Article Type : Research Article
Authors : Fouzder H
Keywords : Drink; Wash; Swimming; Showering; Feel
The term innovation performance is defined
as the use of an ideas or creativity to improve the processes and procedures
that increase the significance, usefulness and performance of the products and
services. For example, when we think about innovating in production and
distribution of water we do not think only in the amount of water that people
want, but also what the use that it will have (drink, wash, swimming,
showering, feel, etc.). In organizations it is very much important to identify
and develop new and innovative ideas in order to reach its goals.
The term innovation performance is defined as the use
of an ideas or creativity to improve the processes and procedures that increase
the significance, usefulness and performance of the products and services. For
example, when we think about innovating in production and distribution of water
we do not think only in the amount of water that people want, but also what the
use that it will have (drink, wash, swimming, showering, feel, etc.). In
organizations it is very much important to identify and develop new and
innovative ideas in order to reach its goals. We know that in recent years,
innovation become increasingly important in all organizations all over the
world including the teaching organizations.
Innovation enables organizations to be able to respond rapidly and
flexibly adapts to changes in the environment and respond better to the actual
needs of consumers or users. Accordingly, the innovative ideas, thinking and
strategies of the university teachers which will help offer creative teaching
learning environment for the students; to achieve competitive advantage and
increase their performance.
A wide body of literature has arisen that identifies
the common factors shared by innovative organizations and the factors that
impact on the ability to manage innovation. The general management literature
often prescribes that organizations should increase their organizational
innovativeness to remain competitive, but the literature often neglects to
address how organizations can impact on their ability to manage innovation
[1-3]. Using this body of literature, we conduct a structured literature review
that identifies the organizational factors that influence the ability to manage
innovation at the firm level. Such a systematic approach to the innovation
literature is missing from the current body of literature. By identifying and
analyzing the factors, we identify where relationships between the factors
exist, this is achieved though identification of the relationships that are
commonly cited in the literature. This will enable academics and practitioners
alike to understand what factors can be manipulated by organizations to
increase their ability to manage innovation. Although this paper does not
provide a prescriptive method for organizations to follow to become innovative,
it does identify what factors and relationships are important in impacting an
organizations ability to manage innovation. The aim of this paper is to provide
a comprehensive view of the factors which influence an organizations ability to
manage innovation. Often studies regarding success factors for innovation
considers these factors independent of each other, we argue in this paper that
the factors are not independent of each other and are in fact interrelated [4].
We therefore put forward the proposition that innovation management needs to be
considered in a holistic manner. To rationalize the factors influencing an
organization’s ability to manage innovation a strategy was used that has been
described in different ways by different authors. Uses ‘Nominal Group’
technique, i.e. a physical gathering where the participants use brain-storming
techniques, and private ranking of ideas and tabulation [5,6]. In pursuit of
clarity we have described what each of the factors mean in the context of this
research as they can often have different meanings in different contexts.
Technology is often discussed as an output of
innovation but in this research we are concerned with its role as an
influencing factor [7]. Technology discussed in this paper is concerned with
the utilization of technology to facilitate innovation and innovative behavior
within and between organizations. Although a few authors discuss the impact of
operational processes on organizational innovativeness, in the context of this
paper processes relate to the generation, development and implementation of
innovations [8-11]. Strategy is a wide subject area and the definition can
often be confusing. Strategy in this research refers to aspects of the
corporate and innovation strategies of the organization and how they impact on
the management of innovation [12,13]. It also refers to the dissemination of
the strategic vision throughout the organization. Organizational structure has
received much attention in the general management literature and often covers
more than the simple configuration of the organization [14]. However, within
this research organizational structure relates to the way the various parts of
an organization are configured and how this impacts on an organizations ability
to manage innovation. Culture here refers to the culture of the organization,
although organizational culture has been discussed widely in general management
literature [15]. In the context of this research it relates to the values and
beliefs of the organization and how these impact the ability to manage
innovation within the organization. It takes into consideration the
organization’s approach to collaboration, communication and risk. Employees
refers to the non-management employees of the organization and the role they
play in affecting innovation management. This factor takes into account the
various personal characteristics associated with employees and the motivation
of employees to become innovative [16,17]. Resources relates to all the resources
that the organization has, human, financial and physical, but they are
discussed in relation to the level of slack resources and how resources are
managed to impact on an organizations ability to manage innovation [18-20].
Knowledge management in this research refers to the management and utilization
of knowledge for innovation management. This covers all aspects of knowledge,
both internal and external to the organization. This factor will also take
organizational learning into consideration as it plays a key role in knowledge
management [21]. Management style and leadership refers to the employees that
have responsibility for the management of the organization. This factor is
concerned with a number of aspects to the way management influences the management
of innovation. For example it takes into account the management style within
the organization and how management can motivate employees to become more
innovative [22-25]. Although our findings do share some common factors with
other studies we have provided a more comprehensive view of the literature
concerning the factors that influence innovation management. The work carried
out in this research encompasses different academic fields and organizational
contexts. The value in this work is not in the identification of the factors
but the examination of the important relationships between the factors. This
provides a more complete view of how these factors and relationships impact on
innovation management. This research aims to open up the debate on innovation
management as a systemic approach by organizations and not merely focused on
singular factors. Frequently innovation management literature discusses the
factors that affect organizations’ ability to innovate in a way that treats the
factors as mutually exclusive, meaning that each factor has an individual
impact on innovation. However, the relationships between the factors and the
impact these relationships have on innovation are largely ignored. This means
that the cumulative effect of the factors and their relationships are not fully
understood. This paper has shown that there are a number of important
relationships that need to be examined in greater detail to understand how
their effects impact on an organization’s ability to manage innovation. Many
studies have been carried out in the field of innovation performance but there
is a visible gap that most of them showed only the theoretical clarification of
the concept, and a few of them have tried to explore the factors that determine
the innovation performance of the university teachers. So this project is an
effort to disclose the above crucial issue and to make the authorities aware
about. Another prominent issue is that only a few works has been carried out in
the perspective of Bangladesh to uncover this crucial issue, so this project is
an effective effort to fulfil the gap.
The objectives of the study are
Data collection tools,
samples and sampling technique
The data for this study was collected through a
questionnaire survey, which from the university teachers of two public
universities in the Mymensingh district of Bangladesh. A well-structured
questionnaire with five point Likert-type scale, where 1= strongly disagree and
5= strongly agree was used for the questions. The questionnaire was distributed
to the respondents through hand to hand and through mail survey. Based on the
previous literature, the researcher described and accumulated 37 different
issues (factors), or elements that indicate the innovation performance of an
individual (see appendix). The questionnaire consists of those elements with
the above stated five point scaling.
Data analysis tools
The study analyzed 185 data collected through the questionnaire
survey. To analyze the collected data from the respondents, SPSS version 25
software and several sets of statistical analyses were used. Descriptive
statistics and the exploratory factors analysis were used to analyze the
collected data from the respondents.
Reliability of data
The reliability of the data was assessed by measuring the Cronbach’s alpha. The alpha value of the 30 items questionnaire was .942 (Table 1). The detailed reliability statistics are shown in the table 1 in the Appendix I. It shows the individual item reliability value and the scale value if any of the items is deleted.
Analysis
of Findings
Demographic profile of
the respondents Kaiser-Meyer-olkin (KMO) and bartlett’s test
The KMO measures the sampling adequacy which should be
greater than 0.5 for a satisfactory factor analysis is to proceed. If any pair
of variables has a value less than this, consider dropping one of them from the
analysis. The off-diagonal elements should all be very small (close to zero) in
a good model. Looking at the table (Table 2) below, the KMO measure is 0.705.
The value 0.5 for KMO test is minimum and barely accepted, values between
0.7-0.8 are acceptable, and values above 0.9 are superb. Bartlett's test is
another indication of the strength of the relationship among variables. This
tests the null hypothesis that the correlation matrix is an identity matrix. An
identity matrix is matrix in which all of the diagonal elements are 1 and all
off diagonal elements are 0. From the same table, we can see that the
Bartlett's test of sphericity is significant That is, its associated
probability is less than 0.05. In fact, it is actually 0.000, i.e. the
significance level is small enough to reject the null hypothesis. This means
that correlation matrix is not an identity matrix.
Descriptive statistics
and communalities
Following table 4 shows the descriptive statistics and
communalities (variances) of all of the items uses in this study for factor
analysis. The table shows that the item knowledge of teaching and learning
methods has the highest mean value (4.46) where the item sufficient resources
has the lowest mean value (2.51). Standard deviation measures the variability
of data. Following (Table 3) shows that the item rewords and recognition has
the highest variability of responses (1.108) on the other hand the item
knowledge of teaching and learning methods had the lowest variability of
responses (.571). The communalities are commonly used in factor analysis to
show how much of the variance in the variables has been accounted for by the
extracted factors (Alam and Bhuiyan, 2014). For instance in the above table 4,
over 88% of the variance in innovative work behavior, over 87% of the variance
in collaboration is accounted for while 46.5% of the variance in Utilization of
knowledge and skills is accounted for.
Number of factors to be
extracted
Total variance explained and the scree plot are
commonly used to identify the number of factors extractable from the analysis.
The factor (component) which has the eigen value (the scree plot in the
Appendix II shows all the components with their eigen values in a single graph)
more than 1 is normally considered to be
extracted as factor (Alam and Bhuiyan, 2014; Talukder et al, 2014). In the
following (Table 4), it is seen that only 8 of the factors have the eigenvalues
over 1 and all other remaining are not significant (>1). So 8 factors can be
extracted in this study.
Factor (Component)
Matrix
The table (Table 5) below shows the loadings of the 30 variables on the 8 factors extracted. The higher the absolute value of the loading, the more the item contributes to the factor. The gap on the table represent loadings that are less than 0.4, this makes reading the table easier. The researchers suppressed all loadings less than 0.4. The following (Table 6) shows that nine items are loaded in the factor 1, six items are loaded in factor 2 and four items are loaded in the factor 3, 4, 5, and 6. The table also shows that some of the items are loaded in several factors such as the item application of management/leadership styles is loaded in both the factors 1 and 6; item quality of educational system is loaded in both the factors 5 and 8. These types of items are extracted based on their highest loaded value in a particular factor. For example, the item application of management/leadership styles has the higher loading value in the factor 1, so it is extracted as an item of the factor 1.
Naming of the factors
Based on the factor matrix in the above table 6 the
researchers named the factors considering the loaded items in each of the
factors. The following table 6 shows the loaded items in each factor and their
names.
The study explored the prominent factors (and the
corresponding items in each factor) that determine the innovation performance
of the university teachers in the public universities of Bangladesh. Therefore,
the findings of the study will have both theoretical and practical values among
the concerns such as the university authorities, faculty members and the
academic researchers. The result of the study will add value to the body of the
literature on innovation performance. It will help concerned authorities of the
universities be aware about the research factors that determine the innovation
performance of the faculty members. The findings will bring awareness among the
faculty members working in different public as well as private universities of
Bangladesh. Moreover, the results from this investigation will help the
university teachers achieve the strong sense of innovation performance and to
adopt more teaching-learning styles and strategies.