Abstract
Purpose
The purpose of this paper is to investigate the impact of customer-focus on small medium enterprise (SME) performance from the perspective of a resource-based view (RBV).
Design/methodology/approach
This research study implemented a survey strategy to gather data from 255 respondents on the registered list of Ghana Enterprise Agency (GEA) in the eastern region of Ghana. Scales used to gather data were operationalized from previous research studies. A structural equation modeling (SEM) path analysis was used to estimate the impact of customer-focus on the performance of SMEs.
Findings
The outcomes of this study indicate that customer-focus has a significant positive impact on SME performance, hence backing the current demand for investigating the distinct influence of customer-focus on SME performance. The results show that customer-focus has a positive and significant relationship with financial performance, customer performance, internal business process performance and learning and growth performance, thus supporting the literature on the positive impact of customer-focus on SME performance. Therefore, customer-focus determinants used in this study, including co-creation, networking ties, customer insight and artificial intelligence marketing (AIM), are critical to the optimization of SME performance.
Research limitations/implications
Notwithstanding the importance of this research study mentioned earlier, the study has limitations. Notably, the sample size of this study can be increased to capture SME respondents in other geographical zones that were not included in this study. Future research studies may address how business environment conditions moderate the relationship between customer focus and performance, and also the cause-effect of the relationship between customer focus and business environment conditions on SME performance.
Practical implications
The practical implications consist of two main items. First, this study empowers SME owners and managers to develop a customer focus technique as a central strategic goal in their quest for SME performance optimization. Second, SME owners and managers should progressively exploit the four determinants of customer focus which include co-creation, networking ties, customer insight and (AIM in order to accrue important resources for effective utilization of their customer focus competences as a way to enhance their performance.
Social implications
This study is targeted at the sound development of SMEs to bring about poverty alleviation and employment. Poverty, unemployment and poor living standards are recognized as vital social challenges in most emerging economies. The establishment of customer focus as an important strategic capability provides opportunities for SME survival, profitability and growth.
Originality/value
Generally, the findings of this research study provide a strong backing to RBV perspective and the proposition that customer-focus and its determinants (i.e. co-creation, networking ties, customer insight and AIM) should be acknowledged as a vital strategic resource for optimizing the performance of SMEs. This research study also provides new knowledge contribution to the present body of knowledge on customer-focus orientation and management literature, particularly in the context of an emerging economy.
Keywords
Citation
Abrokwah-Larbi, K. (2024), "The impact of customer-focus on the performance of business organizations: evidence from SMEs in an emerging West African economy", African Journal of Economic and Management Studies, Vol. 15 No. 1, pp. 31-59. https://doi.org/10.1108/AJEMS-04-2022-0167
Publisher
:Emerald Publishing Limited
Copyright © 2023, Kwabena Abrokwah-Larbi
License
Published by Emerald Publishing Limited. This article is published under the Creative Commons Attribution (CC BY 4.0) licence. Anyone may reproduce, distribute, translate and create derivative works of this article (for both commercial and non-commercial purposes), subject to full attribution to the original publication and authors. The full terms of this licence may be seen at http://creativecommons.org/licences/by/4.0/legalcode
1. Introduction
The recurrent change in the business environment has made it imperative for small medium enterprises (SMEs) to adopt feasible strategies that may bring about their responsiveness and sensitivity to the changing needs of customers. To focus on customers, SMEs need to adopt customer-focus strategy as a strategic choice due to the distinct association that is present between SMEs and their customers (Domi et al., 2020). Customer-focus was created by Deshpandé et al. (1993) as “the set of beliefs that put the customers' interest first, while not excluding those of all other stakeholders including owners, managers, and employees, in orders to create a long-term profitable enterprise.” This definition has been extensively applied in several literature related to marketing and entrepreneurship (Madhani, 2020). On the other hand, Bartley et al. (2007) defined customer-focus as “organizations' concerns with customers' needs, wants, and expectations (i.e. past, present and future); their strong commitment to understand and satisfy them in a proactive manner for long-term growth”. The ultimate aim of customer-focus is the actualization of customer expectation (Han et al., 2021). Customer-focus has been recognized as an important catalyst of business organization performance (Kumar and Reinartz, 2018) and a primary emphasis for any business organization's relationship to its target market (Li et al., 2021). Yet, past research swork such as Pekovic and Rolland (2016) have ever more interrogated the universal acceptance of the positive effect of customer-focus on business organization performance as a result of varied outcomes from different studies. For instance, research studies such as Han et al. (2021) and Setiyaji et al. (2022) have established a positive relationship between customer-focus and business organization performance, while other studies including Husain et al. (2022) and Manishimwe et al. (2022) have established a significant negative relationship between customer-focus and business organization performance. As a result, there has been several recommendations from researchers emphasizing the need to conduct further studies to understand the type or nature of relationship between customer-focus and firm performance in diverse backgrounds (Abrokwah-Larbi, 2020).
Previous studies (Neneh, 2016; Madhani, 2020) continuously contend that the optimal performance outcome of customer-focus can be achieved through a blend of strategic factors. Consequently, Neneh (2018) emphasizes that achieving a competitive edge and improving firm performance does not depend on a single factor, but rather depend on the associations among numerous factors. However, there is little research work on the strategic factors that business organizations can take into consideration when adopting a customer-focus oriented perspective, since existing research work such as Nwokah and Maclayton (2006), Frambach et al. (2016) and Husain et al. (2022) have predominantly concentrated on the relationship between customer-focus and other factors such as new product development, innovation, expansion, competitor orientation and technological orientation. Additionally, customer-focus in general has rarely been assessed from a resource-based view (RBV) perspective until now.
SMEs are mostly limited by lack of resources, and, in several cases, this has hindered their ability to exploit growth opportunities (Donkor et al., 2018). Consequently, customer-focused business organization can still fail to benefit from opportunities originating from customer requirements if they continue to be constrained by resources (i.e. co-creation, network ties, customer insights or knowledge and artificial intelligence marketing (AIM)) to capitalize on such opportunities. This is attributable to the reason that actual customer-focus application and optimization requires resource availability; therefore, its overall positive effect on business organization performance might lessen if the required resources are not available (Al-Gasawneh et al., 2021). In this instance, customer-focus oriented business organizations could profit from resource availability, and in the case of an SME organization this is mostly gotten through determinants including co-creation (Neneh, 2018), customer insight (Hamidi et al., 2020), customer value (Madhani, 2020) and artificial intelligence application (Yau et al., 2021). Even though customer-focus has been empirically verified as an element in many marketing-related studies, most of these empirical studies examined customer-focus in combination with other elements as a domain of customer orientation. As a result, these previous studies failed to consider elements which are specifically pertinent to customer-focus. Furthermore, despite the fact that previous studies have established a positive effect of customer-focus on performance (Islam and Zhe, 2022), most were unsuccessful in recounting the nature of the effect. Furthermore, customer-focus operationalization needs substantial amount of financial support; yet, the outcome of customer-focus has predominantly been in the longer term (Santos et al., 2020). The attention on customer-focus strategy and its expected long-term outcome generates pressure for SME managers/owners who are supposed to meet their short- and medium-term financial performance goals. Recent empirical studies such as Nicolas (2022) and Kurznack et al. (2021) establish that short-term financial metrics such as budget has restricted SME owners/managers from implementing long-term development strategies, such as customer-focus. Therefore, it has become necessary for this current research study to provide empirical evidence of the impact of customer-focus on broader range of performance metrics such as financial and nonfinancial metrics. This current research study, therefore, adopted the balance scorecard as a performance measure because it has broader range of performance measures including financial measures (i.e. financial perspective) and nonfinancial measures (i.e. customer perspective, internal business process perspective and learning and growth perspective) (Kaplan and Norton, 2009).
Based on the preceding discussions, the main objective of this study is to investigate the impact of customer-focus on the performance of SMEs from the perspective of RBV. This will contribute to contemporary knowledge in finding new frontier conditions under which customer-focus can benefit SMEs. Furthermore, this current study contributes to the existing discussion on the direct relationship of customer-focus and business organization performance, particularly by providing evidence from the context of an emerging economy. Lastly, this study has practical implications for SMEs as in how diverse customer-focused variables such as co-creation, customer insight, customer value and AIM can be valuable in getting the most out of opportunities documented from SMEs' customer-focused strategies.
2. Literature review
2.1 Theoretical background
The RBV perspective maintains that business organizations can advance their competitiveness, for example concerning cost, quality or additional elements for distinction, provided they obtain and optimize resources and capabilities considered as valuable, rare, inimitable and non-replaceable (Barney, 2001; Estensoro et al., 2022). The purpose of RBV is to provide insight into the association between dissimilar resources and the extent to which these resources can be integrated to sustain the performance and competitiveness of business organizations (Nayak et al., 2022). Hence, the current research study considers RBV as an appropriate theoretical approach to explore the application levels of customer-focus in SMEs and how dissimilar resources of customer-focus, for example, with regard to co-creation, network ties, customer insights and AIM, interact to achieve competitive advantage and performance of business organizations. According to Hagen et al. (2022), the main idea of the RBV is that the competitive advantage of a business organization is contingent on its ability to obtain, control and configure resources. Business organization resources such as co-creation capability, networking ties, customer insight capability and AIM are considered as critical organizational assets that shape marketing strategies like customer-focus (Setiyaji et al., 2022). The RBV approach depicts a business organization as a collection of particular resources and capabilities that can be utilized to obtain competitive superiority through strategy implementation (Donnellan and Rutledge, 2019). Past studies have established that the success rate for strategy implementation such as customer-focus is just about 10% to 30% (Cândido and Santos, 2019; Gebczynska, 2016). This is rather minimal bearing in mind the measure of resources and financial spending business organizations place into developing strategies such as customer-focus (Estensoro et al., 2022). Therefore, it appears reasonable that the internal configuration of resource (e.g. co-creation, network ties, customer insights and knowledge, and AIM) and strategies (e.g. customer-focus) should be harmonized for fruitful implementation, giving credence to the application of RBV as an approach to establish how business organization resources would most appropriately be aligned with strategies. Hence, it is imperative for business organizations such as SMEs to adopt an approach that enables them to recognize disparities between expected performance and attained performance. One such approach is the RBV, which stresses that the distinctive configuration of resources and capabilities (i.e. co-creation, network ties, customer insight or knowledge, and AIM) is the underpinning for the business organization's strategy (i.e. customer-focus) and its ability to achieve more than average performance (Donnellan and Rutledge, 2019).
Customer-focus is recognized as an internal resource of a business organization which has the ability to improve its competitive superiority (Husain et al., 2022). Previous studies (Flight and Mudiyanselage, 2021; Kang et al., 2021; Kaburu et al., 2021) even consider customer-focus more superior than the external resources of business organization when it comes to the generation of competitive advantage and performance. According to Santos et al. (2020), this may be related to the ripple effect that originates from obtaining customer-focus advantage, which enables the development of competitive superiority, for example, cost, context-based product/service functionality, pricing and other extra and auxiliary service value. Customer-focus advantage is unique to business organizations and integrates resources such as co-creation, network ties, customer insight or knowledge, and AIM in order to support enterprise strategy and objectives (Donnellan and Rutledge, 2019). From a RBV perspective, enterprise performance and competitive superiority can originate from positioning customer-focus when it signifies an intricate enterprise strategy that is both diverse and secure (Fakhreddin and Foroudi, 2022). The process of adjusting co-creation, network ties, customer insight or knowledge, and AIM to customer-focus strategy is a capability that influences a business organizations performance and competitive advantage (Husain et al., 2022). However, it should be noted that customer-focus capability can also be found in other business organizations and as such does not completely deliver a business organization's competitive advantage and performance (Zaman et al., 2022). The competitive advantage and performance happen when customer-focus is adopted to capitalize on business organization's resources (i.e. co-creation, network ties, customer insight or knowledge, and AIM) in a way considered unique (Setiyaji et al., 2022).
However, Osakwe et al. (2022) contend that RBV perspective have a notable limitation, in that “rare” resources may possibly not certainly bring about a competitive superiority or performance for the business organization. For example, a business organization resource that brings about financial performance irrespective of its rarity, may not realize a competitive advantage or performance. That is to say, even though customer-focus may be perceived as critical to the operation of a business organization, it does not mean that the resources (i.e. o-creation, network ties, customer insight or knowledge, and AIM) of this business organization are automatically converted into competitive superiority or performance, notwithstanding the fact that business organizations are confronted by competitors who pursue strategies that differ from theirs (Nayak et al., 2022).
2.2 Customer-focus
Customer-focus involves addressing the needs and anticipations of current and potential customers by developing a wide-ranging insight of customer needs and then conveying recognized value to customers (Islamgaleyev et al., 2020). Business organizations such as SMEs can implement customer-focus as a strategic orientation that identifies their capability to develop and convey improved customer value through the processing of market insight (Aziz et al., 2021). The anticipated results of a customer-focus strategy consist of the creation of value for the customer which brings about customer loyalty and business organization performance (Madhani, 2020). Extant literature shows that customer-focused strategy inspires customer interaction actions which lead to uniqueness and value in customer experience (Madrakhimova, 2021). The actual manifestation of customer-focus strategy is contingent on the entrenchment of customer-focus as a culture throughout the business organization (Lee and Lee, 2020). Customer-focus culture and practices ensures the enhancement of business organization's overall performance (i.e. customer satisfaction, sales, market share, profitability) and development of competitive advantage.
The concept of customer-focus has received attention in extant literature, and its effect has been extensively explored (Flight and Mudiyanselage, 2021; van Assen, 2021; Marta et al., 2021; Santos et al., 2020). Despite the numerous contributions in recent years, the argument about customer-focus has fundamentally been led by propositions made by Narver and Slater (1990), Deshpandé et al. (1993) and Bartley et al. (2007). Both propositions have notable influence on the structures and performance of business organizations and originate from related principle such as customer centricity, market orientation, incorporating cross-functional activities and response to market changes. In this study, Narver and Slater (1990) view customer-focus (or market orientation) as unidimensional construct comprising of three behavioral elements (i.e. customer orientation, competitor orientation and inter-functional coordination) and two decision criteria (i.e. a long-term focus and a profit objective). Even though Narver and Slater (1990) established a substantial positive effect of customer-focus (or market orientation) on profitability, their measures used to define customer-focus (market orientation) did not capture elements that support strong collaboration with and among customers and inter-enterprise learning through network ties. Similarly, performance measures adopted were limited to financial performance measure (i.e. profitability) in preference to a blend of both financial and nonfinancial performance measures. Conversely, the study by Deshpandé et al. (1993) show that customer's evaluation of the supplier's customer-focus correlates with business performance; however, supplier's own evaluation of customer-focus did not agree well to that of the customer, therefore failing to correlate with business performance. This finding seems to provide a perspective that suggests that customer-focus will generate business performance only when customers evaluate the customer-focus orientation of suppliers. Bartley et al. (2007), on the other hand, provide practical insights into how business organizations can become more customer-focused using a framework that evaluates customer-focus culture and a business organization's level of customer-focus. However, their customer-focus measures are mainly centered on elements such as relationship management, customer service KPIs, forecast, induction and training strategies, customer surveys and understanding of customer information. As pointed out by Babu (2018), the concept of customer-focus has been approached in a disaggregated way founded on the perspective that customer-focus basically comprises of intelligence generation and dissemination associated to customers who are considered main players in the market place. A customer-focus oriented business organization places emphasis on customer's current and future needs and has also progressed in its capabilities with respect to co-creation with customers, customer insights, network ties with customers and other enterprises and using machine learning-enabled artificial intelligence (AI) to accurately analyze huge customer data sets to identify context-oriented customer-focus approach (Yau et al., 2021; Madhani et al., 2020; Hamidi et al., 2020; Neneh, 2018).
Therefore, business organizations with high customer-focus orientation invest significant effort in preparing for its customers by developing appropriate customer-focus factors which are co-creation (Hamidi et al., 2020), networking (Neneh, 2018), customer insight (Madhani, 2020) and AIM (Yau et al., 2021).
2.2.1 Co-creation
Co-creation involves processes and procedures by which business organizations collaborate with consumers to develop products or services to attain value that will be shared later (Hamidi et al., 2020). Co-creation helps to advance the customer-focus orientation of business organization through building of strong relationship with customers as both business organization and customers collaborate to develop products and services together (Benchekroun and Soulami, 2021). This brings about the development of innovative and context-oriented products and services that respond to both expressed and latent needs of customers and also build customer loyalty (Domi et al., 2020). Co-creation as an antecedent of customer-focus orientation strengthens customer participation in the creation of core products/services through innovative engagement and is also linked with the conception that “value determination resides exclusively with the customer” (Merz et al., 2018). The application of co-creation in the context of customer-focus requires business organizations such as SMEs to have the capability to collaborate with customers and, most importantly, learn from them (Galdolage, 2021; Roberts and Darler, 2017). Base on this viewpoint, customers cannot anymore be identified as obeisant actors in the marketing and product development process of business organizations. In essence, it signifies a change in reasoning and the concentration of marketing and product/service development process to “collaboration with and among” customers as opposed to “targeted to customers” (Lu et al., 2020). A key advantage of adopting co-creation technique is for business organizations to achieve reproductive knowledge and encourage organizational learning and innovation which is considered critical to customer-focus practice (Sarasvuo et al., 2022). The advent of technologies such as AI and machine learning is helping to reshape co-creation through the application of customer data analytics by machine learning and AI (Leone et al., 2021). The results of customer data analytics allow business organization to identify and prioritize co-creation needs considered by customers as important (Li et al., 2021). Consequently, this leads to the generation of new customer knowledge which help business organizations to make quality decision on their customer-focus strategies (Kulkov, 2021).
2.2.2 Networking ties
Networking ties is an important domain of customer-focus and has become a value resource to business organizations in recent times due to the increasing competitiveness in the business environment (Hasyim and Syahreza, 2021; Neneh, 2018). Networking ties are increasingly gaining prominence because they easily allow business organization such as SMEs to acquire customer knowledge, marketing capabilities, markets and technology. The acquired resource obtained through networking ties helps business organization to carefully focus their marketing efforts to customer demands (Muteshi and Kariuki, 2020). Networking ties such as managerial, business, political and social network ties define processes through which business organizations can create appropriate contextual relationships and bond with its various stakeholders including customers. For instance, business network ties consist of linked business relations that connect SMEs and customers and also permit an effective exchange of value for money (Laage-Hellman and Lind, 2021). SMEs entrenched in networking ties can improve their customer-focus innovation capability through knowledge sharing and inter-enterprise learning, thereby sustaining resilience regardless of unpredictable markets. Therefore, network ties drive customer knowledge management strategy and activities. This provides a strategic direction to a business organization's customer-focus (Lee et al., 2021). The creation of network ties involving SMEs, customers and other stakeholders (i.e. businesses, managerial, political, social space) produces an increased customer satisfaction, customer retention and repeated purchase due to deeper understanding of customer needs obtained through knowledge sharing among network actors (Kimbu et al., 2019). Determining customer latent and visible needs and developing long-term customer relationships through network ties allow SMEs to optimize the use of information and knowledge resources entrenched in customer networks (Ribeiro et al., 2021). This provides capability opportunities to business organizations such as SMEs to contextualize and improve upon their product and service innovations which greatly contributes to their customer-focus development (Neneh, 2018).
2.2.3 Customer insight
Customer insight involves the generation of information and knowledge about targeted customer segments or markets (Madhani, 2020). Customer and market information or knowledge generated from customer insight informs a business organization's customer-focus strategy (Daqau and Smoudy, 2019). Customer insights are usually obtained through data analytics so as to observe customers in different ways, in order to encourage an innovative customer-focus action to meet customer demands more effectively (Zulaikha et al., 2021). The application of customer insights in customer-focus strategy has become increasingly imperative due to reasons such as increasing complexity in consumer journey, constant emergence of novel channels of media consumption, prioritizing immediate customer need satisfaction to customer loyalty, digital transformation of traditional industries and upscaling benchmarks for personalization and digital performance (Thinkwithgoogle, 2019). Customer insight calls attention to individualized purchase behaviors and has the tendency to limit data to a particular customer segment or market (Rajkhowa and Das, 2020). This is how customer insights deliver applicable discoveries where business organizations such as SMEs can execute to enhance customer-focus performance (Einhorn and Löffler, 2021). Insights into customer attitude and opinion obtained through analyzed customer data sets provide focal areas for customer-focus strategy. For example, SMEs can gain knowledge from customer insights to help enhance their brand interaction with customers. This may generate greater customer experience and also help develop a focal area for SMEs' customer-focus strategy (Niemi-Grundström, 2021). Customer insights provide context to customer data sets which makes it possible for business organizations to draw on such context to identify customer desires, needs and motivations for quality customer-focus decisions (Madhani, 2020). This helps business organization such as SMEs to develop the ability to learn and anticipate market tendencies quicker than competition (Mandal, 2022). Hence, customer insights contribute to the enhancement of customer-focus in business organizations.
2.2.4 Artificial intelligence marketing (AIM)
AIM uses machine learning AI to analyze and interpret huge amount of data accurately and also learn from such analyzed data to identify specific focal area for a customer-focus strategy such as trends in buyer behavior (Yau et al., 2021; Kaplan and Haenlein, 2019). The application of AIM solutions to customer-focus allows SMEs to better comprehend and analyze customer data sets, thereby increasing their ability to forecast, plan and exploit impending customer-focus opportunities (Ledro et al., 2022). Customer-focus activities comprise of gathering and skillfully harnessing customer data sets to develop a sustainable means to actualize customer expectation by taking advantage of the understanding of the customer journey (Ciampi et al., 2020). A business organization's customer-focus automation is made more intelligent by AIM. AIM can be integrated with customer-focus automation to allow speedy conversion of customer data sets into decisions, worthwhile communications and positive impact on customer-focus outcomes (Loureiro et al., 2021). One of the most important aspects of AIM, aside data, is the speed and accuracy at which it can process data into implementable customer-focus insights. That is to say the means by which customer-focus tasks are carried out with speed is an essential element AIM brings to business organizations, particularly SMEs (Nalini et al., 2021). In the same vein, AIM aids SME owners and managers to filter their customer-focus strategy options which is critical to the determination of best actions and means to deploy customer-focus agenda (Khrais, 2020). AIM applies knowledge gotten from machine learning to carry out and automate customer-focus processes, such as creating customer-focus intelligence (Soni et al., 2020). This type of capability allows AIM to make evident the personalization of customers, which provides deep insight of their needs and wants (Paschen et al., 2019). The importance of AIM has made it a vital tool that is increasingly becoming an integral part of business organizations in developing customer-focus through the creation, dissemination and application of knowledge (Arsenijevic and Jovic, 2019).
2.3 SME performance
Performance measurement in business organizations such as SMEs has created a lot of interest in recent years in diverse business backgrounds in different sectors. A performance measurement system such as traditional financial metrics has been hugely criticized in recent years. Precisely, several limitations associated to classical financial performance metrics were documented in literature (Lukason and Valgenberg, 2021). These limitations were as a result of excessive focus on short-term measures such as revenue and budget without concentrating on long-term performance metrics such as customer fulfillment, business processes and employee competence, and product or service superiority (Hristov et al., 2019). Typically, the actual emphasis on short-term financial accounting metrics might not provide a satisfactory information of sound performance for business organizations (Rafiq et al., 2020). Novel performance measures are centered on nonfinancial determinants and also provide a focus on determinants such as customer satisfaction, business processes, management and employee competence, and product or service quality performance (Alves and Lourenço, 2022).
Empirical evidence from recent research outcomes suggests an increasing role of nonfinancial performance measures in the management of business enterprises (Abofaied, 2017). Therefore, financial metrics are not adequate in gauging the performance of contemporary business enterprises; however, both financial and nonfinancial performance metrics should be considered (Arjunan et al., 2020). The focus of this study is to use the balanced scorecard (BSC) which combines both financial and nonfinancial measurement to measure the performance of customer-focus strategy of SMEs. The BSC views organizational performance from four perspectives: financial, customer, internal business process and learning and growth. Financial performance metrics shows whether bottom-line development is contributed by business organization's strategy, operation and execution (Sharaf-Addin and Fazel, 2021). They show the level of wellness of a business organization's performance in terms of its profitability targets. Financial performance metrics are typically a reflection of the outcome of past managerial activities. However, an exclusive dependance on financial performance metrics such as return-on-capital-employed (ROCE), sales, revenue growth and profit margin causes the suboptimization of business organizations (Nazari-Shirkouhi et al., 2020). Customer perspectives (i.e. nonfinancial) view how well managers can recognize and target customers and market segments in which the business organization will compete (Abofaied, 2017). This perspective also involves numerous metrics (i.e. customer satisfaction, customer profitability, customer retention and customer acquisition) of effective results from a correctly developed and executed strategy. Internal business process perspective shows how well a business organization is performing based on actions that are pivotal to the meeting of financial and customer purposes. They also involve activities such as core competencies, methodologies and procedures for executing work, and essential technologies the business organization must undertake internally to fulfill its customer and market expectations (Rafiq et al., 2020). The internal business process of the organization must be contextualized to the business organization's strategy and objectives (Tibbs and Langat, 2016). Learning and growth perspective enables a business organization to detect appropriate infrastructure that they can develop in order to generate growth and improvement in the long term. Hamdy (2018) asserts that a business organization's learning and growth originate from three cardinal foundations: people, systems and organizational procedures. Business organization objectives consisting of financial, customer and internal business process objectives of the BSC will certainly expose huge gaps between current competences of people, systems and procedures and what will be needed to accomplish innovative performance (Lassoued, 2018). These gaps can be closed when business organizations focus their investments into retooling employees, improving information technology and systems and entrenching alignment between business organization's procedures and its operations (Singh and Arora, 2018).
Even though the BSC comes as a preferred performance management system compared to other performance management systems (i.e. performance pyramid, performance prism, EFQM excellence model, management by objectives and blue ocean strategy), it has been criticized for ignoring enterprise risks and environmental and sustainability factors as well as neglecting the concerns or rights of relevant stakeholders aside customers (Hristov et al., 2019). Therefore, research studies such as Askarany (2017) mention the development of a broader BSC to capture parameters such as sustainability, risk and environment factors into the four traditional perspectives of the BSC to address its limitations. Similarly, the recent study by Amer et al. (2022) encouraged researchers to concentrate on minimizing the risk of bias in BSC implementation in the future. Amer et al. (2022) further mention that enterprise managers should consider parameters such as employee satisfaction and engagement with BSC implementation.
3. Conceptual model and hypothesis development
In order to empirically examine the interrelatedness between customer-focus on financial performance, customer performance, internal business process performance and learning and growth performance, a conceptual framework is created based on RBV theory and reviewed customer-focus strategy and marketing performance literature. In this conceptualized framework, customer-focus is the independent variable, while financial performance, customer performance, internal business process performance and learning and growth performance are the dependent variables. Figure 1 shows the conceptual research framework. The following sections will discuss the hypothesized relationships between the research constructs.
3.1 Customer-focus and SME financial performance
Customer-focus is associated to the establishment of a market orientation and to the development of innovation and financial performance (Santos et al., 2020). Undoubtedly, customer-focus may be regarded as an essential strategic competence in attaining a market accomplishment. Business organizations such as SMEs require additional capability entrenched within the domains of customer-focus (i.e. co-creation, networking ties, customer insight and AIM) to advance their innovations in order to address the dynamism in the market environment (Setiyaji et al., 2022). SMEs should seek to convert customer insight and knowledge into innovative products or processes such that both expressed and latent needs of the market are met (Yulianthini et al., 2021). The innovative capability derived by SMEs as a result of customer-focus practices encapsulates the SMEs capability to generate, create and develop innovations (Santos et al., 2020). The fundamental purpose is to harness customer-focus capabilities and competence to explore market opportunity in an efficient way. SMEs' customer-focus capability can be a source of financial development and competitive advantage (Islam and Zhe, 2022). Customer-focus constructs such as co-creation, net-working ties, customer insight and artificial intelligence marketing provide SMEs with the capability to develop context-oriented innovative products, services and customer relationships (Chaudhry et al., 2019). This helps business organizations including SMEs to develop and actualize long-term financial performance, which usually manifests in high sales and profit margin (Andreou et al., 2022). Hence, it can be posited that the higher the level of customer-focus, the higher the level of financial performance. Previous empirical evidence has found a positive association between customer-focus and financial performance (e.g. Santos et al., 2020; Islam and Zhe, 2022; and Chaudhry et al., 2019). Therefore, based on the preceding discussion and empirical indication, this study posits that:
Customer-focus has a positive significant effect on financial performance in Ghana.
3.2 Customer-focus and SME customer performance
SMEs are expected to adopt a marketing technique that focuses on customers so as to maintain competitive advantage (Kaburu et al., 2021). The use of financial measures by SMEs is not only considered a short-term approach but also insufficient to encapsulate the customer perspective performance (Hristov et al., 2019). Customer-associated performance measures are therefore required to quantify customer-focus (Rafiq et al., 2020) and to distinguish customers considered valuable for customer-focus efforts (Alves and Lourenço, 2022). Customer-focus serves as an enabler for SMEs to concentrate on strategic customers who are capable of adding value and increasing profitability (Islamgaleyev et al., 2020). For SMEs to focus on fewer but profitable customers, they are required to adopt customer-associated performance measures to gauge, assess and control performance. Therefore, within the background of customer-focus, the adoption of customer-associated performance measures (such as percentage of repeat customers, ratings from customer surveys, percentage of market share, percentage growth of new and existing customers and customer lifetime value) is expected to improve competitive advantage and performance. Customer-focus practices enable SMEs to comprehend both the expressed and latent needs of their customers, and generate customer value through the sharing of customer information throughout the business organization and also allowing organized and focused activities to serve the needs of customers. In order for SMEs to be innovative they need to develop an effective interaction with customers through customer-focus factors including co-creation, network ties, customer insights and AIM (Park, 2020). For instance, the extensive application of AIM in managing customer grievances and response is an example of innovation that is associated to the practice of customer-focus (Armin et al., 2021). Such innovations associated with customer-focus impacts greatly on the customer performance of SMEs in terms of increased market share, high customer loyalty, customer delight, repeated purchase and referrals (Kang et al., 2021). The study by Kim et al. (2017) found that customer-focus derivatives such as effective processes, customer information quality and customer service quality positively influence customer satisfaction and repurchase. Hence, it can be posited that the higher the level of customer-focus, the higher the level of customer performance. Previous empirical evidence has found a positive association between customer-focus and customer performance (e.g. Flight and Mudiyanselage, 2021; Armin et al., 2021; Kaburu et al., 2021). Therefore, based on the preceding discussion and empirical indication, this study posits that:
Customer-focus has a positive significant effect on customer performance in Ghana.
3.3 Customer-focus and SME internal business process performance
Customer-focus applications and operational tools (i.e. co-creation, networking ties, customer insight and AIM) are used in the SME context to analyze, enhance and manage the enterprise and customer value stream (Widelska and Krot, 2021). Certainly, a central action in a customer-focused organization is to develop, analyze and enhance value streams, enterprise processes and methodologies to remove activities that are not contributing to value addition. Hence, activities that contribute to real value addition for the customers are maintained (van Assen, 2021). Customer-focus is therefore viewed as a process enhancement methodology used to distribute products and services more efficiently and effectively (Saleh et al., 2021). Undeniably, customer-focus is pitched toward the growth of operational and internal decision-making efficacy through restructuring and enhancing processes (Jasti and Kodali, 2015). Customer-focus pursues enhancement by process simplification, competence development, identification and removal of tasks that are not contributing to value addition, lessening of redundant internal customer-supplier associations in individual process and the lessening of unproductive process variability (Gudelj et al., 2021). Additionally, customer and market knowledge derived from machine learning AI is essential for developing marketing strategy, since it allows business organizations such as SMEs to make quality decisions concerning product standardization and adaptation in the context of international marketing (Touminen et al., 2022) Hence, it can be posited that the higher the level of customer-focus, the higher the level of internal business process performance. Previous empirical evidence has found a positive association between customer-focus and internal business process performance (e.g. Touminen et al., 2022; Gudelj et al., 2021; van Assen, 2021). Therefore, based on the preceding discussion and empirical indication, this study posits that:
Customer-focus has a positive significant effect on internal business process performance in Ghana.
3.4 Customer-focus and SME learning and growth performance
Customer-focus brings about the development and the use of core competences which usually can be identified in the form of productive resources, diversity of complex skill sets and technologies, shared learning and both implicit and denotative knowledge (Templer et al., 2020). Indeed, this contributes to the competitive advantage of SMEs through established internal business processes that result in greater management of functional activities (McColl-Kennedy et al., 2019). Customer-focus oriented core competencies provide a stage for continuous development and application of novel competences required to maintain future competitiveness, which develops through routinizing tasks and learning (Marta et al., 2021). Consequently, this impacts greatly on SMEs' knowledge expansion and core competence enrichment, which are essential catalysts for their growth. Current theoretical expansions and empirical indication have revealed that SMEs with greater customer-focus competences are better originators of information regarding customer requirements and marketing of products and services that align with customer expectations through synchronized activities such as co-creation, networking ties, customer insight and AIM (McColl-Kennedy et al., 2019). Hence, it can be posited that the higher the level of customer-focus, the higher the level of learning and growth performance. Previous empirical evidence has found a positive association between customer-focus and learning and growth performance (e.g. Templer et al., 2020; Marta et al., 2021). Therefore, based on the preceding discussion and empirical indication, this study posits that:
Customer-focus has a positive significant effect on learning and growth performance in Ghana.
4. Methods
4.1 Data collection procedure and sample
The population of this study comprises of 540 food processing SMEs registered with the Ghana Enterprise Agency (GEA) in the eastern region of Ghana with active operational background of two or more years. A sample size of 230 food processing SMEs was obtained out of SME population of 540 using the Cochran's (1977) formula. Food processing SMEs in this study were segmented into 13 subpopulation (strata) based on various food processing sectors. Stratified random sampling was then used to select food processing SMEs from each stratum according to their proportion to the sample size (i.e. palm oil processing (32 SMEs); cassava processing (30 SMEs); herbal medicine (1 SME); bakery (26 (SMEs); confectionery (6 SMEs); fish and meat processing (26 SMEs); honey processing (9 SMEs); pineapple processing (22 SMEs); mango processing (32 SMEs); papaya processing (9 SMEs); tuber (i.e. yam, cocoyam and sweet potato) processing (22 SMEs); fruit (variety) processing (6 SMEs); and beverage processing (9 SMEs)). Questionnaires were, therefore, targeted at the 230 sampled food processing SMEs. The food processing sector was used because it is the highest contributor to Ghana's economy within the manufacturing industry (GSS, 2020). This study followed an SME criterion based on a blended definition that is in line with SME definitions from the global context, Ghana Statistical Services (GSS) and the GEA. Thus, the selected SMEs had fewer than nine (9) employees and a maximum of 100 employees. A 5-point Likert scale was used in this study for answering all the scale items, extending from strongly disagree (1) to strongly agree (5). Questionnaires were administered to managers or owners of the sampled SMEs with tertiary or secondary/basic education background through a mix of electronic mail and drop-and-pick-later technique. This study also followed up on respondents through phone calls and personal visitation. The main objective of the study was expounded to respondents, and they were also guaranteed of anonymity. Altogether, the sampled size oincluded 225 out of 230 sampled respondents representing 98% returned valid questionnaires. Thus, five questionnaires were noticed to be invalid and were not added to the final analysis.
4.2 Construct measurement
The scales used in this research study were based on previous research work. Changes were made to these scales in order to adapt it to the current background and purpose of this study. “Customer-focus” measure applied six-item scale modified from Hamidi et al. (2020), Neneh (2018), Madhani (2020) and Yau et al. (2021). “Financial performance” measure applied seven-item scale; “Customer performance” measure applied seven-item scale; “Internal business process performance” measure applied nine-item scale; and “Learning and growth performance” applied nine-item scale, all adopted from Kaplan and Norton (2009).
4.3 Data analysis
This study used the SPSS version 23 for the initial coding and imputing of data obtained from the filled and validated questionnaires. The coded and imputed data were then transferred to STATA 15.1 for confirmatory factor analysis, reliability (i.e. Cronbach's alpha and composite reliability) and validity (i.e. convergent and discriminant validity) analyses. Statistical analyses such as descriptive statistics, factor analysis, reliability and validity outcomes were generated for the variables used for this research study. To enable this study to test the hypotheses on the association between customer-focus and SME performance, a linear regression model was estimated using the structural equation modeling (SEM) ath analysis method. Customer-focus (CFi) represented the independent construct, while SME performance constructs consisting of financial performance (FPi), customer performance (CPi), internal business process performance (IBPPi) and learning and growth performance (LGPi) represented the dependent constructs. Thus, the linear regression relation for the study model is represented as:
5. Results
5.1 Respondents' profile
Table 1 shows the cross-tabulated demographic description of the research respondents. The respondents in this study specified their demographic information, including age group, ownership structure, current position, enterprise size and operation and operation duration. The demographic variables (i.e. age group, ownership structure, current position, enterprise size, operation duration) used to describe respondents in this research study show that females constitute 67% (150) of respondentsm while males make up 33% (75) of respondents.
5.2 Construct reliability and validity
The examination of the reliability and validity of customer-focus and performance constructs indicates that customer-focus met the threshold for sampling adequacy using six items (i.e. CF19, CF20, CF21, CF22, CF23 and CF24; see Tables 2 and 4). The KMO (Kaiser-Meyer-Olkin) measure of sampling adequacy for the six items of customer-focus was 0.86, thus confirming the suitability of items of customer-focus. Factor loading values of customer-focus items CF19 (0.83), CF20 (0.78), CF21 (0.72), CF22 (0.70), CF23 (0.77), and CF24 (0.76) were all found to be greater than 0.50, which shows that the items of customer-focus were all suitable to be retained (Malhotra et al., 2017; see Tables 2 and 4). The Cronbach's alpha (α) for customer-focus was 0.89, which exceeds the recommended value of 0.7 (Malhotra et al., 2017). This is an indication of high internal reliability of customer-focus items. Due to Cronbach's alpha (α) sensitivity to the number of items in the scale and its propensity to underrate the internal consistency reliability, the study estimated the composite reliability (CR) of customer-focus items (Malhotra et al., 2017). The CR of customer-focus was estimated at 0.89, which exceeds the recommended value of 0.7. Table 2 indicates that the average factor loading (AFL) of the six items of customer-focus was 0.76, which exceeds the recommended value of 0.7. Similarly, the AVE of customer-focus items was 0.58, which exceeds the recommended value of 0.5. Since the AFL and AVE values of customer-focus items exceed their recommended values, convergent validity of customer-focus is established. In order to determine the discriminant validity of customer-focus, this study applied the Fornell–Lacker criterion, where the square root of each construct's AVE should have a greater value than the correlations with other latent constructs (Rönkkö and Cho, 2022). Table 2 shows that the square root of the AVE of customer-focus, which is √0.58 = 0.762, exceeds the value of its correlation matrix square of 0.00; by this means, discriminant validity of customer-focus is established.
The constructs of SME performance consisting of financial performance (seven items), customer performance (six items), internal business process performance (nine items) and learning and growth performance (nine items) all met the thresholds for sampling adequacy (see Tables 3 and 4). The KMO values of financial performance, FP (0.93), customer performance, CP (0.91), internal business process performance, IBPP (0.92) and learning and growth performance (LGP, 0.91) exceed the recommended value of 0.50, thereby confirming its suitability. The factor loading values of all items of SME performance constructs were either equal or exceeded the recommended value of 0.5, which is an indication confirming the suitability of items to be retained (see Table 3). On the other hand, Cronbach's alpha (α) of financial performance (0.90), customer performance (0.91), internal business process performance (0.91) and learning and growth performance (0.91) exceeds the recommended value of 0.70, which confirms an acceptable internal consistency of SME performance constructs. In the same vein, the composite reliability of financial performance (0.92), customer performance (0.91), internal business process performance (0.91) and learning and growth performance (0.91) exceeds the recommended value of 0.70, confirming a high reliability of SME performance constructs (see Table 3). In the same vein, the convergent validities of financial performance (AFL (0.78) > 0.50), customer performance (AFL (0.76) > 0.50), internal business process performance (AFL (0.73) > 0.5) and learning and growth performance (AFL (0.73) > 0.5) were ascertained, due to the fact that the average factor loading (AFL) of SME performance constructs exceeds the recommended value of 0.5 (Malhotra et al., 2017). Also, discriminant validities of financial performance (√AVE (√0.62 = 0.787) > correlation matrix squared (0.00)), customer performance (√AVE (√0.58 = 0.762) > correlation matrix squared (0.00)), internal business process performance (√AVE (√0.53 = 0.728) > correlation matrix squared (0.00)) and learning and growth performance (√AVE (√0.54 = 0.735) > correlation matrix squared (0.00)) were established, since the square root of AVE values of SME performance constructs exceeds their corresponding correlation matrix squared values (Rönkkö and Cho, 2022).
5.3 Regression analysis and hypotheses tests
The first hypothesis proposed in this study establishes a positive significant relationship between customer-focus and financial performance. The research hypothesis is, therefore, presented as follows: H1: customer-focus has a positive significant effect on financial performance in Ghana. The results of this study show that customer-focus has a positive and significant effect on financial performance (H1: β = 0.45, p value <0.001) (see Table 5). This research study also establishes that customer-focus significantly increases the effect of financial performance among SMEs in Ghana by 45% (i.e. β = 0.45). Therefore, customer-focus is an important strategy that influences the financial performance of SMEs in Ghana (i.e. p value <0.001). The outcome, therefore, supports H1, and as such H1 is accepted at 0.001 significant level. This study proposed the second hypothesis that customer-focus has a positive significant effect on customer performance in Ghana. The hypothesis is, therefore, presented as follows: H2: customer-focus has a positive significant effect on customer performance in Ghana. The results of this study indicate that customer-focus has a positive and significant effect on customer performance (H2: β = 0.54, p value <0.001), (see Table 5). This study establishes that customer-focus significantly increases the effect of customer performance among SMEs in Ghana by 54% (i.e. β = 0.54). Hence, customer-focus is an important strategy that influences the customer performance of SMEs in Ghana (i.e. p value <0.001). The result, therefore, supports H2, and as such H2 is accepted at 0.001 significant level. Again, this study proposed the third hypothesis that establishes a positive association between customer-focus and internal business process performance. Therefore, the hypothesis is presented as follows: H3: customer-focus has a positive significant effect on internal business process performance in Ghana. The results of this study show that customer-focus has a positive and significant effect on internal business process performance (H3: β = 0.60, p value <0.001) (see Table 5). This study establishes that customer-focus significantly increases the effect of internal business process performance among SMEs in Ghana by 60% (i.e. β = 0.60). Thus, customer-focus is an important strategy that influences the internal business process performance of SMEs in Ghana (i.e. p value <0.001). The outcome, therefore, supports H3, and as such H3 is accepted at 0.001 significant level. The study proposed the fourth hypothesis that establishes a positive relationship between customer-focus and learning and growth performance. Therefore, the hypothesis is presented as follows: H4: customer-focus has a positive significant effect on learning and growth performance in Ghana. The results of this study show that customer-focus has a positive and significant effect on learning and growth performance (H4: β = 0.63, p value <0.001) (see Table 5). This study, therefore, establishes that customer-focus significantly increases the effect of learning and growth performance among SMEs in Ghana by 63% (i.e. β = 0.63). Hence, customer-focus is an important strategy that influences the learning and growth performance of SMEs in Ghana (i.e. p value <0.001). The result, therefore, supports H4, and as such H4 is accepted at 0.001 significant level.
5.4 SEM goodness of fit analysis
The root mean squared error of approximation (RMSEA) of the structural equation modeling (SEM) statistics is 0.063, which is close to the recommended value of 0.05 (see Table 6 and Figure 2). The 90% confident interval (CI), lower bound of which is 0.057, is also close to the recommended value of 0.05. Similarly, the 90% CI, upper bound of which is 0.068, is less than the recommended value of 0.1 (Hair et al., 2019). The pclose is 0, which is less than the recommended value of 0.05. Therefore, the population error indices (i.e. RMSEA, 90% CI, lower bound, upper bound and pclose) that measured the SEM model of this study were considered good fit (see Table 6 and Figure 2). Similarly, the baseline comparison assessment indicates that the comparative fit index (CFI) is 0.894 and Tucker–Lewis index (TLI) is 0.887, which are all close to the recommended value 1 (Sarstedt and Cheah, 2019). Hence, the baseline comparison indices (i.e. CFI and TLI) that measured the SEM model of this study were considered good fit (see Figure 2 and Table 6). The size of residuals assessment also shows that the standardized root mean squared residual (SRMR) is 0.125, which is close to the recommended value of 0.00, and the coefficient of determination (CD) is 0.911, which is also close to the recommended value of 1 (Hair et al., 2019). Hence, the size of residuals indices (i.e. SRMR and CD) that measured the SEM model of this research study was considered good fit (see Table 6 and Figure 2).
6. Conclusion and discussion
The primary aim of this study is to investigate the impact of customer-focus on the financial, customer, internal business process and learning and growth performance among SMEs in Ghana.
First, the results from this study show that the relationship between customer-focus and financial performance is fully supported (see Table 7). This provides support to past studies (Islam and Zhe, 2022; Santos et al., 2020; Chaudhry et al., 2019) on the impact of customer-focus on the financial performance. In order for the SMEs to fully realize the financial benefit for customer-focus adoption, they need to harness customer-focus capabilities and competence to explore market opportunity in an efficient way. SMEs' customer-focus capability can be a source of financial development and competitive advantage. Customer-focus elements such as co-creation, net-working ties, customer insight and artificial intelligence marketing provide SMEs with the capability to develop context-oriented innovative products, services and customer relationships. This enables business organizations including SMEs to develop and actualize long-term financial performance, which usually manifests in high sales and profit margin.
Second, the findings of this research study support the relationship between customer-focus and customer performance (see Table 7). This lends support to previous studies (Flight and Mudiyanselage, 2021; Armin et al., 2021; Kaburu et al., 2021) concerning the effect of customer-focus on customer performance. Customer-focus enables SMEs to concentrate on strategic customers who are capable of adding value and increasing profitability. In order for SMEs to concentrate on fewer but profitable customers, they are expected to use customer-associated performance measures to estimate, assess and manage performance. Therefore, based on customer-focus context, the application of customer-associated performance measures (such as percentage of repeat customers, ratings from customer surveys, percentage of market share, percentage growth of new and existing customers and customer lifetime value) is anticipated to enhance competitive advantage and performance. Customer-focus activities allow SMEs to gain insight into both the expressed and latent needs of their customers, and develop customer value through the distribution of customer information across the business organization and allowing structured and focused activities to serve the needs of customers. In order for SMEs to achieve optimum customer performance, they need to create an effective interaction and relationship with customers through customer-focus factors including co-creation, network ties, customer insights and AIM. For example, the considerable use of AIM in managing customer grievances and response is an instance of innovation that is associated to the application of customer-focus. Such innovations associated with customer-focus significantly impact the customer performance of SMEs in terms of increased market share, high customer loyalty, customer delight, repeated purchase and referrals.
Third, the results from this research study indicate that the relationship between customer-focus and internal business process performance is supported (see Table 7). This gives support to previous studies (Templer et al., 2020; Marta et al., 2021) regarding the impact of customer-focus on the internal business process performance of business organizations. Undoubtedly, a focal activity in a customer-focus oriented organization is to create, evaluate and improve value streams, enterprise processes and methodologies to eliminate actions that are not contributing to value addition. Hence, actions that contribute to real value addition for the customers should be sustained and enhanced. Customer-focus, therefore, provides a process enhancement methodology that guides the internal practices of business organizations in a more efficient and effective way. This supports the growth of operational and internal decision-making effectiveness through restructuring and processes improvements. Customer-focus pursues internal business process improvement through process simplification, competence development, identification and removal of tasks that are not contributing to value addition, lessening of redundant internal customer-supplier associations in individual process and the lessening of unproductive process variability. In order to generate continuous change in customer-focus, SMEs should clearly indicate their goal for strategies and initiatives from the perspective of customers, and then link process enhancement to the customer experience.
Fourth, the results from this study show that the positive association between customer-focus and learning and growth performance is supported (see Table 7). This outcome provides support to past studies (Templer et al., 2020; Marta et al., 2021) related to the impact of customer-focus on learning and growth performance of business organizations. Customer-focus provides a cultural foundation for a learning organization and also creates a strong standard for disseminating information throughout a business organization. Customer-focus oriented culture supports importance of complete market intelligence and the need of functionally aligned activities targeted at obtaining competitive superiority and growth. Since the external prominence of customer-focus is centered on the creation of customer and competitor information, the customer-focus-driven SME is strategically placed to predict the emerging needs of its customers and react to them by providing products and services considered as additional innovation by customers. This capability offers the customer-focused SME an improvement in the pace and effectiveness of its reaction to prospects and risks. Therefore, a customer-focus is fundamentally a learning orientation which drives the growth of business organizations.
6.1 Theoretical implications
From the academic perspective, this current study contributes significantly to customer-focus literature through the systematic exploration of the impact of customer-focus on the performance of SMEs in Ghana. This current study contributes to the comprehension and management of customer-focus in different ways. It provides a conceptual framework that incorporates previous research in customer-focus and performance. Even though customer-focus has been empirically verified as a variable in many marketing-related studies, most of these empirical studies examined customer-focus in combination with other elements that usually fall under the title of customer orientation. Therefore, these previous studies failed to consider factors which are specifically pertinent to customer-focus alone. Furthermore, despite the establishment of a positive effect of customer-focus on performance by previous studies, most were unsuccessful in recounting the nature of the effect. As a result, this study fills those gaps by examining customer-focus in exclusivity and also determined the nature of customer-focus effect on SME performance through its determinants (i.e. co-creation, networking ties, customer insight and AIM). The findings of this current study, therefore, support the proposition that customer-focus and its determinants including co-creation, networking ties, customer insight and AIM should be acknowledged as an important strategic tool for optimizing financial performance, customer performance, internal business process performance and learning and growth performance among SMEs.
The current study also contributed to the RBV theory in considerable ways. The RBV maintains that business organizations including SMEs can advance their competitiveness provided they obtain and optimize resources and capabilities considered as valuable, rare, inimitable and nonreplaceable. The current research study supports the RBV theory because it provides a perspective which articulate the application levels of customer-focus in SMEs and how dissimilar resources of customer-focus including co-creation, network ties, customer insights and AIM interact to achieve competitive advantage and performance. The main idea of the RBV is that the competitive advantage of a business organization is contingent on its ability to obtain, control and configure resources. Business organization resources such as co-creation capability, networking ties, customer insight capability and AIM are critical organizational resources that develop customer-focus which, in turn, impacts the competitive superiority and performance of business organizations including SMEs.
6.2 Managerial implications
From the practitioners' perspective, the current study acquiesces that SME industry practitioners including food processing SME owners and managers, can greatly profit from the implications of this study's outcomes. For example, the strong relationship between customer-focus and financial performance, customer performance, internal business process and learning and growth performance is an indication that food processing SME owners and managers should direct their attention to the development of customer-focus through the application of customer-focus determinants (i.e. co-creation, networking ties, customer insight and AIM) in order to optimize their performance. Generally, SMEs are mostly limited by lack of resources, and, in several cases, this has hindered their ability to exploit long-term growth opportunities. Consequently, customer-focused oriented SMEs can still fail to benefit from opportunities originating from customer requirements if they continue to be constrained by resources to capitalize on such opportunities. This can be attributed to the reason that actual customer-focus application and optimization requires resource availability; therefore, its overall positive effect on business organization performance might lessen if the required resources are not available. Food processing SME owners and managers should, therefore, commit to the development of technical resources and infrastructures such as talent capability, artificial intelligence, machine learning capability and ICT that will support the customer-focus determinants indicated in this study. Based on this research outcomes, one can state that food processing SME owners and managers tend to increase in performance (i.e. financial, customers, internal business process and learning and growth) only when they develop customer-focus capability through the operationalization of customer-focus determinants, that is co-creation, networking ties, customer insight and AIM. The findings of this research, therefore, highlight how essential it is for SMEs to generate customer-focus oriented strategies and programs, particularly given the difficult and dynamic state in the external environment. This study also emphasizes the national policy applicability of such interventions by the government of Ghana, including the National Entrepreneurship and Innovation Plan (NEIP) which is targeted at start-ups and early-stage SMEs to improve their market intelligence and facilitation, marketing and technology application skills through supports such as business development services, business incubator hubs and business accelerator services. This is important particularly for food processing SMEs confronted with unpredictable and, usually, out-of-control market situations.
6.3 Limitation and future research
Despite the importance and benefits of this research mentioned earlier, this study has limitations. The sample size of this research study can be increased to capture SME respondents in other geographical zones that were not included in this study. Again, this research study was restricted to Ghana. For the purpose of comparative analysis, future research should consider conducting same study in other emerging economies, particularly in Africa. The use of the four classic parameters of the BSC as performance measures in this study prevented the use of broader performance parameters. Future research studies should incorporate parameters such as enterprise sustainability or endurance, risk and environment factors into the four classic perspectives of the BSC to address this limitation. Also, this study largely could not determine how business environment conditions moderate the relationship between customer-focus orientation and SME performance. Future research may address how business environment conditions moderate the relationship between customer-focus and performance; and also, the cause–effect of the relationship between customer-focus and business environment conditions on SME performance.
Figures
Demographic profile of respondents
| Age groups | Male n(%) | Female n(%) | Total n(%) |
|---|---|---|---|
| 18–30 | 37 (49.33) | 67 (44.67) | 104 (46.22) |
| 31–40 | 25 (33.33) | 62 (41.33) | 87 (38.67) |
| 41–50 | 7 (9.33) | 16 (10.67) | 23 (10.22) |
| 51–60 | 6 (8.01) | 5 (3.33) | 11 (4.89) |
| Total | 75 (100) | 150 (100) | 225 (100) |
| Ownership structure | |||
| Sole proprietorship | 41 (54.67) | 118 (78.67) | 159 (70.67) |
| Partnership | 24 (32) | 25 (16.67) | 49 (21.78) |
| Limited liability | 8 (13.33) | 7 (4.67) | 17 (7.55) |
| Total | 75 (100) | 150 (100) | 225 (100) |
| Current position | |||
| Owner manager | 27 (36) | 86 (57.33) | 113 (50.22) |
| General manager | 27 (36) | 22 (14.67) | 49 (21.78) |
| Nonmanagerial | 21 (28) | 42 (28) | 63 (28) |
| Total | 75 (100) | 150 (100) | 225 (100) |
| Enterprise size | |||
| 1–8 (Small) | 41 (54.67) | 101 (67.33) | 142 (63.11) |
| 9–100 (Medium) | 34 (45.33) | 49 (32.67) | 83 (36.89) |
| Total | 75 (100) | 150 (100) | 225 (100) |
| Operation duration | |||
| 2 years | 19 (25.33) | 35 (23.33) | 54 (24) |
| >2 years | 56 (74.67) | 115 (76.67) | 171 (76) |
| Total | 75 (100) | 150 (100) | 225 (100) |
Source(s): Table 1 courtesy of Abrokwah-Larbi (2020)
Factor analysis, reliability and validity of customer focus items
| Factors | Items | Factor load | Cronbach’s alpha (α) | KMO | Composite reliability | Average factor loading* | AVE** | Correlation matrix square |
|---|---|---|---|---|---|---|---|---|
| Customer focus | CF19 | 0.83 | 0.890 | 0.86 | 0.89 | 0.76 | 0.58 | 0.00 |
| CF20 | 0.78 | |||||||
| CF21 | 0.72 | |||||||
| CF22 | 0.70 | |||||||
| CF23 | 0.77 | |||||||
| CF24 | 0.76 |
Note(s): *Average factor loading >0.7, convergent validity established
**Square root of average variance extracted (AVE) > correlation matrix squared; discriminant validity established
***CF – customer focus
Source(s): Table 2 courtesy of Abrokwah-Larbi (2020)
Factor analysis, reliability and validity of performance variables
| Factors | Items | Factor load | Cronbach alpha (α) | KMO | Composite reliability | Average factor load* | AVE** | Correlation matrix square |
|---|---|---|---|---|---|---|---|---|
| Financial performance | FP7 | 0.50 | 0.90 | 0.93 | 0.92 | 0.78 | 0.62 | 0.00 |
| FP8 | 0.84 | |||||||
| FP9 | 0.82 | |||||||
| FP10 | 0.81 | |||||||
| FP11 | 0.79 | |||||||
| FP12 | 0.86 | |||||||
| FP13 | 0.84 | |||||||
| Customer performance | CP14 | 0.81 | 0.91 | 0.91 | 0.91 | 0.76 | 0.58 | 0.00 |
| CP15 | 0.77 | |||||||
| CP16 | 0.72 | |||||||
| CP17 | 0.84 | |||||||
| CP18 | 0.77 | |||||||
| CP19 | 0.74 | |||||||
| CP20 | 0.70 | |||||||
| Internal business process performance | IBPP21 | 0.74 | 0.91 | 0.92 | 0.91 | 0.73 | 0.53 | 0.00 |
| IBPP22 | 0.73 | |||||||
| IBPP23 | 0.60 | |||||||
| IBPP24 | 0.79 | |||||||
| IBPP25 | 0.75 | |||||||
| IBPP26 | 0.77 | |||||||
| IBPP27 | 0.77 | |||||||
| IBPP28 | 0.68 | |||||||
| IBPP29 | 0.71 | |||||||
| Learning and growth performance | LGP30 | 0.74 | 0.91 | 0.91 | 0.91 | 0.73 | 0.54 | 0.00 |
| LGP31 | 0.71 | |||||||
| LGP32 | 0.77 | |||||||
| LGP33 | 0.72 | |||||||
| LGP34 | 0.60 | |||||||
| LGP35 | 0.73 | |||||||
| LGP36 | 0.80 | |||||||
| LGP37 | 0.78 | |||||||
| LGP38 | 0.81 |
Note(s): *Average factor loading >0.7, convergent validity established
**Square root of average variance extracted (AVE) > correlation matrix squared; discriminant validity established
***FP-financial performance; CP-customer performance; IBPP-internal business process performance; LGP-learning and growth performance
Source(s): Table 3 courtesy of Abrokwah-Larbi (2020)
Customer focus and SME performance measurement items
| Customer focus measurement items |
| CF19 = Customer focus application provides my firm with deep insight of customer needs |
| CF20 = Adoption of customer focus culture has improved my firm's business performance |
| CF21 = Co-creation practices of my firm has improved our customer focus through collaboration |
| CF22 = My firm's networking ties have enabled us to carefully focus our marketing effort to both latent and expressed customer needs |
| CF23 = My firm's customer insight practices provide accurate information for our customer focus strategy |
| CF24 = My firm uses AI and machine learning capability to identify the right customer focus areas to pursue |
| Performance measurement items |
| Financial performance (FP) |
| FP7 = My firm's profitability is satisfactory |
| FP8 = My firm's market share is high compared to competitors |
| FP9 = The financial performance of my firm is supported by a sustainable approach |
| FP10 = Maximizing profitability is a key business goal of my firm |
| FP11 = My firm plans the sales revenue growth of all products/services |
| FP12 = Managers of my firm are pursing innovative strategy to improve its return on investment, ROI |
| FP13 = Productivity improvement is important to my firm's financial objective |
| Customer performance (CP) |
| CP14 = Customer retention has increased in my firm within the last two years |
| CP15 = My firm has realized a steady increase of new customers in the last two years |
| CP16 = Product or service sales to new customers has increased in the last two years |
| CP17 = Product or service sales to existing customers has increased in the last two years |
| CP18 = Customer switching cost has increased within the last two years |
| CP19 = My firm uses innovative methods of targeting customers instead of traditional methods |
| CP20 = My firm uses technology to improve customer experience |
| Internal business process performance (IBPP) |
| IBPP21 = My firm's customer management process contributes to customer value addition |
| IBPP22 = My firm's process enhancement methodology is efficient and effective |
| IBPP23 = My firm captures employee contribution into business process designs |
| IBPP24 = My firm uses technology to develop new business processes |
| IBPP25 = Duration of production in my firm has decreased in the last two years |
| IBPP26 = Customer complaint processes duration is shorter compared to competitors |
| IBPP27 = My firm integrates customer requirement into its business processes |
| IBPP28 = My firm is resourced with technology for new product development |
| IBPP29 = My firm's internal processes contribute to customer satisfaction |
| Learning and growth performance (LGP) |
| LGP30 = My firm have sufficient skilled and motivated employees |
| LGP31 = We have quality database and information system to support our learning and growth |
| LGP32 = My firm has the right organizational culture to achieve its business process objectives |
| LGP33 = My firm provides frequent learning opportunities for our employees though different capacity building programs |
| LGP34 = My firm has seen a steady reduction in employee turn-over rate in the last two years |
| LGP35 = We use technology enabled approach to obtain customer insights |
| LGP36 = My firm integrates employee suggestions into its business process approach |
| LGP37 = Our business methodologies support knowledge and competence development |
| LGP38 = We gather new information about new products or services |
Source(s): Table 4 by Abrokwah-Larbi (2020)
SEM regression table on the impact of customer focus on SME performance
| Standardized coefficient | ||||
|---|---|---|---|---|
| Beta (β) | p value | 95% | Confidence interval | |
| FP | ||||
| CF | 0.45 | <0.001 | 0.332 | −0.566 |
| CP | ||||
| CF | 0.54 | <0.001 | 0.428 | −0.644 |
| IBPP | ||||
| CF | 0.60 | <0.001 | 0.498 | −0.697 |
| LGP | ||||
| CF | 0.63 | <0.001 | 0.534 | −0.722 |
Source(s): Table 5 by Abrokwah-Larbi (2020)
Goodness of fit for SEM (using STATA 15.10)
| Fit statistic | Value | Description |
|---|---|---|
| Population error | ||
| RMSEA | 0.063 | Root mean squared error of approximation |
| 90% CI, lower bound | 0.057 | |
| upper bound | 0.068 | |
| P close | Probability RMSEA ≤ 0.05 | |
| Information criteria | ||
| AIC | 20747.65 | Akaike's information criterion |
| BIC | 21150.75 | Bayesian information criterion |
| Baseline comparison | ||
| CFI | 0.894 | Comparative fit index |
| TLI | 0.887 | Tucker–Lewis index |
| Size of residuals | ||
| SRMR | 0.125 | Standardized root mean squared residual |
| CD | 0.911 | Coefficient of determination |
Source(s): Table 6 by Abrokwah-Larbi (2020)
SEM model assessment results and summary results of hypothesis test
| Hypothesis | Construct structural relationships | Path coefficient (β) | p values | Decision |
|---|---|---|---|---|
| H1 | Customer focus → financial performance | 0.45 | <0.001 | Accept |
| H2 | Customer focus → customer performance | 0.54 | <0.001 | Accept |
| H3 | Customer focus → internal business process performance | 0.60 | <0.001 | Accept |
| H4 | Customer focus → learning and growth performance | 0.63 | <0.001 | Accept |
| Summary results of hypothesis test | |
|---|---|
| Hypothesis | Outcome |
| H1: Customer focus has a significant positive impact on financial performance | Accepted |
| H2: Customer focus has a significant positive impact on customer performance | Accepted |
| H3: Customer focus has a significant positive impact on internal business process performance | Accepted |
| H4: Customer focus has a significant positive impact on learning and growth performance | Accepted |
Source(s): Table 7 by Abrokwah-Larbi (2020)
References
Abofaied, A. (2017), “Evaluation of bank's performance by using Balanced Scorecard: practical study in Libya”, International Journal of Business, Vol. 5 No. 1, pp. 1-14.
Abrokwah-Larbi, K. (2020), “The impact of innovative marketing on the performance of Ghanaian food processing Small and Medium Enterprises (SMEs)”, Ph.D. thesis submitted to the University of South Africa (UNISA).
Al-Gasawneh, J.A., Anuar, M.M., Dacko-Pikiewicz, Z. and Saputra, J. (2021), “The impact of customer relationship management dimensions on service quality”, Polish Journal of Management Studies, Vol. 23, pp. 34-40.
Alves, I. and Lourenço, S.M. (2022), “The use of non-financial measures for managerial compensation: evidence from SMEs”, Journal of Management Control, Vol. 33, pp. 151-187.
Amer, F., Hammoud, S., Khatatbeh, H., Lohner, S., Boncz, I. and Endrei, D. (2022), “The deployment of balanced scorecard in health care organizations: is it beneficial? A systematic review”, BMC Health Services Research, Vol. 22 No. 55, pp. 1-14.
Andreou, P.C., Lambertides, N., Trigeorgis, L. and Tuneshev, R. (2022), “Customer orientation and financial performance during crisis period”, SSRN, pp. 1-35, doi: 10.2139/ssrn.4028608.
Arjunan, L., Habidin, N.F., Yusof, M.M.S. and Muniandy, R. (2020), “Evaluate safety practices of Malaysian Public Universities by using balanced scorecard”, Journal of Cognitive Sciences and Human Development, Vol. 6 No. 1, pp. 20-43.
Armin, D.A., Kamase, J., Plyriadi, A. and Hasan, S. (2021), “The influence of market orientation, service quality and service orientation on customer satisfaction and customer loyalty of PT. Rapid Tirta Sejahtera in Makassar City”, ISOR Journal of Business and Management, Vol. 23 No. 8, pp. 01-08.
Arsenijevic, U. and Jovic, M. (2019), “Artificial intelligence marketing: chatbots”, In Proceedings of the International Conference on Artificial Intelligence: Applications and Innovations, Belgrade, Serbia, 30 September–4 October, 2019.
Askarany, D. (2017), “How can we improve the balanced scorecard?”, Global Journal of Technology and Optimization, Vol. 7 No. 3, p. 202.
Aziz, N.A., Ismail, R., Omar, R., Rahmana, I. and Mulyana (2021), “Customer orientation and marketing innovation: a study of SMEs performance in East Coast Malaysia”, International Journal of Academic Research in Business and Social Sciences, Vol. 11 No. 18, pp. 202-219.
Babu, M. (2018), “Impact of firm's customer orientation on performance: the moderating role of inter-functional coordination and employee commitment”, Journal of Strategic Marketing, Vol. 26 No. 8, pp. 702-722.
Barney, J.B. (2001), “Resource-based theories of competitive advantage: a ten-year retrospective on the resource-based view”, Journal of Management, Vol. 27 No. 6, pp. 747-758.
Bartley, B., Gomibuchi, S. and Mann, R. (2007), “Best practices in achieving a customer-focus culture”, Benchmarking an International Journal, Vol. 14 No. 4, pp. 482-496.
Benchekroun, B. and Soulami, M. (2021), “Study of the impact of the value of co-creation on consumer satisfaction and loyalty”, Revue Internationale des Sciences de Gestion, Vol. 4 No. 4, pp. 462-480.
Cândido, C.J.F. and Santos, S.P. (2019), “Implementation obstacles and strategy implementation failure”, Baltic Journal of Management, Vol. 4 No. 1, pp. 39-57.
Chaudhry, N.I., Aftab, I., Arif, Z., Tariq, U. and Roomi, M.A. (2019), “Impact of customer-oriented strategy on financial performance with mediating role of HRM and innovation capability”, Personnel Review, Vol. 48 No. 3, pp. 631-643, doi: 10.1108/PR-02-2018-0056.
Ciampi, F., Marzi, G., Demi, S. and Faraoni, M. (2020), “The big data-business strategy interconnection: a grand challenge for knowledge management. A review and future perspectives”, Journal of Knowledge Management, Vol. 24 No. 5, pp. 1157-1176.
Cochran, W.G. (1977), Sampling Techniques, 3rd ed., John Wiley & Sons, New York.
Daqau, M.A.M.A. and Smoudy, A.K.A. (2019), “The role of artificial intelligence on enhancing customer experience”, International Review of Management and Marketing, Vol. 9 No. 4, pp. 22-31.
Deshpandé, R., Farley, J.U. and Webster, F.E. Jr (1993), “Corporate culture, customer orientation and innovativeness in Japanese firms: a quadrad analysis”, Journal of Marketing, Vol. 57 No. 1, pp. 23-37.
Domi, S., Capelleras, J.L. and Musabelliu, B. (2020), “Customer orientation and SME performance in Albania: a case study of the mediating role of innovativeness and innovation behavior”, Journal of Vacation Marketing, Vol. 26 No. 1, pp. 130-146.
Donkor, J., Donkor, G.N.A. and Kwarteng, C.K. (2018), “Strategic planning and performance of SMEs in Ghana, the moderating effect of market dynamism”, Asia Pacific Journal of Innovation and Entrepreneurship, Vol. 12 No. 1, pp. 62-76.
Donnellan, J. and Rutledge, W.L. (2019), “A case for resource-based view and competitive advantage in banking”, Managerial and Decision Economics, Vol. 40, pp. 728-737.
Einhorn, M. and Löffler (2021), Transformation of Customer Insight, 1st ed., Emerald Publishing, Bingley.
Estensoro, M., Larrea, M., Müller, J.M. and Sisti, E. (2022), “A resource-based view on SMEs regarding the transition to more sophisticated stages of industry 4.0”, European Management Journal, Vol. 40, pp. 778-792.
Fakhreddin, F. and Foroudi, P. (2022), “The impact of market orientation on new product performance through product launch quality: a resource-based view”, Cogent Business and Management, Vol. 9 No. 1, pp. 1-22, 2108220.
Flight, R. and Mudiyanselage, A.S. (2021), “Customer and competitor orientation, innovation and performance in small and medium sized enterprises”, Marketing Management Journal, Vol. 31 No. 1, pp. 1-24.
Frambach, R.T., Fiss, P.C. and Ingenbleek, P.T.M. (2016), “How important is customer orientation for firm performance? A fuzzy set analysis of orientations, strategies, and environments”, Journal of Business Research, Vol. 69, pp. 1428-1436.
Galdolage, B.S. (2021), “Customer value co-creation intention, practices, co-destruction and experience in self-service technologies”, Journal of Scientific Research and Reports, Vol. 27 No. 4, pp. 12-26.
Gebczynska, A. (2016), “A strategy implementation efficiency on the process level”, Business Process Management Journal, Vol. 22 No. 6, pp. 1079-1098.
Ghana Statistical Services (GSS) (2020), National Industrial Census, Ghana Statistical Service, Accra.
Gudelj, M., Delic, M., Kuzmanovic, B., Tesic, Z. and Tastic, N. (2021), “Business process management model as an approach to process orientation”, International Journal of Simulation Modelling, Vol. 20 No. 2, pp. 255-266.
Hagen, D., Risselada, A., Spierings, B. and Weltevreden, J.W.J. (2022), “Digital marketing activities by Dutch place management partnerships: a resource-based view”, Cities, Vol. 123 No. 103548, pp. 1-10.
Hair, J.F., Risher, J.J., Sarstedt, M. and Ringle, C.M. (2019), “When to use and how to report the results of PLS-SEM”, European Business Review, Vol. 31 No. 1, pp. 2-24.
Hamdy, A. (2018), “Balanced scorecard role in competitive advantage of Egyptian banking sector”, Business and Management Review, Vol. 9 No. 3, pp. 424-434.
Hamidi, F., Gharneh, N.S. and Khajeheian, D. (2020), “A conceptual framework for value co-creation in service enterprises: case of tourism agencies”, Journal of Sustainability – MDPI, Vol. 12 No. 1, pp. 1-21.
Han, S., Reinartz, W. and Skiera, B. (2021), “Capturing retailers' and customer focus”, Journal of Retailing, Vol. 97, pp. 582-596.
Hasyim, S. and Syahreza, D. (2021), “The role of organizational commitment, entrepreneurial orientation, and architectural marketing capabilities on improving marketing performance by using network chain capability of goods in tourism market”, Management Science Letters, Vol. 11, pp. 1415-1420.
Hristov, I., Chirico, A. and Appolloni, A. (2019), “Sustainability value creation, survival, and growth of the company: a critical perspective in the Sustainability Balanced Scorecard (SBSC)”, Sustainability, Vol. 11 No. 7, p. 2119.
Husain, Z., Dayan, M., Sushil and Benedetto, C.A.D. (2022), “Impact of customer focus on technology leadership via technology development capability – a moderating mediation model”, Journal of Business and Industrial Marketing, Vol. 37 No. 2, pp. 282-293.
Islam, M.Z. and Zhe, Z. (2022), “The effect of customer orientation on financial performance in service firms: the mediating role of service innovation”, Management Science Letters, Vol. 12, pp. 101-116.
Islamgaleyev, A., Petrova, M., Kurenkeyeva, G., Shalbayeva, S. and Kadirbergenova, A. (2020), “Increasing customer focus in metal trading”, Entrepreneurship and Sustainability Issues, Vol. 8 No. 1, p. 604.
Jasti, N.V.K. and Kodali, R. (2015), “Lean production: literature review and trends”, International Journal of Production Research, Vol. 52 No. 2, pp. 867-885.
Kaburu, R.W., Karanja, G.W., Wagoki, A.J. and Wanyoike, D.M. (2021), “Influence of customer orientation on the growth of manufacturing firms in Nakuru East and West Dub-Counties Kenya”, The International Journal of Business Management and Technology, Vol. 5 No. 4, pp. 129-138.
Kang, M.-J., Wu, Z. and Hwang, H.-J. (2021), “A study on the mediating effect of customer orientation between O2O service quality and customers' perceived service satisfaction”, Journal of Distribution Science, Vol. 19 No. 2, pp. 37-44.
Kaplan, A. and Haenlein, M. (2019), “Siri, Siri, in my hand: who's the fairest in the land? On the interpretations, illustrations, and implications of artificial intelligence”, Business Horizon, Vol. 62 No. 1, pp. 15-25.
Kaplan, R.S. and Norton, D. (2009), Conceptual Foundation of the Balanced Scorecard, Harvard Business School, Massachusetts, pp. 2-32.
Khrais, L.T. (2020), “The role of artificial intelligence in shaping consumer demand in e-commerce”, Future Internet - MDPI, Vol. 12 No. 226, pp. 1-14.
Kim, E.M., Bae, S.H. and Bae, G.K. (2017), “The effects of the perceived O2O service quality on behavioral intention for purchase: focusing on the moderating effects of reliance on information”, Journal of Foodservice Management Society of Korea, Vol. 20 No. 5, pp. 207-226.
Kimbu, A.N., Ngoasong, M.Z., Adeola, O. and Afenyo-Agbe, E. (2019), “Collaborative networks for sustainable human capital management in women's tourism entrepreneurship: the role of tourism policy”, Tourism Planning and Development, Vol. 15 No.2, pp. 161-178.
Kulkov, I. (2021), “The role of artificial intelligence in business transformation: a case of pharmaceutical companies”, Technology in Society, Vol. 66, 101629.
Kumar, V. and Reinartz, W. (2018), Customer Relationship Management: Concepts, Strategy, and Tools, 3rd ed., Springer, Heidelberg.
Kurznack, L., Shoenmaker, D. and Schramade, W. (2021), “A model of ling-term value creation”, Journal of Sustainability Finance and Investment, Vol. ahead-of-print No. ahead-of-print, doi: 10.1080/20430795.2021.1920231.
Laage-Hellman, J. and Lind, F. (2021), “The role of openness in collaborative innovation in industrial networks: historical and contemporary cases”, Journal of Business and Industrial Marketing, Vol. 36 No. 13, pp. 116-128.
Lassoued, K. (2018), “Balanced scorecard implementation in higher education: an Emirati prespective”, Corporate Ownership and Control, Vol. 15 Nos 3-1, pp. 205-216.
Ledro, C., Nosella, A. and Vinelli, A. (2022), “Artificial intelligence in customer relationship management: literature review and future research directions”, Journal of Business and Industrial Marketing, Vol. 37 No. 13, pp. 48-63.
Lee, S.M. and Lee, D. (2020), “Untact”: a new customer service strategy in the digital age”, Service Business, Vol. 14 No. 1, pp. 1-22.
Lee, D.-M., Fu, Y.-X., Wang, L.-Y. and Nie, T. (2021), “Network ties, social capital and knowledge management”, European Journal of Business and Management Research, Vol. 6 No. 5, pp. 201-203.
Leone, D., Schiavone, F., Appio, F.P. and Chiao, B. (2021), “How does artificial intelligence enable and enhance value co-creation in industrial markets? An exploratory case study in the healthcare ecosystem”, Journal of Business Research, Vol. 129, pp. 849-859.
Li, S., Peng, G., Xing, F., Zhang, J. and Zhang, B. (2021), “Value co-creations in industrial AI: the interactive role of B2B supplier, customer and technology provider”, Industrial Marketing Management, Vol. 98, pp. 105-114.
Loureiro, S.M.C., Guerreiro, J. and Tussyadiah, I. (2021), “Artificial intelligence in business: state of the art and future research agenda”, Journal of Business Research, Vol. 129, pp. 911-926.
Lu, W., Han, Yu. and Chen, S. (2020), “Examining how co-creation and virtual brand community affect brand commitment”, E3S Web of Conference 235, 02045, NETID 2020, pp. 1-8.
Lukason, O. and Valgenberg, G. (2021), “Failure prediction in the condition of information asymmetry: tax arrears as a substitute when financial ratios are outdated”, Journal of Risk and Financial Management, Vol. 14 No. 10, pp. 1-13.
Madhani, P.M. (2020), “Building a customer focused strategy: conceptual frameworks and research propositions”, SCMS Journal of Indian Management, Vol. 17 No. 3, pp. 5-25.
Madrakhimova, M.S. (2021), “Customer-oriented approach as a development strategy of a tourism enterprise”, Middle European Scientific Bulletin, Vol. 12, pp. 311-314.
Malhotra, N., Nunan, D. and Birks, D. (2017), Marketing Research: An Applied Approach, 5th ed., Pearson, London.
Mandal, P.C. (2022), “Marketing information and marketing intelligence: generation of customer insights”, International Journal of Technology Diffusion (IJTD), Vol. 13 No. 1, p. 14.
Manishimwe, T., Raimi, L. and Azubuike, C.J. (2022), “Customer-centric influence of entrepreneurial marketing on business performance of hotels in Nigeria during the COVID-19 crisis”, Journal of Revenue and Pricing Management, Vol. 21, doi: 10.1057/s41272-022-00383-w.
Marta, M.S., Hurriyati, R. and Dewi, P. (2021), “How to understand customer needs? The role of market orientation, innovation capability, and learning orientation”, Journal of Management and Business, Vol. 4 No. 2, pp. 095-109.
McColl-Kennedy, J.R., Zaki, M., Lemon, K.N., Urmetzer, F. and Neely, A. (2019), “Gaining customer experience insights that matter”, Journal of Service Research, Vol. 22 No. 1, pp. 8-26.
Merz, M.A., Zarantonello, L. and Grappi, S. (2018), “How valuable are your customers in the brand value co-creation process? The development of a Customer Co-Creation Value (CCCV) scale”, Journal of Business Research, Vol. 82, pp. 79-89.
Muteshi, D. and Kariuki, A. (2020), “Corporate strategy, networking and firm performance in Africa”, Expert Journal of Business and Management, Vol. 8 No. 2, pp. 139-146.
Nalini, K., Radhakrishnan, P., Yogi, G., Santhiya, S. and Harivardhini, V. (2021), “Impact of artificial intelligence (AI) on marketing”, International Journal of Aquatic Science, Vol. 12 No. 02, pp. 3159-3167.
Narver, J.C. and Slater, S.F. (1990), “Th effect of a market orientation on business profitability”, Journal of Marketing, Vol. 54 No. 4, pp. 20-35.
Nayak, B., Bhattacharyya, S.S. and Krishnamoorthy, B. (2022), “Integrating the dialectic perspectives of resource-based view and industrial organization theory for competitive advantage – a review and research agenda”, Journal of Business and Industrial Marketing, Vol. 38 No. 3, doi: 10.1108/JBIM-06-2021-0306.
Nazari-Shirkouhi, S., Mousakhani, S., Tavakoli, M., Dalvand, M.R., Šaparauskas, J. and Antuchevičienė, J. (2020), “Importance-performance analysis based balanced scorecard for performance evaluation in higher education institutions: an integrated fuzzy approach”, Journal of Business Economics and Management, Vol. 21 No. 3, pp. 647-678.
Neneh, B.N. (2016), “Market orientation and performance: the contingency role of external environment”, Environmental Economics, Vol. 7 No. 2, pp. 1-14.
Neneh, B.N. (2018), “Customer orientation and SME performance: the role of networking ties”, African Journal of Economic and Management Studies (AJEMS), Vol. 9 No. 2, pp. 178-196.
Nicolas, T. (2022), “Short-term financial constraints and SMEs' investment decision: evidence from the working capital channel”, Small Business Economics, Vol. 58, pp. 1885-1914.
Niemi-Grundström, M. (2021), “Customer value as a key concept for enhancing the customer insight in academic library”, Qualitative and Quantitative Methods in Library (QQML), Vol. 10 No. 4, pp. 407-415.
Nwokah, N.G. and Maclayton, D.W. (2006), “Customer-focus and business performance: the study of food and beverages organizations in Nigeria”, Journal of Measuring Business Excellence, Vol. 10 No. 4, pp. 65-76.
Osakwe, J., Waiganjo, I.N., Tarzoor, T., Iyawa, G. and Ujakpa, M. (2022), “Determinants of information systems resources for business organizations' competitive advantage: a resource-based view approach”, IST-Africa 2022 Conference Proceedings, pp. 1-8.
Park, H.S. (2020), “A study on the O2O commerce business with business model canvas”, Journal of Distribution Science, Vol. 18 No. 5, pp. 89-98.
Paschen, J., Kietzmann, J. and Kietzmann, T.C. (2019), “Artificial intelligence (AI) and its implications for market knowledge in B2B marketing”, Journal of Business and Industrial Marketing, Vol. 34, pp. 1410-1419.
Pekovic, S. and Rolland, S. (2016), “Customer orientation and firm's business performance”, European Journal of Marketing, Vol. 50 No. 12, pp. 2162-2191.
Rafiq, M., Zhang, X.P., Yuan, J., Naz, S. and Maqbool, S. (2020), “Impact of balanced scorecard as a strategic management system tool to improve sustainable development: measuring the mediation of organizational performance through PLS-smart”, Sustainability, Vol. 12 No. 4, p. 1365.
Rajkhowa, B. and Das, A. (2020), “Impact of artificial intelligence on customer experience”, International Journal of Recent Technology and Enterprise (IJRTE), Vol. 9 No. 2, pp. 1237-1242.
Ribeiro, M.A., Adam, I., Kimbu, A.N., Afenyo-Agbe, E., Adeola, O., Figueroa-Domecq, C. and de Jong, A. (2021), “Women entrepreneurship orientation, networks and firm performance in the tourism industry in resource-scarce contexts”, Tourism Management, Vol. 86, 104343.
Rönkkö, M. and Cho, E. (2022), “An updated guideline for assessing discriminant validity”, Organizational Research Methods, Vol. 25 No. 1, pp. 6-47.
Roberts, D.L. and Darler, W. (2017), “Consumer co-creation: an opportunity to humanize the new product development process”, International Journal of Market Research, Vol. 59 No. 1, pp. 13-33.
Saleh, M.H.M., Azmin, A.A. and Saraih, U.N. (2021), “The effects of market orientation, product innovation and marketing ethics on firm performance: a theoretical framework”, International Journal of Innovation and Industrial Revolution (IJIREV), Vol. 3 No. 7, pp. 31-47.
Santos, M.J., Perin, M.G., Simões, C. and Sampaio, C.H. (2020), “Customer orientation and financial performance relationship: the mediating role of innovative capability”, Gestão & Produção, Vol. 27 No. 4, pp. 1-20.
Sarasvuo, S., Rindell, A. and Kovalchuk, M. (2022), “Towards a conceptual understanding of co-creation”, Journal of Business Research, Vol. 139, pp. 543-563.
Sarstedt, M. and Cheah, J.-H. (2019), “Partial least squares structural eqaution modeling using SmartPLS: a software review”, Journal of Marketing Analytics, Vol. 7, pp. 196-202.
Setiyaji, A., Alves, G.M.D.F.F. and Wijaya, L. (2022), “The importance of customer focus for organizational performance: a study focus to an information and communication technology company based in Indonesia”, Proceedings of the International Conference on Industrial Engineering and Operations Management Istanbul, Turkey, March 7-10, 2022.
Sharaf-Addin, H.H. and Fazel, H. (2021), “Balanced scorecard development as a performance management system in Saudi Public Universities: a case of Study Approach”, Asia-Pacific Journal of Management Research and Innovation, Vol. 17 Nos 1-2, pp. 57-70.
Singh, R.K. and Arora, S.S. (2018), “The adoption of balanced scorecard: an exploration of its antecedents and consequences”, Benchmarking: An International Journal, Vol. 25, pp. 874-892.
Soni, N., Sharma, E.K., Singh, N. and Kapoor, A. (2020), “Artificial intelligence in business: from research and innovation to market deployment”, Procedia Computer Science, Vol. 167, pp. 2200-2210.
Templer, K.J., Kennedy, J.C. and Phang, R. (2020), “Customer orientation: the interactive effect of role clarity and learning goal orientation”, Journal of Asia Business and Economics Studies, Vol. 27 No. 3, pp. 303-314.
Thinkwithgoogle (2019), “Insights we uncovered in 2019 that will take you into 2020”, 2019 Research Review, pp. 1-11, available at: https://storage.googleleapis.com/think/does/think-with-google-2019-research-review.pdf
Tibbs, C.Y. and Langat, L.K. (2016), “Internal process. Learning perspective of balanced scorecard and organizational performance: a case of Tata, Chemicals Magadi Limited, Kenya”, International Journal of Economics, Commerce and Management, Vol. 4 No. 11, pp. 458-474.
Touminen, S., Reijonen, H., Nagy, G., Buratti, A. and Laukkanen, T. (2022), “Customer-centric strategy driving innovativeness and business growth in international markets”, International Marketing Review, Vol. ahead-of-print No. ahead-of-print, doi: 10.1108/IMR-09-2020-0215.
van Assen, M.F. (2021), “Lean, process improvement and customer-focused performance. The moderating effect of perceived organizational context”, Total Quality Management and Business Excellence Journal, Vol. 32 Nos 1-2, pp. 57-75.
Widelska, U. and Krot, K. (2021), “Customer orientation and innovation – the perspective of top-level management”, Folia Oeconomica Stetinensia, Vol. 21 No. 1, pp. 162-174.
Yau, K.-L.A., Saad, N.M. and Chong, Y.-W. (2021), “Artificial Intelligence Marketing (AIM) for enhancing customer relationships”, Applied Sciences Journal, Vol. 11 No. 18, pp. 1-17.
Yulianthini, N.N., Mayasari, N.M.D.A., Dewanti, M.A. and Atidira, R. (2021), “Customer orientation and competitor orientation influence on the marketing performance of restaurants MSEs in the Buleleng District”, Advances in Economics, Business and Management Research, Vol. 197, pp. 404-410.
Zaman, M., Vo-Thanh, T., Hassan, R., Shams, S.M. and Vukovic, D.B. (2022), “How can hotels create sustainable competitive advantage? A resource-based view”, Journal of Strategic Marketing, Vol. ahead-of-print No. ahead-of-print, pp. 1-16, doi: 10.1080/0965254X.2022.2066558.
Zulaikha, S., Mohamed, H., Kurniawati, M., Rusgianto, S. and Rusmita, S. (2021), “Customer predictive analysis using artificial intelligence”, The Singapore Economic Review, Vol. ahead-of-print No. ahead-of-print, doi: 10.1142/S0217590820480021.
Further reading
Behnam, M., Sato, M., Baker, B.J., Delshab, V. and Winand, M. (2020), “Connecting customer knowledge management and intention to use sport services through psychological involvement, commitment, and customer perceived value”, Journal of Sport Management, Vol. 34 No. 6, pp. 591-603.
Hammouri, Q., Al-Gasawneh, J.A., Abu-Shanab, E.A., Nusairat, N.M. and Akhorshaideh, H. (2021), “Determinants of the continuous use of mobile apps: the mediating role of users awareness and the moderating role of customer focus”, International Journal of Data and Network Science, Vol. 5, pp. 667-680.
Laureani, A. and Antony, J. (2017), “Leadership and lean six sigma: a systematic literature review”, Journal of Total Quality Management and Business Excellence, Vol. 28 Nos 3-4, pp. 1-29.
Papaioannou, A., Kriemadis, T., Kapetaniou, P., Yfantidou, G. and Kourtesopoulou, A. (2018), “Customer oriented strategy and business performance in tourism and hospitality industry”, In Innovative Approaches to Tourism and Leisure, pp. 417-432, Springer, Cham.
Sørensen, H.E. (2011), “Resource specialization, customer orientation, and firm performance: an empirical investigation of valuable resources”, Journal of Strategic Marketing, Vol. 19 No. 4, pp. 395-412.
Zhang, T., Lu, C., Torres, E. and Chen, P.-J. (2018), “Engaging customers in value co-creation or co-destruction online”, Journal of Service Marketing, Vol. 32, pp. 57-69.
Acknowledgements
Awuku-Larbi, Yaw is acknowledged for his contribution to the statistical analysis and its interpretation.
Corresponding author
About the author
Kwabena Abrokwah-Larbi holds a PhD in management studies from the University of South Africa, Pretoria, and lectures marketing at the Koforidua Technical University in Koforidua, Ghana. His current research interest is in micro, small and medium enterprise (MSME) marketing, management and sustainability.