Received: January 8, 2025
Accepted: September 18, 2025
Objective: To identify how technological innovation contributes to the financial performance of Small and Medium-Sized Enterprises (SMEs), offering a comprehensive perspective that underscores the importance of adopting this approach to enhance competitiveness in today’s markets. This paper also seeks to examine how sector, firm age, and workforce size relate to increases in sales and assets.
Design/Methodology: The study followed a quantitative approach with an explanatory, correlational, cross-sectional, and descriptive scope, focusing on SMEs located in Sinaloa, Mexico. Data were collected through surveys administered to 149 companies. Pearson’s correlation analysis and a logit model were applied to analyze the data and identify the relationships between variables and their influence on financial performance.
Findings: The results show that the companies under study attach significant importance to technology, as evidenced by their continuous adoption of technological innovations. It was also found that their employees possess technological knowledge and skills, which is positively associated with financial performance. Additionally, firms with a larger workforce tend to exhibit higher levels of technological competence.
Conclusions: SMEs acknowledge the relevance of technology for their growth and financial outcomes. This awareness stems from the social and economic changes brought about by globalization and the digital age, which together drive the use of emerging technologies that strengthen business management.
Originality: This study provides empirical evidence that technological knowledge and skills, as well as a positive perception of technological innovation, are key factors contributing to strong financial performance, as reflected in higher income and asset growth.
Keywords: predictive models, technological innovation, financial performance, SMEs.
JEL Codes: M1, D22, O31, O3.
Objetivo: identificar cómo la innovación tecnológica contribuye al desempeño financiero de las pymes, al ofrecer una perspectiva integral que resalta la importancia de adoptar estas herramientas para fortalecer su capacidad de competir en el mercado actual, además conocer cómo se correlaciona el sector, la antigüedad y el número de trabajadores con el incremento en ventas y en activos.
Diseño/metodología: el estudio tuvo un enfoque cuantitativo, con un alcance explicativo, correlacional, transversal y descriptivo y se centró en las pymes de Sinaloa, México. La información fue recabada mediante encuestas aplicadas a 149 empresas; para el tratamiento de los datos se emplearon análisis de correlación de Pearson y un modelo logit, con el objetivo de identificar relaciones y explicar la influencia de las variables en el desempeño financiero.
Resultados: los hallazgos indican que las empresas le otorgan importancia a la tecnología, lo que se refleja en su adopción constante en innovación tecnológica. Asimismo, se identificó que los empleados poseen habilidades y conocimientos tecnológicos y ello se relaciona positivamente con su desempeño financiero. Finalmente, un número mayor de trabajadores se asocia con mayores habilidades tecnológicas.
Conclusiones: las pymes reconocen la importancia que merece la tecnología para su crecimiento y su desempeño financiero. Esta percepción responde a los cambios sociales y económicos derivados del proceso de globalización y el surgimiento de la era digital, lo cual impulsa el uso de tecnologías emergentes que fortalezcan la gestión empresarial.
Originalidad: el estudio aporta evidencia de que los conocimientos, las habilidades y la valoración positiva sobre la innovación tecnológica son factores que contribuyen a un correcto desempeño financiero que se manifiesta en un aumento en ingresos y activos.
Palabras clave: modelos predictivos, innovación tecnológica, desempeño financiero, pymes.
Códigos JEL: M1, D22, O31, O3.
Globalization has brought about profound transformations in societies, markets, and competencies, directly affecting organizations and forcing them to prioritize efficiency in their processes and optimize resources (
The elimination of trade barriers between countries and the reduction of transportation costs associated with distance are prominent effects of globalization that have facilitated global business location and relocation processes. These modifications have been enabled by advances in transportation systems and the evolution of Information and Communication Technologies (ICT) (
In addition, globalization has driven a radical technological shift that compels companies to adapt rapidly to remain competitive. In other words, it has become a key factor enabling the swift adoption of new technologies (
Given this context, innovation and technological development emerge as two of the most consequential changes introduced by globalization into the business sphere, forcing organizations to adapt continuously (
According to
Nonetheless, not all companies manage to adapt to globalization and adopt new technologies successfully (
In summary, globalization entails both internal and external transformations that shape organizational innovation and technology adoption across companies of all sizes. Against this backdrop, the present study examines the importance and application of technological innovation in SMEs in Sinaloa, Mexico, through a predictive logistic regression model. The relevance of the study lies in the growing need for SMEs to adopt a strategic approach to innovation—both in developing new products and processes and in enhancing organizational competitiveness locally and internationally. The purpose is to provide a broader perspective on how these companies perceive and adapt to technological innovation, considering the limited number of studies on SMEs that identify the factors driving their growth (
According to data from the National Institute of Statistics and Geography (abbreviated
Despite their importance, SME survival poses a major challenge in today’s highly competitive environment (
In this regard,
To clearly address the innovation dimension, it is necessary to adopt a precise definition of the concept. For this reason, the study draws on the Oslo Manual (
the implementation of a new or significantly improved product (good or service), or process, a new marketing method, or a new organisational method in business practices, workplace organisation or external relations. A common feature of an innovation is that it must have been implemented. A new or improved product is implemented when it is introduced on the market. New processes, marketing methods or organisational methods are implemented when they are brought into actual use in the firm’s operations (p. 56).
Importantly, innovations do not need to be entirely new to the world; they only need to be new to the organizations adopting them, consistent with the Oslo Manual. In other words, product, process, organizational, and marketing innovations should be considered new or improved technologies when viewed from the company’s perspective (
Technological progress–oriented innovation, in particular, is regarded as a key driver of organizational resilience and growth and as one of the fundamental pillars of business competitiveness (
Technological innovation is a strategic factor for organizational transformation and long-term sustainability, as it enables process optimization, creates added value, and enhances business competitiveness (
In recent years, SMEs have faced challenges such as the COVID-19 pandemic, which forced them to accelerate the adoption of technological innovations to mitigate negative impacts on financial performance (
Financial planning, in this regard, involves projecting and strategically coordinating revenues, expenses, and investments to expand the organization’s assets while ensuring operational feasibility (
Therefore, financial planning and performance are closely related to SMEs’ ability to achieve their financial objectives, including profitability, growth, and labor and innovation performance (
Similarly, aligned with
Despite its importance, however, many SMEs remain resistant to change, especially when it comes to adopting new technologies. This resistance often stems from fears of job obsolescence and a limited understanding of the benefits offered by technological tools (
For this reason, SMEs must adopt innovation processes continuously, as their survival and growth depend directly on their capacity to adapt to dynamic and highly competitive environments (
In the first phase, a sample of 383 SMEs distributed across multiple municipalities in the state of Sinaloa, Mexico, was selected. The sample size was determined using the finite population formula, considering the 134,354 companies registered in the National Statistical Directory of Economic Units (abbreviated DENUE in Spanish) and classified according to the criteria established by the Official Gazette of the Federation. A 95% confidence level and a 5% margin of error were applied, assuming maximum variability (p = 0.5; q = 0.5). This formula yielded the required sample size, as shown in Equation 1:
(1)Where:
N: population size under study (134,354)
Z: confidence level (95%)
p: probability of success (0.5)
q: probability of failure (0.5)
e: estimated error (0.05)
n: sample (383)
In the second phase, a survey was administered to decision-makers from an intentional sample of companies. Although the target sample size was 383 companies, only 149 responses were obtained, representing 38.9% of the estimated total. This shortfall is primarily attributable to limited respondent availability and time constraints during data collection. However, these difficulties were exacerbated by the heightened insecurity in the state of Sinaloa, which intensified after September 2024 and restricted access to certain areas. Nonetheless, based on the results of this initial phase, subsequent stages of the study may expand the sample to reduce the margin of error and increase the precision of the findings.
Data collection was carried out using a structured nine-item questionnaire, designed and administered via Google Forms. The instrument was distributed to SME owners and managers who were knowledgeable about the requested information. The sampling frame was obtained from the database of INEGI, which provides updated company-level data by state, as well as DENUE, which includes information on sector, number of employees, company size, geographic location, and specific contact details such as responsible personnel, address, and email.
Table 1 shows the questionnaire used.
Dimension | Item | Definition | Measurement |
| Financial performance | -The organization’s revenues increase consistently each year. -The organization’s assets have grown in proportion to its sales. | Effective management of resources across all areas of the organization to support informed decision-making and the achievement of objectives. | Yes = 1 No = 0 |
| Technological innovation | -The organization consistently adopts technological innovation. -Employees possess technological knowledge and skills. -The organization recognizes the importance of technology for adapting to market changes. -The organization is competitive in technological innovation. | Innovation refers to the implementation of a new or significantly improved product (good or service), process, marketing method, or organizational method in business practices, workplace organization, or external relations. | · Strongly disagree · Disagree · Neither agree nor disagree · Agree · Strongly agree. |
| SME characteristics | - Number of employees | · 1 to 5 · 6 to 10 · 11 to 50 · 51 to 100 · More than 100 | |
| - Company age | · 1 to 5 · 6 to 10 · 11 to 15 · 16 to 25 · More than 25 | ||
| - Economic sector | · Primary · Secondary · Tertiary |
Subsequently, in the third phase, the instrument was subjected to expert evaluation using the Lawshe method. Through this technique, specialists assessed the relevance, clarity, and coherence of each item. The evaluation panel included national and international researchers from institutions such as the Universidad Nacional de Colombia and the Universidad Michoacana de San Nicolás de Hidalgo. After completing the expert review, a pilot test was conducted, followed by an assessment of the instrument’s reliability.
Table 2 presents the content validity index for each item. As observed, all items achieved an acceptable level of agreement among expert judges, with acceptance rates ranging from 75% to 100%, which was sufficient to support their inclusion in the instrument.
| Item | Evaluator 1 | Evaluator 2 | Evaluator 3 | Evaluator 4 | Agreement | % |
| The organization’s revenues increase consistently each year. | X | X | X | X | SÍ | 100 % |
| The organization’s assets have grown in proportion to its sales. | X | X | X | SÍ | 75 % |
|
| The organization consistently adopts technological innovation. | X | X | X | X | SÍ | 100 % |
| Employees possess technological knowledge and skills. | X | X | X | SÍ | 75 % |
|
| The organization recognizes the importance of technology for adapting to market changes. | X | X | X | X | SÍ | 100 % |
| The organization is competitive in technological innovation. | X | X | X | SÍ | 75 % |
The proposed model seeks to examine the relationship between technological innovation factors and the financial performance of SMEs. Specifically, the model posits that technology adoption, employees’ technological knowledge, the importance attributed to innovation, and company-specific characteristics constitute key determinants of improved financial performance. Based on this assumption, the study hypotheses are defined as follows:
H1: Organizations that consistently adopt technology are more likely to improve their financial performance.
H2: Employees’ technological knowledge and skills contribute to improved financial performance.
H3: Organizations that recognize the importance of technological innovation for adapting to market changes exhibit better financial performance.
H4: Competitive technological innovation fosters improved financial performance.
H5: SME characteristics influence financial performance.
Using the survey data, the fourth phase consisted of conducting a logistic regression analysis, which differs from simple regression in that it models the natural logarithm of event probabilities (
The fifth phase is described in detail in the results section, where the binary dependent variable was defined for model construction. The objective was to determine whether, based on technological innovation factors, managers or owners perceive a higher likelihood that their companies will achieve improved financial performance, considering that financial outcomes are today influenced by organizations’ capacity to adopt and utilize ICT (
As explained previously in the methodology, dichotomous items were used to assess respondents’ perceptions of financial performance, while Likert-scale items captured their perceptions of technological innovation. The logistic regression model used is expressed as follows:
Logit 
Where:
\𝑏𝑒𝑡𝑎0: Financial performance
\𝑏𝑒𝑡𝑎1: Consistent adoption
\𝑏𝑒𝑡𝑎2: Technological knowledge
\𝑏𝑒𝑡𝑎3: Importance of technology
\𝑏𝑒𝑡𝑎4: Competitive technological innovation
\𝑏𝑒𝑡𝑎5: Economic sector
\𝑏𝑒𝑡𝑎6: Company age
\𝑏𝑒𝑡𝑎7: Number of employees
Of the 149 companies surveyed, 10.7% belong to the primary sector, 12.1% to the secondary sector, and 77.2% to the tertiary sector. Additionally, 84.6% employ no more than 50 workers, and 88.5% have been operating for 15 years or less. Table 3 presents the descriptive statistics—specifically, the mean values of the responses. All mean scores exceed the midpoint of the respective scales, indicating general agreement with the statements, particularly those related to technological knowledge.
The descriptive results also reveal that 63.8% of companies report increases in both sales and assets, that is, enhanced financial performance. Moreover, all technological innovation items exhibit means greater than 3, reflecting a positive perception of consistent adoption, technological knowledge, importance of technology, and competitive technological innovation.
| N.° | Minimum | Maximum | Mean | Deviation | |
| Financial performance | 149 | .00 | 1.00 | .6376 | .48232 |
| Consistent adoption | 149 | 1.00 | 5.00 | 3.1457 | 1.36820 |
| Technological knowledge | 149 | 1.00 | 5.00 | 3.6510 | 1.17936 |
| Importance of technology | 149 | 1.00 | 5.00 | 3.5705 | 1.16396 |
| Competitive innovation | 149 | 1.00 | 5.00 | 3.6174 | 1.24985 |
| Economic sector | 149 | 1.00 | 3.00 | 2.5497 | .76323 |
| Company age | 149 | 1.00 | 5.00 | 2.6623 | 1.34604 |
| Number of employees | 149 | 1.00 | 6.00 | 2.8609 | 1.65747 |
| Valid N.° (listwise) | |||||
Table 4 reports the model fit assessed using the Hosmer–Lemeshow test, which produced a chi-square value of 8.532 with 8 degrees of freedom and a p-value of 0.383. Because the p-value exceeds the 0.05 threshold, the null hypothesis cannot be rejected, indicating that the model adequately fits the observed data. Similarly, Table 5 shows additional measures of model fit, including a −2 log-likelihood of 149.472 and Cox–Snell and Nagelkerke pseudo R² values of 0.264 and 0.362, respectively. These coefficients indicate that the model accounts for approximately 26.4% to 36.2% of the variance in the dependent variable. Moreover, Table 6 presents the results of the proposed model.
Step | Chi- square | df | Sig. |
1 | 8.532 | 8 | .383 |
Similarly, Table 5 shows additional measures of model fit, including a −2 log-likelihood of 149.472 and Cox–Snell and Nagelkerke pseudo R² values of 0.264 and 0.362, respectively. These coefficients indicate that the model accounts for approximately 26.4% to 36.2% of the variance in the dependent variable. Moreover, Table 6 presents the results of the proposed model.
Step | −2 log-likelihood | Cox–Snell R² | Nagelkerke R² |
1 | 149.472a | .264 | .362 |
B | Std. Error | Wald | df | Sig. | Exp(B) |
||
Step 1a | Consistent adoption | .516 | .214 | 5.821 | 1 | .016 | 1.675 |
Technological knowledge | .415 | .188 | 4.888 | 1 | .027 | 1.514 |
|
Importance of technology | .438 | .177 | 6.162 | 1 | .013 | 1.550 |
|
Competitive innovation | .010 | .213 | .002 | 1 | .963 | 1.010 |
|
Economic sector | .060 | .266 | .051 | 1 | .821 | 1.062 |
|
Company age | -.062 | .162 | .146 | 1 | .702 | .940 |
|
Number of employees | .131 | .141 | .854 | 1 | .355 | 1.139 |
|
Constant | -4.363 | 1.291 | 11.417 | 1 | .001 | .013 |
|
Based on the results obtained from the proposed model—which was developed to evaluate the relationship between technological innovation and the financial performance of SMEs in Sinaloa—the research hypotheses were formulated and tested. The results were interpreted using the regression coefficients and their corresponding significance values. To begin, the constant (or intercept) represents the odds of the event occurring when all independent variables are equal to zero, and in this context refers to the baseline likelihood of observing improved financial performance.
As shown in Table 6, the model identifies three statistically significant predictors: consistent technology adoption (B = 0.516, p = 0.016), employees’ technological knowledge (B = 0.415, p = 0.027), and perceived importance of technology (B = 0.438, p = 0.013). All three variables present Exp(B) values greater than 1, indicating that they increase the odds of companies achieving improved financial performance.
The analysis of the independent variables begins with consistent technology adoption, which exhibits a positive and significant effect. This suggests that organizations are more likely to attain stronger financial performance when they constantly integrate new technologies into their processes. Similarly, employees’ technological knowledge emerges as another significant predictor, underscoring the importance of developing human capital competencies related to technological innovation.
Furthermore, the perceived importance of technology also contributes positively to financial outcomes. Particularly, organizations in Sinaloa that place greater emphasis on the role of technology tend to report higher expectations of favorable financial performance. In contrast, competitiveness in technological innovation does not demonstrate statistical significance in the model. Likewise, the variables representing general SME characteristics—economic sector, company age, and number of employees—also fail to show significant effects.
These results allow for the evaluation of the study’s hypotheses. H1, which proposed that firms consistently adopting technological innovation are more likely to improve their financial performance, is supported, as the variable exhibits a positive and significant effect (p = 0.016). H2 is also supported (p = 0.027), indicating that technological skills and knowledge contribute to stronger financial performance.
Similarly, H3 is supported by the results of the model (p = 0.013), confirming the positive association between the perceived importance of technology and financial performance. By contrast, H4 is not supported (B = 0.010, p = 0.963; Exp(B) = 1.010), as no statistically verifiable effect of competitive technological innovation is identified on the financial performance of the SMEs included in the study. Finally, H5, which relates SME characteristics to financial performance, is also rejected.
According to the results presented in Table 7, the Pearson correlation analysis reveals statistically significant associations between the variables that explain technological innovation and the characteristics of the surveyed SMEs. Notably, company age shows a negative correlation with technology adoption (-0.196*), suggesting that older companies adopt new technologies less frequently. In contrast, the number of employees exhibits a positive correlation with technological knowledge (0.162*), indicating that companies with a larger workforce tend to possess greater technological knowledge.
| Importance Technology | Competitive Innovation | Consistent Adoption | Technological Knowledge | Sector | Age | Employees | ||
| Importance Technology | Pearson correlation | 1 | .509** | .488** | .447** | .044 | -.107 | .050 |
Significance (two-tailed) | .000 | .000 | .000 | .591 | .191 | .541 |
||
N | 149 | 149 | 149 | 149 | 151 | 151 | 151 |
|
| Competitive Innovation | Pearson correlation | .509** | 1 | .505** | .500** | .009 | -.113 | .137 |
Significance (two-tailed) | .000 | .000 | .000 | .909 | .171 | .097 |
||
N | 149 | 149 | 149 | 149 | 149 | 149 | 149 |
|
| Consistent Adoption | Pearson correlation | .488** | .505** | 1 | .365** | -.039 | -.196* | -.084 |
Significance (two-tailed) | .000 | .000 | .000 | .633 | .016 | .310 |
||
N | 149 | 149 | 149 | 149 | 149 | 149 | 149 |
|
| Technology Knowledge | Pearson correlation | .447** | .500** | .365** | 1 | -.071 | -.113 | .162* |
Significance (two-tailed) | .000 | .000 | .000 | .392 | .169 | .048 |
||
N | 149 | 149 | 149 | 149 | 149 | 149 | 149 |
|
| Sector | Pearson correlation | .044 | .009 | -.039 | -.071 | 1 | -.104 | -.145 |
Significance (two-tailed) | .591 | .909 | .633 | .392 | .205 | .076 |
||
N | 149 | 149 | 149 | 149 | 151 | 151 | 151 |
|
| Age | Pearson correlation | -.107 | -.113 | -.196* | -.113 | -.104 | 1 | .290** |
Significance (two-tailed) | .191 | .171 | .016 | .169 | .205 | .000 |
||
N | 149 | 149 | 149 | 149 | 151 | 151 | 151 |
|
| Employees | Pearson correlation | .050 | .137 | -.084 | .162* | -.145 | .290** | 1 |
Significance (two-tailed) | .541 | .097 | .310 | .048 | .076 | .000 | ||
N | 149 | 149 | 149 | 149 | 151 | 151 | 151 |
|
| **. Correlation is significant at the 0.01 level (two-tailed). | ||||||||
| *. Correlation is significant at the 0.05 level (two-tailed). | ||||||||
The resource-based view and the innovation theory provide the foundations for understanding innovation and technology as strategic resources that enable organizations of any size to adapt, differentiate, and achieve long-term sustainability. Accordingly, companies seeking to build competitive strategies must consider the implications of their resources and capabilities to determine how to meet their objectives (
Innovation has long been recognized as a strategic driver of growth, sustainability, competitiveness, and enhanced benefits (
Mexico, one of the world’s largest emerging economies, has sought to strengthen its economic development by promoting innovation (
In the case of Sinaloa,
Given this context, organizations should prioritize strategies such as continuous employee training programs, learning platforms, hands-on workshops on digital skills, and, most importantly, the internal promotion of an innovation culture. Digital transformation, in general, can significantly enhance SMEs’ operational efficiency, agility, and ability to adapt to market changes (
Thus, the present study confirms the importance that SMEs in Sinaloa assign to technology, as reflected in their increased sales and assets. Thus, the decision to adopt—or not adopt—technology becomes a crucial component of SME growth and survival strategies (
For future research, incorporating detailed financial information from SMEs would enable more thorough quantitative analyses based on indicators such as Return on Equity (ROE), Return on Assets (ROA), and Return on Sales (ROS), thereby deepening the assessment of financial performance. It is also recommended to examine specific sectors and expand the sample size to enhance the representativeness and robustness of the results. Furthermore, longitudinal studies would make it possible to determine how these variables evolve over time, offering a more comprehensive understanding of the factors that influence SMEs’ adoption of technological innovation.
The main limitations of this study, based on a sample of 149 companies located in the state of Sinaloa, Mexico, arise from the specific characteristics of the sector analyzed and from the fact that the initially targeted sample size was not fully achieved. Nonetheless, given the similarity of the challenges typically faced by companies of this size and the particular conditions of those operating in the state, this study could be replicated in other Mexican states and even in other Latin American countries.
The results provide evidence that SMEs in Sinaloa acknowledge the importance of technology for achieving solid financial performance—particularly in light of the social and economic transformations brought about by globalization and the digital era, which increasingly encourage the implementation of emerging technologies that support improved business management.
The study confirms that SMEs that adopt technological innovation more consistently, and whose employees possess technological knowledge, tend to achieve better financial outcomes. Moreover, the findings indicate that organizations with a larger workforce exhibit higher levels of technological knowledge, highlighting the need to strengthen innovation-oriented cultures in smaller companies.
Finally, business growth and national economic development cannot be fully understood without recognizing the critical role of technology. Innovation not only advances technological capabilities but also improves the production of goods and services; increases the efficiency of machinery, equipment, and personnel; and strengthens commercial relations among companies and countries. More specifically, innovation fosters the development of new organizational capabilities, particularly those related to human capital and employee knowledge.
The authors declare that they have no financial, professional, or personal conflicts of interest that could have inappropriately influenced the results or interpretations presented in this study.
All authors have made significant contributions to the development of this project, as specified below:
Ana Karen Romero Sainz: Data collection (surveys), writing, data curation, formal analysis, editing, and review.
Deyanira Bernal Domínguez: Data collection (surveys), writing, editing and review of the methodology, and validation.
Heilder Octavio Angulo Trujillo: Data collection (surveys), writing, editing, review of conclusions, and investigation.
Lidyeth Azucena Sandoval Barraza: Data collection (surveys), writing, editing, and review.