Introduction

Societies have distinctive cultures. The culture of a society should be self-sustaining and self-healing. Our society has undergone drastic changes as the environment around us is very dynamic. In other words, the Volatile, Uncertain, Complex and Ambiguous (VUCA) environment has affected our society’s culture as well. Individuals are striving for a better quality of life in the framework of industrial development with the help of technology. In the cut-throat competition of today’s world, there is a lack of strong community associations. People are unable to maintain balance in society as well as ecology. Even though now there are means to do things quickly and efficiently, people are unable to lead a balanced and simple life. Some of the major concerns of human society now are emotional imbalance, lack of happiness, mistrust and lack of care and compassion among fellow human beings. The main reason for this is the skewed development pattern, which is mainly focused on a few areas like the metro cities. There is a strong need for a sensible approach to ensure the well-being of all people in society and balanced economic development. The aim is to provide a model that leads to increased participation and contribution of the rural population within their area of expertise. The education system should also focus on human values and should be able to prepare students with skills such that they can choose a profession or vocation for themselves accordingly.

Organizations try to not only survive but also prosper in the face of ongoing changes and uncertainties in today’s dynamic and constantly changing business landscape. The capacity for innovation and learning has come to be recognized in this endeavour as essential to long-term success. Considering the significance of these talents, this study attempts to explore the complex interactions that occur between learning capacity, innovation capability and customer-based performance inside an organization.

The ability of an organization to gather, process and use knowledge to adjust to its surroundings is referred to as learning capability. Conversely, innovation capability denotes the ability of the organization to produce new concepts, goods or procedures that promote expansion and competitiveness (Oyeniyi, 2011).

In the current customer-centric era, a company’s customer-based performance is a crucial indicator that indicates how well it offers to meet or surpass consumer expectations, resulting in increased customer satisfaction and loyalty. The purpose of this study is to clarify if the learning, innovation and customer-based performance of an organization are significantly correlated or not. For businesses looking to maximize their investments, plans and operational procedures to attain sustainable growth and a competitive advantage in the market, they must comprehend this relationship.

The textile industry has undergone a tremendous transformation over the last few years. This transformation now requires the correct direction so that it is beneficial to society at large. The current industry is strongly influenced by globalization. The manufacturing centres have been shifted to some specific locations only. According to the Reserve Bank of India (2019), there has been a stagnant contribution of 30% by the micro, small and medium enterprises (MSMEs) to the GDP of the country. This implies that the MSMEs are not able to largely grow. This might be because the current model of doing business is not efficient enough. People have been forced to move out of their native places and shift to places where the companies have set up manufacturing centres. This has led to the creation of centralized manufacturing hubs. The phenomena of migration and urbanization have occurred due to the centralization of manufacturing centres in some specific locations. The effect of that is the inequality in development. Some places, that is, the cities developed more rapidly than the rural areas. Such an imbalance in development has social consequences. The current situation is such that almost all the resources that are required for the manufacturing sector are becoming scarce and there is an urgent need for change in the business model as it is not sustainable for the future. The sustainability of the business model is when one can meet the needs of the present generation without compromising the ability to meet future generations’ needs. Building huge infrastructures and a humongous amount of consumable goods on the cost of balance of nature and exploiting natural resources has resulted in massive problems like global warming and a threat to human existence.

Since 2016, the start-up initiative has increased the number of people who have started their businesses. Most of these businesses are in the MSME sector only. It has also created several direct and indirect jobs (Chakraborty, 2019). The lifecycle of start-ups in comparison to traditional businesses has reduced drastically. Usually, companies start innovation when they reach a later stage in the product life cycle (PLC) curve. But, now the need for learning and innovation capability has changed. The new organizations are built on the dual aspect of invention as well as commercialization in a sustainable manner.

Building learning and innovation capability is quite a big challenge for organizations, it is an even bigger and tougher challenge for rural women. Rural women confront several difficulties like restricted access to science and technology, lack of proper education, socio-economic disparities, traditional gender roles and norms, etc. For rural women to be empowered and for sustainable development, learning and innovation capabilities are essential. To overcome these limitations, creative training programs that fit into women’s daily routines should be introduced in rural areas. Sustainable technology is important because it may address issues in rural communities by applying cutting-edge scientific and technological techniques. Rural innovation is greatly aided by female innovators, highlighting the significance of acknowledging and valuing their contribution. Rural women can gain from innovation and technology training.

Objective

The paper attempts to find out the relationship between learning capability, innovation capability and the customer-based performance of a company. It intends to find out whether the relationship between these components is considerable. The dynamic business environment requires companies to continuously work on their learning capability and innovation capabilities to survive in the competitive market environment. Though the current businesses are improving their learning and innovation capabilities, there is a need for a new business model that will encourage these capabilities on a much larger scale. New, small and medium enterprises should try to implement this model so that they can improve their customer-based performance.

Methodology

The research methodology used for this study was based on primary data collected from the stakeholders of a social enterprise and secondary data also. The study has been built based on the concepts of the Gandhian model. The research paper is based on the theoretical concepts of the Gandhian model of development and the business model of an existing social enterprise. The research paper aims to show that the customer-based performance of a company is influenced by the learning and innovation capabilities that the MSME possesses. The questionnaire about the learning capability and innovation capability was adapted from previous research papers. The questions for innovation capability and learning capability were adopted from Hurley and Hult (1998), Calantone et al. (2002) and Salavou et al. (2004); Customer-based performance was adopted from Morgan et al. (2009). The questions were provided to 200 rural women from textile based MSMEs, out of which 192 people responded. These responses were used for analysis using the Smart partial least squares (PLS) software. The questionnaire was on a seven-point Likert scale. Each component of the study had five sub-components. The PLS algorithm was used on the data collected. It was observed that the outer loadings, as well as the outer weights of the sub-components, were insignificant so they were removed. The number of sub-components was thus reduced.

Literature Review

Several studies explore the relationship between organizational learning capability and innovation (Akgun et al., 2007; Alegre & Chiva, 2008; Fang et al., 2011; François, 2002; Gomes & Wojahn, 2017; Ugurlu & Kurt, 2016). Similarly, there are many studies on firm performance and customer-based performance, but they are in different contexts like quality management (Modarres, 2023), insurance sector (Rajapathirana & Hui, 2017), etc. There is a need to study the learning and innovation capability in the textile sector, and how it impacts the customer-based performance of the company.

In this study, the relationship between learning capability and innovation capability has been studied on 192 rural women in micro, small and medium-sized textile industry companies. To understand the objective of the paper, there is a need to understand the terms that are used to test the conceptual model. This includes terms like learning capability, innovation capability and customer-based performance.

Learning Capability

The term ‘learning capability’ of an organization is defined as the characteristic feature or element of an organization that facilitates the learning process or encourages an organization to learn (Goh & Richards, 1997). It has also been described as the ability of an organization to create, acquire, transfer and integrate knowledge. This is used to modify the behaviour of the organization to respond to a new situation to improve organizational performance (Jerez-Gomez et al., 2005). The learning capability of an organization is an important component of the learning process (Alegre & Chiva, 2008; Goh & Richards, 1997). Learning capability is a significant index of an organization’s competitiveness (Jerez-Gomez et al., 2005). Moreover, it also promotes the organization’s ability to identify opportunities in the market and respond to them in a better, faster and cheaper manner. This will ultimately reflect in the development of new products more efficiently (Prieto & Revilla, 2006; Sok & O’Cass, 2011). This helps the companies to utilize the opportunity in a better manner to achieve superior performance. It also allows the companies to implement new strategies and understand the customers, which will ultimately lead to differentiating themselves from their rivals. Thus, the following hypothesis is framed:

    H₁: Learning capability has a positive relationship with customer-based performance.

Innovation Capability

The term innovation capability is defined as the interrelated processes of an organization that help to implement and develop a product innovation (O’Cass & Sok, 2012). Previous literature indicates that the learning capability of a company is commonly linked to innovation (Dodgson, 1993), and it also suggests that the learning capability has a positive effect on innovation capability (Alegre & Chiva, 2008, 2013; Jiménez-Jiménez & Sanz-Valle, 2011). Moreover, learning capability also has a positive influence on the innovation capability of a company (Hsu & Fang, 2009). Li and Mitchell (2009) and Rosenbusch et al. (2011) found in their studies that organizations with strong innovation capabilities have a competitive edge, which enables them to achieve better performance. Thus, the following hypothesis is framed:

    H₂: Learning capability has a positive relationship with innovation capability.

Customer-Based Performance

Customer-based performance is the evaluation and quantification of a company’s efficacy or success based on the attitudes, actions and experiences of its customers (Mohiuddin Babu et al., 2019). This approach acknowledges the crucial function that customers fulfil in moulding the efficacy and prosperity of an enterprise. Customer loyalty, engagement, overall experience and satisfaction are important components of customer-based performance. Customer satisfaction is connected to various branches and metrics of customer-based performance (Tajeddini & Ratten, 2017). Its many capabilities and strategic plans allow staff members to build relationships with clients. Numerous studies highlight the robust relationship between loyalty and consumer pleasure (Chang et al., 2014). Customers who are happy with a brand are more inclined to use it again and to recommend it to others (Fang et al., 2014). A steady customer base lowers acquisition costs and boosts lifetime value when there is high customer loyalty. Engaged customers are more likely to be loyal and contribute positively to a company’s performance. Engagement can be fostered through various means, including social media interactions, personalized communication and loyalty programs. Socially responsible practices positively influence customer perceptions. Companies that are perceived as ethical and socially responsible often enjoy better customer loyalty. Firms need to take decisions and actions based on the resources available, and generate competitive advantages, thereby improving their performance (Ketchen et al., 2007):

    H₃: Innovation Capability has a positive relationship with customer-based performance.

Figure 1 presents the proposed research model of the study. The hypotheses that must be tested and studied among the rural women workers of textile-based MSMEs.

Learning and Innovation Capability in Textile-Based MSMEs

The global textile business is changing in tandem with technological breakthroughs. MSMEs need to constantly learn about and implement new technologies to increase productivity, improve product quality and stay competitive in the market (Eisenhardt & Martin, 2000). MSMEs can maintain an advantage in the fierce market by utilizing their learning and innovation capabilities. MSMEs can set themselves apart and draw in more business by adopting cutting-edge goods, procedures, or design features. MSMEs with significant capabilities for innovation and learning might be able to broaden the range of products that they offer. This will enable them to examine new markets and respond to evolving consumer inclinations. MSMEs will benefit from continuous learning by seeing an increase in overall efficiency, waste reduction and operational efficiency. Process innovations in production can result in lower costs and better use of resources.

Quality can be improved in textile products by learning about and using creative approaches. Quality-focused MSMEs are more likely to establish a solid reputation, which breeds client loyalty and trust. MSMEs in the textile industry need to be aware of global trends and standards due to the globalization of markets. Opportunities for international trade may arise from learning about the needs of the global market and developing innovative solutions to suit those needs. Innovation in environmentally friendly and sustainable techniques is becoming more and more significant. MSMEs may support sustainability and attract eco-aware customers by investing in educating themselves about and implementing eco-friendly technologies and procedures. Building a robust supply chain can benefit from innovation and learning. MSMEs can more effectively negotiate supply chain uncertainty if they can swiftly adjust to disturbances, such as shifts in the availability of raw materials or difficulties with transportation. Employee engagement and morale can be increased in MSMEs by fostering a culture of learning and innovation. Additionally, it offers chances for skill improvement, resulting in a workforce that is better prepared to adjust to changes in the sector. Long-term viability in a business climate that is changing quickly depends heavily on an organization’s capacity for innovation and learning. MSMEs are better equipped to handle difficulties, take advantage of opportunities and guarantee steady growth when they invest in developing these qualities. Thus, textile MSMEs must strategically possess learning and innovation capabilities to adjust to shifting market conditions, boost competitiveness, increase operational effectiveness and guarantee long-term sustainability in a changing and dynamic sector (Charry et al., 2017).

Analysis

The PLS path modelling method was run on the data collected, and Figure 2 represents the diagram of the model that was obtained. The coefficient of determination, R2, is 0.300 for the CP (customer-based performance) endogenous latent variable. This means that the two latent variables, that is, learning capability (LC) and innovation capability (IC) together moderately explain 30% of the variance in CP. Also, LC explains the 28.4% variance of IC.

Based on Figure 2, it can be said that the inner model suggests that LC has the strongest effect on IC (0.533), followed by the effect of LC on CP (0.325) and the effect of IC on CP (0.300). The hypothesized path relationship between LC and IC; IC and CP; and LC and CP are statistically significant. This is because all the standardized path coefficients are higher than 0.1. This figure further shows that the sub-component of learning capability, that is, diagnosing our staff training and educational needs (LC1) and analysing the firm’s unsuccessful activities (LC4) are good indicators of learning capability. Similarly, exploiting the most up-to-date technology available (IC1) and developing new products (IC2) are good indicators of innovation capability. Also, acquiring new customers (CP1) and increasing sales to existing customers (CP2) are good indicators of customer-based performance.

Figure 1. Proposed Research Model

Figure 2. Result Research Model

The diagram also shows that ‘diagnosing our staff training and educational needs’ and ‘analysing the firm’s unsuccessful activities’ have loadings of 0.750 and 0.919, respectively. This implies that they are good indicators of learning capability. Similarly, ‘exploiting the most up-to-date technology available’ and ‘developing new products’ are good indicators of Innovative capability and have a loading of 0.750 and 0.919, respectively. On similar lines, ‘acquiring new customers’ and ‘increasing sales to existing customers’ have loadings of 0.838 and 0.817, respectively, which makes them good indicators of customer-based performance. Thus, it can be concluded that learning capability and innovation capability are both moderately strong predictors of customer-based performance. Moreover, learning capability predicts innovation capability directly.

Figure 3.Bootstrapping Results of the Research Model

Figure 3 shows the bootstrapping of the components that have been listed in this model. The bootstrap procedure can test the significance of a structural path using t-statistic. In SmartPLS, bootstrapping can also be used to test the significance of formative indicators’ outer weight Using a two-tailed t-test with a significance level of 5%, the path coefficient will be significant if the t-statistics is larger than 1.96. According to Figure 2, the t-statistic value of all three paths, that is, is significant. The value of the t-statistic between LC and IC is 4.101, between LC and CP is 3.719 and that between IC and CP is 2.196. This shows that the hypotheses that have been stated earlier are accepted and there is a significant relationship among the components of the model, that is, innovation capability, learning capability and customer-based performance.

Findings and Suggestions

This research study shows that innovation capability is influenced by the learning capability of the business. The result of the learning and innovation capability can be seen in the customer-based performance. This suggests that the newly set-up companies like start-ups should focus on improving their learning and innovation capabilities so that their customer-based performance can improve. Continuous improvement in the performance of the company will occur when its learning and innovation capabilities are high. The study emphasizes improving learning and innovation capability. This has helped them to expand and sustain their business. The research paper suggests that new start-up businesses should focus on improving their learning and innovation capability so that the business can have a good customer-based performance.

Theoretical and Practical Implications

This research study highlights a link between innovation capability and the learning capacity of a business. This suggests that companies should not view innovation as an isolated process because there is continuous learning within the organization. The study establishes a theoretical foundation that shows learning and innovation as drivers of customer-based performance. This implies that organizations seeking to enhance customer satisfaction and loyalty should prioritize investments in learning initiatives and foster a culture of innovation. Companies should thus embrace a philosophy of ongoing learning and innovation to adapt to changing market dynamics and customer expectations.

The study implies that learning should be integrated into the overall business strategy of the company. Companies, especially those in their early stages, should consider learning not just as a byproduct but as a deliberate strategy for fostering innovation and, subsequently, improving customer-based performance. Organizations should be flexible and adaptable as the business landscape is constantly evolving. A commitment to continuous learning and innovation allows companies to adapt to changing customer preferences and market conditions. Companies can learn from industry best practices in terms of fostering innovation and continuous learning. This involves benchmarking successful companies known for their innovative approaches and incorporating relevant strategies into their operations.

The creation of localized micro-factories is the way ahead for sustainable growth and development in all places. This will lead to not only balanced regional development but will also provide people with the opportunity to work in their nearby micro-factories as per their skill.

Limitations and Scope for Future Research

The study mainly focuses on the textile industry and its MSMEs in rural areas, limiting its generalizability to other industries. Different sectors may have distinct characteristics, so the findings may not be universally applicable.

The study has a limited sample size, and the participants might not be fully representative of the broader business community. This could impact the study’s external validity, making it challenging to extrapolate the findings to a larger population.

Conclusion

The study takes a cue from the Gandhian model and then analyses the business activities of textile-based MSMEs in terms of their learning and innovation capability concerning their customer-based performance. The paper also provides insight into the managers of small and medium scale enterprises that for superior customer-based performance in the marketplace, companies must develop their learning and innovation capabilities. The companies must ensure that they offer products that meet the needs of the customers while seeking to improve the skills of local people and make use of local resources. This way the whole society will benefit, and there will be balanced development. Thus, aligning the learning and innovation capabilities to achieve superior performance is vital for MSME managers.

Declaration of Conflicting Interests

The author declared no potential conflicts of interest with respect to the research, authorship and/or publication of this article.

Funding

The author received no financial support for the research, authorship and/or publication of this article.

ORCID iD

Oly Mishra  https://orcid.org/0000-0002-5595-8705