Innovation orientation and firms’ financial performance: The moderating role of new product development

Abstract

Previous studies on the relationship between innovation orientation and firms’ financial performance have churned out conflicting results. These contradictions motivated this study. Specifically, this study sought to examine the relationship between innovation orientation and firms’ financial performance. The study also assessed the moderating effect of new product development on the relationship between innovation orientation and firms’ financial performance. Data from 200 manufacturing firms in Ghana were quantitatively analysed using SPSS. Moderated hierarchical regression test was carried out to examine the relationships between the constructs. While a positive relationship between innovation orientation and the financial performance of firms was established, the study findings revealed that new product development capabilities have no moderating effect on the relationship between innovation and firms’ financial performance. The study contributes to the innovation orientation and financial performance literature. It extends our knowledge of how new product development influences the innovation orientation-financial performance relationship of firms.

Keywords:

• new product development (NPD)
• innovation
• financial performance
• manufacturing firms
• Ghana

1. Introduction

Organizations’ capacity to innovate is considered an important determinant of survival and success in the ever-increasing competitive and sophisticated markets (Cooper, 2019; Ferreras-Mendez et al., 2022; Triani & Handayani, 2018). As the business environment keeps changing due to intense competition, customer sophistication, and globalization, firms have turned to innovation as a strategic tool for achieving competitive advantage (Bigliardi, 2013; Mu et al., 2017). Innovation creates value for shareholders (Lee & Chen, 2009); increases customer satisfaction and loyalty (Narver & Slater, 1990); increase sales and profitability (Chaudhry et al., 2019; Cooper, 2019; Mai et al., 2019), and engender access to credit and state support (Mai et al., 2019). Innovation also ensures firms’ survival (Zhang et al., 2018) and increases the general competitiveness of firms (Anning-Dorson, 2016). Innovation may be firm-driven; however, the impact goes beyond the firms as it has become the catalyst for economic growth and social development (Chen, 2017; Phung et al., 2021). Hence, many countries (both advanced and less developed) are focusing on innovation to drive economic growth and general development (Acs et al., 2016; Chen et al., 2018).

In response to the changing competitive environment, there has been a dramatic increase in the number of new products introduced by firms in emerging economies in recent years, and this has attracted considerable scholarly attention (Sun & Lee, 2013). Given that financial performance and non-financial performance are the main variables used in measuring firm performance (Anning-Dorson, 2016; Jaworski & Kohli, 1993), several studies have examined the impact of innovation on a firm’s financial performance. While there is no ambiguity about the theoretical context of innovation, empirical findings on the phenomenon are still inconclusive (Gonzalez-Fernandez & Gonzalez-Velasco, 2018; Mai et al., 2019). Previous research on the relationship between innovation and a firm’s financial performance has churned out mixed results (de Oliveira et al., 2018). While some studies on innovation and firms’ financial performance have found that innovation has a positive impact on firms’ financial performance (e.g. Anning-Dorson et al., 2017; Bierly & Chakrabarti, 1996; Liao & Rice, 2010), others have reported a negative relationship between innovation and firm’s financial performance (see Santos et al., 2014). This lack of unanimity in the findings is motivating further studies (Jimenez-Jimenez & Sanz-Valle, 2011; Mai et al., 2019) such as this. Besides, the conceptualization of innovation and its effect on firms’ financial performance from the developing countries’ perspective is still evolving (Wadho & Chaudhry, 2018) since the majority of studies on innovation have been carried out in the developed economy context (Jugend et al., 2018).

According to Cooper (2019), a firm’s profitability and growth are tied to new product development (NPD). Innovation is not limited to minor changes to existing products or services or processes but includes turning big ideas into new or enhanced and unique products or services that consumers perceive as new offerings that satisfy their needs (Zhao et al., 2021). New product development has emerged over the years as a key source of competitive advantage for firms (Mu et al., 2017; Yan et al., 2020). Indeed, NPD has engaged the attention of both scholars and practitioners as a result of its significant impact on firms’ performance (Akroush & Awwad, 2018). Unlike this current study, which sought to examine the moderating effect of NPD on the relationship between innovations and firms’ financial performance, previous studies on NPD have focused on the types of resources, capabilities, competencies, skills, and other requirements that are needed to ensure the success of NPD (Akroush & Awwad, 2018). There is an agreement between researchers and practitioners that for NPD to succeed two things are required; that is, market resources (e.g. customer knowledge) and technological resources (e.g. technological knowledge) (Jin et al., 2019; Sethi et al., 2012). This notwithstanding as high as 40% of new products fails at the launch stage (Cooper, 2017). There is therefore the need for organizations to appreciate the return on investment and the financial implications of their innovative activities.

In response to the conflicting findings on innovation and firms’ financial performance, this study argues that other factors such as NPD could influence the impact of innovation on firms’ financial performance. Specifically, the study examined the impact of innovation on the financial performance of manufacturing firms in Ghana. The study also assessed the moderating role of NPD on the relationship between innovation orientation and firms’ financial performance. Given that NPD is considered by firms as a risky and costly endeavour that could severely impact a firm’s bottom line. This study, thus makes some valuable contributions to the extant literature on NDP, by examining its effects on innovation orientation and firms’ financial performance.

The study makes modest yet significant contributions to the marketing and management literature, particularly from the perspective of innovation orientation and firm financial performance. First, the current study seeks to address the geographical context gap that exists in the literature as a result of the underrepresentation of emerging economy in the innovation orientation and firm financial performance literature (Mai et al., 2019; Pundziene et al., 2022). Second, the study also addresses the so far neglected theoretical gap of empirically testing the effect of new product development on firm innovation orientation and financial performance relationship. The study found new product development to have a negative moderating effect on innovation orientation and firms’ profitability relationship and this appears to be at variance with theoretical assumptions. This presents an opportunity for further empirical examination of the model vis-a-vis the theory. Third, this study extends the development of the dynamic capabilities theory by discussing its dimensions which hitherto remained unexplored. Again, it provides empirical evidence on the phenomenon from the perspective of a resource-constrained context. Furthermore, the findings of the study provide some useful lessons for business executives and management practitioners. We demonstrate that innovation could be used as a strategic tool and as an avenue for achieving profitability for firms.

2. Theoretical settings and hypothesis development

2.1. Dynamic capability theory

Dynamic capability is regarded as a concept in both theory and practice (Zhou et al., 2019). Teece et al. (1997) in their pioneering work defined dynamic capability as the harnessing of a firm’s various resources and competencies to redesign and configure its processes to respond to the changing demands of the market. In other words, Dynamic capabilities encompass “the management of capabilities and resources of all functions of the firms, with the overall objective to get a competitive advantage” (Arranz et al., 2020, p. 1495). Dynamic capabilities have their antecedents in the concept of the resource-based view of the firm (RBV), which can be traced to the work done by Penrose in 1957 (Ferreira et al., 2021). However, the development of the concept of dynamic capabilities has been shaped by contributions from other scholars such as the evolutionary theory of economic change (Nelson & Winter, 1982), Schumpeter’s views on creative destruction, the behavioural aspects of the firm (Cyert & March, 1963) and Williamson’s (1975) views on markets and hierarchies. Scholars have posited that dynamic capabilities have two dimensions, thus explorative and exploitative dimensions (Vahlne & Jonsson, 2017). While the explorative dimension connotes disruption and acquisition of new knowledge, exploitative capabilities refer to the discovery of actual knowledge anchored on efficiency and improved methods (O’Reilly & Tushman, 2008).

Scholars at the inception of the dynamic capabilities concept presumed that it has a direct effect on company performance (Ambrosini & Bowman, 2009; Teece et al., 1997). Subsequent studies have shown that the dynamic capabilities do not always result in improved firm performance (Eisenhardt & Martin, 2000). Despite the extensive research on dynamic capabilities, the winning formula to save companies from failures is yet to be found (Pundziene et al., 2022). Eisenhardt and Martin (2000) contend that firms necessarily would not gain competitive advantage and improved performance directly from dynamic capabilities but the effective configuration created from dynamic capabilities. In a similar view, Zott (2003) posits that there is no direct relationship between dynamic capabilities and firm performance. Some scholars argue that under some circumstances dynamic capabilities could harm firms more than good especially when the opportunity cost is high (Winter, 2003; Zahra et al., 2006). Despite the confounding nature of the debate on dynamic capabilities (Schilke, 2014), which is sometimes exacerbated by the lack of empirical studies (Danneels, 2012) it is a useful concept in practice. According to O’Reilly and Tushman (2008), dynamic capabilities make it possible for firms to exploit both accumulated knowledge and competencies and fresh competencies as well as recalibrated process to latch on to opportunities in the market. The significance of dynamic capability to firms’ general growth and performance cannot be overemphasized as it signifies the accumulation of capabilities embedded in a firm (Hsu & Wang, 2012). Hence, a firm’s dynamic capability has a positive effect on its performance (Pundziene et al., 2022).

3. Innovation orientation and financial performance

A firm’s capacity to innovate is considered an important determinant of its survival and success in the ever-increasing competitive markets (Cooper, 2019; Triani & Handayani, 2018). Cheng and Huizingh (2010) noted that firms who are desirous of achieving a prominent position in the market and sustainable high profits ought to adopt innovation as a strategic tool. It is a widely held view (though not conclusive) that innovation capability has an impact on firms’ financial performance (Suharyono et al., 2014; Suliyanto, 2011). It is argued that the relationship between innovation and a firm’s performance should be looked at from two perspectives (Mai et al., 2019). Some financial analyst contends that the implementation of innovative strategies by firms is a difficult exercise and often come with associated risks (Chouaibi, 2021; Fernandes & Paunov, 2015; Ferreras-Mendez et al., 2022). For instance, when new products are developed it has to scale several hurdles including technical challenges, market acceptability, competition, and competitors’ sales strategies among others (Mai et al., 2019). That said, some scholars hold the view that the benefits associated with product innovation far outweigh the risks (Mai et al., 2019). This is why Freeman (1994) posits that successful firms are most likely to pursue product innovation. Among other benefits of innovation orientation capability are access to credit, government support (Mai et al., 2019), and increased sales and profitability (Chaudhry et al., 2019; Cooper, 2019). Empirically, some studies have suggested a positive relationship between innovation orientation and a firm’s financial performance (see Xiea et al., 2019). For instance, Leyva de la Hiz et al. (2018) suggest a positive relationship between a firm’s focused environmental innovation and its financial performance. Based on this, this study hypothesizes that;

H1: Innovation orientation is positively related to the financial performance of firms.

4. New product development (NPD), innovation orientation, and financial performance

Innovation is not about minor changes to existing products or services or processes but includes turning big ideas into new enhanced and unique products or services that consumer perceives as new offering that satisfies their requirements (Yulianto & Supriono, 2023; Zhao et al., 2021). New product development has emerged over the years as a key source of competitive advantage for firms (Mu et al., 2017; Yan et al., 2020). Indeed, NPD has engaged the attention of both scholars and practitioners as a result of its significant impact on firms’ performance (Akroush & Awwad, 2018). Cooper (2019) asserts that a firm’s profitability and growth are tied to new product development (NPD). It is important to acknowledge the challenges that come along with new product development. For instance, a product innovation strategy could mean an increase in firms’ budgets, which could result in a demand for more capital injection from shareholders. Hence, this increase in cost could result in increased cost of products and ultimately lower profits. However, firms that engage in sustained innovation activities tend to get over these initial costs to enjoy increased profits as the product gains market acceptability.

Product innovation has become a key source of competitive advantage and long-term profitability for firms, particularly those in the manufacturing sector markets (Guiné et al., 2020; Horvat et al., 2019). Therefore, firms must explore the key factors that drive new product success in the market. Cooper (2018) suggests that a new product’s success depends on understanding customers’ requirements, competition, and market dynamics. New products need to succeed as heavy investments are often expended on R&D and the entire new product development process which could affect the firm’s profitability should the product fail. In light of this, the study hypothesizes that;

H2: New product development moderates the influence of innovation orientation on the financial performance of firms.

These hypothesized relationships are illustrated in figure 1 as the conceptual framework that guides this study.

Figure 1. Conceptual model.

5. Methodology

5.1. Research design and procedure

The study adopted a quantitative research design, as it aims at testing hypotheses with the help of statistical tools. The target population of the study was manufacturing companies in Ghana. A list of these companies was sourced from the Register General Department of Ghana to form the sample frame. A convenient sampling technique was used to select 250 firms to participate in the study. A convenient sampling technique was appropriate as it ensured that the survey took a limited (3 weeks) to be completed (Hair et al., 2003). The questionnaire was developed after an extensive literature review. The scale items for innovation were adapted from Al-Shuaibi (2016), while the scale items for financial performance were adapted from Jain et al. (2017). The scale items were assessed by two senior lecturers with innovation and entrepreneurship backgrounds for face and content validity.

The questionnaire for the study had sections on the background information of the firms. It also had sections on the predictor and moderator variables. As recommended by Hair et al. (2007) a pilot test was conducted to assess the measurement items for clarity, comprehension, and suitability. The feedback from the 10 participants who were involved in the pilot test helped to refine the questionnaire. The constructs were measured using a seven-point likert-scale ranging from 1 = not at all to 7 = to a large extent and 4 = moderately. Out of 250 questionnaires sent out during the survey 230 were retrieved representing 92 response rate and after assessing them for completeness and outliers, 200 were deemed useable representing 80% final usable sample. To forestall concerns for common method bias, information was taken from people who were in charge of R&D and innovation in the various firms as they were deemed to have required knowledge the study was seeking (Podsakoff et al., 2012).

5.2. Control variables

Most empirical studies on strategy-performance relationships usually include some business characteristics as control variables to guarantee that the study result is not unreasonably confounded by these factors (Schamberger et al., 2013). As suggested by previous studies (Hirvonen et al., 2013; Mason, 2007), the suitability of a firm’s strategy such as innovation and new product development largely depends on the competitive business setting, which is often a combination of organizational and environmental exigencies. Given this, the study followed previous studies and controlled for industry type, Dedicated R&D, Business experience, number of full-time staff, and industry dynamism (Odoom & Mensah, 2019; Odoom et al., 2017).

6. Data analysis and results

6.1. Sample characteristics

Data was collected on the basic characteristics of the participating firms. A filtering question was used to reveal if a sampled firm has developed new products in the last 3 years. If the answer to this question was in the affirmative the respondent was then asked to proceed and answer the rest of the questionnaire items. The analyses show that 92% of firms have been engaged in NPD in the last 3 years, while 8% were not. The majority (29.57%) of the sample had between 50 and 100 employees, while most (42.61%) of the firms’ managers have Bachelor’s degrees. The majority (30%) of these managers are reasonably experienced in NPD. The details of these characteristics are illustrated in Table 1.

Table 1. Sample characteristics

Sample Features	Frequency	Percentage
Did your company develop new products over the last three years?
Yes	230	92.0
No	20	08.0
Total	250	100
What is the total number of employees in your firm?
1-50 employees	57	24.78
51-100 employees	68	29.57
101-150 employees	48	20.87
151- 200 employees	36	15.65
200 and above employees	21	9.13
Total	230	100
How many years you have been working in your industry?
1-2 years	56	24.35
3-5 years	69	30.0
6-8 years	43	18.70
9-10 years	38	16.52
Above 10 years	24	10.43
Total	230	100
Managers’ academic qualifications
SHS and below	11	4.78
Diploma	19	8.26
Degree	98	42.61
Postgraduate	85	36.96
Others	17	7.39
Total	230	100
How long have you been working on new products?
1-2 years	25	10.87
3-5 years	83	36.09
6-8 years	69	30.0
9 years and above	53	23.04
Total	230	100

6.2. Assessment of reliability and validity of measurement model

As indicated in Table 2, the different benchmarks for reflective constructs, including the criteria for convergent validity of both indicators and constructs as well as the consistency reliability of the constructs are presented. In assessing the reliability and discriminant validity of the measurement model, the three-step criteria proposed by Fornell and Larcker (1981) were followed. That is 1) the item reliability of each measure, 2) the composite reliability of each construct, and 3) the average variance extracted (AVE). The item reliability test was assessed based on the factor loadings of the constructs and the item loadings were all above 0.5 and all were significant at 0.000, demonstrating that convergent validity exists at the level of indicators (Peng & Lai, 2012).

Table 2. Measurement properties of constructs

Constructs	Indicators	Mean	Std. Dev.	Factor Loading	Alpha Cronbach	Composite Reliability	AVE
NDPC					0.907	0.903	0.654
	NPDC1	4.40	1.383	.710
	NPDC2	4.37	1.588	.655
	NPDC3	4.16	1.637	.790
	NPDC4	4.22	1.516	.813
	NPDC5	3.96	1.687	726
INNOV					0.909	0.907	0.661
	INNOV1	4.47	1.410	.687
	INNOV2	4.15	1.636	.777
	INNOV3	3.96	1.846	.759
	INNOV4	3.90	1.823	.819
	INNOV5	4.67	1.493	.659
PERF					0.906	0.830	0.620
	PERF1	4.72	1.363	774
	PERF2	4.77	1.330	.881
	PERF3	4.80	1.359	.818
	PERF4	4.68	1.386	.659

Sampling adequacy (Kaiser-Meyer-Olkin measure greater than 0.5): 0.870

Total variance explained: 0.60

Model goodness-offit χ2 P ≥0.05 NFI≥0.90 CFI≥ 0.90 GFI≥0.90 AGFI≥0.90 RMSEA<0.06 CMIN-df≤3.84 PCFI≥0.50 PClose >0.05

indices: desired level

Model indices results: 117 P=0.000 0.947 0.972 0.941 0.905 0.064 1.992 0.736 0.088

The internal consistency reliability for the evaluation of reflective measures was appraised through composite reliability and Cronbach’s alpha (Hair et al., 2016). In this model, both values were higher than the criterion of 0.7 set by Fornell and Larcker (1981), indicating high reliability for all three constructs. The AVE results show that all values are above the minimum threshold of 0.5 as shown in Table 3 and the square root of the AVEs was greater than the correlation coefficients of the constructs demonstrating the uniqueness of each construct, hence support for discriminant validity. We subjected all the scale items to exploratory factor analysis (EFA). Our factor analysis was deemed appropriate for analysing the data as indicated by an index of Kaiser’s measure of sampling adequacy (overall MSA = 0.870) and Bartlett’s test of Sphericity χ2 (p≥0.000). Also, as illustrated in Table 2, founded on an eigenvalue greater than 1, the results of EFA show that the study items loaded on five factors explain 60% of the total variance, which offers empirical support to the study constructs’ literature.

Table 3. Descriptive statistics and correlations matrix

Variables	Mean	S.D	Min	Max	1	2	3	4	5	6	7	8
1.INNOV	4.230	1.6416	1	7	(0.813)
2.NPDC	4.222	1.5622	1	7	0.645	(0.809)
3.PERF	4.743	1.3595	1	7	0.626	0.753	(0.788)
4.INDUT	.58	.495	0	1	0.149	0.236	0.220	−
5.Experie	24.73	13.564	2	50	0.193	0.296	0.287	0.027	−
6.FUNC	.48	.501	0	1	0.164	0.171	0.074	0.093	0.156	−
7.SIZE	142.37	384.908	2	4000	0.048	0.064	0.054	0.093	0.156	0.156	−
8.DYNA	4.09	1.506	1	7	0.325	0.237	0.209	0.000	−0.029	0.506	0.506	−

The square roots of the AVE are presented on the diagonal in bold in brackets. The numbers below the AVE values are the correlation between the relevant construct with another construct in the model.

To validate the outcome that emerged from using EFA, the model was evaluated by CFA using ISPSS Amos software. As presented in Table 3 the measurement model has acceptable fit indexes (χ2 = 117), comparative fit index = 0.972, root mean square error of approximation = 0.064, adjusted goodness-of-fit index = 0.905 and parsimony comparative fit index = 0.054. Also, the modification indexes presented no indications of significant cross-loadings. The CFA as well provided further evidence that suggests that the resulting measures are reliable and valid as shown by the relatively high CR and average variances extracted, as presented in Table 2 (Fornell & Larcker, 1981). To achieve convergent validity, the items of a specific construct should share a high proportion of variances in common. The convergent validity is pointed out by all factor loadings being significant; the relatively high average variances extracted, and a higher than 0.7 CR as Bagozzi (1980) recommended.

7. Path model evaluation and hierarchical moderated regression analysis

A moderated hierarchical regression (MHR) test (see table 4) was conducted to determine the statistical relationship between innovation and firm performance under the influence of NPD. The MHR test was deemed appropriate because of its ability to provide an interactive approach with a complementarity procedure beyond the extraction of the initial residuals separately on each of the moderator and predictor variables (Aiken & West, 1991). Aside from being able to determine the contribution attributable to each predictor variable, MHR helps in determining the exact value the moderator adds to the predictor—outcome relationship (Odoom & Mensah, 2019). In carrying out these tests composite scores were created from the averages of all the constructs items to reduce model complexity (Ping, 1995). In addition, the scale of each construct, which was meant for multiple interactions, was mean-centered to reduce the likelihood of multicollinearity and clarify the effects of the interaction (Aiken & West, 1991).

Table 4. Path model evaluation and hierarchical moderated regression anaylsis model summary

Model	R	R Square	Adjusted R Square	Std. Error of the Estimate	Change Statistics
					R Square Change	F Change	df1	df2	Sig. F Change
1	.087^a	.008	−.013	1.20894	.008	.363	5	239	.873
2	.522^b	.272	.254	1.03745	.265	86.546	1	238	.000
3	.554^c	.307	.287	1.01422	.035	12.026	1	237	.001
4	.554^d	.307	.284	1.01636	.000	.004	1	236	.952

a. Predictors: (Constant), Environment dynamism, Industry Type, Business experience (Number of Years), Number of Full-time Staff, Dedicated R&D Function

b. Predictors: (Constant), Environment dynamism, Industry Type, Business experience (Number of Years), Number of Full-time Staff, Dedicated R&D Function, Innovation

c. Predictors: (Constant), Environment dynamism, Industry Type, Business experience (Number of Years), Number of Full-time Staff, Dedicated R&D Function, Innovation, NPD Capacity

d. Predictors: (Constant), Environment dynamism, Industry Type, Business experience (Number of Years), Number of Full-time Staff, Dedicated R&D Function, Innovation, NPD Capacity, Intereaction1

Hypothesis 1 proposed that innovation orientation is positively related to the financial performance of firms. As shown in Table 5, the results indicate that the innovation orientation (β = .454; t = 4.303) has a positive impact on financial performance, and the squared term of innovation orientation (β = .202; t = 2.360) is negatively related to financial performance. Hypothesis 1 is therefore supported. This result corroborates the findings of previous research on innovation orientation and firms’ financial performance (see Chaudhry et al., 2019; Cooper, 2019; Mai et al., 2019).

Table 5. Results of regression analysis for financial performance

	PERF
Predictors	β	R^2	∆R^2	t-values	p-values
Step 1
Control Variables*		0.008
Step 2
INNOV	0.454	0.272	0.265	4.303	0.000
Step 3
NDPC -Moderator	0.181	0.307	0.035	3.468	0.001
Step 4
Interaction Variable	−0.002	0.307	0.000	−0.060	0.925

Control Variables - Environment dynamism, Industry Type, Business experience (Number of Years), Number of Full-time Staff and Dedicated R&D Function

Hypothesis 2 proposed that new product development capability moderates the relationship between innovation orientation and financial performance. The results indicate that the linear interaction between innovation orientation and new product development capability has a significant effect on financial performance (∆R² = 0.035, t − 3.468, p-0.001), this indicates a 3.5% variance in firms’ financial performance (see Table 3) and new product development capability (β = −.002; t = −0.060; p = 0.925) negatively moderates the relationship between the squared term of innovation orientation and financial performance as detailed in Table 5. This demonstrates that Hypothesis 2 is not supported. This outcome complements the findings of Muharam et al., (2020). Muharam and his colleagues examined the effect of process innovation and marketing innovation on firms’ financial performance and found that the two variables each have a significant positive effect firm’s financial performance. This study found product innovation to have a negative effect on the relationship between innovation orientation and firm’s financial performance.

8. Discussion and conclusions

The study examined the innovation orientation -firm financial performance relationship. It again investigated the moderating effect of new product development capabilities on this relationship. Relying on the dynamic capability theory and the innovation orientation literature, two hypotheses were formulated to examine these relationships. The findings of the study support the claim in H1 that innovation orientation is positively related to firms’ financial performance. This finding lends support to previous studies that have reported similar findings (Anning-Dorson et al., 2017; Bierly & Chakrabarti, 1996; Cooper, 2019; Liao & Rice, 2010; Mai et al., 2019). This leads us to conclude that companies with superior innovation capabilities would stay competitive (Anning-Dorson, 2016) and consequently increase their bottom line (Cooper, 2019; Mai et al., 2019). This finding is, however, at variance with previous that found a negative relationship between innovation capabilities and firms’ financial performance (Santos et al., 2014).

The second hypothesis of the study proposed that new product development moderates the influence of innovation orientation on firms’ financial performance. Disproving H2 the study findings revealed that new product development has little or no moderating effect on the relationship between innovation and firms’ financial performance. The possible explanation for this finding could be the increase in the adoption of technology and the incorporation of customer insight in the new product development process (Jin et al., 2019; Sethi et al., 2012). Furthermore, this finding lends support to that of Chaarani et al. (2021) who found that product innovation has no significant impact on the financial performance of SMEs in Lebanon. This enables companies to reduce the failure rate of new product development and thus the cost associated with the new product development process. Based on these findings, we conclude that a firm’s new product development capabilities do not affect its financial performance.

9. Implications for theory

The findings from the study as presented above offer opportunities for advancing theoretical and empirical research to increase our understanding of the subject matter. The study makes modest yet significant contributions to the marketing and management literature, particularly from the perspective of innovation and firm performance. First, the current study progresses our scholarly understanding of the innovation orientation literature by investigating the effect of complementary firm capability (New Product Development) on firm innovation orientation- performance relationship. In addition, this study extends the development of dynamic capabilities theory by discussing its dimensions which hitherto remained unexplored. This discussion of the theory aided the development of the measurement scales used in collecting data for the study. Further, this study brings a new perspective to the relationship between innovation capabilities and firms’ financial performance by looking at the influence of new product development on the relationship, which the study found to be negative.

10. Managerial implications

The findings of the study provide some useful lessons for business executives and management practitioners. This study has shown that innovation is not only a strategic tool but an avenue for increased profitability for firms. Business managers ought to strive for continuous innovation if they are to survive in the ever-increasing competitive market. The findings of the study suggest to business managers to integrate the firms’ acquired knowledge with that of customer insight in their innovation processes. This is because innovation (be it a process or new product) requires the acceptance of customers to be successful in the market, thus customers’ input at every stage of the innovation process is critical. Though this study found NPD to have a negative moderating effect on innovation and firms’ profitability relationship, it should not be mistaken by managers to mean a license for gut-feeling innovations. We suggest that companies still adopt a methodical approach to their innovations. This is because a haphazard innovation process could have a very costly effect on a company’s bottom line. This finding notwithstanding, there is an acceptable view that the innovation process is a cost item for companies that must be guided with a carefully thought out plan in order to reduce the associated cost.

11. Limitations and future research avenues

This study, nevertheless, is not without limitations. The identified limitations present opportunities for further research. First, given that the study design was cross-sectional and data collected from a developing country, an assumption of a static relationship among the variables is created. This shortcoming could be cured by a replicated study with a longitudinal research design or multi-country context study as this could ferret out more nuanced dynamics of the innovation and firm’s financial performance analogy based on differences in socio-economic and cultural values. The study found new product development to have a negative moderating effect on innovation orientation and firms’ profitability relationship and this appears to be at variance with theoretical assumptions. This presents an opportunity for further empirical examination of the model vis-a-vis the theory. Further studies may be carried out to examine variations, if any, in the hypothesized relationships across different business sectors. For instance, while the current study focused on firms in the manufacturing sector, future studies could look at the financial services sector or the hospitality industry.

Disclosure statement

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

Additional information

Funding

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

Notes on contributors

Zakari Bukari

Zakari Bukari is a marketing researcher with keen interest in the issues of green behaviour, climate insurance, strategy, political economy, voters` behaviour, customer/service experience, SME growth, resilience in emerging market during and after the global pandemic and consumer behaviour. He holds a Ph.D. in Marketing from Putra Business School, University Putra Malaysia, an MPhil from the University of Ghana Business School and BSc in marketing from the University of Professional Studies, Accra, respectively. Dr Bukari had previously worked as a Graduate Teaching and Research Assistant at the University of Ghana Business School. Dr Bukari has also worked as an adjunct lecturer at the IPE School of Management. He is a Global Awareness Society International Scholar. He won the 2019 Ph.D. candidate Global Scholar award, the 2020 Global Scholar award, and the 2023 young faculty Global Scholar award by the Global Awareness Society International (GASI). He has also been a reviewer and track committee member for the 2020 Academy of Marketing Science (AMS) world marketing congress and conference held in Australia and USA. He currently reviews for the Journal of Politics and Policy and the Journal of European Business and Management. H e is a Lecturer at University of Professional Studies Accra.