Corporate entrepreneurship is a well-defined field of study, which has been in existence for more than four decades (Bierwerth et al. 2015; Kuratko et al. 2015; Kuratko & Morris 2018). Since its inception, it has gone through various stages, regarded by Kuratko and Audretsch (2013) as the 1980s, 1990s and 21st century, of defining what it is and strengthening its theoretical grounding. In the 1980s, corporate entrepreneurship was conceptualised as ‘embodying entrepreneurial behaviour requiring organizational sanctions and resource commitments for the purpose of developing different types of value-creating innovations’ (Kuratko & Audretsch 2013:325). For instance, Miller (1983) focused on elements such as product innovation, proactiveness and risk-taking which enable the organisations to pursue opportunities.

In the 1990s, corporate entrepreneurship was seen as two distinct, yet complementary features: corporate venturing and strategic renewal of the existing business (Guth & Ginsberg 1990; Sharma & Chrisman 1999). One of the popular definitions of corporate entrepreneurship is a:

The main objective in the 1990s was to provide organisations with a competitive advantage and improved financial performance (Kuratko & Audretsch 2013; Lumpkin & Dess 1996; Zahra 1993).

During this era, the multidimensionality of corporate entrepreneurship – denoting renewal, innovation, risk-taking, proactiveness, corporate venturing – was a central argument. A quote from Covin and Miles (1999) says:

Recently, in the 21st century, focus changed to internal and external corporate entrepreneurship and the involvement of managers in corporate entrepreneurship (Hornsby et al. 2009; Hornsby, Kuratko & Shaker 2002; Kuratko & Audretsch 2013). The last addition is strategic entrepreneurship, which is focused on substantial innovation that will significantly improve the company’s competitive advantage (Kuratko, Morris & Covin 2011). Covin and Miles (1999) observed that innovation is the single common theme underlying all forms of corporate entrepreneurship. Table 1 is a brief summary of some of the key definitions and dimensions of corporate entrepreneurship.

Kuratko et al. (1990:49) encouraged scholars to ‘continuously reassess the components or dimensions that predict or explain or shape the environment in which corporate entrepreneurship flourishes’. A review of the literature reveals the various dimensions or elements of corporate entrepreneurship that significantly contribute to developing a ‘theoretically grounded understanding of corporate entrepreneurship that can be readily identified from the extant literature’ (Kuratko et al. 2015:245). The dimensions, which form the CEAI, are management support, work discretion, rewards and reinforcement, time availability and organisation boundaries (Hornsby et al. 1999; Kuratko et al. 1990, 2014). This instrument is effective in measuring the managers’ approach to corporate entrepreneurship (Hornsby et al. 2009).

In the case of management support, management needs to play the role of a facilitator. It is further argued by Demirci (2013) that senior and middle management are responsible for creating a suitable environment for corporate entrepreneurship. Work discretion – delegation of authority – when afforded to employees, provides them with the latitude to make decisions. This power influences employee attitudes and requires tolerance of failures from management. Time availability should also be considered as a resource to come up with innovative ideas and perform innovative activities. Flexibility of the organisational boundaries will enable information from the external environment to reach the internal environment of the organisation and facilitate innovative ideas (Hornsby et al. 2009; Kuratko et al. 2014; Miller, Fern & Cardinal 2007). In 2017, a study conducted on a sample of 3180 respondents demonstrated that CEAI can be shorted to 20 measurement items and still maintain a good reliability score above 0.7 (Steyn 2017).

After reviewing the different approaches to corporate entrepreneurship (such as strategic renewal, corporate venturing, proactiveness, risk-taking, entrepreneurial orientation, strategic entrepreneurship), this study used CEAI to measure corporate entrepreneurship in a financial institution and how it predicts service innovation. The main reason for this choice was to examine how managers support entrepreneurial activities within their organisations (Hornsby et al. 2002, 2009; Kuratko et al. 2014).

‘Today, continuous innovation – in terms of products, processes, and administrative routines and structures – is needed to compete effectively in the global markets of the 21st century.’ (Kuratko et al. 2014:37)

The quote by Kuratko et al. (2014) emphasises the significance of innovation including that of services in today’s business world. Services rendered are not thought of in terms of delivering a tangible product, which makes it somewhat difficult to measure and define. Service can be defined as an output of the interaction between service providers, consumers and technical characteristics (Morrar 2014). The definition of services by Morrar (2014) comprises four attributes, which include intangibility (products or processes that are not tangible), heterogeneity (non-uniformity in the end result), inseparability (consumers cannot be separated from the service experience) and perishability (services cannot be stored or exchanged and are thus transitory). Similarly, Katzan (2015:5) mentioned four dimensions to service innovation, which comprise ‘the service concept, the client interface, the service delivery system, and technology options’. In this study, service innovation is defined as the creation of a new service to the benefit of the customers, and to increase the competitive advantage of the company (Barcet 2010; Grant 1991).

Legrand and Ljoiem (2013) argued that one of the core differences between the types of innovation, when contrasted with service innovation, is that service innovation has a strong focus on the customer. Morrar (2014) argued that through customers’ feedback, an information loop is created that allows incremental innovation and new services to be offered. This shows that innovation in services is not solely reliant on technological research and development, but instead relies on human capital to add dimensions of strategy and competitiveness (Morrar 2014). Therefore, the accumulated knowledge of customers is also a source of bringing about innovation in services.

Although service innovation research has attracted scholars from different disciplines, there is a growing need to refine and promote the service research agenda (Ostrom et al. 2015; Wang et al. 2015) and incorporate corporate entrepreneurship (Calisto & Sarkar 2017). One of the arguments is that service innovation has been discussed from a conceptual perspective, and has received less empirical research (Wang et al. 2015). Moreover, research focused on product and process innovation, consequently ignoring service innovation and its potential to contribute to the existing knowledge (Calisto & Sarkar 2017; Carlborg et al. 2014). The reason given for this neglect is that service is perceived to consist of activities with low innovative frequency (Carlborg et al. 2014). Filling this gap, this study makes a contribution by combining the field of entrepreneurship with service innovation in a technology-driven industry (Yunis et al. 2018).

A recent meta-analytic study demonstrated that corporate entrepreneurship is associated with organisational performance, both financial and nonfinancial (Bierwerth et al. 2015). On one hand, several studies found a positive relationship between corporate entrepreneurship and financial indicators. To name a few, financial indicators include return on sales and growth in sales (Zahra 1993); return on assets and return on sales (Zahra & Covin 1995); sales growth, market share and profitability (Lumpkin & Dess 1996) and market performance (Jancenelle, Storrud-Barnes & Javalgi 2017). On the other hand, corporate entrepreneurship has been positively associated with nonfinancial measures such as organisations’ performance relative to their competitors (Yunis et al. 2018) and product innovation (Chen et al. 2015). In addition to nonfinancial measures, this study uses service innovation as a measure of organisational performance, which is hypothesised to be predicted by corporate entrepreneurship. Figure 1 shows the dimensions of corporate entrepreneurship which may predict service innovation.

The study adopted a deductive approach and made use of existing literature on corporate entrepreneurship and service innovation to better understand the phenomenon studied. The initial strategy was to target a sample of South African companies in the financial services industry, predominantly companies that were classified as diversified banks. The intention was to target such companies because of the wide spectrum of business services that align fairly accurately with the objective of the study. Because of the lack of interest by companies to participate in this study, a case study strategy was chosen by focusing on a single organisation to gain the necessary findings and insights in line with the research objectives. The organisation that was selected had met the criteria of being classified as a diversified bank and was willing to allow its employees to participate in the survey. Eventually, the sampling unit or unit of analysis for this study was a financial services company in the form of a bank.

Quantitative data were collected using an online survey, which contained questionnaires that represented scales for corporate entrepreneurship and service innovation. The scale for CEAI, was adopted from Kuratko et al. (2014), while the scale that measured service innovation was adopted from Grawe et al. (2009). CEAI had five dimensions, namely, management support, work discretion, rewards and reinforcement, time availability and organisational boundaries. Each of these CEAI dimensions and service innovation was measured through a set of measurement items, which utilised a Likert scale with five ordinal choices. The responses ranged from 1 = strongly disagree, 2 = disagree, 3 = neutral, 4 = agree and 5 = strongly agree.

Upon receipt of formal consent from the authority within the organisation, the website link to the online survey was distributed via email to employees. Respondents who were invited to participate included process engineers, business analysts, software test analysts, as well as managers from junior to middle and senior management. The content of the email explicitly stated that the details of the company will be kept anonymous, and the findings will be reported and stored without identifiers. The first email was distributed via email on 15 August 2016, signalling the commencement of the data gathering process. Subsequent to this email, a reminder email was distributed on the 1 September 2016 as a gentle reminder to respondents. The reminder email also conveyed gratitude to those who had responded since the initial email. The official data gathering process concluded on 6 September 2016.

Before data analysis could begin, the data were prepared by dealing with the missing values, correcting the skewness of the data, re-coding reversed measurement items and testing the data distribution. Next, simple descriptive statistics were computed to provide an overview of the data. Moving to inferential statistics, the reliability and validity of the scales adopted were tested. These tests conducted comprised an iterative process of factor analysis, eliminating weak variables or items, with the aim of mathematically depicting dimensions (Hair et al. 2010). A reliability test was conducted using Cronbach’s alpha coefficient, which further strengthened the dimensions derived from the factor analysis (Kline 2011). After computing the factor scores, a simple correlation test between the corporate entrepreneurship dimensions and service innovation was executed. Finally, a multiple regression model, comprising all dimensions of corporate entrepreneurship (independent variables) and service innovation (dependent variable), was run.

There were 97 responses gathered from the data. Their designations are as follows: business analysts (41%), process engineers (24%), management (28%) and other (7%). The ‘other’ category includes technical consultants, administration officer, business transformation leader, communications specialist and business coaches. The categories of work experience showed that participants had work experience ranging from 0 to 5 years (33%), 6 to 10 years (32%), 11 to 15 years (21%), 16 to 20 years (9%) and 5% of more than 20 years. Their management levels consisted of non-managerial (e.g. specialist role) (47%), junior management (e.g. team leader or senior specialist role) (16%), middle management (e.g. head of business function) (18%), senior management (e.g. general manager) (13%) and executive management (6%). The data show that over 53% of the respondents were in managerial positions.

The reliability of the research instrument was tested before the main analysis and the results showed that all dimensions had Cronbach’s alpha values above 0.70, indicating that the scale had internal consistency and measured what was intended (Kline 2011). The findings showed management support with α = 0.904, work discretion with α = 0.808, rewards and reinforcement with α = 0.827, time availability with α = 0.718, organisational behaviour with α = 0.732 and service innovation with α = 0.901.

Hair et al. (2010) indicated that the factor analysis is designed to define the underlying structure among the variables in the analysis. Factor analysis was executed over nine iterations to arrive at the set of nine factors or components. Although the factors comprised a single variable, the items were removed in preparation for the next iteration of the factor analysis. The Kaiser–Meyer–Olkin measure and Bartlett’s test of sphericity were observed through each iteration of the factor analysis to assess, if the data were fit for factor analysis (Hair et al. 2010). Furthermore, the scree plot graphs produced were observed for the point of inflection. Any items with absolute value below 0.50 were omitted from the factor analysis. After the ninth iteration, there were 9 factors with 39 items, Kaiser–Meyer–Olkin value of 0.796 and Bartlett’s test of sphericity with p = 0.00.

The rotated factor matrix shown in Table 2 illustrates the factor loading after the ninth iteration of the factor analysis.

Table 2 depicts the variables that were grouped together. If a variable was associated across more than one factor, the highest factor loading took precedence. Post-factor analysis, the following items in Table 3 were grouped to form the new factors or components. Their reliability scores were above the recommended 0.7 (Kline 2011)

Table 3 shows that all five independent variables were retained. Although the variables were retained, some of the measurement items from the original scale were omitted as a result of the factor analysis. The dependent variable, service innovation, retained all items from the service innovation scale adopted from Grawe et al. (2009). In addition to this, two other items were added from management support, which are ‘my organisation is quick to use improved methods that are developed by workers’ and ‘my organisation is quick to use improved work methods’.

Table 4 depicts the Pearson correlation coefficients for each of the corporate entrepreneurship dimensions against the service innovation scale.

The summary of the correlation findings reveals that management support (r = 0.687) has its strongest significant association with service innovation, followed by work discretion (r = 0.550), rewards and recognition (r = 0.585) and time availability (r = 0.355), respectively. Organisational boundaries were negatively correlated with service innovation, suggesting that more rigid organisational boundaries may result in decreased service innovation. This finding will be confirmed by multiple linear regression presented in the next section.

All dimensions of corporate entrepreneurship that represent the independent variable were computed together in multiple regression analysis to predict service innovation. The model summary and coefficients computed are depicted in Table 5.

The multiple correlation coefficient R was 0.773, supporting the notion that the independent variables comprising corporate entrepreneurship as a collective are good predictors of dependent variable service innovation. The R² was computed as 0.597 with the adjusted R² computed as 0.575. The R² value explained the variance in the dependent variable that was attributable by the independent variables. Therefore, it can be said that 59.7% of the variance in service innovation was attributable to corporate entrepreneurship (see Table 5).

Results from the analysis of variance (ANOVA) test displayed in Table 6 showed that the proposed model was a good fit for the data with p = 0.000.

The equation to the model was derived using the B (beta) column under the unstandardised coefficients shown in Table 7.

The coefficients shown in Table 7 demonstrate that when all variables were computed together in multiple regression, rewards and recognition (sig. = 0.00), management support (sig. = 0.000) and time availability (sig. = 0.044) were significant predictors of service innovation. Organisational boundaries (sig. = 0.418) and work discretion (sig. = 0.786) were found to be insignificant predictors of service innovation.

The model equation can be written as: Service innovation = 0.055 + 0.642 (management support) + 0.425 (rewards and reinforcement) + 0.180 (time availability).

Through the application of factor analysis, all dimensions of CE were identified. However, they were reduced in size in terms of their associated measurement items. Based on the multiple linear regression results, the hypotheses are concluded, as shown in Table 8.

The case study approach only provides a view from a single organisation, and thus is not representative for all companies in the financial services industry in South Africa. Moreover, with only 97 responses obtained from various levels in the organisation, this provided a limited sample size from which to draw inferential statistics that were representative of the entire organisation. Therefore, this study cannot be generalised to other banking institutions. However, it has provided great insights about using corporate entrepreneurship to improve the competitive advantage of the firm.

Although the service innovation scale in this study proved to be reliable, there are no scales to measure the extent to which services are innovated within an organisation. Based on service design practitioners’ tool and techniques, service innovation scales can be enhanced through focus on innovation and by expanding the focus on the customer. Furthermore, at a high level, the scale could also be architected to focus on visible as well invisible aspects (Morrar 2014) to develop a service innovation framework.

Studies in financial service companies should also establish their portfolio of innovation to establish the extent to which emphasis is placed on production innovation compared to service innovation. Neither of these innovation types should be neglected; however, a fair balance needs to be maintained. In addition, congruence between these two innovation methods should be attained to personify efficacy of the overall innovation efforts, with the primary focus placed on the customer. Future research in this regard will contribute to the development of scales to measure these innovation types and the level of integration in efforts to achieve alignment.

A quantitative study, including several financial companies, will validate the results of this study, especially work discretion and organisational boundaries which were found to be non-significant predictors of service innovation. Future studies can use the context or the nature of the firm as a moderating variable between corporate entrepreneurship and service innovation or any organisational performance measure.

Finally, there is a need to focus on banking or technology capabilities that may facilitate corporate entrepreneurship, and which will consequently impact on organisational performance. These studies demonstrate how companies can improve their competitive advantage by taking cognisance of the factors working within the organisation.