Volume 7.
Number 1, 2026 https://ijble.
com/index.
php/journal/index Driving Agribusiness MSME Performance:
Linking Service Quality to Innovation Capability Agus Usman1.
Windarko2 1,2Department of Management.
Universitas Pembangunan Jaya.
Indonesia Coresponding Author: agus.
usman@upj.
ABSTRACT
This study examines the effect of service quality on small and medium-sized enterprise (SME) performance, with innovation capability serving as a mediating variable.
A quantitative research design was employed using Partial Least Squares Structural Equation Modelling (PLS-SEM).
The study involved owners and managers of SMEs operating in the processed food sector based on agricultural commodities.
Data were collected through a structured questionnaire and analysed using SmartPLS version 4.
The results demonstrate that service quality has a significant positive effect on SME performance and acts as a key driver of innovation capability.
Furthermore, innovation capability significantly mediates the relationship between service quality and performance, indicating that SMEs can convert superior service quality into improved performance outcomes through enhanced innovation.
These findings highlight the strategic role of innovation capability in strengthening the impact of service quality on business This study contributes to literature by providing empirical evidence from agribusiness-based SMEs and emphasizing innovation as a critical factor for achieving sustainable competitiveness at both local and global levels.
The findings offer important managerial implications for SME practitioners and policymakers in designing strategies that integrate service excellence with innovation development.
Keywords:
Service quality, innovation capability.
SMEs Performance.
DOI.
https://doi.
org/10.
56442/ijble.
INTRODUCTION
Service quality has been widely acknowledged as a critical determinant of business performance, particularly in increasingly competitive and customer-centric Seminal studies argue that superior service quality enhances customer satisfaction, trust, and loyalty, which subsequently improve financial and market performance (Cronin & Taylor, 1.
Subsequent empirical research across service and manufacturing sectors confirms that service quality contributes significantly to profitability, market share, and cu stomer retention (Zeithaml et al.
, 1.
competition intensifies and customer expectations rise, service quality has evolved from an operational concern into a strategic resource that supports sustained competitive advantage (Yu et al.
, 2.
However, despite strong empirical support for the direct service qualityAeperformance relationship, firms often struggle to sustain performance gains in volatile, innovation-driven environments.
To address this limitation, recent studies emphasize innovation capability as a key mechanism through which service quality can be converted into long-term performance outcomes.
Innovation capability refers to a firmAos ability to develop and implement new ideas related to products, processes, and services in response to changing market demands (Cavusgil, 2.
High service quality facilitates closer interaction with customers and stakeholders, enabling firms to acquire market knowledge that stimulates organizational learning and innovation (Chen et al.
, 2.
Volume 7.
Number 1, 2026 https://ijble.
com/index.
php/journal/index From the Resource-Based View (RBV) and Dynamic Capabilities Theory, innovation capability represents a higher-order capability that allows firms to sense opportunities, seize them through innovation, and reconfigure resources to adapt to environmental turbulence (Teece et al.
, 2.
Empirical evidence from Scopus-indexed studies consistently demonstrates that innovation capability has a significant positive impact on business performance across industries and firm sizes (Saunila, 2020.
Saunila et , 2.
Despite growing scholarly interest in service quality and innovation capability, research examining their integrated relationship remains relatively limited.
Most prior studies focus on their direct effects on performance, while fewer investigate the underlying mechanisms that explain how service quality translates into superior performance outcomes.
Recent studies suggest that innovation capability may serve as a critical mediating variable, enabling firms to transform service-related resources into innovative solutions and competitive advantage (Jimynez-Jimynez.
& SanzValle, 2011.
Wang & Ahmed, 2.
Understanding this mediating role is particularly important for firms operating in dynamic environments where continuous innovation is essential for sustaining performance.
Therefore, this study aims to examine the relationship between service quality and business performance and to analyze the mediating role of innovation capability, thereby contributing to the capability-based performance literature and offering strategic insights for managers seeking sustainable growth.
Literature Review and Hypotesis Development Extant literature consistently demonstrates that service quality has a significant positive effect on SME performance, particularly in competitive and relationship-based High service quality enhances customer satisfaction, trust, and loyalty, which subsequently improve financial outcomes and market performance (Cronin & Taylor.
Parasuraman et al.
, 1.
In SME contexts, superior service quality functions as a strategic intangible resource that strengthens customer relationships and supports competitive advantage (Yu et al.
, 2.
Empirical studies in emerging economies further confirm that service quality positively influences operational and financial performance among SMEs, including agri-based firms (Sureshchandar.
Rajendran, and Anantharaman, 2002.
Ngo and Nguyen, 2.
Grounded in the Resource-Based View (RBV), these findings support the argument that service quality is a valuable and difficult-to-imitate capability.
Accordingly, this study proposes.
H1:
Service quality has a positive effect on SME performance.
In addition to its direct performance impact, service quality has been found to play a crucial role in strengthening innovation capability.
Close interactions with customers and supply-chain partners enable firms to acquire market knowledge that stimulates learning and innovation activities (Garcia & Calantone, 2.
Studies show that service-oriented SMEs are more likely to translate customer feedback into product, process, and service innovations (Grawe.
Chen, and Daugherty, 2.
From a Dynamic Capabilities perspective, service quality enhances firmsAo ability to sense customer needs and reconfigure internal resources to support innovation (Teece et , 2.
Empirical Scopus-indexed studies confirm a significant positive relationship between service quality and innovation capability in SMEs operating in turbulent environments (Prajogo & Sohal, 2003.
Sok & OAoCass, 2.
Therefore, this study H2: Service quality has a positive effect on innovation capability.
Volume 7.
Number 1, 2026 https://ijble.
com/index.
php/journal/index Innovation capability itself has been widely recognized as a key determinant of SME performance.
Firms with strong innovation capability are better positioned to differentiate offerings, improve efficiency, and respond to environmental changes (Kankam, 2.
In agribusiness contexts, innovation capability supports adaptation to technological change, sustainability requirements, and shifting consumer preferences, thereby enhancing productivity and competitiveness (Bigliardi, 2013.
Zastempowski and Glabiszewski, 2.
Empirical evidence from Scopus-indexed journals consistently reports a positive and significant relationship between innovation capability and SME performance across both manufacturing and agri-food sectors (Dean & Terziovski, 1998.
Jin & Choi, 2019.
Rajapathirana & Hui, 2018.
Saunila.
Accordingly, this study proposes.
H3: Innovation capability has a positive effect on SME performance.
Finally, recent studies increasingly emphasize that innovation capability acts as a mediating mechanism through which service quality influences performance.
Service quality facilitates organizational learning and knowledge accumulation, which enhances innovation capability and, in turn, leads to superior performance outcomes (Jimynez-Jimynez.
& Sanz-Valle, 2011.
Kankam, 2.
Scopus-based empirical research supports mediation models in which internal capabilities interact to generate competitive advantage rather than operating independently (Wang & Ahmed, 2.
In agribusiness SMEs, innovation capability strengthens the performance impact of service quality by enabling firms to convert customer-oriented service practices into innovative solutions and operational improvements.
Therefore, this study advances.
H4: Innovation capability mediates the relationship between service quality and SME Figure 1.
Research Framework Volume 7.
Number 1, 2026 https://ijble.
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php/journal/index METHOD This study employs Confirmatory Factor Analysis (CFA) to examine the interrelationships between the proposed variables.
The structural model is evaluated using the Partial Least Squares Structural Equation Modeling (PLS-SEM) approach.
Given the relative complexity of the proposed research model, statistical testing is deemed necessary to ensure empirical robustness (Hair et al.
, 2020.
Usakli & Kucukergin, 2.
Hypothesis testing is conducted using SmartPLS version 4 The selection of PLS-SEM is justified by its effectiveness in handling construct models with single-item measures and its capability to analyze data that does not follow a normal distribution (Ramayah.
Cheah.
Chuah.
Ting, & Memon, 2018.
Ramayah.
Cheah.
Chuah.
Ting, & Mumtaz Ali Memon, 2018.
Usakli & Kucukergin.
Data collection was carried out through a survey questionnaire distributed to MSME owners and managers.
Each item was measured using 7point Likert scale, ranging from 1 .
trongly disagre.
to 7 .
trongly agre.
, to ensure a high degree of response granularity (Taherdoost, 2.
The instrument's suitability was rigorously assessed through comprehensive validity and reliability testing.
Regarding the sample size, this study adheres to the minimum requirement of 100 respondents for a fiveitem construct model (Hair et al.
, 2.
Specifically, this research involved 150 respondents from the agribusiness-based food processing MSME sector, thereby exceeding the minimum threshold and ensuring sufficient statistical power for the Table 1.
Respondent Demographic Profile Based on Business Age
Business Age Year
Count
Percent
29,33%
16,67%
Referring to the table above, the majority of respondents operate businesses that have been running for 2Ae3 years, with a total of 81 respondents .
% of the This finding indicates that the processed food SME sector in South Tangerang is highly dynamic, characterized by a high rate of new business entry in recent years.
Most of these enterprises are likely in the early transition toward the growth phase, where firms begin to stabilize operations while expanding market reach and production capacity.
In contrast, 44 respondents .
33%) reported operating their businesses for 4Ae6 years, while only 25 respondents .
67%) had enterprises that have been in operation for more than six years.
The declining proportion of firms as business age increases suggests the possibility of business exits or failures occurring between the third and sixth years of operation, highlighting the vulnerability of SMEs during this critical development This pattern underscores the need for targeted support strategies to improve business sustainability and long-term performance in the processed food SME sector.
Table 2.
Demographic Sample Based On Business Revenue Revenue .
Count
Percent
28,00%
35,33%
20,00%
10,67%
6,00%
Volume 7.
Number 1, 2026 https://ijble.
com/index.
php/journal/index Based on Table 2, most SMEs are micro-scale enterprises, accounting for 33% of the total respondents and having monthly revenues below IDR 20 million.
Within this category, the smallest revenue group enterprises earning less than IDR 5 million per month represent 28% of the total sample.
Meanwhile, the revenue group of IDR5Ae20 million per month accounts for the largest proportion, at 35.
33% of SMEs with monthly revenues of IDR 21Ae50 million, which are also classified as small enterprises, contribute 20% of the sample .
contrast, firms classified as small medium scale enterprises, with monthly revenues exceeding IDR 50 million, represent only 16.
67% of the total respondents .
00%).
This distribution indicates that the SME landscape in the study area is largely characterized by micro and small enterprises, highlighting the structural dominance of lower-revenue firms and the limited presence of larger-scale businesses.
RESULTS AND DISCUSSION
Outer Model Analysis Reliability and Validation of Internal Consistency In the initial stage, we examined whether the independent variables exhibited appropriate or near-linear relationships.
The Composite Reliability (CR) values for each construct were expected to exceed 0.
60, while CronbachAos alpha (CA) values were required to be greater than 0.
The results indicate that all constructs achieved CR values above 0.
60, demonstrating that all measurement items are valid.
CronbachAos alpha values exceeding 0.
70 confirm that each construct demonstrates high internal consistency and reliability.
Furthermore, the Average Variance Extracted (AVE) values ranged from 0.
711 to 0.
780, exceeding the recommended threshold of 0.
50 for convergent validity.
These findings indicate that the construct explains a substantial proportion of the variance in their respective Therefore, it can be concluded that all constructs demonstrate adequate convergent validity and are suitable for the purposes of this study.
The detailed results are presented in Table 3.
Table 3.
Reliability Of Internal Consistency And Convergent Validity Innovation Capability SMEs Performance Service Quality Management AVE Loading Factor (Outer Mode.
The results of the measurement model assessment indicate that all indicators used to measure Service Quality Management.
Innovation Capability, and SME Performance meet the requirements for convergent validity.
This is evidenced by the outer loading values, which are all above the recommended threshold of 0.
More specifically, for the Service Quality Management construct, the lowest loading value is 831 (SQ.
, while the highest reaches 0.
922 (SQ.
The Innovation Capability construct exhibits loading values ranging from 0.
775 (IC.
919 (IC.
Meanwhile, the SME Performance construct shows loading values between 0.
(SP.
908 (SP.
These results confirm that all indicators are valid and exhibit strong reliability in representing their respective latent constructs.
Therefore, the measurement model Volume 7.
Number 1, 2026 https://ijble.
com/index.
php/journal/index demonstrates adequate convergent validity and is deemed suitable for further structural model analysis.
Table 4.
Loading Factor IC.
IC.
IC.
IC.
IC.
IC.
SP.
SP.
SP.
SP.
SP.
SP.
SP.
SP.
SQ.
SQ.
SQ.
SQ.
SQ.
SQ.
Innovation Capability SMEs Performance Service Quality Management Keterangan Valid Valid Valid Valid Valid Valid Valid Valid Valid Valid Valid Valid Valid Valid Valid Valid Valid Valid Valid Valid Structure model (Inner mode.
Table 5.
Goodness Of Fit (GOF) Analysis Innovation Capability SMEs Performance Service Quality Management Average Average extracted (AVE) R-square GoF The evaluation of the Goodness of Fit (GoF) for this PLS-SEM model assesses how well the operationalized model explains the empirical data.
Based on the structural model and the corresponding measurement results, the model demonstrates a high level of fit, as detailed below:
Predictive Power and Model Explanatory Ability (R.
SMEs Performance (R2 = 0.
: This value indicates that the model explains 4% of the variance in SME performance.
According to established statistical thresholds, this result is categorized as substantial, signifying that the combination of service quality management and innovation capability provides a near-complete explanation of performance outcomes within this study.
Innovation Capability (R2 = 0.
: This construct possesses an explanatory power of 73.
5%, which is also classified as substantial or strong.
Measurement Model Quality (Outer Loading.
The GoF is further supported by the high quality of the measurement model, where every indicator for Service Quality Management (SQ).
Innovation Volume 7.
Number 1, 2026 https://ijble.
com/index.
php/journal/index Capability (IC), and SMEs Performance (SP) exceeds the required threshold of Key indicators such as SQ.
IC.
, and SP.
demonstrate exceptional representativeness, ensuring that the latent variables are accurately captured by their respective instruments.
Statistical Significance and Reliability The entire structural model is statistically significant, as evidenced by P-values 000 for all hypothesized paths.
Furthermore, the reliability of the indicators is confirmed by the significant Pvalues .
associated with each individual outer loading, ensuring that the measurement model is robust.
The research model is deemed to have an excellent fit, characterized by substantial predictive power (R.
and highly valid measurement components.
These results provide a strong foundation for the subsequent hypothesis testing and managerial implications.
Table 6.
R-Square Analysis R-square R-square adjusted Innovation Capability SMEs Performance The results show that Service Quality Management has a significant impact on Innovation Capability and SME Performance, accounting for 73.
3% and 90.
3% of their variance, as indicated by the adjusted R-square values.
These high percentages indicate that the model is very effective at predicting these outcomes, proving that management quality is the primary factor behind the success observed in these This essentially means that, for the SMEs in this study, how they handle service quality is the most critical factor in driving internal innovation and overall business Table 7.
F-Square Analysis Innovation Capability SMEs Performance Service Quality Management Innovation Capability SMEs Performance Service Quality Management Service Quality Management on Innovation Capability (F2 = 2.
The effect size of Service Quality Management on Innovation Capability is recorded at 2.
According to Cohen's .
criteria, a value exceeding 0.
indicates a large effect.
This suggests that Service Quality Management plays a critically dominant role in fostering innovation within the organization, consistent with its exceptionally high T-statistic of 24.
940 in the hypothesis testing.
Service Quality Management on SMEs Performance (F2 = 0.
Service Quality Management also exerts a large effect on SMEs Performance, with an F2 value of 0.
This indicates that, even without considering other factors, quality-of-service management remains a primary driver of business This substantial contribution explains why the overall R 2 for SMEs Performance is extremely high at 0.
Volume 7.
Number 1, 2026 https://ijble.
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php/journal/index Innovation Capability SMEs Performance (F2 The contribution of Innovation Capability to SMEs Performance is measured at 595, which is also categorized as a large effect.
This result confirms that the firm's ability to innovate is not just a secondary factor but a vital engine for enhancing The significant impact of this variable justifies its role as an effective mediator in the relationship between service quality and firm growth.
All tested relationships in the model exhibit a large effect size (F2 > 0.
, proving that Service Quality Management and Innovation Capability are powerful and essential predictors of SMEs Performance.
Hypotesis Analysis Table 8.
Hypotesis Analysis Innovation Capability -> SMEs
Performance Service Quality Management -> Innovation Capability Service Quality Management -> SMEs Performance Service Quality Management -> Innovation Capability -> SMEs
Performance Original (O) Sample mean (M) Standard
(STDEV)
T statistics (|O/STDEV|) Pvalues The Influence of Innovation Capability on SMEs' Performance The statistical analysis reveals that Innovation Capability exerts a significant positive influence on SMEs Performance, as evidenced by a T-statistic of 9.
641 and a P-value of 0.
This finding aligns with Saunila's .
research, which posits that innovation capability serves as an intangible asset that enables SMEs to respond agilely to market shifts for long-term profitability.
This relationship is further validated by the performance indicator SP.
2, which demonstrates a robust loading factor of Furthermore.
Partanen et al.
emphasize that process innovation can effectively reduce operational costs, thereby directly enhancing firm performance.
The synergy of resources within an SME, as noted by Fu et al.
, underscores that the alignment between innovative ideas and market execution is a primary determinant of growth, a sentiment consistent with the high R-square value of 0.
904 for this model's The Influence of Service Quality Management on Innovation Capability Service Quality Management is proven to have a substantial impact on Innovation Capability, recording the highest T-statistics in the model at 24.
According to Anning-Dorson .
, effective quality management establishes a structured framework that facilitates experimentation and staff creativity.
This is empirically supported by the indicator SQ.
2, which shows a loading factor of 0.
positioning service quality as the foundation for innovation.
In line with Bouranta et al.
Sangwan & Bhakar, 2.
, an orientation toward service quality drives firms to continuously seek novel ways to satisfy customers through service innovation.
Additionally.
Qu et al.
argue that a philosophy of continuous improvement within quality management acts as the primary engine for internal process innovation.
Volume 7.
Number 1, 2026 https://ijble.
com/index.
php/journal/index The Influence of Service Quality Management on SMEs Performance The hypothesis stating that Service Quality Management directly improves SMEs Performance is accepted, supported by a T-statistic of 11.
089 and a P-value of This result corresponds with the literature focusing on customer retention.
Niyi Anifowose et al.
contend that high service standards foster customer loyalty, a major revenue driver for SMEs.
Operational efficiency also plays a role, as notes that effective quality management minimizes errors, subsequently increasing overall profit Despite the typically small scale of SMEs, building a brand reputation remains vital.
Akter et al.
emphasize that for small businesses, service quality is the most effective marketing tool for establishing market trust, which is reflected in the high reliability of the performance indicators in this model.
The Mediating Role of Innovation Capability Innovation Capability is proven to significantly mediate the relationship between Service Quality Management and SMEs Performance, with a P-value of 0.
Research by Qu et al.
explains this mechanism, suggesting that innovation acts as a bridge that transforms quality inputs into higher and more unique economic value.
Regarding long-term impact.
Castillo Apraiz et al.
found that while service quality alone may offer short-term benefits, the impact becomes more sustainable when mediated by innovation.
Furthermore.
Sahoo & Yadav .
asserts that SMEs must maintain dynamic competitiveness, as static quality standards without innovation are easily imitated by competitors.
The validity of this mediation path is statistically ensured by the strong outer loading indicators, such as IC.
1 at 0.
Figure 2.
Graphical Output Volume 7.
Number 1, 2026 https://ijble.
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php/journal/index CONCLUSION This study concludes that Service Quality Management and Innovation Capability are critical determinants of SMEs Performance within the agribusiness The empirical results demonstrate that service quality exerts a substantial direct impact on business performance and serves as a fundamental catalyst for enhancing a firmAos innovation capability.
Furthermore, the findings confirm that Innovation Capability plays a vital mediating role, acting as a strategic bridge that transforms quality-driven resources into unique economic value and sustainable The high predictive power of the model, indicated by an R-square of 0.
904 for business performance, reinforces the conclusion that managing service quality is the most essential element for modern SMEs to thrive in volatile environments.
Despite these significant findings, this study has limitations that should be The research focused specifically on agribusiness-based food processing MSMEs in South Tangerang, which may limit the generalizability of the results to other industries or geographical regions.
Additionally, the cross-sectional nature of the data collection provides a snapshot in time, whereas the relationship between innovation and performance often develops over a longer duration.
Future researchers are encouraged to conduct longitudinal studies or expand the scope to include diverse sectors to further validate these interrelationships and address the potential for environmental turbulence more comprehensively.
Acknowledgment The authors would like to express their sincere gratitude to all individuals and organizations that contributed to the completion of this research.
Special appreciation is extended to the Advisors for their invaluable guidance, insightful feedback, and academic mentorship throughout the development of this manuscript.
We are also deeply grateful to the owners and managers of the agribusiness-based MSMEs in South Tangerang who participated as respondents, providing the essential data that made this analysis possible.
Furthermore, this research was made possible through the support of our Financial Supporters and funding bodies.
Their contributions were instrumental in facilitating the data collection and processing phases of this study.
Finally, we thank our colleagues and family members for their continuous encouragement and administrative assistance during the preparation of this academic effort.
Reference