Influence of Innovation on Performance of Textile and Clothing Businesses in Nairobi County, Kenya

Influence of Innovation on Performance of Textile and Clothing Businesses in Nairobi County, Kenya

Dieu-Merci Nehemie Bashulile^*, Dorothy Kirimi, Moses Muriuki

School of Business and Economics, Kenya Methodist University

^*Corresponding Author

DOI: https://dx.doi.org/10.47772/IJRISS.2025.90400361

Received: 10 April 2025; Accepted: 15 April 2025; Published: 16 May 2025

ABSTRACT

This study investigates the influence of innovation on the business performance of textile and clothing (T&C) businesses in Nairobi County, Kenya. Innovation is a critical driver for improving organizational performance, especially in industries characterized by fast-paced change and competition. The study used a descriptive research design to examine the relationship between innovation and business performance. A total of 85 T&C businesses were targeted. Data were collected through a structured questionnaire, which assessed both the implementation of innovative practices and the performance of businesses in terms of profitability, market share, and customer satisfaction. Descriptive and inferential statistical techniques, including regression analysis, were used to analyze the data. The findings revealed a significant positive relationship between innovation and business performance, with businesses that embraced innovation in product development, customer service, and the adoption of advanced technologies reporting higher performance outcomes. The study established that innovation functions as a crucial element in boosting business achievement by helping companies achieve competitive market positions. The research team outlined three main recommendations that included establishing innovation cultures within businesses and creating supportive innovation environments with policymakers alongside studying the specific innovation types that drive performance results the most. The research findings deliver essential knowledge to textile and clothing sector managers policymakers and business owners about innovation’s critical role in enduring development and sustainability.

Keywords: Innovation, Business Performance, Textile and Clothing Industry.

INTRODUCTION

Small enterprises and businesses play a crucial role in the development and growth of the Kenyan economy. The success of these firms depends on their ability to innovate and keep up with the changes in the market (Kipkosgei & Kithae, 2019). As such, firms must innovate and keep themselves abreast with the demands in the market if they are to stay competitive. With the high competition in the industry, firms in the Kenyan market must innovate to identify better solutions that create unique value propositions compared to the competitors’ products. Innovation is thus critical for the survival of small firms in the Kenyan market which in turn enables small firms to contribute positively to the economy Anyanga and Nyamita (2016) explain that small firms such as the textile and clothing businesses in Kenya can leverage innovation to offer products and services that meet specific needs in the market.

The concept of innovation refers to the implementation of a new product or service or an improvement to an existing product or service. Innovation and creativity and innovation are related as they help firms to improve on their product or service offering thus meeting the market needs (Ndalira, Ngugi, & Chepkulei, 2013). The concept of innovation in the textile and clothing sector in Kenya is critical in enabling the sector to meet the local demand while at the same time competing with foreign firms. Innovation will enable the textile and clothing businesses to reconceptualize their business models to create sustainable customer value. Such innovation will involve continuous research and development to ensure the products and services offered remain successful in the market.

The textile industry plays a crucial role in the economic growth and development of any nation, given its labor-intensive methods (Kipkosgei & Kithae, 2019). This sector can create employment in almost every value chain, making it an important contributor to national growth. In the USA, for instance, the textile and clothing sector employs around half a million workers as of 2023 and produces about $64.8 billion (Harsanto et al., 2023). In China, the sector contributes about 20 million people, making it a global powerhouse (Xiaoyi et al., 2023). The sector contributes significantly to the country’s economy through exports and domestic consumption. This sector is a major source of employment for both locals and migrant workers. In Egypt, the textile and clothing industry contributes about 34% of the industrial output and 3.4% of the GDP.

In Kenya, the clothing and textile industry is a major source of employment for the youth and women. It has become a major source of foreign exchange earners as the country focuses on export processing zones to revive the sector (Mugo, Kahuthia, & Kinyua, 2019). The textile industry in Kenya is labor intensive, making it an easy source of employment across the value chains. This sector employs about 320,000 people, with 80,000 working in the sector directly while the other 240,000 working indirectly (Kipkosgei & Kithae, 2019). The textile and cloth industry in Kenya is broad and consists of yarn and thread production, fabric manufacturing, and apparel manufacturing. These sectors contribute about 7% of the Kenya Association of Manufacturers, providing numerous jobs to Kenyans.

Despite the numerous benefits of the textile and clothing sector in Kenya, a lack of innovation has impacted the growth of the sector negatively. The liberation of the economy and lack of innovation have led to a massive decline in the sector. Many firms such as Rivatex and Kisumu Cotton Millers are some of the firms that have ceased to exist due to lack of innovation (Mwasiagi et al., 2023). These companies played a crucial role in providing direct employment opportunities to locals and improving the social economic development of the surrounding areas. Lack of innovation saw these firms succumb because they were unable to compete with more innovative firms from abroad.

Hast (2024) explains that the fashion industry is one of the fastest-changing in the world with fashion firms having to continuously innovate to keep up with the changing consumer preferences. As such, the importance of innovation in the industry cannot be overemphasized if forms are to succeed. Despite the undeniable need for innovation, the Kenyan textile and clothing sector has not been able to keep up with these demands (Anyanga & Nyamita, 2016). It is against this backdrop that this study seeks to examine the Influence of Innovation on the Performance of Textile and Clothing Businesses in Nairobi County, Kenya. The results from this study will offer important insights into how the Kenyan textile sector can leverage innovation to improve its performance and contribute positively towards economic growth and development.

THEORETICAL AND LITERATURE REVIEW

Resource Based View

The resource-based view (RBV) was introduced by Penrose in 1959 who looked at the firm as a bundle of resources. This theory noted that the firm’s competitiveness varies considerably even within an industry due to the inherent resources possessed by a firm (Khanra et al., 2022). These inherent resources that cannot be imitated by the competitors are the reason for the high competitiveness of a firm. This theory focuses on the strategic resources within a firm which lead to a competitive advantage if deployed effectively (Barney, Ketchen & Wright, 2021).  Importantly, the model explained that firms require resources to meet the market demand implying that the resources and products play a similar role.  Importantly, affirm can either possess tangible or intangible resources that can be a source of weakness or strength in the firm.

The RBV shows the difference between the firms and their ability to create and sustain a competitive advantage. The firm’s internal resources are the drivers that determine the firm’s profitability or its ability to gain a competitive advantage (Davis & DeWitt, 2021).  Firms have to keep on responding to the customer preferences and the technological advancement implying that they must have the resources to actualize this.  Firms have to look inside and utilize their internal resources while at the same time keeping tabs on the competitors’ strategies.  In the context of the textile and clothing industry, the resources should be able to help the firms achieve long-term competitive strength. The resources should help the firm to produce innovative activities, take advantage of commercial activities, and improve their knowledge.

Lukovszki, Rideg, and Sipos (2021) explain that the RBV theory can be used to explain how firms manage innovations to remain competitive. Firstly, the existence of internal resources determines whether a firm will be able to take advantage of the opportunities for innovation. For instance, financial capability and knowledgeable human resources are great enablers of innovation in affirming. In this regard, the textile and clothing industry can leverage human capital to execute innovative strategies in the marketing and positioning of products (Barney, Ketchen & Wright, 2021). Besides, this theory explains the need for organizations to use their financial resources as this will enable them to acquire equipment that meets the current needs in the market. This theory will help the clothing and textile industry to understand the resources that will help them adapt to the current needs in the market while creating a competitive edge that is hard to copy by rivals.

EMPIRICAL REVIEW

Kipkosgei and Kithae (2019) examined the role of marketing innovation and performance of textile manufacturing firms in Nairobi County. The research was descriptive to identify a population of 145 firms. A simple random sampling technique was employed whereby a sample of 105 was selected. The data was collected using a structured questionnaire through emails. The study targeted senior personnel in the firm because these personnel are familiar with the innovative strategies employed by the firm. The results were analyzed using quantitative and qualitative analysis.  The study also used regression analysis to show the link between innovation and performance. The results revealed that innovation accounts for about 78% of the firm’s performance. The study recommended that firms should ensure that innovation strategies are carried out to completion to remain competitive. This study offers great insights into how innovation impacts the performance of apparel and clothing firms in Nairobi County.

Mwasiagi et al. (2023) studied the effects of eco-innovation on the performance of the Kenyan textile and apparel industry. The data in this research was collected using desktop research from the key stakeholders in the textile and apparel sector in Kenya. The data was collected using a structured questionnaire which was distributed using a drop-and-pick method. A stratified sampling technique was involved in identifying the target people in the research. The population consisted of 10 large textile firms in Nairobi County whereby a sample size of 106 respondents was targeted. Both open-ended and close-ended questionnaires were employed to gather qualitative and quantitative data. The data was analyzed using SPSS statistics whereby inferential and quantitative techniques were used. The results showed innovation has a positive impact on the performance of the textile and apparel industry in Kenya. The study recommended that textile firms should ensure they budget to invest in innovative processes to stay ahead of their rivals.  While this study was done in Kenya, it focused on eco-innovation which may not show the impacts of other innovation strategies on performance. As such, the results from this study cannot be used to make a generalized conclusion on the effects of innovation on the performance of apparel and clothing companies in Nairobi County.

Gültekin (2020) studied the effects of innovation on company performance in Bursan. The data was collected using a survey method whereby convenience sampling was employed. The target population consisted of the employees working in the automobile industry in Bursa. The sample size consisted of 160 workers from 55 companies. The study used an innovation scale which was developed by Karabag which shows the relationship between innovation and the company’s performance. A survey method was used to collect data whereby the target was employees working in the automobile firms in Bursan.  A convenient sampling technique is used to identify the respondents in the research. The surveys were sent through online questionnaires to the targeted employees. The data was analyzed using SPSS and presented in the form of charts and tables.  The results showed that marketing innovation has a positive impact on the company’s performance. The study also shows that process innovation has a statistically positive effect on the performance of the company. The research explains the need for firms to ensure that the employees are prepared to engage in the firm’s innovation. The main limitation of this study is that the research was done in Bursan which has a different economic and social environment compared to Kenya. Thus, this study presents a contextual gap in the current topic implying that the research cannot be used to make generalized conclusions on the effects of innovation on the performance of apparel and clothing firms in Nairobi County.

Damanpour (2020) examined the role of innovation on organizational performance by using the first-mover advantage as the mediating variable. The study used a meta-synthesis from a systematic review model. A meta-analytic review was employed on management journals whereby the Hunter method was used to fish out the journals. The selection of the study articles started by initiating a search on the abstracts of articles between 2015 and 2023.  The most recent articles on innovation were selected from this pool. The second pool entailed searching for articles on diffusion innovation whereby only English language sources were sourced. The articles were selected if they met several criteria: they contained the dependent variable, and the analysis was done on an organizational level rather than at an individual level. Thirdly, articles were chosen if the innovation model was based on at least two innovations. Lastly, only journals and books were considered in the research. The research focused on 13 quantitative reviews to understand whether innovation impacts a firm’s performance. The study used innovation type and radicalness as the research variables. The results indicated that innovation impacts performance across different organizations. However, the moderating variable was not found to have any significant impact on the firm’s performance. The main limitation of this study is that it was focused on systematic review which is different from the quantitative method used in the current study. As such, the results may vary due to the difference in the data collection methods used.

Gorski (2025) explored the role of innovation on performance and competitive advantage. This study employed a bibliometric analysis from the web search on science collection. The study focused on English articles written between 2015 and 2025. The results of the articles were further analyzed using SciMAT software to identify the relationships between the keywords and the concepts. The results showed that innovation leads to a positive impact on financial performance, human resource management, and sustainable governance. Besides, the findings showed that technological innovation has a positive impact on the organization’s capability which in turn increases performance. Lastly, the study showed the mediating role of transformational leadership on the role of innovation on performance. The main limitation of this study is that it was done entirely from secondary sources, which may lead to bias in the current study. As such, the results from this article can be generalized in the case of analyzing the impacts of innovation on the performance of apparel firms in Nairobi County.

Larios-Francia and Ferasso (2023) examined the link between innovation and MSMEs in emerging countries. The research used investment and collaboration in the organizations as the mediating variables.  The least-square model was used to analyze 104 SMEs in the apparel industry in Colombia. The study used both qualitative and quantitative data models to collect and analyze the data. The qualitative data was collected using open-ended questions while the quantitative data was collected using close-ended questions. A structured questionnaire was used and sent to the respondents through emails. The study targeted managers working in the top 5 apparel firms in Colombia.  The results showed that process innovation accounts for about 40% of the firm’s performance and 39.5% of commercial performance. The study also noted that product innovation does not have a significant impact on organizational performance. The moderating effect of investment was only important in organizational performance and productive performance. The main limitation of the study is that was done in South America which has a different market dynamic compared to Kenya. Consequently, the findings from this study cannot be used to generalize the impacts of innovation on the performance of apparel firms in Nairobi County.

DATA AND METHODS

A descriptive design was applied to describe the relationship between innovation (independent variable) and business performance (dependent variable). This design was chosen because it allows for the collection of both quantitative and qualitative data, providing a comprehensive overview of how innovation affects performance. Descriptive research is particularly suitable for identifying patterns and trends within the data, without inferring cause-and-effect relationships. The target population consisted of 85 registered T&C businesses in Nairobi County, with a focus on owners and key managers (e.g., HR, finance, and procurement managers). These businesses were selected due to their significance in the local economy and their potential to provide valuable insights into the role of innovation in business performance.

Data were collected using a structured questionnaire, designed with both closed and open-ended questions. The questionnaire gathered demographic information and explored the impact of innovation on business performance. The performance indicators included profitability, market share, and customer satisfaction, while innovation was assessed based on the implementation of new processes, products, and technologies within the businesses. The questionnaire was administered through both physical drop-off and electronic means to reach a broader range of participants. A pilot study was conducted in a similar setting to test the validity and reliability of the instrument, and feedback was incorporated to refine the final version. Data collection took place over two months, ensuring ample time for responses. Quantitative data were analyzed using descriptive statistics (e.g., means, frequencies) to summarize the responses, while inferential statistics, including regression analysis, were used to examine the relationship between innovation and business performance. The regression model evaluated how innovation, along with other entrepreneurial orientation dimensions, influenced business success.

RESULTS AND DISCUSSIONS

Response Rate

The response rate for this study was calculated based on the number of completed questionnaires returned relative to the number of questionnaires distributed. Out of the 85 textile and clothing businesses targeted in Nairobi County, 76 completed questionnaires were returned, resulting in an 89.4% response rate. This high response rate is indicative of strong participation and suggests that the findings of the study are likely to be representative of the broader population of T&C businesses in the county.

Descriptive Statistics on Innovation

Table 1 presents the descriptive statistics for the innovation factor, which is a key variable in understanding the influence of innovation on business performance in textile and clothing businesses in Nairobi County. The data was collected through a survey and the following table outlines the responses.

Table 1: Descriptive Statistics on Innovation

The first statement, “Our business has often new products for the customers,” has a mean of 3.68, suggesting that businesses generally agree that new product development is frequent. The standard deviation of 0.97 indicates moderate variability in responses, with most respondents aligning on the statement’s validity. The second statement, “The promising new ideas are not prematurely shot down in our business,” shows a mean of 3.84 and a standard deviation of 0.92. This implies a positive inclination towards openness to innovative ideas, with a slightly lower variability in responses compared to new product development.

The third statement, “Our business agrees to introduce the changes, such as changes in practices, rules, procedures, and categorization of products,” has a mean of 3.84 and a standard deviation of 1.01. This suggests that businesses are generally open to implementing changes, though the greater standard deviation indicates some level of disagreement among participants. The final item, “My business adopts manufacturing tools like IoT, AI, 3D technologies, and data-driven solutions to improve internal questions, control human resources, and improve product quality and production,” has a mean of 3.79, with a standard deviation of 0.97. The findings support previous research by Lumpkin and Dess (1996) about innovation being a fundamental factor for organizational success. According to Gebreeyesus (2011), innovation helps firms meet changing market requirements which leads to satisfied customers who stay loyal.

Descriptive Statistics on Business Performance

Table 2 presents the descriptive statistics for five items related to business performance, focusing on long-term growth contributions, customer satisfaction, product quality, resource investment, stakeholder motivation, and strategic diversification.

Table 2: Descriptive Statistics on Business Performance

The first statement, “Our business contributes to long-run growth and development on the quality and effectiveness of government policies,” has a mean of 3.76, indicating that businesses generally agree with the positive impact of their contributions on long-term growth. The standard deviation of 0.89 shows some variation in the responses. “Our customers are always satisfied by the products and they always come back for repeat services” has a mean of 3.82 and a standard deviation of 1.04, suggesting a generally positive view of customer satisfaction, with a moderate variation in responses.

“Our business makes more convenient, attractive, and palatable products for customers” yielded a mean of 3.66 and a standard deviation of 0.97, indicating moderate agreement that businesses prioritize improving product quality. “Our business continues to invest in resources and upgrades its resources to create new strategic growth options” has a mean of 3.86 and a standard deviation of 0.83, showing a strong agreement that businesses are investing in their growth.

“Our stakeholders motivate us to satisfy the wishes to achieve successful goals” scored a mean of 3.84, with a standard deviation of 0.86, reflecting strong stakeholder support. Finally, “Our business is diversifying strategies and using technology to perform due diligence” scored a mean of 3.79, with a standard deviation of 0.87, indicating that businesses are employing diverse strategies to maintain competitive advantage. These findings align with the literature in the thesis, where businesses that prioritize customer satisfaction, invest in resources, and adopt innovative strategies are more likely to achieve higher business performance and long-term success (Zulkifli & Rosli, 2013).

Regression Analysis

A regression analysis was conducted to determine the influence of innovation on business performance among textile and clothing businesses in Nairobi County, Kenya. The results of the analysis are shown in the table, which includes the model summary, ANOVA, and coefficient outputs.

Table 3 Model Summary

1. Dependent Variable: businesses performance
2. Predictors: (Constant), Innovation

The regression model yielded an R-value of 0.719, indicating a moderate positive correlation between innovation and business performance. The R-squared value of 0.516 suggests that approximately 51.6% of the variance in business performance can be explained by innovation. The adjusted R-squared of 0.510 confirms that the model is a good fit, accounting for potential degrees of freedom adjustments. The ANOVA table shows an F-statistic of 78.996 with a significance value (p-value) of 0.000, which is well below the conventional alpha level of 0.05. This indicates that the regression model is statistically significant, and the relationship between innovation and business performance is not due to random chance. The coefficients table provides the unstandardized and standardized coefficients for the predictor variable, innovation. The unstandardized coefficient for innovation is 0.655, meaning that for every unit increase in innovation, business performance is expected to increase by 0.655 units, holding all other factors constant. The standardized coefficient (Beta) of 0.719 shows that innovation has a strong positive impact on business performance. The t-value of 8.888 and p-value of 0.000 confirm that the influence of innovation is statistically significant. The regression analysis indicates a strong, statistically significant positive relationship between innovation and business performance in Nairobi’s textile and clothing sector. The results suggest that increased innovation contributes to enhanced business performance.

The findings of this study are consistent with previous scholarly work emphasizing the positive effect of innovation on organizational performance. Mwasiagi et al. (2023) in their investigation of eco-innovation in Kenya’s textile and apparel industry, found that innovative practices significantly enhanced industry performance, an outcome that supports the current study’s results. Likewise, Damanpour (2020) examined the relationship between innovation and performance through the perspective of the first-mover advantage as a mediating factor. While innovation was confirmed to influence performance positively across various organizations, the mediating variable did not show a significant effect. Further agreement was from Gorski (2025), whose research linked technological innovation to strengthened organizational capabilities, ultimately contributing to improved performance and a competitive edge.

CONCLUSIONS AND RECOMMENDATIONS

Conclusion

The research investigated how innovation affects business performance in textile and clothing companies operating in Nairobi County Kenya. The regression analysis results showed that innovation generates positive effects on business performance. The research outcomes demonstrate that innovation stands as a fundamental factor that drives business expansion in industries that experience continuous change such as textile and clothing. Organizations that adopt innovative methods through new product launches and advanced technology implementation as well as change-readiness see better business results. Innovation, therefore, serves as a key driver of competitive advantage and long-term success for T&C businesses in Nairobi.

Theory Recommendations

This study validates the Resource-Based View (RBV) theory by demonstrating how innovative resources create competitive advantages for business performance. Business performance success depends heavily on adaptable innovative resource reconfiguration according to the Dynamic Capabilities Theory. Future studies in this area would benefit from developing theoretical models that concentrate on the particular forms of innovation (product versus process methods) that yield the best results for various market sectors. The Innovation Diffusion Theory would help researchers understand how different T&C businesses adopt innovation while identifying elements that promote or block adoption procedures.

Practice Recommendations

T&C businesses must establish innovation as a top organizational priority to achieve their best results. The organization should support staff participation at every level to generate ideas and accept technology and process experiments. Managers need to fund research and development activities to maintain ongoing product and process advancement. Businesses need to develop their ability to use IoT AI and 3D technologies to optimize their manufacturing process while delivering superior products. Upgraded tools regularly help businesses maintain their market competitiveness in today’s fast-moving industry. Organizations that provide training and development opportunities to their staff members will develop innovative thinking which leads to better organizational performance.

REFERENCES

1. Anyanga, S. O., & Nyamita, M. O. (2016). The major growth strategies adopted by small and medium enterprises in Kenya: A case of Kisumu County. International Journal of Advanced and Multidisciplinary Social Science, 2(1), 11-26.
2. Barney, J. B., Ketchen Jr, D. J., & Wright, M. (2021). Resource-based theory and the value creation framework. Journal of Management, 47(7), 1936-1955.
3. Damanpour, F. (2020). Innovation and Organizational Performance. Organizational Innovation. https://doi.org/10.4337/9781788117449.000174.     Davis, G. F., & DeWitt, T. (2021). Organization theory and the resource-based view of the firm: The great divide. Journal of Management, 47(7), 1684-1697.
4. Gebreeyesus, M. (2011). Innovation and microenterprises growth in Ethiopia. Entrepreneurship, innovation, and economic development, 31, 1-30. https://collections.unu.edu/eserv/UNU:57/wp2009-053.pdf
5. Gorski, A.T. (2025). Innovation and Performance Management: Mapping the Research Landscape using Bibliometric Analysis. Revista Economica. https://doi.org/10.56043/reveco-2024-0005
6. Gültekin, A.K. (2020). The Effect of Innovation on Company Performance: A Study on Bursa Automotive Industry. The Journal of International Social Research, 13, 939-956. https://doi.org/10.17719/jisr.10568
7. Harsanto, B., Primiana, I., Sarasi, V., & Satyakti, Y. (2023). Sustainability innovation in the textile industry: a systematic review. Sustainability, 15(2), 1549.
8. Hast, A. (2024). An Exploratory Analysis of the Clothing Sector in Kenya: Key Actors and its National Socio-Economic Relevance from 1900 to 2024.
9. Khanra, , Kaur, P., Joseph, R. P., Malik, A., & Dhir, A. (2022). A resource‐based view of green innovation as a strategic firm resource: Present status and future directions. Business Strategy and the Environment, 31(4), 1395-1413.
10. Kipkosgei, K. E. & Kithae, P., P. (2019). Marketing Innovation and Performance of Textile Manufacturing Firms in Nairobi County, Journal of Marketing and Communication, Vol. 2(2), 1-18.
11. Kipkosgei, K. E., & Kithae, P. P. (2019). Marketing innovation and performance of textile manufacturing firms in Nairobi County. Journal of Marketing and Communication, 2(2), 1-18.
12. Larios-Francia, R. P., & Ferasso, M. (2023). The relationship between innovation and performance in MSMEs: The case of the wearing apparel sector in emerging countries. Journal of Open Innovation: Technology, Market, and Complexity, 9(1), 100018.
13. Lukovszki, L., Rideg, A., & Sipos, N. (2021). Resource-based view of innovation activity in SMEs: an empirical analysis based on the global competitiveness project. Competitiveness Review: An International Business Journal, 31(3), 513-541.
14. Lumpkin, G. T., & Dess, G. G. (1996). Clarifying the entrepreneurial orientation construct and linking it to performance. Academy of Management Review, 21(1), 135-172. https://doi.org/10.5465/amr.1996.9602161568
15. Mugo, A. N., Kahuthia, J., & Kinyua, G. (2019). Effects of infrastructure on the growth of small and medium enterprises in Kenya: A case of clothing and textile businesses in Nairobi Central Business District. International Academic Journal of Human Resource and Business Administration, 3(6), 133-149
16. Mwasiagi, J. I., Mpofu, N. S., Kariuki, E., & Chepkwony, K. (2023). Eco-innovation: A Case Study of the Kenyan Textile and Apparel Industry. In Circularity in Textiles (pp. 19-38). Cham: Springer Nature Switzerland.
17. Mwasiagi, I., Mpofu, N. S., Kariuki, E., & Chepkwony, K. (2023). Eco-innovation: A Case Study of the Kenyan Textile and Apparel Industry. In Circularity in Textiles (pp. 19-38). Cham: Springer Nature Switzerland.
18. Ndalira, D. W., Ngugi, J. K., & Chepkulei, B. (2013). Effect of the type of innovation on the growth of small and medium enterprises in Kenya: a case of garment enterprises in Jericho, Nairobi. European Journal of Management Sciences and Economics, 1(2).
19. Schumpeter, J. A. (1976). Ii. capitalism, socialism, and democracy, 1942. https://media4.manhattan-institute.org/sites/as/files/SKM_C45818012317090.pdf
20. Xiaoyi, Z., Yang, H., Kumar, N., Bhutto, M. H., Kun, W., & Hu, T. (2023). Assessing Chinese textile and apparel industry business sustainability: the role of organization green culture, green dynamic capabilities, and green innovation in relation to environmental orientation and business sustainability. Sustainability, 15(11), 8588.
21. Zulkifli, R. M., & Rosli, M. M. (2013). Entrepreneurial orientation and business success of Malay entrepreneurs: Religiosity as moderator. International journal of humanities and social science, 3(10), 264-275.