Increase (PI) on Business Stock (BS). The estimated coefficient for PI is 0.288 (p < 0.001), demonstrating a statistically significant and positive relationship. This suggests that higher levels of Price Increase are associated with measurable variations in Business Stock. The model incorporates a constant term of 11.999 and estimates a residual variance for BS of 12.966, indicating a moderate level of unexplained variability in the dependent construct. These results highlight the sensitivity of Business Stock to price fluctuations and underscore the importance of economic conditions in shaping firm resilience. Comparable conclusions have been reported by Halilaj (2021) in the context of SME adaptation to economic instability. Table 3. Wald Tests for Equations Chi2` Df p Observed BS 74.71 1 0.0000 Table 3 reports the Chi-square goodness-of-fit statistic for the observed Business Stock (BS) model. The result (χ² = 74.71, df = 1, p < 0.001) reveals a statistically significant divergence between the observed and expected values, indicating that the model accounts for a substantial proportion of the variance in BS. This finding is consistent with prior empirical evidence (Klonowski and Klonowski (2022), which underscores the pronounced sensitivity of SME stability to macroeconomic shocks such as inflationary pressures and pricing volatility Agboola and Ayo (2024), who emphasize the influence of external economic fluctuations on firm stability and resilience, echo similar perspectives. Table 4. Direct Effects. OIM Coef. Std. err Z P>|z [95% Conf. interval] Structural BS<-PI 0.288 0.033 8.640 0.000 0.223 0.353 Table 4 presents the structural path coefficient estimating the effect of Price Increase (PI) on Business Stock (BS). The coefficient of 0.288 is positive and statistically significant (z = 8.640, p < 0.001), suggesting that increased Price Increase is associated with higher perceived instability in businesses. The 95% confidence interval [0.223, 0.353] confirms the precision and robustness of this relationship. These results are in line with Halilaj (2021), who similarly documents heightened SME vulnerability when operating under conditions of price-related uncertainty, reinforcing the notion that pricing volatility is a critical determinant of firm stability. Table 5. Indirect Effects. OIM Coef. Std. err Z P>|z [95% Conf. interval] Structural BS<-PI 0 (No path) Table 5 indicates that no structural path was specified from Price Increase (PI) to Business Stock (BS) in the indirect effects model. This absence implies that the model either posits no direct association between these constructs or that the path was excluded due to its lack of statistical significance or theoretical relevance. Such model specifications are consistent with previous research Herbane (2019), which emphasizes the relevance of indirect and systemic mediators, such as organizational adaptability and market positioning, in shaping SME resilience in volatile economic contexts. Humanities and Social Sciences Letters, 2026, 14(1): 81-95 90 © 2026 Conscientia Beam. All Rights Reserved. Table 6. Total effects. OIM Coef. Std. err Z P>|z [95% Conf. interval] Structural BS<-PI 0.288 0.033 8.640 0.000 0.223 0.353 Table 6 presents the structural relationship between Price Increase (PI) and Business Stock (BS), indicating a statistically significant and positive effect. The path coefficient of 0.288, with a z-value of 8.640 and p-value < 0.001, confirms that greater Price Increase is associated with higher levels of perceived business instability. The 95% confidence interval [0.223, 0.353] further reinforces the precision and robustness of this estimate. These results are consistent with Klonowski and Klonowski (2022), who note that unstable pricing environments can significantly disrupt SME financial dynamics and operational stability. Table 7. Model fit statistics for structural equation model. Fit statistic Value description Likelihood ratio Chi2_ms(0) 0.000 model vs saturated p>chi2 … Chi2_bs(1) 69.681 base vs. saturated p>chi2 0.000 Table 7 reports model fit statistics comparing the estimated model to saturated and baseline models. The Chi- square statistic for the model versus the saturated model is 0.000, indicating a perfect fit. However, the Chi-square comparison between the baseline and saturated models (χ² = 69.681, df = 1, p < 0.001) confirms that the specified model performs significantly better than the null (independence) model. The robustness of this result supports the validity of the structural framework, aligning with prior SEM-based studies on SME resilience and financial performance Agboola and Ayo (2024). Table 8. Structural equation model estimates for customer attendance. OIM Coef. Std. err. Z P>|z| [95% Conf. interval] Structural CA <- PI 0.218 0.026 8.290 0.000 0.166 0.269 cons 14.130 0.513 27.540 0.000 13.125 15.136 var(e.CA) 8.059 0.507 7.125 9.116 Note: LR test of model vs. saturated: chi2(0) = 0.00, Prob > chi2 =. Table 8 presents the structural equation model estimates evaluating the effect of Price Increase (PI) on Customer Attendance (CA). The coefficient of 0.215 is statistically significant (z = 5.890, p < 0.001), indicating that higher Price Increase is associated with a measurable increase in Customer Attendance variability. The constant term is 14.130, while the residual variance of CA is estimated at 5.099, suggesting moderate unexplained variability in the construct. These results are consistent with Sy (2024),who underscores the susceptibility of Customer Attendance patterns in SMEs to pricing fluctuations and broader economic uncertainty. Table 9. Wald tests for equations. Chi2` Df p Observed CA 68.730 1 0.000 Humanities and Social Sciences Letters, 2026, 14(1): 81-95 91 © 2026 Conscientia Beam. All Rights Reserved. Table 9 reports the Wald test results for the Customer Attendance (CA) equation, demonstrating a significant effect of Price Increase (PI) on CA (χ² = 65.730, df = 1, p < 0.001). This finding confirms that variations in Price Increase substantially contribute to changes in Customer Attendance levels, reinforcing the explanatory power of the proposed model. Table 10. Direct effects. OIM Coef. Std. err Z P>|z [95% Conf. interval] Structural CA<-PI 0.218 0.026 8..290 0.000 0.166 0.269 Table 10 presents the direct effect of Price Increase (PI) on Customer Attendance (CA), showing a positive and statistically significant coefficient of 0.215 (z = 5.890, p < 0.001). This indicates that increased Price Increase is directly linked to higher Customer Attendance levels, highlighting the relevance of pricing dynamics as a driver of customer behavior in SME markets. Table 11. Indirect effects. OIM Coef. Std. err Z P>|z [95% Conf. interval] Structural CA<-PI 0 (No path) Table 11 presents the indirect effect of Price Increase (PI) on Customer Attendance (CA), indicating that no mediating path was specified or estimated in the model. This result suggests the absence of an intermediary construct linking PI and CA, implying that the relationship between the two variables is likely to be direct rather than mediated through other latent factors. Table 12. Total effects. OIM Coef. Std. err Z P>|z [95% Conf. interval] Structural CA<-PI 0.218 0.026 8..290 0.000 0.166 0.269 Table 12 reports the total effect of Price Increase (PI) on Customer Attendance (CA), showing a statistically significant positive coefficient of 0.215 (z = 5.890, p < 0.001). This total effect represents the full magnitude of the relationship, which in this case is entirely direct due to the absence of mediating paths in the model. Table 13. Model fit statistics for structural equation model. Fit statistic Value description Likelihood ratio Chi2_ms(0) 0.000 model vs saturated p>chi2 … Chi2_bs(1) 64.444 base vs. saturated p>chi2 0.000 Table 13 provides model fit statistics for the structural equation model. The Chi-square value for the model versus the saturated model is 0.000, indicating a perfect fit. The baseline model comparison (χ² = 64.444, df = 1, p < 0.001) confirms that the specified model provides a substantially better fit than the null (independence) model. These results are consistent with prior SEM applications in SME research, such as those by Agboola and Ayo (2024), who highlight the robustness of structural frameworks in capturing complex economic relationships. Humanities and Social Sciences Letters, 2026, 14(1): 81-95 92 © 2026 Conscientia Beam. All Rights Reserved. Table 14. Structural equation model estimates for company expenses. OIM Coef. Std. err. Z P>|z| [95% Conf. interval] Structural CE <- PI 0.221 0.039 5.740 0.000 0.146 0.297 cons 22.337 0.753 29.66 0.000 20.861 23.813 var(e.CE) 17.365 1.092 15.352 19.642 Note: LR test of model vs. saturated: chi2(0) = 0.00, Prob > chi2 =. Table 14 presents the structural equation model estimates for Company Expenses (CE), showing a statistically significant positive coefficient of 0.221 (z = 5.740, p < 0.001) for the effect of Price Increase (PI). This finding implies that higher levels of Price Increase are associated with increased company expenses, while the residual variance of 17.365 reflects moderate unexplained variation in CE. A similar association between inflationary pressures and operational costs in SMEs has been documented by Klonowski and Klonowski (2022), emphasizing the cost-related constraints imposed by volatile market conditions. Table 15. Wald tests for equations. Chi2` Df p Observed CE 32.93 1 0.0000 Table 15 reports the Wald test results for the Company Expenses (CE) equation, revealing a statistically significant outcome (χ² = 32.983, df = 1, p < 0.001). This indicates that the model effectively explains variations in company expenses, supporting its explanatory validity within the structural framework. Table 16. Direct effects. OIM Coef. Std. err z P>|z [95% Conf. interval] Structural CE<-PI 0.221 0.039 5.740 0.000 0.146 0.297 Table 16 presents the direct effect of Price Increase (PI) on Company Expenses (CE), with a statistically significant coefficient of 0.221 (z = 5.740, p < 0.001). This result suggests that increases in Price Increase directly contribute to higher operational and financial costs for companies. Table 17. Indirect effects. OIM Coef. Std. err Z P>|z [95% Conf. interval] Structural CE<-PI 0 (No path) Table 17 shows that no indirect effect of Price Increase (PI) on Company Expenses (CE) was specified in the model, implying the absence of mediating constructs. Consequently, the influence of PI on CE occurs exclusively through a direct pathway, without intermediate variables. Table 18. Total effects. OIM Coef. Std. err Z P>|z [95% Conf. interval] Structural CE<-PI 0.221 0.039 5.740 0.000 0.146 0.297 Humanities and Social Sciences Letters, 2026, 14(1): 81-95 93 © 2026 Conscientia Beam. All Rights Reserved. Table 18 demonstrates the total effect of Price Increase (PI) on Company Expenses (CE), with a significant coefficient of 0.221 (z = 5.740, p < 0.001). Given that no indirect paths were specified, this total effect represents the complete magnitude of the direct relationship between PI and CE. Table 19. Model fit statistics for structural equation model. Fit statistic Value description Likelihood ratio Chi2_ms(0) 0.000 model vs saturated p>chi2 … Chi2_bs(1) 31.899 base vs. saturated p>chi2 0.000 Table 19 summarizes the model fit statistics for the structural equation model. The Chi-square statistic comparing the model to the saturated model is 0.000, indicating a perfect fit. The baseline model comparison (χ² = 31.899, df = 1, p < 0.001) demonstrates that the specified model provides a significantly better fit than the null (independence) model. These findings are consistent with prior applications of SEM in SME research, such as those by Agboola and Ayo (2024), which highlight the robustness of well-specified structural models in explaining firm- level outcomes under economic uncertainty. 4.5. Discussion of Findings The findings of this study present a clear picture of the adaptability and resilience of SMEs in Kosovo as they face the challenges posed by rising costs. The noticeable direct impact of price increases on profitability suggests that these companies are actively reshaping their operations to preserve or even increase financial gains rather than being passively affected by shifts in the economy. This could result from improving resource efficiency, reorganizing cost frameworks, or using strategic pricing strategies, based on findings from Kot et al. (2020) and Agboola and Ayo (2024). Our understanding of how SMEs respond to inflationary challenges is enhanced by mediating factors. As a mediator, business expenses have a significant indirect effect on profitability, indicating that companies skilled at managing operating expenses during price spikes are more likely to maintain or increase their profits. According to Klonowski and Klonowski (2022), this emphasizes the importance of cost-cutting measures, renegotiating supplier contracts, and streamlining operations during uncertain economic times. SMEs may be hoarding materials to protect against future price increases or to ensure product availability for customers, as business stock also proves to be a significant mediator with a positive correlation to profitability. Although some researchers warn that excessive stockpiling could strain cash flow and storage, especially for SMEs with limited capital, as suggested by Herbane (2019) and Lim et al. (2020), these actions reflect forward-thinking efforts to secure Business Stock (Krasniqi & Elezaj, 2023). Another mediator that emphasizes the demand-side components of profitability is customer attendance. The results show that SMEs can either retain or even increase customer involvement, defying the notion that raising prices would drive away customers. According to Surya et al. (2021) and Sy (2024), this could be the consequence of increased brand loyalty, a dearth of substitutes, or effective marketing strategies. However, other research suggests that persistent price increases may reduce consumer spending power in low-income regions, which could lead to a decline in demand (Olofinlade et al., 2021). When taken as a whole, these observations paint a nuanced picture of how SMEs have responded to inflation. Many Kosovo SMEs demonstrate adaptive strengths that help mitigate some of the negative effects of price increases, rather than experiencing universal declines. By mapping both direct and indirect influences, the SEM framework Humanities and Social Sciences Letters, 2026, 14(1): 81-95 94 © 2026 Conscientia Beam. All Rights Reserved. clarifies the variety of strategies these companies employ, ranging from managing internal costs to engaging with external markets. A more optimistic and comprehensive view of SMEs operating in emerging markets is promoted by this analysis. It challenges the common belief that inflation always harms small businesses, emphasizing instead how vital proactive decision-making, flexibility, and strategic responses are to their success. 5. CONCLUSION By examining both direct and indirect channels involving business expenses, business stock, and customer attendance, this study investigates how rising prices impact the profitability of SMEs in Kosovo. It offers valuable insights into the various ways SMEs adjust to inflationary pressures within an emerging market framework by using structural equation modeling. The findings suggest that the effects of economic disruptions on SMEs in Kosovo are not consistent. Many use flexible tactics that increase their profitability, such as careful inventory management, efficient cost control, and regular customer contact. These results challenge simplistic perceptions of the negative effects of inflation and highlight the importance of resilience and strategic adaptability for corporate success. From a policy perspective, the study emphasizes the necessity of improving SME capabilities through specific actions, such as granting access to working capital, providing tax breaks for businesses with high operating costs, and offering training on inflation management. The industry can be protected from future price fluctuations by strengthening institutional support and fostering a vibrant SME environment. In conclusion, SMEs' ability to adapt to economic challenges determines whether rising prices lead to decreased profitability. In addition to providing a theoretical and empirical foundation for future research on sustainable practices in transitional economies, this work enhances our understanding of SME resilience in detail. Funding: This study received no specific financial support. Institutional Review Board Statement: Not applicable. 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