Unlocking SME success: optimizing capability development amidst dynamic market conditions in emerging economies

Abstract

Purpose

The business landscapes in Asia and Africa are predominantly characterized by small and medium enterprises (SMEs) facing significant resource constraints. Understanding the capability dynamics of these enterprises in such contexts carries significant implications for theory and practice. This paper aims to addresses a crucial question of whether increasing customer involvement capability consistently yields the necessary rent for enterprises operating under resource constraints in emerging markets in Asia and Africa. By investigating this question, the paper offers SMEs a more nuanced approach to capability development, enabling them to achieve better returns on their investments.

Design/methodology/approach

To ensure the robustness of the findings, data were collected from SME service firms operating in two emerging economies: India (Asia) and Ghana (Africa). Data were collected in two waves to allow for catering to specific environmental conditions not accounted for in the study. Two-stage data analysis was then conducted to test the hypothesized relationships across the two countries.

Findings

The findings reveal that customer involvement capability does not always lead to an increase in firm-level competitiveness, and the effect follows an inverted U-shaped pattern. However, the nature of this relationship varies under different market conditions in both contexts. Specifically, in periods of low customer demand and intense competition, the relationship is linear and positive. On the other hand, in periods of high demand and competition, the relationship becomes inverted U-shaped, returning to a direct relationship with firm-level competitiveness.

Originality/value

This paper provides a resolution to the critical issue of whether customer involvement capability consistently delivers firm performance benefits, particularly for resource-constrained SMEs in emerging markets. By explaining how SMEs in emerging markets can fully capitalize on their capability development to optimize their resources, this paper makes a distinctive contribution. Moreover, it sheds light on the importance of aligning involvement capabilities with prevailing market conditions for SMEs to reap the maximum benefits.

Citation

Anning-Dorson, T. (2023), "Unlocking SME success: optimizing capability development amidst dynamic market conditions in emerging economies", Journal of Entrepreneurship in Emerging Economies, Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/JEEE-11-2022-0336

Introduction

The development and effective utilization of firm capabilities play a crucial role in establishing and sustaining competitive advantage (Teece et al., 1997; Buyukbalci and Dulger, 2022; Pigola et al., 2022). Augier and Teece (2009) emphasized that performance differences among firms can be attributed to their distinct capabilities. These capabilities encompass a collection of intricate skills and knowledge embedded within organizational processes, forming the foundation for creating competitive advantages (Helfat and Peteraf, 2003). Consequently, their impact on firm performance has garnered substantial attention in management literature (Feng et al., 2017; Hernández-Linares et al., 2021) and small business literature (Aghazadeh and Zandi, 2022; Nusair et al., 2022) over the past decades.

Despite the popularity of the capabilities perspective, it has faced criticism for its lack of clearly defined boundary conditions and the complex discussion surrounding the effect of dynamic capabilities (Fainshmidt et al., 2019; Nayak et al., 2019). Particularly in the small and medium enterprise (SME) literature, questions have been raised regarding the extent to which small businesses, constrained by limited resources (Li, 2018), should invest in capability development (Anning-Dorson, 2021). This raises a critical question that requires careful consideration by SME and management scholars: does capability development always result in increased performance and competitiveness for an enterprise? Answering this fundamental question is crucial, as it allows scholars in regions such as Asia and Africa to contribute meaningfully and practically to the dominant SME sector in emerging economies. Therefore, this paper aims to make such a contribution by examining customer involvement as a significant capability within service firms and exploring the extent to which an increase in this capability development leads to performance benefits for SME service firms operating in emerging markets.

Customer involvement is a fundamental aspect of cocreation that has been empirically shown to offer advantages to service firms (Nenonen et al., 2019; My-Quyen and Hau, 2021). This paper aims to shed light on this topic by investigating key conditions that provide context for addressing a pressing question: does capability development, such as customer involvement capability, consistently lead to performance enhancement for enterprises in Asia and Africa? Seeking to respond to this inquiry and contribute to the existing literature, this study examines different conditions under which capabilities, including customer involvement capability, create opportunities for performance improvement in the mentioned regions. Three specific conditions in the form of questions are explored to bring clarity to the issues:

Q1.

What is the optimal level of capability (customer involvement) that drives superior competitiveness in SMEs?

Q2.

At what levels of market conditions (e.g., market competition and demand) would capabilities, such as involvement capability, foster superior SME competitiveness? and

Q3.

Do the answers to the above questions vary in different regional contexts, such as Asia and Africa? These questions are explored in the context of services, where value cocreation predominantly shapes value appreciation and value capture.

The core outcome variable in dynamic capability theory is the potential of capabilities to create competitive advantage and enhance firm performance (Teece et al., 1997; Anning-Dorson, 2019). An entity is said to possess a competitive advantage when it outperforms its current or potential competitors in the industry (Mahdi et al., 2019; Peteraf and Barney, 2003). Consequently, superior firm performance relative to rivals is often used as an empirical indicator of competitive advantage. In the context of involvement capabilities, they are conceptualized as organizational routines (Anning-Dorson, 2018) that enable service firms to adapt to customer and market demands, thereby improving their performance. Specifically, customer involvement capability is defined as “the extent of a firm's ability to engage customers in the value creation and delivery process” (Anning-Dorson, 2018, p. 270). This capability is considered crucial to the value delivery process and has significant implications for firm performance (Dixit et al., 2019; Prahalad and Ramaswamy, 2004). In the context of services, customer involvement holds even greater significance due to the customer's role as a resource and value assessor (Grönroos and Voima, 2013). Therefore, this paper contends that involvement capability is a pivotal capability that generates advantages in the services sector.

In the service environment, customer involvement is seen as a prerequisite for value creation as value is more than ever cocreated (Vargo and Lusch, 2004; Hollebeek et al., 2022). Hence, it is believed that an Asian or African SME service firm that can develop and deploy customer involvement capabilities will enjoy a competitive advantage and enhanced performance. However, the present study questions this long-held belief, asking whether, at any level of involvement capability and market condition, such a positive linear relationship exists? Although recent studies such as El Nemar et al (2022) and El Chaarani et al (2022) have investigated the potential effects of internal firm mechanisms such as human resources, brand reputation and strategic competitive innovation have on competitiveness, there are still questions that needs answers. Sharma et al. (2014) admonished that developing such firm-level capabilities will enhance the customer value cocreation efficiency and effectiveness, which will, in turn, improve competitiveness. However, the effect of customer involvement may not be linear, and operational inefficiencies might occur if involvement is intensified, which might erode competitiveness. There is therefore a possibility of curvilinear relationship which must be explored to help SMEs in Africa and Asian to benefit from such capability development.

Additionally, the analysis of boundary conditions, specifically market conditions, under which the potential curvilinear relationship between customer involvement capabilities and competitiveness exists, is crucial. Scholars like Sinha and Sheth (2018) have emphasized the competitive nature of the business environment in contexts such as India and Ghana, impacting both multinational corporations and SMEs. Understanding the link between capabilities and market trends is essential for explaining the conditions in which SMEs can derive the most advantage from their capabilities to enhance competitiveness. As Schilke (2014) suggests, the efficacy of dynamic capabilities is tested under varying environmental conditions. The complexity of today's business environment challenges any assumption of a consistent ordered relationship between SME capabilities and performance, particularly in economic contexts like India and Ghana. Changes in market conditions, such as shifts in customer demand and competitive intensity, may redefine the nature of this relationship (Lane and Maxfield, 1996; Zhang et al., 2020). Moreover, different markets or economic contexts may respond differently to the proposed curvilinear relationship between customer involvement capabilities and competitiveness. For example, Anning-Dorson (2018) found that the linear relationship between customer involvement capability and firm performance was influenced by the economic context.

Based on the above considerations, this paper contributes to the literature in three significant ways. First, it makes a theoretical contribution by presenting a new, integrative perspective on the relationship between capability development, market dynamics and SME competitiveness. By integrating existing views, the paper proposes a novel inverted U-shaped moderating effect, indicating that the association between involvement capabilities and competitiveness is stronger at intermediate levels of customer demand and competitive intensity but comparatively weaker when these factors are low or high. Second, the paper contributes to the SME service management literature by delving into customer involvement at the service firm level, an aspect that has received insufficient attention, particularly in the SME literature (Anning-Dorson, 2021; Sharma et al., 2014). Additionally, the quadratic effect of service firm capabilities has been relatively overlooked in the service literature, and this study sheds light on the possible nonlinearity effect of service firm capability development. The empirical findings demonstrate how SME service firms can optimize customer involvement capabilities to achieve enhanced performance within the complex service ecosystem. Lastly, this study extends the analysis of boundary conditions by empirically testing the model in two different emerging markets. As advocated by Ostrom et al. (2015), exploring diverse economic, social, and geographic contexts enriches our understanding of a domain in terms of both theory and practice. Therefore, this study validates the capability theory paradigm by enriching current theorization with appropriate boundary conditions.

Theoretical background and hypotheses

The theoretical inspiration for this study comes from the broader capability perspective which has its roots within the resource theory which has been used in SME studies such as El Nemar et al (2022). The capability theory suggests that firms build their competitiveness through capability building and exploitation (Zahra et al., 2022; Teece, 2019). Hence, Teece and Pisano (2003) assert that firms with the necessary capabilities over time are more competitive than those with less capabilities. Recent studies such as, Dejardin et al. (2023) and Clampit et al. (2023) have found a strong relationship between SME capability development and exploitation and firm performance and competitiveness. According to the fundamental paper by Teece et al. (1997), capabilities are within the routines and processes of firms which enable them to respond to their environment in a dynamic fashion. The current study, therefore, theorizes that SMEs could exploit their routines and processes within their value cocreation process where they can involve their customers in the value production process. According to Anning-Dorson (2018), firms can exploit their customers as market-based resources which is supported by Grönroos (2008). SMEs that have strong customer involvement capability can use the customer as a market-based resources to create competitive advantage for itself.

Customer involvement capability and small and medium enterprise competitiveness

Customer involvement and cooperation have been linked to improved enterprise performance in the extant literature (Morgan and Anokhin, 2023; Yuk and Garrett, 2023). Encouraging customer participation is considered a major shift from a goods-centered to a service-centered logic for marketing (Vargo and Lusch, 2004; Tuan, 2022). Bendapudi and Leone (2003) have opined that it is an important frontier for competitive advantage creation and effectiveness. This is explained by the fact that the customer has become an active participant in the value creation process (Gallan et al., 2013). In services, customer involvement delivers value to both the customer and firm (Cheung and To, 2021) such that Bendapudi and Leone (2003), for instance, found that participating customers were more satisfied than nonparticipating customers. Chen et al. (2015) also found that firms that encouraged customer participation produced positive effects on employees’ job satisfaction, and Bendapudi and Leone (2003) found customer participation to be positively associated with firm performance. These findings, therefore, suggest that firms that can develop their capabilities with respect to customer involvement would create advantages that will enable them to outperform the competition.

Customer involvement capability is a marketing capability that creates and delivers better value to customers – an important competitive advantage (Quach et al., 2021; Vorhies et al., 2011). Orr et al. (2011) described such capabilities as facilitating the necessary building of customer relationships, which Dimitriadis and Stevens (2005) defined as the “integration of all the activities across the firm, linking those activities to both firm and customer value” (p. 157). By that, SMEs can deploy their relational assets through their involvement capabilities (Orr et al., 2011). Relational assets are relationship-based and are important in the practice of marketing, particularly in services marketing. They are usually based on factors such as trust, dependency and reputation, presenting the potential for firms to develop intimate relations with customers to the point that they may be relatively rare and difficult for rivals to replicate. Srivastava et al. (2001) maintained that relational assets tend to be intangible and are hard to measure and, therefore, can go unnurtured. Firms that can exploit relational assets create a competitive advantage, as they will be relatively rare and difficult for rivals to replicate. It takes involvement capability for firms to fully exploit the relational asset – an important competitive advantage – to increase firm performance (Srivastava et al., 1999).

Contrariwise, although developing involvement capabilities might increase competitiveness and SME performance, they may offer negative returns, depending on the level. The literature on customer involvement has hinted at a possible curvilinear effect (Anning-Dorson, 2021; Chan et al., 2010). Indeed, the literature shows that findings on increasing customer participation (analysis at the customer level) have not been all positive (Auh et al., 2007; Bendapudi and Leone, 2003). Increasing a firm’s ability to involve customers may bring efficiency problems (Chan et al., 2010), which can increase production costs. Additionally, it has been found that customer involvement “may not unequivocally create positive value” (Chan et al., 2010, p. 48), as a disproportionate increase of involvement may shift more power from the SME and its employees to customers. This may increase employee workloads and role conflicts (Hsieh et al., 2004) and overall service performance time an SME may have to invest into a customer. The returns on involvement capability will begin to reduce if the investment is disproportionate. Finding the right balance for involvement capability investment would return higher value creation opportunities for an SME service firm to create higher competitiveness and superior performance. Further, because environmental conditions will differ from country to country, the effects are expected to differ as well. Because the environmental conditions will differ in India from Ghana, the effect is expected to differ. Because the linear relationship has been established in previous studies, the current study only hypothesizes for the quadratic relationship; hence, it is hypothesized that:

H1.

1a – Customer involvement capability has a quadratic relationship with SME competitiveness and that 1b – the results will differ significantly from country to country.

Moderating effects of customer demand and competitive intensity

Business environments are characterized by frequent changes in customer needs and preferences as well as unpredictable competitive strategies (Story et al., 2015). Sheth (2011) asserts that emerging markets such as India and Ghana are experiencing frequent changes in needs and wants which is in line with the economic transformation, democratization of information communication and technology and growing middle class. Such environments are often classified as dynamic, and research shows that increased environmental dynamism is the strongest determinant of market uncertainty (Yuan et al., 2021; Jaworski and Kohli, 1993). The success of businesses in such conditions depends on their ability to develop strategies and deal with uncertainties in the environment (Ahammad et al., 2021; Augier and Teece, 2009). Teece (2007) proposed that firms require dynamic capabilities to adapt to changing environments and shape the ecosystems they occupy. Dynamic capabilities enable firms to renew their competencies to meet changing market requirements, which is an important competitive advantage. However, when the business environment is in a state of flux, it supports customer variety-seeking, unpredictable competition, promotional wars, change in customer preference and change in purchase behavior (Szymanski et al., 2007). These environmental factors can have a telling effect on whether business activities, such as customer involvement, will improve firm performance outcomes (Li et al., 2019). Mowery and Rosenberg (1993) identified the market condition as a key environmental condition that influences the relationship between business activities and the level of performance. More recent study by Feng et al. (2017) shows that environmental dynamism and market conditions moderate the relationship between firm capabilities and performance. The present study posits that demand uncertainty and competition are two market conditions that would affect the involvement capabilities – SME competitiveness relationship in the dynamic emerging markets of India and Ghana.

The involvement capability-competitiveness relationship may be influenced by customer activities such as the level of market demand. Studies have found that increasing customer involvement has the potential of introducing inefficiencies in service production and delivery – indeed, that customer involvement “may not unequivocally create positive value” (Chan et al., 2010, p. 48), as increased involvement may shift more power from employees to customers, which may increase employee workloads and role conflict (Hsieh et al., 2004). In high customer demand periods, for instance, increasing customer involvement may be counterproductive (Anning-Dorson, 2016) and, therefore, will not yield superior performance for the SME service firm. Additionally, in low demand periods, investment in the involvement capability of an SME may outweigh the benefits it might bring, which is expected to differ in both countries as per the environmental arguments put forward. It is consequently hypothesized that:

H2.

2a – The quadratic relationship between involvement capability and SME competitiveness will be reduced by the level of customer demand and that 2b – the results will differ significantly from country to country.

It has been long established that environmental dynamics such as competitive intensity moderates the effectiveness of organizational characteristics (Child, 1972; Slater and Narver, 1994; Abu-Rahma and Jaleel, 2017). Studies (McKee et al., 1989; Snow and Hrebiniak, 1980) have long established that competitive intensity moderates the effectiveness of strategic actions. More recent studies in emerging markets, such as Lyu et al. (2022) and Rasheed and Ahmad (2022), have confirmed this assertion. Competitive intensity describes the market competition faced by a firm (Cui et al., 2005), with magnitude determined by the strength – or otherwise – of the rival firms’ activities (Molina-Castillo et al., 2011). Competition puts pressure on firms to adopt new measures to improve their competitiveness and thus performance. Competition also creates a sense of urgency for SMEs to match or beat the competition and, therefore, offers insufficient time for integration across the enterprise. By contrast, when competition in a market is mild, SMEs may face less pressure and have sufficient time to develop and use their capabilities to exploit other resources and capabilities to compete. Involvement capabilities, for instance, have been found to exploit other capabilities such as innovation (Ordanini and Parasuraman, 2011; Prahalad and Ramaswamy, 2004). Capabilities have been found to develop over time and require an enduring effort by the entire firm. In a highly competitive market, the activities and offerings that one competitor can provide will quickly be matched by others, and, as such, customers are offered alternatives, which reduces competitiveness (Jaworski and Kohli, 1993).

Anning-Dorson (2016) asserted that competitive intensity in the service sector is borne out of resource constraints and that firms are limited in their investment abilities, which is direr in the case of SMEs. The competitive service sector is characterized by the existence of many competitors, which has asphyxiated opportunities for growth (Auh and Menguc, 2005). The increasingly competitive business environment features greater rivalry among incumbents (Li et al., 2008), stronger competitors (Ang, 2008) and competitor activities (Cui et al., 2005) such as imitation (Chen et al., 2010), increased avenues for customer participation (Sharma et al., 2014) and cocreation (Vargo and Lusch, 2008). Drawing on the above arguments, this study posits that the effect of competitive intensity will mitigate the positive relationship between involvement capability and performance of service firms as they face resource constraint, lack of growth opportunities and time constraints; this is expected to differ in both countries as per the environmental arguments put forward. Hence, it is hypothesized that:

H3.

3a – The quadratic relationship between involvement capability and service firm competitiveness will be reduced by sector-level competition and that 3b – the results will differ significantly from country to country.

Methods

Study setting, sample and procedure

The study tested three hypotheses using SME service firms from two emerging economies, India and Ghana, with the aim of validating the findings and demonstrating the model's robustness. Ghana is recognized as an emerging sub-Saharan African market (Burgess and Steenkamp, 2006; Adu-Gyamfi and Korneliussen, 2013; Sheth and Sinha, 2015). Its growth since the end of the military regime in 1992 is partly attributed to a thriving private sector. The service sector has been expanding steadily and constituted nearly 60% of its GDP as of the last quarter of 2019 (Ghana Statistical Service, 2020a, 2020b). In the case of India, the services sector has played a significant role in its recent economic growth and development (Nair et al., 2015). An economic survey presented to the parliament in 2017–2018 revealed that the service sector contributed 72.5% to India's GDP in 2017. Renowned as a global hub for services, India excels in IT, accounting, legal, investment banking and consulting (Sheth, 2011).

A random sample of SME service firms was targeted in both India and Ghana. To gather comprehensive data and accommodate specific environmental conditions not covered by the study, two separate data collection instruments were distributed to the participating firms. The first instrument, focusing on customer involvement capability, competitive intensity and market demand, was completed by nonfinancial managers responsible for marketing, operations, business development and related areas. The second instrument, dedicated to competitiveness and encompassing financial and nonfinancial performance, competitive advantages across the marketing mix and adaptability to changes in the business environment variables, was exclusively answered by finance managers/accountants or accounting managers.

Respondents’ competence in providing information on the respective subjects was assessed in three key areas (Chuang et al., 2015):

• knowledge about the questions;

• accuracy of the information provided; and

• confidence in the answers given.

These three key areas were present in both samples and evaluated on a 7-point Likert scale (1 = strongly disagree; 7 = strongly agree). The findings revealed that both the Ghanaian and Indian informants demonstrated high knowledge and confidence in their responses, obtaining minimum scores of 6.25 and 6.31, respectively.

In Ghana, a total of 627 service firms were initially contacted through an online portal listing various companies’ services. Out of these, 627 were identified as service firms with available contact information, and 336 expressed willingness to participate. After two email reminders and phone call follow-ups, complete responses were received from 201 firms, which were subsequently used in the study. The participating enterprises represented sectors such as hospitality, communication and media, digital marketing services, accounting services and business support. Data collection was focused on the three major cities of Accra-Tema, Kumasi and Sekondi-Takoradi.

In India, a total of 600 SME service firms were identified and contacted through the alumni network of a B-school. Among them, 379 firms positively responded to the survey invitation. The specific instructions on who should respond to which instrument were conveyed by email to each consenting company. Ultimately, 311 responses were received, out of which 213 were deemed complete and suitable for analysis. These SMEs operated in various sectors, including IT and communication, retail, consulting, brokerage and support services, and were located in cities such as Lucknow, Indore, Delhi and Mumbai.

Measures

Competitiveness was measured with the three categories specified by Akimova (2000). She explained that firms seeking to be competitive must create advantages from the marketing mix according to the peculiarities of the environment. As such, 12 items measured advantages across the marketing mix. Akimova also stated that competitive companies should adapt to the changing business environment; this was also measured by 12 items. Adaptability reflects a company’s adjustment activity to a turbulent environment. Lastly, competitive companies should perform well financially. However, the current study added nonfinancial performance measures. A total of five financial measures and three nonfinancial measures were used. That all three themes subjectively measured underlying competitiveness was due to the difficulty in assessing objective measures especially regarding financial performance in emerging markets. In emerging economies like Ghana and India, hard data across these measures for a large number of enterprises were unavailable (Malik and Kotabe, 2009). Previous studies have found a strong correlation between subjective assessments and their objective counterparts (Slater and Narver, 1994). Competitiveness was treated as a second-order variable in testing the hypotheses and structural model.

Competitive advantage items were measured on a 7-point Likert scale across marketing mix areas (1 = Completely disagree that our firm has this competitive advantage; 7 = Completely agree). Environmental impact on marketing management of the company and its adjustment activity was measured across marketing mix decisions using a 7-point Likert scale (1 = Impact is very high or Adjustment measure was used very often; 7 = Impact is very low or Adjustment measure was never used). Since the adjustment activity of the companies across particular measures could vary because of differences in the environmental impact on their marketing decisions, it was useful to compare the level of environmental impact on the marketing management decisions of the companies with the level of adjustment activity across the marketing mix. Using Shama’s (1992) “impact/adjustment” paradox, the study computed Shama’s coefficient as the difference between the adjustment mean scores and the impact mean scores across a marketing mix decision. This was used as the measure of a company’s adaptability. Performance was measured relative to major competitors within a firm’s market. This enabled the study to control for performance differences caused by differences among industries and served markets. Performance measurement was extended beyond what Akimova (2000) did by adopting the three measures of Katsikeas et al. (2016). The present study used financial, nonfinancial and market performance measures. Again, all items on firm performance used the 7-point Likert scale (Last year our company showed much better performance across these indicators than the main competitors; 1 = much worse to 7 = much better performance). Competitiveness was therefore analyzed as a second-order variable.

Involvement capability was measured by following the work of Anning-Dorson (2018, 2019). Five items were used to measure involvement capabilities (7-point Likert scale ranging from 1 = strongly disagree to 7 = strongly agree). The items measured how service firms allowed customers to direct the interactions, encouraging customers to participate in service delivery, codesign and coproduction. The items also measured how customer insights were gathered, incentivizing the customer participation and invitation of prospective customers.

The study conceptualized and measured competition based on the works of Jaworski and Kohli (1993). The study assessed competition by the level of interfirm rivalry within the industry, promotional wars, competitive moves and matching competitive offers on a 7-point Likert scale. Measures for customer demand were adapted from (Anning-Dorson, 2017) to assess the current level of demand from customers, their penchant for new products, price sensitivity and customers’ product preference due to time change. Four items were used to measure customer demand, also on a 7-point Likert-scale.

To partial out the effect of certain firm-level and specific sector characteristics, the study controlled for such characteristics. The study controlled for firm size (log of the total number of full-time employees), type of service (industry effect), firm age (log of the number of years) and the number of owners as having a potential impact on the performance of financial service firms. The importance of the industry in which a firm competes as a predictor of firm-level variables is widely recognized in the literature (Dess et al., 1990). The study also controlled for the number of owners.

Assessment of measures and measurement model

To test the hypothesized relationships among the constructs, the study followed the commonly established two-stage procedure of structural equation modeling (SEM) (Anderson and Gerbing, 1988), using Amos 21 and maximum likelihood estimation procedure. SEM allows the paper to simultaneously examine the different relationships without intercorrelation (El Nemar et al., 2022). In the first step, a confirmatory factor analysis (CFA) was conducted on both samples to assess the validity of the measurement model and the discriminant validity of individual constructs. The second stage used SEM to test the stated hypotheses. The two samples showed acceptable model fits. The model fit indices for Ghana were as follows: χ²/(d.f.) = 902.122 (512), root-mean-square error of approximation (RMSEA) = 0.058, nonnormed fit index (NNFI) = 0.948, comparative fit index (CFI) = 0.966 and standard root-mean-square residual (SRMR) = 0.039; those of India were: χ²/(d.f.) = 814.221 (492), RMSEA = 0.052, NNFI = 0.951, CFI = 0.972 and SRMR = 0.032. Both samples met the thresholds of all the indices (Schreiber et al., 2006).

A test of equivalence for the measures was necessary since two countries/cultures were involved. This step was taken to ensure that respondents of the two countries ascribed the same meanings to the scale items. Measurement invariance tests have become essential for cross-cultural/country analysis (Steenkamp and Baumgartner, 2000). The study, therefore, followed best practices to prove that the measurement of the constructs across the two samples were equally reliable (Runyan et al., 2012). The multigroup CFA analysis indicated that configural, metric, scalar, factor variance and error variance invariances existed, which means that the absence of cross-cultural differences in the scales shows that there are no biases in the way managers from Ghana and India responded to the scales.

The study assessed reliability, convergent validity and discriminant validity on both samples. The study assessed the reliability of individual items by inspecting their internal consistency values and the loadings of the items on their respective constructs (Fornell and Larcker, 1981; Lu et al., 2010). The positive and significant loadings confirm convergent validity of the measures. Table 1 shows that composite reliability (CR) and discriminant validity of the variables are acceptable, with indices exceeding a minimum cutoff point of 0.60 and 0.05, respectively (Bagozzi and Yi, 2012). The measures also indicated satisfactory discriminant validity by showing a larger average variance extracted (AVE) for all constructs being over and above the interconstruct squared correlations (Hair et al., 1998). The study, therefore, concluded that each of its constructs was unique and captured phenomena that other measures did not. Table 2 shows the correlations of the variables across the samples.

Common method bias

Aside the procedural measure, the study statistically tested for common method bias on two fronts. A Lindell and Whitney’s (2001) test was first conducted through the marker variable approach before a Harman one-factor test. The results showed that the correlation between the marker variable item and the dependent variable was not significant (r = 0.0083; p > 0.10). The study also showed low nonsignificant correlations between the marker variable item and other constructs, ranging between 0.008 and 0.047 and indicating that CMV effects do not substantially account for the relationships between the constructs studied. Subsequently, a Harman’s one-factor test in CFA returned a poor model fit for both the India and Ghana samples. Single factor analysis – as per Herman through EFA – also showed that no single factor explained more than 25% of the variance extracted.

Results

To assess the hypotheses, the study created quadratic and multiplicative indicants, as suggested by the literature (Ping, 1995). Initially, the study computed the quadratic term for involvement capability (IC) by squaring its scores. Second, the multiplicative terms of IC-squared × customer demand and IC-squared × competition were also created. Finally, the study followed the recommended procedures by Aiken et al. (1991) and created other lower-order interactions in conjunction with the direct effects, firm size, age, service type, foreignness, number of owners and public/private as control. The study orthogonalized all variables that were involved in multiplicative and quadratic interactions. The mean-centered helped reduce the potential of multicollinearity problems arising from the introduction of multiplicative and quadratic terms in the structural model.

Two nested models were estimated to check for the superiority of the hypothesized model. A restricted model was estimated in which only main effects paths were estimated. Using the chi-squared comparison approach, the unrestricted structural model produced superior fit indices [χ²(18) = 31.099; NFI = 0.98; Tucker–Lewis index (TLI) = 0.96; incremental fit index (IFI) = 0.98; CFI = 0.98; RMSEA = 0.057; SRMR = 0.038] to the restricted model [χ²(14) = 38.672; NFI = 0.95; TLI = 0.92; IFI = 0.94; CFI = 0.94; RMSEA = 0.076; SRMR = 0.059]. The R² for the restricted model recorded 28% while that of the unrestricted model was 39%.

The details of the path estimates and their respective t-values are shown in Table 3. The assessment of the quadratic relationship between involvement capability and competitiveness showed significant relationships in both contexts. A χ² difference test via path-constraint approach using critical ratios showed that the relationship in H1 differs from country to country. In H2 and H3, similar findings were obtained, as shown in Table 3 in path coefficients with a significant difference between the two countries confirming both hypotheses.

To fully appreciate the nature of the moderated relationships, quadratic two-way interaction graphs were plotted for each moderator and sample in Figures 1 to 5. Both Figures 2 and 3 show a quadratic shape for high customer demand periods, whereas in low demand periods in both Ghana and India, a linear relationship is observed. These findings suggest that service firms will benefit substantially in a low demand environment by increasing their involvement capability deployment and investments. However, in high demand periods, increasing customer involvement shows an inverted U-shape, which suggests that increasing involvement beyond the intermediate point will yield a decreasing return on investment into involvement capability for the firm. Competitive intensity shows similar traits in Figures 4 and 5. The graphs show that, in both contexts, highly competitive intensity exhibits a quadratic relationship between involvement capability and firm competitiveness.

Discussion

This study answers the question, does capability always increase firm competitiveness? To adequately answer the above question, three subquestions were formulated. First, at what level (low, mid or high) of customer involvement would a firm enjoy an optimal level of competitiveness? Second, what levels (low, mid or high) of market conditions in the form of customer demand and competitive intensity will involvement capability enhance firm competitiveness? The last question sought to assess if the answers to questions one and two will differ in different economic contexts/markets.

The findings show that the relationship between involvement capability and competitiveness is inverted U-shaped such that the relationship is optimal at the intermediate level of investment into customer involvement capability building. This finding brings clarity to the real effect of customer involvement on firm performance, which has seen mixed results from different studies (Sharma et al., 2014). The explanation is that involvement capability can bring both positive and negative returns if the optimal level is not ascertained by the firm. This finding confirms other studies, such as that of Storey and Larbig (2018), who, in studying involvement at the customer level, found that increasing customer involvement can increase complexity, which will have a negative impact on the outcome. This finding is in line with Chan et al.’s (2010) idea that going beyond the optimal level of involvement will bring about efficiency problems that will, in turn, detract from competitiveness.

The study addressed question two by examining the moderating effect of market factors – customer demand and competitor intensity. This study found that involvement capability showed a more stable impact – an increasingly positive impact – on firm competitiveness in low levels of market conditions – customer demand and competitive intensity. However, in high periods of these market conditions, the returns rise to a point, and then start decreasing. The findings provide empirical support for Sharma et al.’s (2014) assertion that involvement may bring about operational inefficiencies and may be counterproductive. This study empirically showed the periods of conditions in which operational inefficiencies may occur – in terms of increasing demand and competitive intensity. Again, as espoused by Schilke (2014), the efficacy of a dynamic capability such as involvement capability has been put to test to identify how firms can adequately benefit from them. Indeed, the market conditions, as explained by Lane and Maxfield (1996), redraft the relationship between involvement capability and the benefit it offers. Although Chan et al. (2010) and Hsieh and Yen (2005) hinted at a potential curvilinear effect of involvement capability, the current study has empirically and robustly shown the effect using data from two emerging market contexts. The study has shown the level at which involvement may necessitate shifting power disproportionately to customers (Kelley et al., 1990) and signals the level at which firms can optimize their involvement to create value for both customer and firm.

The findings suggest that although market conditions may put pressure on firms to adopt new measures, such as increasing involvement, the current study clarifies what the firm’s action should be responding to market pressures, as an increase in involvement capability has some negative repercussions. The current study offers that firms should increase involvement in low demand and competitive periods, to benefit more from their involvement capability. The possible reasons are that, in such periods, the service firm can use its involvement capability to exploit other capabilities, such as innovation capabilities (Ordanini and Parasuraman, 2011), without time and competitive pressures. Attempting more involve in high levels of market condition does not offer a lot for a firm. Firms enjoy more from involvement capability at the intermediate levels than at low or high levels. The findings, therefore, suggest that firms decrease their involvements in both high demand and competitive periods but increase at moderate and in low periods if they want to enjoy the maximum benefits.

Implications and conclusion

Theoretical and practical implications

This study carries significant theoretical implications for the literature on capability building and SME resource management. First, the findings challenge the conventional belief that capabilities always lead to firm rent. Contrary to the linear relationship posited by capability theory between capability building, competitiveness and firm performance, this study reveals that the positive impact of capability exploitation on performance is not straightforward for SMEs. Instead, there exists an optimal point at which a positive effect is achieved. This highlights the presence of boundary conditions for SMEs concerning customer involvement capability and competitiveness.

Second, the relationship between capability and competitiveness is context-dependent, with marketing conditions playing a crucial role in determining the extent of the positive effect. The study identifies market conditions, such as market demand and competitive intensity, as explanatory factors for the returns SMEs can attain from their capability investments. By doing so, this paper presents a novel, integrative perspective on the connection between capability development, market dynamics and SME competitiveness, demonstrating an inverted U-shaped moderating effect that links involvement capabilities and competitiveness to market conditions.

Furthermore, this research fills a notable gap by exploring customer involvement within SME service firms, which has previously received insufficient attention (Anning-Dorson, 2021; Sharma et al., 2014). By doing so, it provides a research path and theoretical lens for the study of SME involvement capabilities. Moreover, the empirical findings shed light on the quadratic effect of service firm capabilities, a subject that has received limited attention in the SME service literature. The paper emphasizes the rationale behind the nonlinearity effect of service firm capability development, thus guiding future studies in this area. The study contributes to the understanding of how SME service firms can optimize customer involvement capabilities within the complex ecosystem of service, thereby enhancing performance.

Practically, considering SMEs' resource constraints, this study offers a pathway for capability development and exploitation. Although customer involvement may present a competitive advantage for SME service firms, it is crucial to monitor the returns on investment in customer involvement. As evidenced in this study, exceeding the optimal level of involvement may lead to inefficiencies in SME operations, increasing the cost of service production and delivery. Moreover, the deployment of customer involvement capability must align with market conditions, such as the level of market demand and competitive intensity. Although value cocreation is central to service delivery, effectively deploying the customer as a resource is critical to SME profitability. Therefore, SME managers should continuously measure, monitor and manage the returns on each capability development and exploitation, especially when market-based resources, such as the customer, drive such development.

Conclusions

In conclusion, this study reveals that customer involvement does not always lead to increased SME competitiveness, indicating that capabilities do not always guarantee rent for SMEs. The research demonstrates that there exists an optimal level at which SMEs can enhance their competitiveness through involvement capability. Over the long run, the relationship between involvement capability and SME competitiveness takes an inverted U-shaped form. It is essential for SME managers to identify the level at which their enterprises can derive the most benefit from involving customers in the value creation and delivery process.

Furthermore, two market conditions, namely, customer demand and competitive intensity, play a significant role in determining the level at which involvement capability generates the highest returns for SMEs. During periods of low customer demand and intense competition, SME service firms can continuously increase their involvement capability, as the relationship with competitiveness is linear and positive. However, in periods of high customer demand and competition, the relationship becomes inverted U-shaped, indicating that SME managers must adjust their strategies to find the optimal level of involvement.

It is crucial for SME managers to thoroughly understand the prevailing market conditions before deploying involvement capability. In low market conditions, such as low customer demand and intense competition, increasing involvement can yield high levels of firm benefits. Conversely, in high-demand and competitive environments, the strategy should shift to find the optimal level of involvement. Thus, involvement should be aligned with firm-level operations, customer demand and competitive intensity to optimize firm returns on customer involvement capability.

For future research, testing the study's model in different contexts and comparing potential differences in developed, emerging and developing economies would be valuable. Additionally, investigating different market conditions and their impact on customer involvement capability could provide further insights. Lastly, exploring other SME capabilities and testing their quadratic effect on performance would offer valuable guidance on SME resource utilization. By delving deeper into these areas, researchers can continue to enrich the understanding of SME competitiveness and resource management.

Figures

Figure 1.

Conceptual framework

Figure 2.

Ghana sample: customer demand as a moderator

Figure 3.

India sample: customer demand as a moderator

Figure 4.

Ghana sample: competitor intensity as a moderator

Figure 5.

India sample: competitor intensity as a moderator

Table 1.

Model measurement

Constructs/Measurement items	Loadings
	Ghana	India
Involvement capability Ghana: CR = 0.92, AVE = 0.80 | India: CR = 0.93, AVE = 0.73
We allow customers to direct the interaction during service delivery at all times	0.824	0.864
We always encourage our customers to help us in the production of the quality service	0.863	0.893
Our customers generally codesign and coproduce most of our products	0.833	0.865
We continuously encourage our customers to persuade prospective customers to experience our products/services	0.842	0.814
We frequently provide incentives to foster participation of customers in new product/service development	0.796	0.846
Customer demand Ghana: CR = 0.87, AVE = 0.63 | India: CR = 0.89, AVE = 0.67
Our customers tend to look for new products all the time	0.721	0.768
Sometimes our customers are very price sensitive	0.822	0.856
New customers tend to have product-related needs that are different from those of our existing customers	0.779	0.812
In our kind of business, customers’ product preferences change quite a bit over time	0.856	0.841
Competition Ghana: CR = 0.89, AVE = 0.68 | India: CR = 0.90, AVE = 0.72
One hears of a new competitive move almost every day	0.835	0.882
Anything that one competitor can offer others can match readily	0.798	0.834
There are many promotion wars in our industry	0.845	0.873
Competition in our industry is cutthroat	0.812	0.791
Competitiveness
Competitive advantage Ghana: CR = 0.96, AVE = 0.75 | India: CR = 0.97, AVE = 0.75
Competitive pricing	0.855	0.864
Service quality	0.871	0.892
Speed of reaction to customer needs	0.889	0.891
Company/brand image	0.801	0.832
Personal selling	0.902	0.893
Product range offered	0.913	0.923
Distribution coverage	0.789	0.814
Marketing research	0.820	0.834
Product performance	0.882	0.863
Cost advantage	0.898	0.911
After sales service	0.823	0.843
Marketing Communication	0.811	0.804
Adaptability Ghana: CR = 0.96, AVE = 0.72 | India: CR = 0.97, AVE = 0.75
Stronger emphasis on profit margin	0.922	0.910
Frequent price adjustments	0.856	0.868
Extra service to justify higher prices	0.809	0.821
Increased sales volume	0.909	0.894
Carry marginally profitable products to satisfy consumers	0.833	0.872
Capitalize on new markets	0.798	0.772
Reduce product line	0.906	0.894
Introduce new products	0.898	0.907
Increase R&D	0.904	0.882
Increase promotion	0.722	0.820
Broaden sales force responsibility	0.829	0.830
Re-examine distribution channels	0.838	0.854
Firm performance
Financial performance Ghana: CR = 0.93, AVE = 0.82 | India: CR = 0.94, AVE = 0.83
Better profit	0.911	0.927
Better return on investment	0.932	0.909
Better cash flow	0.876	0.901
Market performance Ghana: CR = 0.90, AVE = 0.82 | India: CR = 0.92, AVE = 0.85
Better sales volume	0.889	0.915
Better market share	0.918	0.929
Nonfinancial performance Ghana: CR = 0.90, AVE = 0.75 | India: CR = 0.91, AVE = 0.77
Service quality	0.843	0.866
Customer satisfaction	0.855	0.891
Employee satisfaction	0.899	0.882

Note:

All loadings were significant at 0.001 (two-tailed)

Source: Author’s own work

Table 2.

Variable correlation across the Ghana and India samples

Constructs	1	2	3	4	5	6	7	8	9	10	11	12
1. Size	1	−0.045	−0.359**	−0.087	−0.139	−0.031	0.261**	−0.101	0.103	0.074	−0.261**	0.238**
2. Age	0.327**	1	0.140	0.030	−0.022	0.079	−0.162	0.202**	0.062	0.064	0.129	0.048
3. Service type	0.052	0.059	1	0.007	0.303**	0.239**	0.139	0.162*	−0.010	0.137	0.089	0.037
4. Involvement capability	0.256**	0.086	0.151*	1	0.143	0.106	0.312**	0.312**	0.280**	0.009	0.196**	0.273**
5. Customer demand	0.289**	0.005	0.084	0.278**	1	0.346**	0.292**	0.325**	0.198**	0.122	0.036	0.140
6. Competitor intensity	0.096	0.135	−0.092	0.129	0.251**	1	0.332**	0.293**	0.147	0.288**	0.179*	0.331**
7. Competitiveness	0.310**	−0.090	0.273**	0.305**	0.328**	0.041	1	0.735**	0.774**	0.581**	0.426**	0.445**
8. Competitive advantage	0.301**	0.061	0.307**	0.322**	0.273**	0.043	0.894**	1	0.523**	0.075	0.171*	0.193**
9. Adaptation	0.256**	0.031	0.273**	0.298**	0.409**	0.031	0.917**	0.797**	1	0.122	0.187*	0.238**
10. Financial Performance	0.254**	0.113	0.250**	0.280**	0.346**	−0.022	0.860**	0.714**	0.722**	1	0.536**	0.517**
11. Non-Financial Performance	0.215**	−0.008	0.245**	0.275**	0.317**	−0.081	0.828**	0.732**	0.769**	0.819**	1	0.515**
12. Market Performance	0.217**	0.057	0.277**	0.368**	0.249**	0.081	0.606**	0.641**	0.516**	0.593**	0.599**	1

Notes:

Correlations for the Ghana sample appear in the lower-left half of the matrix. Correlation is significant at the 0.01** and 0.05* level (two-tailed)

Source: Author’s own work

Table 3.

Results on hypotheses testing: dependent variable = competitiveness

H	Independent variable	Path coefficients (Ghana)	t-values (Ghana)	Path coefficients (India)	t-values (India)
	Hypothesized effects
H1	IC Squared – H1	−0.16	3.21	−0.20	4.05
H2	IC Squared*CD – H2	−0.14	2.17	−0.16	2.98
H3	IC Squared*CT – H3	−0.17	3.39	−0.15	2.69
	Nonhypothesized effects
	Competition (CT)	0.02	0.54	0.04	0.91
	Customer Demand (CD)	0.25	5.86	0.33	7.22
	Involvement capability (IC)	0.35	7.93	0.16	4.81
	IC*CD	−0.05	−1.30	−0.09	−2.01
	IC*CT	0.12	2.22	0.02	0.36
	Controls
	Size	0.11	2.77	0.13	1.79
	Age	−0.04	0.74	−0.09	1.99
	Service Industry (type)	0.08	4.72	0.19	5.02

Source: Author’s own work