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Archives of Business Research – Vol. 9, No. 3
Publication Date: March, 03, 2021
DOI: 10.14738/abr.93.9726. Mkalama, B., Ndemo, B., Maalu, J., & Pokhariyal, G. (2021). Determinants of Innovativeness in Manufacturing Small and Medium
Enterprises in Kenya: Unpacking Entrepreneurial Orientation. Archives of Business Research, 9(3). 1-27.
Determinants of Innovativeness in Manufacturing Small and
Medium Enterprises in Kenya: Unpacking Entrepreneurial
Orientation
Ben Mkalama
University of Nairobi, Kenya
Bitange Ndemo
University of Nairobi, Kenya
Jackson Maalu
University of Nairobi, Kenya
Ganesh Pokhariyal
University of Nairobi, Kenya
ABSTRACT
In spite of firm innovativeness being identified as essential for
growth, there exists a dearth of studies that relate
entrepreneurial orientation and innovativeness in
manufacturing small and medium enterprises in the developing
world. In this article, we unpack the dimensions of
entrepreneurial orientation and examine their influence on
innovativeness of manufacturing small and medium
manufacturing enterprises. This was a cross sectional survey
with a stratified sample size of 363 firms. Regression models
were used to validate the derived hypothesis. We discuss the
implications of the results which show that the dimensions
were individually not found to have a significant effect on
innovation but yet entrepreneurial orientation had an influence
on firm innovativeness. We identify the need for additional
studies to broaden the scope of future studies across several
geographies. We conclude by challenging the ever-dynamic
local institutional policies that have not had a significant impact
on the effect of entrepreneurial orientation on innovativeness
of SMEs across many developing countries.
Keyword: Entrepreneurial Orientation, Innovativeness, Open
Innovation, SMEs, Manufacturing, Developing World, Kenya.
INTRODUCTION
At a time when rapid technological change creates shorter innovation cycles, one would not
be faulted for assuming that small and medium enterprises (SMEs) in emerging economies
should be the panacea for their challenges. This has however not happened leading
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Mkalama, B., Ndemo, B., Maalu, J., & Pokhariyal, G. (2021). Determinants of Innovativeness in Manufacturing Small and Medium Enterprises in
Kenya: Unpacking Entrepreneurial Orientation. Archives of Business Research, 9(3). 1-27.
URL: http://dx.doi.org/10.14738/abr.93.9726.
scholars to wonder, what causes disparities in innovation amongst SMEs in the emerging
economies? Scholars have demonstrated that a high SME sectoral output value serves as a
tonic to a country’s economic growth, because SMEs generally stimulate wealth creation by
causing additional goods, consumption, investments flows and job creation (O'Regan &
Ghobadian, 2005; Gilbert, 2007; Buli, 2016; Neneh & Zyl, 2017; Muriithi, 2017). SME
owners continue to grapple with decisions that would allow the right choices on the basis
of limited resources so that they could stimulate further innovation in their firms. Similarly,
to address the consistent policy dilemma, decision makers need to determine appropriate
triggers at a macroeconomic level to stimulate innovation in SMEs (Buli, 2016; Mamman,
Bawole, Agbebi, & Alhassan, 2019).
Although it has been argued that innovation comes about as a result of the entrepreneurial
actions of the firm owners, (Miller, 1983; Covin & Slevin, 1989; Dess, 2005; Wiklund and
Shepherd, 2005) there is no convergence of knowledge on the triggers for innovativeness
and growth in SMEs (Ejdys, 2016; Wales, 2016; Hochleitner, Arbussa, & Coenders, 2017;
Games, 2019; Mamman et al., 2019). Entrepreneurial orientation remains the leading
concept that seeks to explain the mindset and subsequent actions of the entrepreneurs
(Miller, 1983; Covin & Slevin, 1989). However, scholars have posited that to understand
entrepreneurial orientation and firm innovation within SMEs, there is a need to study it
separately as opposed to studying it from the context of a large organisation (McAdam,
Keogh, Reid and Mitchell, 2007; Oly & Agarwal, 2014).
As a result of the broadness of information requirements at a global level, there is limited
consensus on the causes of firm innovativeness in SMEs in the emerging economies
(Ayyagan, Beck, & Demirgue-Kunt, 2007; Ardic, Mylenko, & Saltane, 2011; Oly & Agarwal,
2014; Mamman et al., 2019; Maldonado-Guzmany, Pinzon-Castro & Rodriguez-Gonzalez,
2019). That notwithstanding, previous studies have shown that entrepreneurial
orientation affects the individual’s vision, resilience, as well as motivation to continually
improve their businesses (Covin & Slevin, 1989; Kuratko, Ireland, and Hornsby, 2001).
Even though scholars have previously argued that entrepreneurial orientation gives SMEs a
better competitive advantage (Wiklund & Shepherd, 2005), the conversations about the
influence of entrepreneurial orientation on SME innovation are still ongoing (Wang,
Hermens, Huang, & Chelliah, 2015; Mamman et al., 2019). Besides, the discourse on the
relationship between entrepreneurial orientation and firm innovation within the context of
developing countries has so far been limited (Rauch, Wiklund, Lumpkin, & Frese, 2009;
Buli, 2016; Mamman et al., 2019). This study sought to strengthen the theorisation of the
influence of entrepreneurial orientation on firm innovation from the context of a
developing economy.
Even though entrepreneurial orientation has been extensively studied (George & Marino,
2011; Andersen, Kreiser, Kuratko, Hornsby, & Eshima, 2015; Wales, 2016; Mkalama,
Ndemo and Maalu, 2018), the discourse on the causal relationships within the dimensions
of entrepreneurial orientation has similarly not been exhausted (Miller, 2011; Andersen et
al., 2015; Wales, 2016; Neneh & Zyl, 2017). The study further sought to strengthen the
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Archives of Business Research (ABR) Vol 9, Issue 3, March-2021
theorisation around each of the individual dimensions of entrepreneurial orientation from
an emerging markets context.
It has previously been argued that manufacturing rather than the agricultural sector leads
greater economic growth (Chege, Ngui, & Kimuyu, 2014; Su & Yao, 2017). However, a study
by African Development Bank (AfDB) averred that the manufacturing sector’s contribution
to GDP and employment across East Africa, was minor when compared to other territories
with its diversification being limited and the sector associated with low technological
development (AfDB, 2018). For instance, over the previous 11 years, the overall
manufacturing sector contributed a stagnant 11% of Kenyan income (GOK, 2015), and had
been on a downward spiral with a sectoral GDP growth rate of 0.2% in 2017 (World Bank
Group, 2018). This was inadequate to address the underlying problems of low economic
growth and resultant unemployment. As a result of this, the study focused on
manufacturing SMEs in Kenya who have been linked to little automation that was
estimated at 32% within the segment and low value addition and ensuing low productivity
(GOK, 2013; KNBS, 2016; KAM, 2019; Ndemo & Mkalama, 2018).
The study adopts the lens of the resource-based view (RBV) (Wernerfelt, 1984; Barney,
1991; Wernerfelt, 1995) which argued that firms differentiated themselves on the basis of
the valuable, unique, inimitable and limited resources that exist within it (Wernerfelt,
1995). According to RBV, the available resources include financial, physical, human,
technological, reputational or organizational resources (Barney, 1991). Entrepreneurial
orientation is therefore viewed as that intangible resource that provides competitive
advantages and therefore higher levels of innovation to SMEs (Wiklund & Shepherd, 2005;
Maldonado-Guzman et al., 2019).
The contribution of this article is context specific because previous studies have been
focused in other territories. Indeed, Mamman et al., 2019 argued that entrepreneurial
orientation as conceptulialised did not consider the African social norms and traditions and
thus entrepreneurial orientation may need to be laced with additional exogenous factors to
have adequate influence on entrepreneurship. The article demonstrates that the
conceptualisation of firm innovativeness in SMEs in developing countries is still
inconclusive. The study contributes to the discourse by hypothesising that four dimensions
of entrepreneurial orientation, namely autonomy, proactiveness, risk taking and
competitor aggression are related and influence firm innovation. Furthermore, the article
demonstrates that there is a need for additional conceptualisation on entrepreneurial
orientation and its relationship to firm innovation. Being as it is, the complexity of SME
information requirements is such that the article further highlights a need for future
empirical research that would encompass a simultaneous examination across several
geographies using the same set of research instruments in a bid to examine the same set of
factors.
THEORETICAL FRAMEWORK
Entrepreneurial Orientation
Originally from the pioneering work of Mintzberg (1973), entrepreneurial orientation is
commonly considered as a multidimensional construct that is made up of dimensions that
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Mkalama, B., Ndemo, B., Maalu, J., & Pokhariyal, G. (2021). Determinants of Innovativeness in Manufacturing Small and Medium Enterprises in
Kenya: Unpacking Entrepreneurial Orientation. Archives of Business Research, 9(3). 1-27.
URL: http://dx.doi.org/10.14738/abr.93.9726.
include pro-activeness, innovativeness, risk taking (Miller, 1983; Covin & Slewin, 1989),
competitive aggressiveness and autonomy (Lumpkin & Dess, 1996; George & Marino,
2011). These dimensions were empirically found as significant across different sizes and
complexities of firms (Miller, 1983). The influence of these dimensions varies and may
range from the internal reasons to external factors (Lumpkin & Dess, 1996; Miller, 2011).
There is no common position on what other dimensions beyond the initial three Miller
dimensions should be considered (Miller, 2011; George & Marino, 2011; Andersen et al.,
2015; Wales, 2016; Neneh & Zyl, 2017). Being that this is a glaring research area which
requires additional research (George & Marino, 2011; Andersen et al., 2015; Wales, 2016),
the focus of this paper will add to the theorisation on the four dimensions within the
emerging markets context.
Firm Innovation
Innovation is explained as that openness to a new way of doing things with a view of
attaining the same or superior quantity and quality of products (Miller,1983; Covin &
Slewin, 1989; Wiklund & Shepherd, 2005). Innovativeness has been defined as a
continuous process that includes the culture, level and potential that creates a new
product, service or process that will be commercialized to allow an economic or social
impact (Hult , Hurley, & Knight, 2004; Gilbert, 2007; Neely & Hii, 2012; Doroodian, Ab
Rahman, Kamarulzaman, & Muhamad, 2014). Innovativeness has been extensively studied
by scholars (Oscarsson, 2003; du Preez & Louw, 2008).
Distinct from innovation which is an output, innovativeness is cognised as that constant
latent process that creates a new product, service or process that will be subsequently
commercialised to allow an economic or social impact (Doroodian, Ab Rahman,
Kamarulzaman, & Muhamad, 2014; Neely & Hii, 2012). A review of literature indicates that
there is no coherence in the conceptualization of innovativeness and its antecedents
(Perez-Luno, Wiklund, & Cabrera, 2010). It should be further noted that innovation is
incremental, accumulated over a period of time (Suarez-Villa, 1990) and is a combination
of exploration and exploitation (Perez-Luna et al, 2010; Ejdys, 2016).
The most commonly accepted indicators of innovation and innovativeness, include number
and types of new products and services as well as the amount spent on research and
development (OECD, 2005; Massa & Testa, 2008; Perez-Luno & Blasco, 2015). Other
indicators include specialised skills of staff, number of licenses, patents and trademarks
generated as a result of the activity, information disseminated in literature, the absolute
amount of sales of innovative products, the number of innovations, and even the increase in
revenue and market share as a result of new products (Massa & Testa, 2008).
Research Objective
A synthesis of the literature review indicated that there was a need to further examine the
validity of entrepreneurial orientation with a specific reference to the developing world. On
this basis, our research objective was formulated so as to establish the influence of
entrepreneurial orientation as a second order construct on firm innovativeness in
manufacturing SMEs in Nairobi. The conceptual model is shown as Figure 1.
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Figure 1: Conceptual Model
In the model, the dimensions of entrepreneurial orientation have been operationalised as
autonomy, proactiveness, risk taking and competitor aggression. Firm innovativeness is
considered as the dependent variable in this relationship.
Development of Research Hypothesis
Entrepreneurial Orientation and Firm Innovativeness
Empirical studies albeit with limited consensus have shown entrepreneurial orientation to
be a prerequisite for innovativeness (Hult et al., 2004; Avlonitis & Salavou, 2007; Perez- Luno, et al., 2010; Laforet, 2011; George & Marino, 2011; Ruiz-Ortega et al., 2013; Wales,
2016; Ejdys, 2016). The relationship however remains inconsistent because whereas in
some cases entrepreneurial orientation has been constructed as a predictor variable, in
other cases it has been constructed as a predicted variable. Additionally, in some cases
entrepreneurial orientation has had a moderating influence, yet in other cases it has been
found to have mediating action on other constructs (Madhoushi, Sadati, Delavari,
Mehdivand, & Mihandost, 2011; Acosta, Nabi, & Dornberger, 2012; Joshi, Das, & Mouri,
2015; Ma, Guo, & Shen, 2019; Covin & Wales, 2019). Furthermore, the focus of most of the
studies has not been on innovation as an outcome thus creating a conceptual gap.
Numerous studies have been carried across different regions studying the relationship
between composite entrepreneurial orientation and other study variables with varying
results (Rauch et al., 2009; George & Marino, 2011; Andersen et al., 2015; Wales, 2016).
Even though entrepreneurial orientation was considered to influence competitive
advantage, Neneh and Zyl (2017) established that the level of entrepreneurial orientation
on SMEs was moderate and that this had an effect on the growth of South African SME
firms. Pustovrh, Jaklic, Martin, and Raskovic (2017) opined that even though
entrepreneurial orientation affects innovativeness and thereafter facilitate innovativeness
in Slovenian SMEs, subsequent commercialization was not certain without
commercialisation enablers being in place.
The conversation around the key dimensions of entrepreneurial orientation is also yet to
be exhausted (Perez-Luno et al., 2010; Joshi et al., 2015, Ejdys, 2016).) The debate on which
of the dimensions of entrepreneurial orientation to apply remains open (Neneh & Zyl,
2017). Neneh and Zyl (2017) argued that the concerns ranged from concerns on overlaps
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Mkalama, B., Ndemo, B., Maalu, J., & Pokhariyal, G. (2021). Determinants of Innovativeness in Manufacturing Small and Medium Enterprises in
Kenya: Unpacking Entrepreneurial Orientation. Archives of Business Research, 9(3). 1-27.
URL: http://dx.doi.org/10.14738/abr.93.9726.
in the dimensions to lack of discrimination between some of the dimensions. It was evident
that there were still divergent opinions on the causal relationships within the dimensions
of entrepreneurial orientation and other variables (Wiklund & Shepherd, 2005; Miller,
2011; George & Marino, 2011; Andersen et al., 2015). This is notwithstanding the fact that
there is a need for further studies to validate these arguments across various geographies,
cultures and industries (Acheampong, 2017; Chang, Eggers, Rigtering, & Kraus, 2017).
Contextually, most of the research has been carried out in the developed world and on
specific industries and thus may not universally apply (Rauch, et al.,2009; Buli, 2016).
There is a need that similar studies be carried out in other countries and industries so as to
validate the empirical data with theory because it has been shown that as entrepreneurial
orientation behaves differently in different cultural contexts (Lumpkin & Dess, 1996; Chang
et al., 2017; Watson, Dada, Wright, & Perrigot, 2019). Furthermore, most of the studies
reviewed in Kenya studied entrepreneurial orientation with dependent variables other
than innovativeness (Ngoze & Bwisa, 2014; Katialem, Muhanji, & Otuya, 2018; Mkalama et
al, 2018). Other studies did not focus on all dimensions of entrepreneurial orientation
(Gudda, 2017). This article uniquely provides context specific attention to the five different
dimensions as it seeks to strengthen the previous theorisation on firm innovativeness.
Entrepreneurial Orientation was constructed as having five dimensions, namely Autonomy,
Proactiveness, Risk taking, Innovativeness and Competitor Aggression (Lumpkin & Dess,
1996; Lumpkin et al., 2009; Andersen et al., 2015).
Autonomy and Firm Innovativeness
Autonomy is considered to be the self-ability to make a decision without undue influence
from other interested parties and seeing through all ideas to fruition (Lumpkin & Dess,
1996; Wiklund & Shepherd, 2005). Unlike the original three dimensions of entrepreneurial
orientation, the influence of the dimension of autonomy and competitor aggressiveness
have not been exhaustively researched (Mason, Floreani, Miani, Beltrame, & Cappelletto,
2015).
A number of studies on the concept have nevertheless been carried out but the findings
have not been consistent. For instance, Felicio, Rodrigues, and Calderinha (2012)
established a positive influence of autonomy of intrapreneurship in Portuguese SMEs.
Lechner and Gudmundsson (2014) also studied the influence of autonomy on
differentation strategy and firm performance and confirmed a significant postive influence
on the relationship. Ngoze and Bwisa (2014) established that autonomy in Kenyan
manufacturing firms had a positive and significant effect on their performance. Gautam
(2016) established that autonomy positively affected with firm performance on Nepalese
handicraft firms. Katialem et al., (2018) in a Kenyan study on manufacturers established
that autonomy was related to business performance.
Conversely, Musa, Ghani and Ahmad (2014) were not able to establish a significant
relationship between autonomy and performance on a sample of cooperative firms.
Similarly, Mason et al., (2015) were not able to establish the influence of autonomy on SME
firm performance in Italian firms. Additionally, Shah and Ahmad (2019) studied but were
unable to establish the influence of autonomy on SME firm performance, in as much as
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Mkalama, B., Ndemo, B., Maalu, J., & Pokhariyal, G. (2021). Determinants of Innovativeness in Manufacturing Small and Medium Enterprises in
Kenya: Unpacking Entrepreneurial Orientation. Archives of Business Research, 9(3). 1-27.
URL: http://dx.doi.org/10.14738/abr.93.9726.
There are several approaches to the discourse on risk taking. The first approach argues
that risk taking positively affects innovativeness (Joshi et al., 2015; Gudda, 2017), whereas
the second approach posits that risk taking negatively affects innovativeness (Kreiser,
Marino, Kuratko, & Weaver, 2013; Lechner and Gudmundsson, 2014). Furthermore in their
study, Felicio et al., (2012) separated the propensity for risk taking in two latent variables;
risk propensity in the face of uncertainty and risk propensity in the face of new challenges.
The study by Felicio et al concluded that both latent variables influenced intrapreneurship
in corporate firms.
Perez-Luno et al., (2010) established that risk taking as a dimension of entrepreneurial
orientation positively affected innovations generated by Spanish SMEs. Conversely, Kreiser
et al., (2013) found that risk-taking showed a predominantly negative U-shaped
relationship with SME performance. These results were incongruent with those of
Rigtering (2013) and Musa et al., (2014) whose effect of risk taking on innovativeness was
not found as significant. Lechner and Gudmundsson (2014) established negative significant
influence of risk taking on the relationship between differentation strategy and firm
performance in Iceland SMEs.
Joshi et al., (2015) investigating the role of risk taking concluded that it has a significant
positive linear influence on innovativeness in technology-based firms in United States.
Ejdys (2016) also confirmed that risk taking affected pro-activeness of Polish SMEs, but
was unable to confirm that risk taking as a dimension affected innovativeness. Gudda
(2017) established that risk taking dimensions positively affected SMEs product
innovativeness on Kenyan manufacturing SMEs thus confirming the results of previous
studies. Neneh and Zyl (2017) showed that SME firms have a weak propensity for risk
taking.
This review demonstrated that there were inconsistencies in the influence of risk taking on
innovativeness creating a need for further firm-level research of this nature so as to
conceptualize this relationship further. Risk taking requires an assessment and
determination of the nature of uncertainly and the potential reward in place. Risks that are
not well thought out will be poorly executed and most likely not perceived as innovative.
We postulate that there is a positive relationship between risk taking and firm innovation,
whereby more well thought risks lead to greater innovation. This led to the formulation of
the following sub hypothesis; -
H1c: Risk Taking significantly affects firm innovativeness in Manufacturing SMEs
Competitor Aggression and Firm Innovativeness
Competitor Aggression can be said to be that behaviour of a firm that robustly gives it an
advantage over its competitors (Lumpkin & Dess, 1996). Not much conceptualisation has
been done on this dimension with respect to SMEs (Mason et al., 2015). In the case of the
studies reviewed, the findings were inconsistent. For instance, whereas Ngoze and Bwisa
(2014) established that competitor aggression had a positive and significant effect on firm
performance, Musa et al., 2014 was not able to establish a significant relationship between
competitor aggression and performance on a sample of Malaysian cooperative firms.
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Mkalama, B., Ndemo, B., Maalu, J., & Pokhariyal, G. (2021). Determinants of Innovativeness in Manufacturing Small and Medium Enterprises in
Kenya: Unpacking Entrepreneurial Orientation. Archives of Business Research, 9(3). 1-27.
URL: http://dx.doi.org/10.14738/abr.93.9726.
administration assessment aided in reducing the non-response rate. Where the potential
respondents were not interested or did not fall in the defined scope of firms, the
enumerator did not issue the questionnaire and instead proceeded to the next randomly
selected respondent firm. No incentives were provided to the respondents.
During the full-scale survey, a total of 245 questionnaires were completed and returned. A
pre-analysis check eliminated 8 questionnaires as not falling within the scope of the survey
leaving a total of 237 usable survey responses. This worked out to a response rate of 65.3%
which was considered adequate. Of the responses received, none of the strata exceeded
more than 25% of the entire sample population.
As a preliminary step, upon receipt of the completed questionnaire, they were checked for
consistency and to isolate any obvious inconsistencies. Data coding, and entry thereafter
happened. The posted data was subsequently reviewed for any data entry errors or
illogical gaps and responses. Analysis was then carried out using Version 25 of the
Statistical Package for the Social Sciences (SPSS) to search for trends and relationships in
the data. Of the 237 responses that were considered usable, a majority were completed
exhaustively whereas a few had elements of missing data. These were analysed and treated
as missing at random (MAR) but overall findings retained (de Leeuw, Hox, & Huisman,
2003).
Measurements of the Constructs
The measurement of the constructs involved elements of subjectivity and relativity and
therefore multi-item scale was used to obtain the data on the independent variables.
Previously validated instruments provided the basis of the instrumentation applied (Miller
& Friesian, 1983; Covin & Slewin, 1989; Lumpkin & Dess, 1996, 2001; Massa & Testa, 2008;
Lumpkin et al., 2009; Perez-Luno & Blasco, 2015). An adaptation of the commonly used
Miller/Covin and Slewin (1989) Entrepreneurial Orientation Scale (Lumpkin & Dess, 1996;
Lumpkin, Cogliser, & Schneider, 2009) was used to measure the dimensions of
entrepreneurial orientation. This was a multi-item Likert type scale that had various
measures in the dimensions of entrepreneurial orientation. However, in the
operationalization of entrepreneurial orientation, innovativeness was dropped as a
dimension on the independent variables and innovation outcomes used as a dependent
variable. This was also consistent with previous research (Sekaran& Bougie, 2013; Joshi et
al., 2015; Ejdys, 2016; Gudda, 2017).
In the measurement scales, the respondents scored between 1 and 5 for each statement
representing a sub variable, with 1 being lowest score of “Strongly Disagree” whereas 5
was the highest score at “Strongly Agreed”. A higher overall score on the scales indicates
higher orientation whereas lower scores indicate a more conservative orientation.
Similarly, an adaptation of the Miller and Friesian (1983) Scale was used to measure
innovation (Miller & Friesian, 1983; Massa & Testa, 2008). Respondents to evaluate
innovation in their firms based on the basis of three items that focussed on products,
service and systems change on a 5-point Likert scale. A summary of the codes used in the
statements appears in Appendix I.
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predictors used in the analysis. Consistent with the recommendations by Hair, Black, Babin,
& Anderson, (2014), a hierarchical multiple regression Model was used to test the
hypothesis that entrepreneurial orientation significantly affect firm innovativeness. The
model was statistically controlled for percentage creativity and innovation budget for the
firm in the past year, years of operation, and estimated annual sales of the firm for the past
year. This approach was consistent with the recommendations of Pallant (2005). The
models applied were; -
Y1=a11 + μ11Q + b11X1 + b12X2 + b13X3 + b14X4 + e1
Where Y1,2 = Firm Innovativeness; Q = Control variables; X1 = Autonomy; X2 = Proactivity;
X3 = Risk Taking; X4 = Competitor Aggression; e1 = Error
The coefficients of correlation (R) and determination (R2) and Adjusted (Ra2) were also
obtained and analysed in each of the models. In addition to this, coefficient (β) that
indicated correlations between the predictor and the outcome variable were obtained. The
model summary as captured in Table 4 was derived; -
Table 4: Hierarchical Multiple Regression Model Summary Predicting Firm
Innovation Outcomesc
Model R R2 Adjusted R2 Std. Error of the
Estimate
Change Statistics
∆R2 ∆F df1 df2 ∆Sig. F
Base
Model
.344a .118 .104 3.25056 .118 8.622 3 193 .000
Main
Effects
Model
.362b .131 .099 3.26104 .013 .690 4 189 .599
a. Predictors: (Constant), Percentage creativity and innovation budget for the firm in the past year,
Years of Operation, Estimated annual sales of the firm for the past year (logarithmically transformed)
b. Predictors: (Constant), Percentage creativity and innovation budget for the firm in the past year,
Years of Operation, Estimated annual sales of the firm for the past year, (logarithmically
transformed); Risk Taking, Competitor Aggression, Autonomy, Proactiveness (Actual values)
c. Dependent Variable: Firm Innovation Outcomes
The data suggest a moderate relationship between the independent and dependent
variables, R = 0.362. The coefficient of determination showed a low variability of the
variables around the regression line, R2 = 0.131. The adjusted findings of the coefficient of
determination suggest an overfitting of the original model, Ra2 = 0.099. This implied that
9.9% of firm innovativeness was explained by the independent variables in the model. In as
much as the R2 values are low, this is not uncommon in social sciences as they are mostly
predicated on human behaviour, which is often unpredictably immeasurable (Moksony,
1990; Hair, Ringle, & Sarstedt, 2013).
A comparison of the various correlations between the predictor and dependent variable is
presented in Table 5.