Digital transformation in an emerging economy: exploring organizational drivers

Abstract

While there is sufficient evidence from empirical studies that digital technologies are strategic resources for value creation, existing literature on the theme lacks general concepts that explore an organization’s strategic resources concerning digital orientations and transformation initiatives. This study hence builds on a resource-based view with digital orientation literature to conceptualize a novel strategic orientation concept to understand the attitude toward digital innovation integration among firms in an emerging and developing country. This study tests a new conceptual framework using survey data from 472 employees of small-to-medium-sized service-based firms and employing structural equation model analysis with a variance-based SEM approach. Our empirical results showed that IT infrastructural availability and digital innovation investment are significant organizational drivers that have a direct relationship with attitude toward digital innovation integration among firms whereas IT competencies, digital innovation management, and knowledge of digital innovation are not significant with attitude toward digital innovation integration. More importantly, our findings advance the literature on a firm’s strategic resources and bring the realms of strategy and digital orientation closer together. The study provides valuable insights for management and shareholders regarding the specific drivers that affect the adoption of digital technologies among service-based SMEs in emerging economies.

Keywords:

• Digital orientation
• transformation
• digitalization
• service-based firms
• Ghana

REVIEWING EDITOR:

• Nashwa Attallah
• Tourism Studies Department, Alexandria University Faculty of Tourism and Hotels
• Alexandria, Egypt

SUBJECTS:

• Information & Communication Technology (ICT)
• Internet & Multimedia - Computing & IT
• Management of IT

1. Introduction

Undoubtedly, the performance of service-based firms in the digitalized environment is not under contention since digital technology evolution supports intelligence and reduces operating bottlenecks (Harrigan et al., 2012; Kwarteng et al., 2021) but research in this area has recently emerged as an important research topic (Rha & Lee, 2022). In the work of Bitner et al. (2010) the advances in technology have profoundly changed the nature of service provision and influenced how service is delivered, innovated, and managed. It is also fundamentally transforming the way of information sharing, collaboration, and value creation, enhancing organizational team-building and management (Li et al., 2023; Wu et al., 2023). According to Lee et al. (2021), intense competition in various markets (both domestic and international) has resulted in the adoption of digitalization. Meanwhile, governments of both developed and developing economies are gradually implementing strategies and initiatives geared toward firms including SMEs’ adoption and utilization of digitalization (Fu & Shi, 2022; Li et al., 2023). Again, contemporary enterprises are adopting digital orientation for effective resource management and improved productivity (Polyakov & Kovshun, 2021). It has been argued that SME firms with digitalization processes survive in the international markets.

Li and Shao (2023) summarise that digital orientation provides guidance and principles through which organizations adopt and utilize technologies to achieve superior advantage and sustainable growth. Specifically, digital orientation is centered on the collaboration and amalgamation of technological and business strategies (Mathafena & Msimango-Galawe, 2023). Firms’ orientation towards digitalization recently enables them in organizational learning and information sharing, which is essential in business continuity (Neligan et al., 2023). Despite the contribution of digital orientation to businesses (SMEs), Watson et al. (2018) pointed out resource scarcity, financial resources, and government policies as the main challenges faced by businesses (SMEs). At the same time, Taiminen & Karjaluoto (2015) identified financial constraints, lack of human resources, and lack of technical know-how as the other barriers to organizational digital orientation. In addition, previous studies have found that social, market, and organizational drivers play a significant role in firms’ digital orientation (Li & Shao, 2023).

Although SMEs face challenges in adopting digital orientation (Biggiero, 2006; Parviainen et al., 2022), other scholars have buttressed the point that digital orientation is beneficial for SMEs and thus facilitates organization and communication (Garzoni et al., 2020; Salih et al., 2024). In SMEs’ quest to succeed, Ketchen et al. (2007) reveal the need to adopt conscious behaviors that tailor the attributes of the contemporary market they are in Theodosiou et al. (2012), including investing in the resource capacities of the firm. In turn, these behaviors are guided by the organization’s strategic and operational orientation. Graf et al. (2019). The majority of businesses in developing economies including Ghana can be categorized under SMEs. Given this, the primary question of how organizations can succeed in the digital environment requires a comprehensive understanding of the antecedents that best equip organizations to compete in a digital environment, and what conditions consequently support the development of that orientation (attitude towards digital orientation integration). Since innovative SMEs are essential for long-term economic success in this region (Abubakar et al., 2019), it is critical to have a better knowledge of the perceptions and impeding factors associated with the promotion of digital orientation in such settings.

Past literature has focused on digital adoption and utilization among SMEs in both developed and emerging economies (Capello et al., 2022; Vrontis et al., 2022) and digital transformation (Abudaqa et al., 2022, Albukhitan, 2020; Kim & Lee, 2021; Li & Shao, 2023). However, a few empirical studies have been conducted on drivers of digital orientation in the SME context (Bendig et al., 2023; Beutel et al., 2019; Li et al., 2021); thus, this study seeks to identify the drivers of digital transformation among service-based SMEs. Investigate the organizational drivers of digital orientation from the SMEs in the emerging economies perspective. Moreover, given the significant contribution of SMEs to the economic growth of emerging economies, the current study focused on service-based firms in Ghana to specifically assess what drives them to adopt digital orientation and how it shapes their operational objectives, since questions relating to how digital orientation shapes service-based firms also remain unanswered (Buera & Kaboski, 2012; Ngai & Petrongolo, 2017), hence a call for further investigation (Suppatvech et al., 2019). The study therefore addresses this question by building on the work of Barney, 1991 (using a resource-based view) to explore how the capability of organizations to create or acquire these resources affects their performance and competitiveness over their competitors in the industry.

The contributions of this study to digital entrepreneurship and strategic management literature focusing particularly on SMEs are four-fold. First, despite the economic importance of SMEs globally, little is known about the antecedents, consequences, and challenges of SME digitalization (Eller et al., 2020), hence the study augments the few existing literature on digital orientation and SMEs in emerging economies context. Second, previous literature has argued for enriching the resource-based view (RBV) by accounting for digital resources (Bharadwaj et al., 2013) so by building on the fresh perspective on the RBV for the digital age (Kindermann et al., 2021), we also add our voice to the notion that SMEs will be able to generate competitive advantage by focusing on exploiting the benefits of applying digital technologies (Barney, 1991; Ladeira et al., 2019; Muhos et al., 2019). Third, the study contributes to current SME research to better comprehensively understand impeding factors associated with the promotion of digital orientation among service-based SMEs, by strengthening the basis for understanding digitalization as a resource through the lens of the RBV. Finally, the findings of this study will help service-based SME managers and policymakers better understand the value of this organizational resource- digital technologies and how to integrate digitalization with other factors to help create a competitive advantage for these firms. Knowing this will also reduce the risk, time, and cost of a SMEs’ digitalization process (Pfister & Lehmann, 2021; Ramdani et al., 2022).

The remainder of the paper is structured as follows. The next section reviews the key literature to establish our theoretical background and hypotheses. We then explain the methodology for our empirical research before we present and explain our results, particularly about extant literature. Finally, we discuss our main contributions and results, research limitations, and possible avenues for further research.

2. Theoretical background

Strategic orientations, such as market orientation (Slater & Narver, 1999), learning orientation (Sinkula et al., 1997), and entrepreneurial orientation (Lee et al., 2019), have been extensively studied as individual or complementary sources of competitive advantage for firms (Schweiger et al., 2019). Nonetheless, organizations increasingly incorporate digital aspects in their strategy and strategizing (Bharadwaj et al., 2013; Mithas et al., 2013). Therefore Quinton et al. (2018) proposed a digital orientation that leverages the combination of market orientation, entrepreneurial orientation, and learning orientation to help take advantage of the opportunities presented by digital technologies. Thus, digital orientation is an organization’s guiding principle to pursue digital technology-enabled opportunities to achieve competitive advantage (Kindermann et al., 2021). However, whether this presents an opportunity or a challenge for small and medium organizations depends on how these organizations approach it, strategically (Quinton et al., 2018). Still, our understanding of how organizations build and benefit from a digitally enabled strategic orientation remains surprisingly incomplete (Kindermann et al., 2021). Besides, extant literature lacks holistic concepts that capture an organization’s strategic orientation concerning digital innovation and transformation initiatives (Firk et al., 2021; Kindermann et al., 2021).

2.1. The Resource-Based View (RBV)

As one of the most widely accepted theories of management (Barney et al., 2001; Davis & DeWitt, 2021; Kellermanns et al., 2016; Newbert, 2007), the resource-based view (RBV) claims that if an organization has and uses resources and capabilities that are valuable, rare, inimitable, and non-substitutable, it can strengthen its competitive position (for instance in terms of costs, quality, or further factors for differentiation (Barney, 2001; Newbert, 2008)). Understanding how different resources interact and how resources might be combined to retain competitive advantage is the goal of the RBV (Barney, 2001; Peteraf, 1993). According to Amit and Schoemaker (1993), resources are the factors owned or controlled by the firm and capabilities are the firm’s capacity to deploy those resources. The RBV assumes that organizational resources are composed of tangible and intangible assets that a firm uses to develop and implement strategies aimed at improving efficiency and effectiveness (Barney, 1991). Against this backdrop, intangible organizational resources, and capabilities such as digital orientation, if effectively exploited, should facilitate the development of competitive advantage, and thereby improve performance (Ferreira et al., 2019). Therefore, researchers have called for the examination of diverse firm types with differing resource endowments to test RBV’s assertion that unique resources influence organizational outcomes (Endres et al., 2022; Kraus et al., 2023).

Quite recently, RBV has been used to study how three orientations (market, entrepreneurial, and learning) can improve firm performance in SMEs (Lonial & Carter, 2015), SMEs’ transitioning to more sophisticated stages of industry 4.0 (Estensoro et al., 2022), the impact of three main SME resources-information technology, employee skills, and digital strategy on digitalization (Eller et al., 2020), resources to support SMEs’ internationalization via digital channels (Elia et al., 2021), SMEs’ ICT use and firm performance (Karim et al., 2022; Pfister & Lehmann, 2021) among others. In low digitalized economies, the application of innovation and sophisticated technologies in service-based firms’ operations remained underused (see Davis & DeWitt, 2021; Zahra, 2021). The current study, therefore, takes inspiration from the lens of RBV to strengthen the present argument that; for digital technologies to be fully integrated into modern service-based firms in a developing context, the resistance to its adoption, hitherto, must be unearthed for a strategic management consideration from the viewpoint of technology developers to technology users (service-based firms). Thus, this study synthesizes resource availability (in the case of digital technologies) as a critical success factor for firms’ competitiveness, performance, and sustainability.

2.2. SMEs and digitalization

SMEs appear to be underutilizing the full potential of new digital tools, failing to capitalize on the opportunities they provide (Taiminen & Karjaluoto, 2015). SMEs, particularly in developing countries, have been particularly hard hit by the COVID-19 outbreak, owing to their limited use of digital technologies (Bai et al., 2021). Regardless, SMEs use digital technologies to improve customer communication and information processing (Harrigan et al., 2011; Kendall et al., 2001; Tse & Soufani, 2003), increase operational efficiency (Borges et al., 2009; Pfister & Lehmann, 2021), and expand their businesses (Bhaskaran, 2013). Furthermore, technology can help SMEs obtain new organizational structures and improve organizational structure both between and within organizations (Tan et al., 2009; Peña et al., 2011). With social media, digital technologies can also help an SME extend its value proposition and manage customer relationships (Ainin et al., 2015; Wang et al., 2016) and business networking (Bocconcelli et al., 2017). SMEs may also thrive in a digitalized organizational environment because digital technology facilitates intelligence gathering, cost reduction, and audience expansion (Borges et al., 2009; Harrigan et al., 2011). SMEs, on the other hand, may struggle to adapt to changes due to a lack of technical or marketing expertise (Nguyen et al., 2015; O’Toole, 2003).

Given the importance of SMEs in the economy (EG, 2013; Matthews et al., 2017), particularly during periods of dramatic structural change (Carsrud & Cucculelli, 2014), it is critical to explore how service-based SMEs are constrained with full integration of digital orientation given the evolution of digital technologies. Scholars have generally highlighted the novel challenges that businesses face when embarking on digitalization initiatives (e.g. Yoo et al., 2012). Specifically, SMEs face challenges in implementing Industry 4.0 (Estensoro et al., 2022). The lack of experience in SMEs has been identified in Industry 4.0 research, particularly in terms of a limited number of roadmaps, maturity models, frameworks, and readiness assessments that reflect the specific resources of SMEs (Estensoro et al., 2022; Mittal et al., 2018; North et al., 2020). Although SMEs lack the required knowledge, they need to utilize new technologies/methods such as the Internet of Things (IoT) and artificial intelligence (AI) to stay competitive (Hansen & Bøgh, 2021). Figure 1 presents the conceptual framework for the study.

Figure 1. Conceptual framework.

3. Related works and hypotheses development

3.1. Digital Orientation

Digital orientation refers to an organization’s ability and willingness to adapt to and leverage digital technologies in its operations, strategies, and overall business practices (Kindermann et al., 2021). It involves developing a mindset and adopting behaviors that align with the digital transformation process (Saunila et al., 2021). Digital orientation encompasses understanding the potential of digital technologies, embracing innovation, and utilizing digital tools and platforms to enhance productivity, efficiency, customer experience, and overall business performance. Following Kindermann et al. (2021) perspective of digital orientation, this study construes the phenomenon as an organization’s study toward digital innovation integration. It has been proposed that attitude toward digital innovation integration shapes SMEs’ adoption of digital orientation (Iliescu, 2020). Saunila et al. (2021) argued that firms that have a positive attitude toward digital innovation and have a well-presented digital strategy are likely to embrace digital orientation.

Furthermore, firms that embrace digital orientation are rapid in responding to newly informed customers and achieving sustainable growth (Theodosiou et al., 2012; Wang et al., 2018). Mehrtens et al. (2001) pointed out that the decision to embrace digital orientation is influenced by certain factors including attitude toward digital innovation. In the context of underdeveloped countries, Beckinsale et al. (2006) evidenced that attitudes toward digital innovation have a major influence on digital orientation among SMEs. Moreover, Mubarak and Petraite (2020) highlighted that attitudes toward digital innovation integration have been shown to significantly impede the adoption of digital orientation. It was observed that attitude toward digital innovation may be a menace to SMEs since they have limited resources and financial challenges, which ultimately affect the digital orientation (Khrais & Alghamdi, 2022). Oni and Papazafeiropoulou (2014) also argued that a lack of understanding directly affects the attitude toward digital innovation and its effective application. SME managers’ negative attitude towards digital innovation may influence their willingness to adopt digital orientation (Peltier et al., 2009). Although the perspective of digital orientation varies as presented by extant studies (Quinton et al., 2018; Khrais & Alghamdi, 2022), the decision to integrate emerging technologies among SMEs is contingent on factors such as the availability of IT infrastructure and commensurate investments, technical and managerial skill to manage the technology integration process (Ardito et al., 2021; Liu et al., 2022; Ramdani et al., 2022; Zhang et al. (2023).

3.2. IT infrastructure availability

The availability of IT infrastructure is essential to formulating a digital orientation strategy (Carlan et al., 2017; Wang & Cheung, 2004). Thus, the information technology infrastructure facilitates the effective implementation of digital orientation (Lucchetti & Sterlacchini, 2004). Extant literature has highlighted the essence of IT infrastructure in the implementation of successful digital orientation in an organization (Ardito et al., 2021; Chavez et al., 2022, Khrais & Alghamdi, 2022). Omrani et al. (2022) argued that the availability of ICT infrastructure has had a profound impact on digital orientation implementation. The study by Ardito et al. (2021) indicated that the implementation of digital orientation based on sound infrastructures supports innovation performance (Ardito et al., 2021). However, Fichman et al. (2014) posit that adoption and utilizing digital orientation is challenging due to poor infrastructural facilities such as ICT infrastructure and other technical dynamism, particularly in underdeveloped countries. Botta et al. (2016) further argued that limited IT infrastructural development hinders digital innovation among firms, especially SMEs. According to Tan and Teo (2000), Estensoro et al. (2022), SMEs’ inability to adopt digital orientation is mainly due to inadequate IT infrastructure, especially in under-developed countries. It has been observed that countries with good IT infrastructure support have the potential to embrace the digital orientation (Ling, 2001; Kenneth et al., 2012), thus providing opportunities for small and medium enterprises (Nambisan et al., 2019; Trinugroho et al., 2022). Thus, this study hypothesizes that;

H1: The availability of IT infrastructure will positively impact managers’ and employees’ attitudes toward the integration of digital innovations in service-based SMEs.

3.3. Digital Innovation Investment

Recently, firms are increasingly investing in digitalization as a strategic priority, aiming at achieving competitive advantage due to market dynamics to remain competitive (Davenport & Westerman, 2018; Nwankpa & Datta, 2017). Businesses invest in digital innovation to aid business processes and perform other organizational functions (Liu et al., 2022; Nwankpa & Merhout, 2020). In the background of Nwankpa and Merhout (2020), digital innovation investment was described as ‘a firm’s strategic technology investment for exploring how cutting-edge digital technologies could potentially differentiate the firm’s business, transactions, and operations’. It was also pointed out that investment in the Internet of Things (IoT), big data analytics, artificial intelligence (AI), and social media applications is what is termed digital investment (World Economic Forum, 2018).

Regardless, digital innovation investments remain complex and unpredictable in the competitive marketplace digital technologies increase the complexity, turbulence, and dynamism in the competitive landscape (Fang & Repnikova, 2022; Nan & Tanriverdi, 2017). This presents a major challenge for firms especially SMEs in investing in digital innovation, thus affecting their adoption of digital orientation (Mocker et al., 2014). In addition, Vial (2021) argued that SMEs lack digital technologies initiatives and good organizational conditions which are prerequisite requirements for digital innovation investment. In this study, we argue that digital innovation investment impedes SMEs from successfully implementing digital orientation for business processes and competitiveness. Thus, the study hypothesizes that;

H2: Digital innovation investment will positively influence managers’ and employees’ attitudes toward the integration of digital innovations in service-based SMEs.

3.4. Digital innovation management

According to Nambisan et al. (2017), digital innovation is the ‘use of digital technology during the process of innovating’. Scholars have argued that digital innovation can be either a process or an outcome (Fichman et al., 2014; Henfridsson & Lyytinen, 2010). Nambisan et al. (2017) further described digital innovation management as the practices, processes, and principles that underlie the effective orchestration of digital innovation. In this study, we argued that digital innovation management is dynamic and complicated, hindering SMEs from embracing digital orientation. Digital innovation management is perceived to be a complex and interrelated process in its implementation (Gebhardt et al., 2006). This implies that the complex nature of digital orientation creates greater mistrust about SMEs’ successful application, hence hindering their decision to adopt digital orientation (Roy et al., 2016).

Due to the financial and limited resource constraints in the context of SMEs, implementing complex and interrelated processes, especially digital orientation becomes challenging (Nambisan et al., 2017, 2019) since human and other resources are required to carry out digital orientation strategy (Ardito et al., 2021; Johri et al., 2022). Ramilo and Embi (2014) study focused on the key determinants and barriers to digital innovation adoption. Their study sampled data from architectural organizations and concluded that the complex nature of the digital innovation management process and financial barriers were highlighted as the main challenges faced by small and medium-sized architectural organizations. Moreover, other studies have highlighted SMEs’ inability to integrate digital orientation due to the risk level of innovation (D’Este et al., 2012; Lee et al., 2010; Setkute & Dibb, 2022). Hence, the study proposes that,

H3: Digital innovation management will positively affect managers’ and employees’ attitudes toward the integration of digital innovations in service-based SMEs.

3.5. Knowledge of digital innovation

The knowledge of digital innovation is a strong determinant of digital orientation (Shen et al., 2022). Lim (2018) highlights the vital role played by digital Knowledge in digital orientation. To adopt and implement digital orientation, Van Gestel, 2021 and Firk et al. (2022) recently postulate that knowledge and knowledge of digital innovation positively impact digital orientation in an organization. In addition, acquiring knowledge and competence expedites digital orientation within an organization (Day, 2011). Specifically, willingness to innovate and grow challenges leaders in an organization to open to digital technologies and exploit the opportunities they present (Jones et al., 2014). However, it has been argued that limited knowledge of digital orientation may be detrimental to its adoption and implementation by firms (Quinton et al., 2018). As a result, SMEs are found to have limited resources and limited knowledge of the adoption of digital orientation, thus affecting its implementation and utilization (Selase et al., 2019). Bengtsson et al. (2007) opine that limited knowledge affects the decision to adopt a digital orientation for SMEs. A study conducted by Shelton and Archambault (2018) focused on electronic marketing orientation among SMEs and witnessed that knowledge of digital technologies is critical to developing digital orientation competence in the SMEs context. Thus, SME managers’ commitment to digital orientation may be impaired if they have little knowledge of digitalization (Chibelushi & Costello, 2009; Ramdani et al., 2022). Following the above discussion, the study hypothesizes that;

H4: Knowledge of digital innovation will positively influence managers’ and employees’ attitudes toward the integration of digital innovations in service-based SMEs.

H5: Managers’ and employees’ level of knowledge of digital innovation will positively affect digital innovation management.

3.6. IT competencies

According to Sambamurthy et al. (2003), IT competence is generally regarded as essential to digital orientation. IT competence can be described as the application and effective use of IT in an organization. Di Vaio et al. (2021) highlighted the relevance of IT infrastructure quality, IT investments, and IT human capital in digital orientation competence within an organization. IT competence facilitates and provides the foundation for the effective application of digital orientation. Studies have established that firms with higher IT competence levels are perceived to achieve competitive advantage and business growth (Ramos et al., 2022; Teng et al., 2022). With this, investing in IT competencies can develop distinctive firms’ capabilities, hence improving firm performance (Mahdi, 2019). Stich et al. (2020) observed that SMEs need a comprehensive approach to successfully implementation of digital orientation. Nonetheless, owing to the small nature of SMEs, Zhang et al. (2023) argued that, SMEs faced insufficient capabilities, limited resources, and limited IT competencies which accounts for their reasons for their failure to successfully implement digital orientation. Further to this, scholars (Peillon & Dubruc, 2019; Stentoft et al., 2021; Urbach & Röglinger, 2019) also indicated that SMEs lack the requisite expertise and IT know-how to implement digital orientation. In line with this, the authors conceptualize IT competencies as one of the factors that impede SMEs from effectively applying digital orientation. Thus, the study hypothesizes that;

H6: Managers’ and employees’ knowledge of digital innovation will positively impact their IT competence.

H7: Managers’ and employees’ IT competence will positively affect their attitude toward the integration of digital innovations in service-based SMEs.

4. Methodology

4.1. Study context, sampling, and data collection

The literature on entrepreneurship recognizes the significance of digital technology, yet there is still limited understanding of how much it affects a country’s entrepreneurial activities (Berman et al., 2023; Zhang et al., 2023;). In light of this, we examined hypotheses within the context of SMEs by collecting data from a Ghanaian setting. The achievements of the SME sector in Ghana have long been acknowledged (Kayanula & Quartey, 2000). Despite COVID-19’s negative impact on the nation, Ghana’s economy expanded by 5.4% in 2021, with the services sector driving growth (Asare, 2022). The services sector, contributing 49% to Ghana’s GDP in 2021, saw expansions in ICT, health, and education services, among others (US International Trade Administration, 2022). According to the Ghana Statistical Service (2018), the bulk of business activities in the services subsector involve trading (wholesale and retail trade). However, SMEs in Ghana face challenges limiting their ability to expand, as revealed by Ayyagari et al. (2017). Although these challenges have been extensively examined in the literature with various solutions proposed (Donbesuur et al., 2020; Mamman et al., 2019), they have primarily focused on SMEs in general. Seidel-Sterzik et al. (2018) have proposed a sector-based strategy to address SME challenges, hence our focus on service-based SMEs in Ghana.

For the study’s participants and responders, the researchers chose convenience sampling, a non-randomized technique. This type of sampling has been widely adopted in recent studies (Haris et al., 2022; Hatammimi & Purnama, 2022; Walmsley et al., 2023) due to its low cost, simplicity, and accessibility of subjects. Data was collected from managers and employees of selected service-based SMEs in the Ghanaian economy. The choice of such respondents was based on their in-depth knowledge, possession of relevant information, and constant use of digitalization for various purposes.

A structured questionnaire was created and disseminated among service-based firms. To facilitate responses, the questionnaire was designed in two sections (demographics and study constructs) and distributed via Google Forms through respondents’ emails and other prescribed social platforms. The online Google Forms were limited to one respondent to avoid duplicate responses. An offline approach was also adopted, where hard copies of the questionnaires were administered to respondents on their office premises during break times, with most of the offline questionnaires received later.

As a matter of ethics, permission was obtained from chosen firms via emails asking for authorization to start data collection. A pilot study involving 60 respondents was conducted to ascertain the validity of the research constructs using Cronbach’s alpha values. Results from the pilot study indicated that the researchers could proceed with the main study, as Cronbach’s alpha values met the minimum threshold of 0.5 (Hair et al., 2019). The researchers spent six months, from January 2023 to June 2023, soliciting information (data collection), during which each respondent was expected to spend an average of ten to twelve minutes answering the questionnaire. Out of the 568 questionnaires administered, 502 responses were received (both online and offline versions).

In total, 502 responses were received, but 472 responses representing 83.10 percent were appropriate for data processing/analysis. Thirty valid responses were deemed unfit due to anomalies, inequalities, discrepancies, etc. Though, 302 valid responses were from the offline method, while 170 were from the Google form/link. According to Hair et al. (2019), a quantitative study with a valid response of over 300 is deemed appropriate for processing/analysis, and this study meets that criterion.

4.2. Analytic techniques

Partial Least Square Structural Equation Modeling (PLS-SEM), particularly Smart PLS (version 4), was adopted as the main statistical software for running and analyzing the data, determining the research model, and testing the proposed hypotheses. Smart PLS is an intuitive program for confirmatory composite analysis and composite-based structural equation modeling, offering an easy-to-use approach with a quick-to-learn graphical user interface. Table 1 depicts the participants’ details of the study.

Table 1. Participants’ details.

Details	Groups	Frequency	Percentage
Age	20–30years	142	30.08
	31–40years	177	37.50
	41–50years	101	21.40
	51 above	52	11.02
Gender	Male	302	63.98
	Female	170	36.02
Academic Qualifications	Cert/Diploma/HND	105	22.26
	Degree	195	41.31
	Masters/PhD	95	20.18
	Others	77	16.31
Work Experience	1–5years	189	40.04
	6–10years	145	30.72
	15 years or more	138	29.24
Employees Size	Micro (1–10) employees	65	13.77
	Small (11–60) employees	185	39.19
	Medium (61–100) employees	141	29.87
	Large (above 100) employees	81	17.16
Industry Categories	Financial Service sector	289	61.23
	Non–Financial service	183	38.77
Respondents Segmentation	Finance Department	75	15.89
	Marketing Department	86	18.22
	Customer Service Department	130	28.26
	Operations Department	132	27.54
	Others	49	10.38
Sample	Total	472	100

Source: (field data from January to June 2023).

4.3. Measurement of the constructs

To measure the study constructs, the researchers adopted the five-point Likert scale approach ranging from 1 completely disagree, 2 disagree, 3 neutral, 4 agree, and 5 completely agree. It is important to highlight that the five-point Likert has been used by most researchers and scholars recently (Alrawad et al., 2023; Kim, 2022; Kuceba et al., 2021; Rachmawati et al., 2021) since it offers the opportunity to ascertain the level of respondent’s opinions and understanding on the subject matter. The study constructs were adapted from previous literature: Availability of IT Infrastructure (Buyana et al., 2014; Miller & Spoolman, 2014), Digital Innovation Investment (Ericson et al., 2016; Egala & Afful-Dadzie, 2022), Digital Innovation Management (Haseeb et al., 2019; Chan et al., 2018; de Mello & Ter-Minassian, 2020), Knowledge of Digital Innovation (Su et al., 2014; Vaterlaus et al., 2015), IT competencies (Amoah et al., 2023; Zhang et al., 2023), and Attitude toward Digital Innovation Integration (Kindermann et al., 2021; Quinton et al., 2018). The ordinal scale was adopted in measuring the constructs. The ordinal scale was chosen because it assesses how strongly the respondent feels about the constructs under consideration. Tables 2 and 3 depict how the various constructs were measured. It is quite important to highlight that the study’s constructs were adapted and modified from previous studies to suit the researchers’ study context.

Table 2. Test of validity and reliability research constructs.

Constructs	Cronbach’s Alpha	Jöreskog’s rho (ρc)	Composite Reliability	Average Variance Extracted (AVE)
Attitude toward Digital innovation integration	0.795	0.803	0.866	0.619
Knowledge Digital Innovation	0.704	0.758	0.833	0.629
IT Competencies	0.814	0.721	0.709	0.452
Availability of IT Infrastructure	0.823	0.835	0.884	0.657
Digital Innovation Investment	0.778	0.852	0.866	0.686
Digital innovation management	0.701	0.699	0.809	0.514

Source: Field data (January–June 2023), retrieved from Google form and offline.

Table 3. Construct items, loading factor, and Variance Inflation Factor (VIF).

Construct	Indicator	Loading	VIF
Availability of IT Infrastructure (AIT)	AIT1: My organization has firm-wide or business unit applications and databases.	0.844	2.139
	AIT2: My organization has business-unit-specific applications, usually on a chargeback or contractual basis.	0.850	2.084
	AIT3: My organization has the electronic provision of management information e.g. EIS or DSS	0.849	1.978
	AIT4: My organization has a firm-wide communication network services; e.g. LAN and wireless.	0.687	1.380
Digital innovation investment (DII)	DII1: My organization has a strong emphasis on projects on unique, one-of-a-kind approaches rather than revisiting tried and true approaches used before.	0.695	1.412
	DII2: My organization always tries a unique way when learning new things rather than doing it as everyone else does.	0.881	1.890
	DII3: My organization favors experimentation and original approaches to problem-solving rather than using methods others generally use for solving their problems	0.895	1.783
Digital innovation management (DIM)	DIM1: My organization always co-creates with customers to solve important problems.	0.719	1.507
	DIM2: My organization firm has an efficient and flexible approach to development projects.	0.731	1.703
	DIM3: My organization implements a profitable digital business.	0.686	1.082
	DIM4: My organization makes quick consistent and clear digital business decisions.	0.732	1.597
Knowledge of digital Innovation (KDI)	KDI1: We are committed to using digital technologies in developing our new solutions.	0.631	1.207
	KDI2: New digital technology is readily accepted in our organization.	0.871	1.656
	KDI3: We always look out for opportunities to use digital technology in our innovation.	0.855	1.581
IT competencies (ITC)	ITC1: My organization optimizes the use of external digital resources.	0.714	1.059
	ITC2: My organization ensures proactive awareness of trends and relevant opportunities.	0.747	1.065
	ITC3: My organization is adaptable to digital transformation	0.637	1.073
Attitude Towards Digital Innovation Integration (ATD)	ATD1: My organization is happy at the prospect of this change.	0.773	1.516
	ATD2: My organization thinks that the changes arising from this innovation program will be stimulating.	0.740	1.808
	ATD3: This change will probably enable me to work better.	0.853	2.203
	ATD4: My organization believes that this innovation program can contribute to improving unsatisfactory work situations.	0.778	1.565

Source: Authors’ processing from SmartPLS 4.0 software.

4.4. Test of common method variance

Common Method Variance (CMV) is described as the ‘variance that is attributed to the measuring procedure rather than to the construct of interest (Bagozzi & Yi, 1988). According to Richardson et al. (2009), CMV is a ‘systematic error variance shared among measured variables with and added as a function of the same method and source. The researchers realized the possibility of common method variance since the data collection was done independently. Also, the study’s respondents were informed that their answers would remain secret as there was no right or wrong way to answer each of the survey’s questions. According to Bagozzi et al. (1998), the researchers developed the survey by the specification on the frontispiece and addressed respondents or participants with absolute conviction after discovering the existence of Common Method Bias (CMB). To be more specific, the survey was developed such that participants could decide to opt-out whenever they wished. Again, it was extremely important to determine the presence of Common Method Bias (CMB). This was done through the test of variance inflation factor (VIF). Since such criteria are fewer than ten (10) according to the post-hoc study findings, CMV only has a minor prevalence predicated on VIFs (see, Table 3) (see Kock & Hadaya, 2018; Salmeron Gomez et al., 2020). Therefore, the CMB poses less of a threat because the difficulties with the CMB in this survey are considered to be minimal.

5. Model measurement

5.1. Reliability test and Cronbach’s alpha

Testing for validity and reliability has always been recommended when assessing the capacity of an instrument for gathering data. The reliability was determined using Cronbach alpha and composite reliability, whereas the validity was determined using the average variance extracted (Hair et al., 2012). As suggested, the reliability of each statement on the related construct is examined (Hair et al., 2012). Leveraging on Dijkstra-rho Henseler’s and Cronbach’s alpha coefficients was the most effective way to examine construct reliability and validity since the researchers were spurred by the PLS-SEM literature (Bagozzi & Yi, 1988; Hair et al., 2019). The reality that all threshold values were greater than 0.5 in Table 2 illustrates the robust coefficients of construct constancy determined by Bagozzi and Yi (1988); Hair et al. (2019) apart from IT Competencies that fall below the minimum threshold. The predictive validity of the constructs and enabling items were evaluated using PLS-SEM version 3.3. To be acknowledged as a useful metric to assume construct reliability, the minimum value of 0.5 for Average Extracted Variance (AVC) and Cronbach alpha’s value of 0.7 must be assigned (Bagozzi & Yi, 1988). Furthermore, per the PLS-SEM estimations, the values met the specified cut-offs, demonstrating the reliability of the research constructs they were predicated on. Both Jöreskog’s rho (pc) and Composite reliability values exceeded the necessary thresholds of 0.7 and 0.8, respectively. The average variance extracted (AVE) demonstrated convergent validity with a minimum threshold of 0.5. At the same time, composite reliability provided the outcome, with a minimal reliability coefficient of 0.709 and a maximum of 0.884 (see Table 2).

The indicator loadings of the latent constructs, on the other hand, were thoroughly considered and stuffed to their corresponding constructs. According to Baggozzi and Yi (1988), factor loadings with a threshold of above 0.6 is regarded as the best. Moreover, all the estimated values of the current study met the minimum threshold. This means that the loadings values were in good standing with a minimum of 0.631 and a maximum of 0.895 as shown in Table 3. As a result, Table 3 presents an overview of all study constructs, associated items, and the corresponding loadings (coefficients) (Table 4).

Table 4. Test of discriminant validity – fornell-larcker criterion.

S/N	Constructs	1	2	3	4	5	6
1	Attitude toward Digital innovation integration	0.787
2	Knowledge of Digital Innovation	0.266	0.793
3	IT Competencies	0.442	0.448	0.673
4	IT Infrastructure Availability	0.593	0.425	0.497	0.811
5	Digital Innovation Investment	0.405	0.226	0.382	0.409	0.829
6	Digital Innovation Management	0.305	0.340	0.519	0.248	0.408	0.717

Source: processing from Smart PLS 4 software. The diagonal (in bold) is the average variance extracted (AVE).

A recognizable and commonly employed technique for evaluating the discriminant validity of measurement models is the Fornell-Larcker criterion as seen in Table 2. All the same, Fornell-Larcker’s (1981) criterion was applied in determining the construct’s discriminant validity to establish whether there were any latent variables with discriminant validity (Henseler et al., 2015). It is essential to point out that the AVE values in the vertical (in bold) of Fornell Larcker’s Table 5 indicate tested constructs, and experts urge that these values be more than 0.5 (see Hair et al., 2019; Henseler et al., 2015). Yet, to show discriminant validity, each construct’s AVE should have a larger coefficient at both the column and row location than other constructs. The outcome demonstrates that the constructs meet both fundamental and strict presumptions, establishing discriminant validity.

Table 5. Hypothetical path coefficient -PLS-SEM.

Constructs	Original sample	Sample mean	Stand. Dev	T-Stat	P-Values	Decision
H1: IT Infrastructure availability → Attitude toward Digital innovation integration	0.471	0.469	0.065	7.283	0.000	Accepted
H2: Digital Innovation Investment → Attitude toward Digital Innovation Integration	0.140	0.147	0.062	2.273	0.023	Accepted
H3: Digital Innovation Management → Attitude toward Digital Innovation Integration	0.077	0.077	0.079	0.976	0.330	Rejected
H4: Knowledge of Digital Innovation → Attitude toward Digital innovation integration	−0.054	−0.056	0.058	0.933	0.351	Rejected
H5: Knowledge of Digital Innovation → Innovation Management	0.340	0.345	0.057	5.923	0.000	Accepted
H6: Knowledge of Digital Innovation → IT Competencies	0.448	0.454	0.045	9.897	0.000	Accepted
H7: IT Competencies → Attitude toward Digital Innovation Integration	0.138	0.138	0.076	1.804	0.072	Rejected
		R^2	Adjust. R^2
Attitude toward Digital innovation integration		0.407	0.396
IT Competencies		0.200	0.197
Innovation Management		0.116	0.112

Source: Author’s processing from SmartPLS version 4.0.

5.2. Structural modeling-path analysis

The researchers also concluded that path analysis is required following model fit evaluation. Since it shows how the study constructs highlighted in the analysis relate to one another, this analysis is crucial. From Table 5, it is deduced that four of the proposed hypotheses of the current study have a significant effect on the dependent variable (attitude towards digital innovation integration) while three of the hypotheses do not have a significant effect on the dependent variable (attitude towards Digital innovation integration). In addition, the table below shows the coefficient of determination, Beta, and significant values, T-values greater than 1.96 (P-values 0.05). The regression model’s coefficient of determination (R²) was used to assess the predictive capacity of the research constructs. The coefficient indicates the proportion of the dependent variable’s variance that can be assigned to the independent (predictor) variable. In terms of the study model’s capacity for prediction, the coefficient of determination (R²) of the regression model was assessed. The Adjusted R² displays how much of the variance in the endogenous construct is explained by the external constructs. As a result, the R² of the predictor variable, which is 40%, 20%, and, 11% are appropriately displayed in Table 5 below and in Figure 2.

Figure 2. Estimated research model. Source: Authors’ processing from SmartPLS 4.0 software.

6. Discussion

Digital service innovation is a paradigm shift in technological innovation that can improve service-based firms’ performance, especially in the financial and non-financial industries. While these technologies complement traditional sources of innovation, they help increase the institution’s profit margins, especially in business-to-business contexts with long product life spans. However, some service-based firms, especially in developing countries, may exhibit a deficit of digital orientation due to impaired resources. It is based upon this study contends that these inhibiting factors are a bane to the performance of service-based SMEs. Based upon that the study made some propositions.

First, the study hypothesized that the availability of IT infrastructure will positively impact managers’ and employees’ attitudes toward the integration of digital innovations in service-based SMEs. This hypothesis was accepted. The acceptance of this hypothesis suggests that the availability of IT infrastructure has a significant influence on managers’ attitudes toward integrating digital innovations in service-based SMEs. Consistent with extant studies (Ardito et al., 2021; Chavez et al., 2022, Khrais & Alghamdi, 2022; Omrani et al., 2022), IT infrastructure underlies the technological foundation that supports an organization’s digital operations. Trinugroho et al. (2022) opine that, when IT infrastructure is readily available, managers are more likely to have a positive attitude toward the integration of digital innovations. Omrani et al. (2022) study concludes that the availability of IT infrastructure plays a pivotal role in shaping digital innovation strategies in SMEs. This finding emphasizes that a robust IT foundation positively influences the adoption of digital technologies. In other words, a robust IT infrastructure provides the necessary resources, tools, and capabilities to implement and support digital initiatives effectively (Ardito et al., 2021). While research recognizes the importance of digital technologies, El-Haddadeh (2020) contends that a firm’s competitiveness is not solely determined by the availability of IT infrastructure. Other factors, such as organizational culture, also play a significant role.

Following this, the study hypothesized that, digital innovation investment will positively influence managers’ and employees’ attitudes toward the integration of digital innovations in service-based SMEs which was also accepted. This implies that managers’ attitudes toward integrating digital innovations in service-based SMEs are influenced by their investment in digital innovation (Fang & Repnikova, 2022; Nan & Tanriverdi, 2017). The finding suggests that financial commitment to digital initiatives is positively associated with a proactive approach and positive attitudes among managers. Nwankpa and Merhout (2020) affirm that investment in digital innovation serves to strengthen a firm’s strategic technological initiatives aimed at improving how advanced digital technologies can potentially distinguish the firm’s business, transactions, and operations. Thus, managers’ attitudes are positively impacted when there is a substantial investment in digital innovation projects. The finding highlights that a dedicated investment approach fosters a culture of openness and adaptability This is because investing in digital innovation demonstrates a recognition of its importance and potential benefits, leading to a more favorable attitude toward its integration (El-Haddadeh, 2020). Contrary to the supporting literature, Radicic and Petković (2023) provide a nuanced perspective, suggesting that the impact of digitalization on innovation activities in SMEs is heterogeneous. While investment is recognized, the study indicates that the effects might be modest and vary across different SMEs.

The study hypothesized that digital innovation management will positively affect managers’ and employees’ attitudes toward the integration of digital innovations in service-based SMEs was however rejected. The rejection of this hypothesis suggests that digital innovation management does not significantly impact managers’ attitudes toward integrating digital innovations in service-based SMEs. Contrary to the study results, studies like (Nambisan et al., 2017, 2019) affirm that digital innovation management processes, strategies, and practices employed by management help facilitate the decision to integrate digital innovation within an organization. Johri et al. (2022) for instance add that effective management of digital innovation is important for successful implementation. Yet, the interpretation of this hypothesis may imply that it may not directly influence managers’ attitudes towards integration in contravention of the literature. Nonetheless, Endres et al. (2022) contend that the impact of digitalization on innovation activities is heterogeneous among SMEs. This implies that the effectiveness of digital innovation management may vary, leading to a rejection of a universal positive influence on managers’ attitudes.

Similarly, the hypothesis that Knowledge of digital innovation will positively influence managers’ and employees’ attitudes toward the integration of digital innovations in service-based SMEs was also rejected. This hypothesis suggests that managers’ attitudes toward integrating digital innovations are influenced by their knowledge of digital innovation. However, the rejection of this hypothesis indicates that knowledge of digital innovation does not have a significant impact on managers’ attitudes. It implies that managers’ attitudes are not solely dependent on their level of knowledge about digital innovation but may be influenced by other factors such as organizational context, resources, and strategic priorities. This contravenes the findings of Ramdani et al. (2022) which affirm that managers limited understanding of digital orientation significantly affects their motivation to innovate. Felicetti et al. (2023) also add that digital transformation and innovation in SMEs support the idea that a well-informed approach to digital transformation positively influences SMEs

On the other hand, the hypothesis, that managers’ and employees’ level of knowledge of digital innovation will positively affect digital innovation management was accepted and consistent (Van Gestel, 2021; Firk et al., 2022). This finding implies that managers’ level of knowledge of digital innovation influences the digital innovation strategies implemented by the management. When managers possess a higher level of knowledge regarding digital innovation, they are more likely to develop and implement effective digital innovation strategies (Selase et al., 2019). Prior studies (Day, 2011; Shaltoni et al., 2018) knowledge that the acquisition of knowledge on digital orientation plays a crucial role in shaping the direction and effectiveness of digital innovation strategies in service-based SMEs. The role of digital innovation in knowledge management systems emphasizes its crucial role in business governance, highlighting the relevance of digital innovation. Selase et al. (2019) conclude that the innovation effects of digitalization are modest, indicating a nuanced relationship between digitalization and innovation in SMEs.

Furthermore, the study hypothesized that managers’ and employees’ knowledge of digital innovation will positively impact their IT competence. The acceptance of this hypothesis suggests a profound relationship between a manager’s understanding of digital innovation and their ability to effectively navigate Information Technology (IT) in the context of business management. Di Vaio et al. (2021) contribute to the literature by investigating how the acquisition of knowledge, particularly in digital innovation, influences managerial competencies. The accepted hypothesis establishes a direct link between the depth of a manager’s knowledge in digital innovation and their IT competence. Ramos et al. (2022) support the notion that a manager’s IT competence extends beyond mere technical skills. It encompasses the manager’s capacity to understand, utilize, and effectively manage IT resources and technologies. This holistic perspective aligns with the evolving role of IT in modern businesses. The acceptance of the hypothesis implies that managers with a higher level of digital innovation knowledge are more likely to possess stronger IT competence. This, in turn, empowers them to leverage IT resources effectively. Stentoft et al. (2021) and Urbach and Röglinger (2019) corroborate this, emphasizing that such managers can navigate and utilize IT resources strategically.

Finally, the study hypothesized that managers’ and employees’ IT competence will positively affect their attitude toward the integration of digital innovations in service-based SMEs. The rejection of the hypothesis positing that managers’ IT competence influences their attitude toward integrating digital innovations in service-based SMEs prompts a nuanced exploration. Despite extant studies acknowledging the crucial role of IT competence in driving curiosity and mitigating integration challenges (Peillon & Dubruc, 2019; Stentoft et al., 2021), this hypothesis did not find support. Studies by Peillon and Dubruc (2019) and Stentoft et al. (2021) highlight the positive relationship between managers’ IT competence and their curiosity, emphasizing their role in overcoming integration challenges. However, the rejected hypothesis challenges the direct impact of IT competence on managers’ attitudes toward digital innovation integration. The rejection suggests that managers’ IT competence alone may not significantly impact their attitudes. Instead, other factors, such as organizational culture, leadership support, and resource availability, may wield more influence (Zhang et al., 2023). This aligns with the broader perspective that successful digital transformation involves a complex interplay of various organizational elements. Zhang et al. (2023) propose that a supportive organizational culture and leadership are pivotal in shaping managers’ attitudes. The rejection implies that these factors overshadow the direct contribution of IT competence in determining managers’ attitudes toward digital innovation integration.

6.1. Study implications

To adapt to the global business environment, service-based firms need to adopt behaviors that facilitate digital orientation and asset acquisition. Entrepreneurial firms, including SMEs, play a significant role in digital innovation, leveraging digital technologies to generate value and drive digital transformation. Integrating digital innovation capabilities is crucial for value creation in service-based firms, involving Big Data Analytics, Cloud Computing, and IoT to enhance managerial decision-making, information technology infrastructure, operational activities, and overall firm performance. This study makes a valuable contribution to both theoretical and practical domains by enhancing our comprehension of the factors that impede digital orientation among service-based small and medium enterprises (SMEs) in an emerging economy. The results of this study have the potential to provide valuable insights for policymakers, managers, and stakeholders, facilitating informed decision-making and promoting effective collaboration. Ultimately, these outcomes can contribute to the successful implementation and integration of digital technologies within these organizations.

This research investigates the barriers that impede the digital orientation of service-based SMEs in an emerging economy. By identifying and exploring these factors, this study seeks to shed light on the challenges faced by such enterprises in adopting digital technologies. The analysis can yield valuable insights regarding the challenges encountered by these firms in effectively adopting and integrating digital technologies. Gaining a comprehensive understanding of these obstacles is essential to developing effective strategies and interventions aimed at surmounting them and fostering digital orientation within SMEs. Through an analysis of the dynamic relationship between these orientations and their impact on digital orientation, this study aims to offer a comprehensive understanding of the various factors that influence the acceptance and incorporation of digital technologies within SMEs. In doing so, this study seeks to contribute to the existing body of literature on this topic. The study has the potential to enhance comprehension of the distinct obstacles encountered by service-oriented SMEs within these economies. Furthermore, the research endeavor can investigate potential variations in the obstacles impeding digital orientation between emerging economies and developed economies.

Theoretically, the study contributes to theoretical advancements in the field of digital transformation and SMEs by adopting the Resource-Based View (RBV) theory. The resource-based view (RBV) perspective provides a framework for examining how organizations can utilize their internal resources and capabilities to attain a competitive advantage by adopting a digital orientation. The study expands the application of the RBV theory within the specific context of digital orientation in SMEs. The role of a firm’s resource endowments, encompassing both tangible and intangible assets, in shaping its digital orientation can be demonstrated. The results of this study have the potential to enhance the existing RBV literature by emphasizing the significance of digital resources and capabilities in attaining a competitive advantage through the process of digital transformation.

Practically, the research findings have the potential to provide valuable insights for policymakers and other relevant stakeholders regarding the specific obstacles that impede the adoption of digital technologies among service-based SMEs in emerging economies. This acquired knowledge has the potential to inform the formulation of specific policies and the implementation of supportive initiatives that are designed to effectively tackle these obstacles. As an illustration, governmental initiatives may prioritize the provision of technical education, access to digital infrastructure, and financial assistance to assist SMEs in surmounting resource limitations and developing their digital competencies. Through the identification of the various factors that impede digital orientation, managers can actively devise strategies to effectively address and surmount these obstacles. For example, organizations can prioritize the cultivation of an environment that encourages and supports innovative thinking, enhance the digital literacy of their workforce, and forge strategic alliances to gain access to specialized digital knowledge and skills. The comprehension of these factors can guide decision-making and resource allocation to effectively facilitate digital transformation endeavors.

7. Conclusion

This study investigates the drivers that support the attitude toward digital orientation integration among service-based firms in a developing economy setting (Ghana). The study leveraged the RBV as the theoretical lens to formulate the study hypothesis. The study case was in Ghana and focuses on service-based firms specifically, the financial and non-financial SMEs. The choice of the case was motivated by the stern competition among businesses in this sector given the recent economic global austerities. Based on this, 472 management staff were sampled. Through convenience sampling, the data collected was analyzed using PLS-SEM. Based on the seven hypotheses formulated, four hypotheses were supported with three not supported. Specifically, the study found IT infrastructure and innovation investment to have a positive effect on management’s attitude toward digital innovation integration. Unfortunately, innovation management, knowledge of innovation, and IT competence did not affect management attitude toward the integration of digital innovation in SME operations. Based on the study outcome, it can be concluded that digital orientation integration into the operations of service-based SMEs is critical in enhancing their profitability and competitive advantage.

7.1. Limitations

This study has some limitations. First, the study focuses on service-based SMEs in the financial and non-financial sectors which limits the generalization of the study outcome. Perhaps future studies looking at other sectors of the economy and how digital orientation is integrated would be appropriate. Again, the RBV theory used for the study could also be a limitation especially when other theories could also be leveraged to explore similar phenomena. Thus, future studies could explore extending the theory or extending the RBV theory with other variables of interest in similar phenomena. Perhaps other relevant technology and organizational theories could be explored to investigate the phenomenon. Given the number of SMEs in the study context, the sample size could be relatively small. The number of respondents, juxtaposing the number of managers in the sectors may not be encompassing. Hence, future studies could explore larger samples and use other methodologies to extend the studies. Thus, future studies could increase the number of respondents to include other units of managers in the SME sector. A longitudinal study of different segments of the SME sectors could also be explored in future studies. Nonetheless, we relish that the conclusions drawn from this study provide several empirical and practical implications.

Acknowledgment

The authors are grateful to the various reviewers for their constructive comments in shaping the manuscript.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Notes on contributors

Sulemana B. Egala

Sulemana B. Egala Holds a Ph.D. in Management Science and Engineering with specialization in Data mining and Information Management from the University of Electronic Science and Technology of China (UESTC). He also holds a bachelor’s and master of philosophy degrees in computing and information systems. He is currently a lecturer at the Department of Informatics, Faculty of ICT at the SDD University of Business and Integrated Development Studies (SDD-UBIDS), Wa. He has a vast interest in the areas of health Informatics, Open Data, and social business analytics.

John Amoah

John Amoah holds a PhD from the Tomas Bata University, Zlin Czech Republic. He is currently a lecturer at KAAF University College, Kasoa, Ghana. His main research areas are SME Development, Social Media Analysis, Marketing and Innovation, Consumer Behavior, and Service Marketing among others. The results of his research have been published in peer-reviewed scientific journals and presented at numerous international conferences around the globe.

Abdul Bashiru Jibril

Dr. Abdul Bashiru Jibril is a Senior Lecturer (Marketing) at Westminster International University in Tashkent, Uzbekistan. Dr Jibril holds a PhD in Marketing Management from Tomas Bata University in Zlin, Czech Republic. His research focuses on Technology adoption, social media analytics, Service marketing, Brand management, and Sustainable e-tourism. He is interested in deploying data mining techniques in extracting intelligence to improve business decision making especially for marketers and corporate success in emerging and developing economies. He has led and been involved in a research team to execute several external projects in Europe and Africa. He is currently a principal investigator of a Fair Work project (UK) between the University of Oxford and the International University of Rabat, Morocco. The results of his research have been published in impacted and ABS/ABDC ranking journals, such as the International Journal of Information Management, International Journal of Consumer Studies, etc., and contributed to book chapters (in Springer) and Conference proceedings. He has also actively participated and presented in numerous international scientific conferences (indexed in WoS/Scopus/Springer), with host countries such as the USA, UK, France, Germany, Saudi Arabia, etc. He serves as Associate Editor for Cogent Business and Management (Taylor & Francis), Editorial review board member for the International Journal of Neuroscience and Neuroinformatics (IJNN) (IGI Global), and Sectional Editor for Current Social Sciences (Bentham Science Publishers).

Robert Opoku

Robert Opoku is a faculty member at the Donald School of Business, Science, and Computing, Red Deer Polytechnic, Canada. He has a proven record of scholarship, academic inquiry, and research. His eclectic mix of research spans several areas of marketing and entrepreneurship, with a special focus on online branding and communications; culture and decision-making; consumer ethnocentrism, place, and destination marketing; financial services marketing; gift-giving; as well as micro-foundation of entrepreneurial intentions in emerging economies. Robert has published more than 30 research articles in several peer-reviewed journals such as Tourism Management, Journal of Business Research, Industrial Marketing Management, Journal of International Management, and others. He has also presented at more than 15 conferences spanning four continents.

Emmanuel Bruce

Emmanuel Bruce is a Doctoral researcher at the University of Electronic Science and Technology of China, Chengdu-China, School of Management and Economics. Emmanuel has been in the research domain for the past three years and the results of his research have been published in high-ranked respected journals. He also serves as a reviewer for some respected journals around the globe. His main research areas are SME development, social media Analysis, and Service Marketing among others.