Content uploaded by Mesfin Mala Kalko
Author content
All content in this area was uploaded by Mesfin Mala Kalko on Jul 15, 2022
Content may be subject to copyright.
Full Terms & Conditions of access and use can be found at
https://www.tandfonline.com/action/journalInformation?journalCode=rajs20
African Journal of Science, Technology, Innovation and
Development
ISSN: (Print) (Online) Journal homepage: https://www.tandfonline.com/loi/rajs20
Technology management practices and
innovation: Empirical evidence from medium- and
large-scale manufacturing firms in Ethiopia
Mesfin Mala Kalko, Obsa Teferi Erena & Sara Adugna Debele
To cite this article: Mesfin Mala Kalko, Obsa Teferi Erena & Sara Adugna Debele (2022):
Technology management practices and innovation: Empirical evidence from medium- and large-
scale manufacturing firms in Ethiopia, African Journal of Science, Technology, Innovation and
Development, DOI: 10.1080/20421338.2022.2040828
To link to this article: https://doi.org/10.1080/20421338.2022.2040828
© 2022 The Author(s). Co-published by NISC
Pty (Ltd) and Informa UK Limited, trading as
Taylor & Francis Group
Published online: 27 Mar 2022.
Submit your article to this journal
View related articles
View Crossmark data
Technology management practices and innovation: Empirical evidence from medium- and
large-scale manufacturing firms in Ethiopia
Mesfin Mala Kalko
1
, Obsa Teferi Erena
2
and Sara Adugna Debele
2
1
Faculty of Management and Economics, Tomas Bata University in Zlin, Mostni 5139, Zlin 760 01, Czech Republic
2
College of Business and Economics, Hawassa University, P.O.Box: 05, Hawassa, Ethiopia
*Corresponding author email: kalko@utb.cz
In order to investigate empirically the effects of technology management on firm innovation, this paper considers the
antecedents and multidimensional views of technology management mechanisms on innovation performance in
medium- and large-scale manufacturing firms in a developing country, namely Ethiopia. Using simple random
sampling, a total of 200 firms were chosen for this study to obtain responses from respondents. Four hypotheses were
proposed for testing. Structural equation modelling and cross-sectional design were used to analyze the data using the
LISREL 8.80 SIMPLIS program software tool. This study finds technology transfer and technology acquisition have
significant positive effects on process innovation, product innovation, and method innovation. Technology process has
a significant positive effect on process and method innovation. Technology absorption has a significant positive effect
on product innovation. The major implication of this study is that technology management, coupled with appropriate
technology management policies and strategies, is an appropriate resource to be used in the organization to enhance
firm performance, particularly innovation and creativity. The paper contributes to the literature in that, unlike previous
studies that are based on one aspect of technology management practices, this study examined the effects of each
different type of technology management dimension on firms’innovation. Thus, this study helps to gain further
insights into the effects of technology management practices on firm innovation.
Keywords: technology management, innovation, structural equation modelling, manufacturing firms, Ethiopia
Introduction
Technology management is defined as the cross-functional
operations core competency of designing, managing, and
integrating a firm’s technological fundamentals to create
a competitive advantage (Utterback 1971). Hitt, Ireland,
and Lee (2000) recommend that technology advance is
the main factor of firm performance in the twenty-first
century. Hung and Chou (2013) reveal that technological
innovation is one of the most important factors for a firm
to enhance its performance in the current global industry.
Hsu et al. (2014)confirm that technology management
positively influences innovation. In addition, regardless
of the industry in which they operate, innovative firms
are more likely to enjoy revenue growth (Thornhill
2006). Ortega (2010) evaluates the positive role of techno-
logical capabilities in moderating the relationship between
competitive strategies and a firm’s performance. Building
technological or innovative capacity requires a huge
amount of resources (human and financial) and takes a
long time to attain the optimum benefits.However,ifa
firm needs to operate a business (deliver products or ser-
vices), there is no alternative but to elevate its technological
innovation capability through investing in research and
development, learning, and exploiting existing or new
knowledge. Furthermore, as competition in global
markets becomes more intense and frequently driven by
technology, technological knowledge may become even
more important for firms with global ambitions (Boudreau
et al. 1998).
The innovative capacity of a firm usually reveals the
extent of its competitiveness at the national or
international level. The mode of foreign technology pro-
curement also determines the firm’s innovative capacity
and performance. Nevertheless, acquiring external tech-
nology alone is not enough to increase productivity.
It needs to be changed, modified, improved and conceptu-
alized locally to promote innovation. In this regard,
empirical evidence (Wakeford et al. 2017; Oqubay
2018; UNDP, 2018; Chebo and Wubatie 2020) confirms
that the Ethiopian manufacturing sector is characterized
by low technological know-how, a shortage of skilled
labour, a lack of industry knowledge, a low rate of techno-
logical products and innovation, weak inter-and intra-sec-
toral linkages, and weak links with universities and
research institutions. In addition, the World Economic
Forum’s(2019)Global Competitiveness Index report
ranked Ethiopia 126th out of 141 economies, suggesting
that the sector needs enormous structural changes in
terms of technological capacity, innovation, organiz-
ational learning, leadership, and corporate governance in
order to be competitive both in national and international
markets. As a result, the issue of what empowers innova-
tive activity and later enhances firm performance in Ethio-
pian manufacturing firms continues to be on the research
agenda. The World Bank’s(2014) report on doing
business however confirms that Ethiopia has better ease
of doing business and an innovative environment for
industrial development than many other African
countries. It recommends that improvements in this
regard should be coordinated with R&D and skills devel-
opment to foster technological investment at the firm
level. The United Nations report (2015) also supports
African Journal of Science, Technology, Innovation and Development is co-published by NISC Pty (Ltd) and Informa Limited (trading as Taylor & Francis Group)
This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives License (http://creativecommons.org/
licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited, and is not
altered, transformed, or built upon in any way.
African Journal of Science, Technology, Innovation and Development, 2022
https://doi.org/10.1080/20421338.2022.2040828
© 2022 The Authors
the idea that no industrial policy is complete without an
accompanying innovation policy.
There have been few studies on the relationship
between technology management practices and inno-
vation. For example, Hussen and Çokgezen (2019) ana-
lyzed the external factors of firm innovation in
Ethiopian manufacturing firms. Kang, Jo, and Kang
(2015) used a binomial regression model to evaluate
whether external technology acquisition is complemen-
tary or substitutive to internal research and development
operations and activities in South Korean firms. García-
Vega and Vicente-Chirivella (2020) applied propensity
score matching techniques to investigate the influence
of technology transfers on firm innovativeness in
Spanish firms. Lim (2004) analyzed the effects of basic
and applied research on innovation in semiconductor
and pharmaceutical firms worldwide. Cepeda-Carrion,
Cegarra-Navarro, and Jimenez-Jimenez (2012) also
examined the association between absorptive capacity
and company innovativeness in large Spanish companies.
However, most of these studies focused on a single aspect
of technology management practices and on developed
economies, leaving a gap regarding other dimensions of
innovation and developing economies. This study
attempts to fill that gap in the literature by examining
the effects of each different type of technology manage-
ment dimension on firms’innovation using structural
equation modelling in medium- and large-scale manufac-
turing firms in Ethiopia. Thus, this study helps to gain
further insights into the effects of technology manage-
ment practices on firm innovation.
In the current study, technology management (intro-
duced as the independent variable) is represented by
four constructs, namely: technology process, technology
acquisition, technology absorption, and technology trans-
fer. Innovation is introduced as the dependent variable and
operationalized by three construct variables, namely:
process, product, and method innovation. This study con-
tributes to the theoretical notation that technology is a
source of competitive advantage, which is achieved
through encouraging technological innovation. Technol-
ogy management is an essential strategy that helps firms
identify, select, acquire, exploit, and protect technology
(Gregory 1995; Durrani et al. 1998). However, it would
be challenging for firms characterized by low-skilled
human resources, insufficient know-how about technol-
ogy, and inadequate investment in R&D because the tech-
nology base cannot be built in a one-off process; rather, it
takes time and huge capital investment. Like other scien-
tific research, this study has certain limitations that are
addressed in forthcoming research projects in the area.
First, the sample size used is not large enough, as struc-
tural equation modelling requires a large sample size to
test the hypothesis. Second, most of the items applied to
measure technology management constructs and inno-
vation constructs have been designed by researchers, so
further investigation needs to be performed to ensure
the validity and reliability of the items in different
countries. Finally, we used one-time data to test the con-
ceptual model. Future researchers should use more com-
prehensive data consisting of time series and cross-
sectional data to examine the impact of technology man-
agement on innovation in depth.
The remainder of the paper is organized as follows.
The next section provides an overview of the relevant
theoretical framework and hypothesis development on
the subject. This is followed by a section that describes
the research methodology. The section thereafter presents
the results of the study. Findings are discussed in the
penultimate section. Finally, the last section concludes
the results and discussions.
Conceptual framework and hypotheses
Researchers have investigated and identified technology
management mechanisms, namely, technology process
(Henard and McFadyen 2005), technology acquisition
(Tsai and Wang 2007), technology absorption (Fosfuri
and Tribo 2008; Lichtenthaler 2009; Pradana, Pérez-
Luño, and Fuentes-Blasco 2020), and technology transfer
(Rajan, Dhir, and Sushil 2021) that are crucial to the entire
value creation (i.e., antecedents) and enhance innovations
in the organization. Prior literature on the relationship
between technology management and firm innovation is
large, but most studies focus on a single aspect of technol-
ogy management practices (see Guan et al. 2006; Cepeda-
Carrion, Cegarra-Navarro, and Jimenez-Jimenez 2012;
Kang, Jo, and Kang 2015; Lin, Qin, and Xie 2020,
among others). This study intends to fill this gap in the lit-
erature by examining the effects of each different type of
technology management dimension on firms’innovation.
Thus, this study helps to gain further insights into the
effects of technology management practices on firm
innovation.
Technology process
This study defines the technology process as an ordered
sequence of steps that a company follows and implements
in investing in basic and applied research initiatives to
encourage creativity, innovation, and firm performance
and maintain a continued competitive advantage. Prior
studies (e.g., Henard and McFadyen, 2005) have indicated
that investments in applied and basic research were
crucial for innovative research initiatives. Firms that
rely on a continuous flow of product innovations to
provide a stable income source should generally invest
in applied research initiatives. Further investments in
directed basic research initiatives will increase future
applied projects and constitute a sustainable competitive
advantage (Henard and McFadyen 2005). The theoretical
underpinning of the relationship between the technology
process and innovation is based on the perspective of
knowledge creation theory (e.g., Cohen and Levinthal
1990; Simon 1991; Nonaka 1994), which states that
knowledge is formed or created via the sharing and com-
bining of information and ideas (which are fundamental
premises of applied and basic research initiatives)
through exchange interactions (Simon 1991; Nonaka
1994), which in turn, facilitates the creation of new
knowledge, and ultimately, new products, and enhances
innovative activities. Prior studies (Nelson 1959;
Aghion and Howitt 1996) pointed out that fundamental
advances in technological knowledge occur through
2Kalko, Erena and Debele
basic research, which in turn, opens up doors for sub-
sequent research. This basic research helps applied
research build upon it, allowing these opportunities to be
realized. In a similar spirit, Akcigit, Hanley, and Serrano-
Vel a rde ( 2020) indicated that although basic research
appears to command a significant premium over applied
research, both basic and applied research contribute to
firm productivity and generate spillovers that influence
subsequent innovation within a specific industry. Further-
more, Belderbos, Kelchtermans, and Leten (2021)find a
positive relationship between internal basic research and
afirm’s innovative performance. The authors further
suggest that by investing in basic research, firms can use
both internal and external scientific knowledge as a map
for technology developments. On the basis of this theoreti-
cal and empirical evidence, we hypothesize that:
H1: The technology process is positively linked to
innovation.
Technology acquisition
External technology acquisition refers to a company’s
attempts (activities) to gain access to technical knowledge
located outside of its borders (Cassiman and Veugelers
2006; Tsai and Wang 2008). Similarly, Vanhaverbeke,
Duysters, and Noorderhaven (2002) and Hoegl and
Wagner (2005)defined external technology acquisition
as the process of absorbing technologies from outside
sources, such as through in-licensing or strategic alli-
ances. The theoretical basis for supporting the association
between technology acquisition and firm innovation is
based on the perspective of the transaction cost theory
(Williamson 1975,1991) and the knowledge-based view
(Grant 1996). Transaction cost theory posits that the
decision to acquire technology from outside their bound-
aries leads to a higher return on investment, lower costs,
increased flexibility, access to specialized skill sets, and
creativity (i.e., the relative costs of developing internally
in relation to buying a technology). According to the
knowledge-based view, a firm gains a competitive advan-
tage through exploring, exploiting, and integrating differ-
ent specialized skills and knowledge through external
technology acquisition and internal research and develop-
ment activities.
Prior studies on the relationship between technology
acquisition and innovation indicate indecisive findings.
One stream of literature finds technology acquisition is
positively associated with innovation, whereas other
studies indicate no such linkage. Some studies (see Van-
haverbeke, Duysters, and Noorderhaven 2002; Calantone
and Stanko 2007; Montoya, Zárate, and Martín 2007;
Jeon et al. 2015; Charmjuree, Badir, and Safdar 2021)
confirmed a positive relationship between technology
acquisition and innovation. Calantone and Stanko
(2007) indicate that external technology acquisition has
been regarded as a vital competence for long-term
product and process innovation success. They further
indicate that firms have increasingly sourced technology
beyond their borders in order to decrease development
time and costs, share risks, and access expertise not acces-
sible in-house because of increasing technological com-
plexity, shorter product life cycles, and rising
technology development expenses. Jeon et al. (2015)
also found a positive relationship between external tech-
nology acquisition and innovation performance in US
pharmaceutical industry. External technology acquisition,
as indicated by inward technology licensing, has a posi-
tive impact on the firm performance of high-technology
firms in Taiwan, especially when the level of the firms’
internal research and development (R&D) efforts
increases, and is, thus, in turn, viewed as an important
strategy adopted by firms to achieve/foster innovation
(Tsai and Wang 2007). Firms can better cope with the
increasing speed, cost, and complexity of technological
developments by obtaining and acquiring technologies
from outside sources (Vanhaverbeke, Duysters, and Noor-
derhaven 2002). This practice of acquisition can increase
a company’s technological capacity, resulting in long-
term performance advantages over competitors
(Montoya, Zárate, and Martín 2007). Furthermore, using
data from a sample of Spanish manufacturing firms,
Nieto and Santamaría (2007) revealed that technological
collaborative networks with different partners (except
competitors) positively influence the degree of novelty
in product innovation. In addition, Charmjuree, Badir,
and Safdar (2021) also indicate that both external technol-
ogy acquisition and external technology exploitation have
a positive effect on a firm’s process innovation perform-
ance in small- and medium-sized software development
firms in Thailand. Conversely, Tsai and Wang (2009)
found external technology acquisition, as indicated by
inward technology licensing, does not improve innovation
performance in low- and medium-technology firms in
Taiwan. Kessler et al. (2000) indicated that a firm that
spends a lot of time and money on knowledge integration
for better technological innovation may lose its competi-
tive advantage if it is more active in internal R&D and, at
the same time, outsources more R&D. Thus, we posit that:
H2: Technology acquisition is positively associated with
innovation.
Technology absorption
Absorptive capacity is the ability of firms to perceive the
importance of new information, assimilate it, and apply it
to business goals (Cohen and Levinthal 1990, 128). In a
similar fashion, Lewin, Massini, and Peeters (2011) and
Zahra and George (2002)defined absorptive capacity as
a company’s ability to use external knowledge through
the acquisition, assimilation, transformation, and exploi-
tation phases of organizational learning processes. It is a
key driver of a firm’s competitive advantage (Lichtentha-
ler 2009). The theoretical foundation for the relationship
between technology absorption and innovation is based
on organizational learning theory, which states that
firms should be able to perceive and recognize the value
of new knowledge, assimilate that knowledge, and
apply it to value creation in order to innovate (Cohen
and Levinthal 1990; Todorova and Durisin 2007).
Existing research (see Becker and Peters 2000; Kosto-
poulos et al. 2011; Pradana, Pérez-Luño, and Fuentes-
Blasco 2020; Pinheiro et al. 2021) has found a positive
relationship between technology absorption and inno-
vation in manufacturing firms. For instance, Pinheiro
African Journal of Science, Technology, Innovation and Development 3
et al. (2021) indicate a strong, positive, and direct effect of
absorptive capacity on innovation (both exploitative and
exploratory) competencies in Portuguese manufacturing
firms. Becker and Peters (2000) also found a positive
relationship between absorptive capacity and innovation
output in German manufacturing companies. Kostopoulos
et al. (2011) indicated that absorptive capacity serves as a
means to attain superior innovation and financial perform-
ance over time and translate external knowledge inflows
into tangible gains in manufacturing and service firms in
Greece. Using a sample of 138 Spanish companies from
the wine industry, Pradana, Pérez-Luño, and Fuentes-
Blasco (2020) found that absorptive capacity allows
firms to fully capture the benefits of innovation.
In a similar vein, Cohen and Levinthal (1989) indi-
cated that absorptive capacity assists firms in identifying
and exploiting useful external knowledge from univer-
sities, government laboratories, and competitor spillovers.
This exploitation capability assists the company in con-
verting knowledge into new products (Gao et al. 2008).
Using data from 246 Spanish technological firms,
Garcia-Morales, Ruiz-Moreno, and Llorens-Montes
(2007) also pointed out that absorptive capacity facilitates
changes in R&D investment, organizational culture, inter-
action mechanisms, and other factors, all of which have a
great influence on organizational innovation. Further-
more, Kneller and Stevens (2006) state that the firm’s
capacity to absorb new technology impacts innovation.
On the basis of this theoretical and empirical evidence,
we hypothesize that:
H3: Technological absorption is positively linked with
innovation.
Technology transfer
Technology transfer is a deliberate, goal-oriented inter-
action between two or more social entities during which
the pool of technological knowledge remains stable or
grows when one or more constituents of technology are
transferred (Autio and Laamanen 1995). Similarly,
Appiah-Adu, Okpattah, and Djokoto (2016)defined tech-
nology transfer as the process of transferring novel
methods, technologies, inventions, and specialized techni-
cal abilities and skills from one organization to another to
foster creativity, innovation, and firm performance. To
assure the production of new products and services,
organizations must identify and manage technology trans-
fer operations and activities (Bozeman 2000). Any tech-
nology transfer has the primary goal of introducing new
technologies and processes, improving existing technol-
ogies, and developing new knowledge (Hsiao et al.
2017), all of which are thought to encourage organizations
to innovate (Masa’deh, Obeidat, and Tarhini 2016;
Novickis, Mitasiunas, and Ponomarenko 2017). The rel-
evant theories underlying the relationship between tech-
nology transfer and innovation are the knowledge-based
view and organizational learning perspectives, which
state that technology transfer requires transmission of
knowledge as well as knowledge absorption and use
(Davenport and Prusak 1998). Prior studies (Lichtenthaler
2005; Lichtenthaler and Ernst 2007; Cinar et al. 2021)
found a positive relationship between technology transfer
and innovations. Lichtenthaler (2005) indicated that tech-
nology transfer has a positive influence on innovation pro-
cesses. According to Lichtenthaler and Ernst (2007),
organizations can strengthen their research and develop-
ment efforts by leveraging new technology and knowl-
edge by transferring technology from other
organizations. Similarly, using data obtained from 252
Turkish export firms, Cinar et al. (2021) found a positive
effect of technology transfer on innovation and firm per-
formance. Shenkoya and Kim (2020) pointed out that
technology transfer coupled with appropriate technology
transfer policies is essential to economic development
and the generation of income while fostering innovation
in South Korea. Cardamone, Pupo, and Ricotta (2015)
also indicated that the activities of technology transfer
by universities play a critical role in the probability of
innovation by manufacturing firms in Italy located in
the same province as the university. In a similar vein,
Lin, Qin, and Xie (2020)find that foreign technology
transfer generates significant localized spillovers in
terms of growth in patenting activities and higher pro-
ductivity and revenue growth among firms close to the
direct receivers of foreign technologies in the high-
speed rail sector of China. Thus, we posit that:
H4: Technology transfer is positively associated with
innovation.
The proposed conceptual framework of the study is
depicted in Figure 1.
Research methodology
Study design
To test the hypothesis, we used cross-sectional data,
which assumes observation over a single period across
various firms. It has several advantages: For example,
the effect of time among sample firms could be mini-
mized. All firms have a chance to be considered in the
study, regardless of their age, business experience, or
size. This could also minimize biasedness among firms
and increase the representativeness of the sample size
(Cresswell 2014; Malhotra et al. 2017). The study was
carried out in 2019.
Population and sample size
The target population for this study comprises medium-
and large-scale manufacturing firms in Ethiopia. The
Ministry of Trade and Industry report provided us with
information on a list of medium- and large-scale manufac-
turing firms. The list consists of 3500 firms registered and
operating in the country in the year 2019. To classify
enterprises into medium- and large-scale manufacturing
firms, we used benchmarks from the Federal Democratic
Republic of Ethiopia’s Ministry of Trade and Industry
and the Ethiopian CSA (2018). Firms with more than 10
but fewer than 51 employees are classified as medium-
scale, while those with 51 or more employees are classi-
fied as large-scale. This study focuses on medium- and
large-scale manufacturing firms because they are more
likely to engage in creative or innovative activities
(Gebreeyesus 2009). In addition, medium- and large-
scale firms are mature, knowledge-based firms and they
4Kalko, Erena and Debele
have increased opportunities to develop innovative sol-
utions and are additionally conscious of gaining a com-
petitive advantage (Sözbilir 2018). Around 45% of the
sampled firms are medium-scale, while the remaining
55% are large-scale manufacturing firms. With regard to
sectoral distribution, Ethiopia’s manufacturing firms are
engaged in various sub-sectors, namely the production
of food and beverages, tobacco, textile manufacturing,
wood, pulp and paper, chemicals, rubber and plastic,
non-metallic minerals, metal, furniture, and others. The
food and beverage sector is the dominant sector in terms
of output and employment, followed by the non-metallic
mineral manufacturing sector (CSA 2018; Erena, Kalko,
and Debele 2021). Even though the number of target
firms is larger, they are not organized into industrial
zones or clusters and are geographically scattered across
parts of the country. So, in the current survey study, 200
firms were randomly approached via questionnaire, and
a total of 153 usable responses were received, resulting
in a response rate of 76.5%. We have followed a sort of
procedure in collecting data from the target firms:
Firstly, a pilot study was conducted on 10 manufacturing
firms in order to examine the reliability and validity of the
instruments in terms of readability, language clarity,
coherence, and appropriateness. Second, the original
version of the questionnaire was revised and reworded
while retaining its original meaning based on the feedback
from the pilot study. Third, we recruited and trained pro-
fessional data enumerators. Lastly, the questionnaire was
distributed or supplied to the company’s production or
technical department.
Item development
The survey questionnaire was designed after a thorough
review of the literature, with a focus on producing a
pool of items that reflect the key theoretical constructs.
In this study, technology management is operationalized
by four constructs, namely, technology process, technol-
ogy acquisition, technology absorption, and technology
transfer. The technology process is scrutinized with
twelve-question items. Technology acquisition is interro-
gated as an eight-question item. Technology absorption is
measured with four question items. Technology transfer
is measured with ten question items. We developed/pre-
pared measures of technology management constructs
based on empirical studies on technology management
roadmaps (Gregory 1995; Durrani et al. 1998;Phaal,
Farrukh, and Probert 2001; White and Bruton 2011;
Small and Wainwright 2014; Fartash et al. 2018). Survey
respondents were asked to evaluate their firm’s technology
management practice using a five-point scale, with 1 repre-
senting ‘nothing was done’and 5 representing ‘very high’.
The survey questionnaire on innovation addressed three
innovation factors: product, process, and method inno-
vation. Product innovation was operationalized with five
question items. Process innovation was operationalized
with four items. Five items were used to measure method
innovation. Survey respondents were asked to rate their
agreement with the statements using five-point Likert
scales ranging from 1 = strongly disagree up to 5 = strongly
agree.
Reliability, validity, and structural equation model
goodness of fit
We tested the reliability and validity of survey items. Two
reliability tests were performed, namely, composite/
internal consistency and individual item reliability. Com-
posite reliability is used to test whether the items measur-
ing the same construct are similar in their scores. The
individual indicators’reliability was tested using factor
loading, and items with more than 0.65 loadings, signifi-
cant at 1%, were taken. Similarly, two types of validity
tests were performed: convergent validity and discrimi-
nant validity. The average variance extracted is used to
assess the convergent validity. Discriminant validity was
applied to test how the latent variables are unique and
different from each other. After the reliability and validity
tests were satisfied, we performed goodness of fit tests for
measurement models, structural models, and second-
order models. Unlike conventional multivariate analysis,
Figure 1: Conceptual model.
African Journal of Science, Technology, Innovation and Development 5
the structural equation model provides several good-
nesses-of-fit tests. The statistical indices and the rec-
ommended threshold rules of thumb are presented in
Table 1.
Results
Measurement model
This study aims to examine the effect of technology man-
agement on technological innovation. The technology
management factors involve technology process, technol-
ogy acquisition, technology absorption, and technology
transfer. Similarly, technological innovation was operatio-
nalized using product innovation, process innovation, and
method innovation. As the usual procedure in structural
equation modelling analysis, first, the measurement
models were assessed for reliability, validity, and good-
ness of fit using confirmatory factor analysis in LISREL
8.80, a SIMPLIS program with a maximum likelihood
estimation method. Table 2 and Figures 2 and 3indicate
the detailed results containing mean, standard deviation,
standardized factor loadings, composite reliability (CR),
average variance extracted (AVE), and fit indexes. In
this study, an item with more than 0.65 standardized load-
ings (i.e., a squared correlation between a single manifest
variable and its respective construct) and significant at
0.01 was taken. The results in Table 2 show that all
items have sufficiently loaded on the constructs they
measure, suggesting item reliability or internal consist-
ency reliability. The composite reliability (CR), which
assesses the internal consistency of the scale, ranges
from 0.853 for technology absorption to 0.937 for tech-
nology process. It implies all constructs assumed in the
current models have obtained reliability which is much
higher than the general rule of thumb of 0.70.
The average variance extracted (AVE) for all con-
structs exceeded the cut-off criterion of 0.50, demonstrat-
ing sufficient convergent validity. In addition to
convergent validity, the study evaluated discriminant val-
idity, which refers to the degree to which a given factor or
construct differs from other factors or constructs, or the
extent to which given factor indicators are distinct from
similar indicators designed to measure other constructs.
The most common means of measuring discriminant val-
idity is by comparing the square root of the average var-
iance extracted from a construct to the correlation
coefficient between two constructs (Fornell and Larcker
1981). The square root of AVE should be greater than
the shared variance between constructs to provide
evidence of discriminant validity. Table 3 presents the
square root of the AVE diagonal printed in bold and con-
structs correlation in off-diagonal elements, which sup-
ports discriminant validity.
As clearly indicated in Figure 2, the technology man-
agement measurement model has yielded satisfactory
goodness of fit statistics. These include Normed ᵡ
2
=
1.458, RMSEA = 0.055, NFI = 0.95, NNFI = 0.98, CFI =
0.98, IFI = 0.98, and GFI = 0.90. Figure 3 depicts the
innovation measurement model, and the fit indexes were
Normed ᵡ
2
= 1.578, RMSEA = 0.062, NFI = 0.97, NNFI
= 0.99, CFI = 0.99, IFI = 0.99 and GFI = 0.90. Those
values indicate a good fit between the model and the
observed data. Furthermore, the assumptions of unidi-
mensionality and normality were verified before running
structural equation modelling to test the conceptual
hypotheses. A confirmatory factor analysis was per-
formed to check for cross-loading among observed vari-
ables or error terms. The result for the test indicated that
each item was more loaded on its respective factor,
suggesting that unidimensionality is satisfied. We tested
both univariate normality and bivariate normality for
ordinal data and the results are reported in appendices 2
and 3. No excess skewness or kurtosis was found in the
data. To compute bivariate normality, root mean square
error of appropriation (RMSEA) was used. The results
for each pair of variables were at an acceptable level,
which is less than 0.10 as recommended by Jöreskog
(2005).
In Figure 2, we also assessed the reliability and val-
idity of technology management constructs as a second-
order model. Technology management (TM) is specified
as a second-order construct, whereas technology process
(TECHPROC), technology acquisition (TECHAC), tech-
nology absorption (TECHABS), and technology transfer
(TECHTR) are first-order factors. The result shows all
first-order factors have a significant positive correlation
with the second-order construct, supporting convergent
validity. The second-order construct has obtained strong
construct validity as shown by the composite reliability
score of 0.904 and the average variance extracted (AVE)
score of 0.70.
The second-order model for innovation is reported in
Figure 3, and all first-order factors are significantly and
positively correlated to the second-order construct, inno-
vation (INNOV). The values of CR and AVE statistics
are 0.958 and 0.886, respectively, implying that construct
validity is adequately satisfied in the model. The results in
Table 1: Model fit indices.
Indices statistics Recommended cut-off rule Reference
ᵡ
2
–
df –
p-value >0.05
ᵡ
2
/df <5 Wheaton et al. (1977)
Root Mean Square Error of Appropriation (RMSEA) ≤0.1 Steiger and Lind (1980)
Normed Fit Index (NFI) ≥0.90 Bentler and Bonett (1980)
Comparative Fit Index CFI ≥0.90 Bentler (1990)
Incremental Fit Index IFI ≥0.90 Bentler (1990)
Goodness of Fit Ibdex (GFI) ≥0.90 Jöreskog and Sörbom (1989)
6Kalko, Erena and Debele
Figures 2 and 3strongly assure that the measurement
model scales are sufficiently valid and reliable, suggesting
further analysis in structural equation modelling, i.e.,
testing the conceptual hypothesis.
Structural model
The structural model was performed in LISREL 8.8 to test
the linkage between technology management, which is an
exogenous variable, and innovation, an endogenous vari-
able. In the literature of structural equation modelling,
there is a consensus that in addition to sample size, the
number of factors in a model influences the goodness of
fit (Hair et al. 2019; Cheung and Rensvold 2002). Follow-
ing the literature, we run two models by classifying the
technology management constructs. Model 1 specified
technology process and technology acquisition as
exogenous variables. While technology absorption and
technology transfer were specified in model 2.
The results of model 1 are summarized in Figure 4 and
Table 4. Model 1 has obtained excellent goodness of fit
statistics, and all fit indexes are within the acceptable
range. The Normed ᵡ
2
= 1.915, RMSEA = 0.078, NFI =
0.94, NNFI = 0.97, CFI = 0.97, IFI = 0.97, RFI = 0.93
and GFI = 0.90. Those results indicate the model reason-
ably fits the observed data. As shown in Table 4, the tech-
nology process has a significant positive effect on both
process innovation (PCI) (UC = 0.23, t-value 2.50) and
method innovation (MI) (UC = 0.18, t-value 1.99). No
significant coefficient is found between the technology
process and product innovation. The coefficients
between technology acquisition and all three constructs
of innovation are positive and strongly statistically
Table 2: Summary statistics of measurement models.
Constructs Items Mean SD Standardized loading (λ)CR AVE
Technology Process (TECHPROC) TP1 2.75 1.01 0.73 0.937 0.554
TP2 2.88 0.97 0.75
TP3 2.95 0.95 0.75
TP4 3.06 0.98 0.75
TP5 2.98 0.99 0.72
TP6 3.03 0.97 0.76
TP7 2.95 0.97 0.72
TP8 3.05 1.01 0.74
TP9 2.97 0.98 0.74
TP10 3.06 0.94 0.75
TP11 3.05 0.93 0.79
TP12 3.0 0.98 0.74
Technology Acquisition (TECHAC) TAC1 3.01 1.06 0.71 0.900 0.532
TAC2 3.03 0.96 0.73
TAC3 3.07 0.91 0.72
TAC4 3.10 0.91 0.65
TAC5 3.03 0.98 0.71
TAC6 3.04 0.93 0.74
TAC7 3.11 0.93 0.80
TAC8 3.17 0.92 0.76
Technology Absorption (TECHABS) TAB1 3.09 0.94 0.82 0.853 0.595
TAB2 3.14 0.93 0.63
TAB3 3.23 0.92 0.74
TAB4 3.29 0.91 0.68
Technology Transfer (TECHTR) TT1 2.99 1.02 0.70 0.924 0.553
TT2 2.88 1.05 0.72
TT3 2.86 1.00 0.73
TT4 2.90 0.99 0.70
TT5 2.98 0.95 0.75
TT6 3.00 0.92 0.83
TT7 3.11 1.00 0.82
TT8 3.07 0.99 0.75
TT9 2.82 0.97 0.73
TT10 2.96 1.02 0.69
Process Innovation (PCI) PCI1 3.01 0.95 0.83 0.886 0.610
PCI2 3.04 0.93 0.77
PCI3 3.10 1.03 0.73
PCI4 3.09 1.00 0.84
PCI5 3.03 0.96 0.74
Product Innovation (PDI) PDI1 2.92 0.99 0.71 0.864 0.560
PDI2 2.98 0.98 0.82
PDI3 2.82 1.00 0.73
PDI4 2.90 1.00 0.76
PDI5 2.97 1.03 0.72
Method Innovation (MI) MI1 2.98 0.98 0.76 0.889 0.616
MI2 2.93 0.96 0.75
MI3 2.95 1.03 0.86
MI4 3.03 1.02 0.77
MI5 2.97 0.99 0.79
African Journal of Science, Technology, Innovation and Development 7
significant: process innovation (PCI) (UC = 0.62, t-value
6.07), product innovation (PDI) (UC = 0.83, t-value
7.35), and method innovation (MI) (UC = 0.62, t-value
5.83). Moreover, on average, model 1 has defined about
0.67% (R
2
) of the variance in innovation, suggesting suf-
ficient model validity.
The second model is graphically demonstrated in Figure
5, and the detailed result is reported in Table 5. The scores of
all fit index statistics met the usual standard norms, Normed
ᵡ
2
= 1.787, RMSEA = 0.072, NFI = 0.95, NNFI = 0.97, CFI
= 0.98, IFI = 0.98, RFI = 0.95 and GFI = 0.91. Thus, the
overall goodness-of-fit indices indicate that the model is
Figure 2: Technology management measurement model (i.e., technology management second-order model).
8Kalko, Erena and Debele
acceptable. In Table 4, technology absorption has a signifi-
cant positive effect on product innovation (PDI) (UC = 0.17,
t-value 2.19). However, the coefficients for process inno-
vation and method innovation are insignificant.
Technology transfer has a potential significant posi-
tive impact on process innovation (UC = 0.87, t-value
8.75), product innovation (UC = 0.81, t-value 8.03) and
method innovation (UC = 0.77, t-value 7.29). This result
implies that technology transfer is the key driver of firm
innovation. Mode 2, on average, defined a 0.81% variance
in innovation, showing strong model validity.
Discussion
The primary objective of this study is to investigate
empirically the effects of technology management
practices, including technology processes, technology
acquisition, technology absorption, and technology
transfer, on firm innovative development, such as
process, product, and method innovation, in medium-
and large-scale manufacturing firms in Ethiopia. Tech-
nology management is termed as a multidisciplinary
study involving technology, science, and management.
It is the process of planning, identifying, and implement-
ing technological tools, equipment, skills, and knowl-
edge into a manufacturing system. In this study, four
dimensions were used to represent technology manage-
ment: technology process, technology acquisition, tech-
nology absorption, and technology transfer. The results
showed technology process has a significant positive
effect on product innovation and method innovation,
Figure 3: Innovation measurement model (i.e., innovation second-order model).
Note: RMSEA-root mean square error of approximation; NFI-normed fit index; NNFI-non-normed fit index; CFI-comparative fit index;
IFI-incremental fit index; RFI-relative fit index; GFI-goodness of fit index.
Table 3: Discriminant validity.
Variable 1 2 3 4 Variable PDI PCI MI
TECHPROC 0.744 PDI 0.781
TECHAC 0.48 0.729 PCI 0.58 0.748
TECHABS 0.46 0.33 0.771 MI 0.41 0.52 0.784
TECHTR 0.53 0.35 0.40 0.743
Note: The square root of AVE values is shown on the diagonal and printed in bold; off-diagonal elements are the construct variables correlations.
TECHPROC-technology process, TECHAC-technology acquisition, TECHABS- technology absorption, TECHTR-technology transfer, PDI- product
innovation, PCI-process innovation, MI-method innovation, TM-technology management. Second-order (TM) CR = 0.904, AVE = 0.70.
African Journal of Science, Technology, Innovation and Development 9
but no significant effect on process innovation. It implies
that a firm that has invested in technology processes like
applied research, basic research, technology production,
implementation, and enhancement is more likely to
improve its innovation performance and subsequently
yield a competitive advantage. Moreover, firms need to
build their internal competencies, for example, research
and development capacity that helps to generate new
knowledge or ideas and convert them into a product,
process, or service. This result is in line with studies
by Wu et al. (2010) and Phaal, Farrukh, and Probert
(2001), who have suggested a firm with higher technol-
ogy management capacity can have better innovation
performance.
Technology acquisition appeared to be the major ante-
cedent of three innovation constructs: product, process,
and method innovation. This reflects the degree to
which a firm engages in technology acquisition activities
like joint-ventures, collaborating with other firms, con-
tracting R&D, licensing, or buying technology (hardware
or software), and the acquisition of new equipment sig-
nificantly contributes to innovation. A strategy of technol-
ogy acquisition from external parties can substitute or
complement in-house development of technology that
requires highly skilled human resources (researchers), a
laboratory, a budget, equipment, and other tools. It can
be inferred from this result that, given the capacity of
the firm, appropriate external technology acquisition has
Figure 4: Effect of technology management (i.e., technology process and technology acquisition) on innovation.
Table 4: Structural model 1 results.
Variable Standardized coefficient Std. Error t-value R-square
TECHPROC -> PCI 0.23 0.091 2.50* 0.64
TECHAC -> PCI 0.62 0.10 6.07**
TECHPROC -> PDI 0.06 0.084 0.74 0.76
TECHAC ->PDI 0.83 0.062 7.35**
TECHPROC->MI 0.18 0.089 1.99* 0.63
TECHAC ->MI 0.62 0.11 5.83**
Where TECHPROC–technology process; TECHAC-technology acquisition; PCI-process innovation; PDI-product innovation; MI-method innovation;
RMSEA-root mean square error of approximation; NFI-normed fit index; NNFI-non-normed fit index; CFI-comparative fit index; IFI-incremental fit
index; RFI-relative fit index; GFI-goodness of fit index. Note: **,* denote a significant level at 1% and 5%, respectively.
RMSEA = 0.078 NFI = 0.94 NNFI = 0.97 CFI 0.97 IFI = 0.97 RFI = 0.93 GFI = 0.85.
10 Kalko, Erena and Debele
a vital role in shaping new technological innovation. This
result is consistent with the findings of Goedhuys and
Veugelers (2012) that indicate that process and product
innovation success occurs mostly through embodied tech-
nology acquisition (i.e., through external technology
acquisition or technology buy strategy, particularly the
purchase of machinery and equipment, either alone or in
combination with internal development or technology
make strategy) in Brazilian manufacturing firms.
Technology absorption has a significant positive influ-
ence on product innovation, but the coefficient for process
and method innovations is insignificant. Thus, a firm that
effectively exploits and learns technology from external
parties can improve its product innovation. Our results
are consistent with the findings of Engelman et al.
(2018) that confirmed the positive influence of absorptive
capacity on product innovation in Brazil. Our finding is
also consistent with the results of several previous
studies (Durrani et al. 1998; Lichtenthaler 2007; Lich-
tenthaler and Ernst 2009; Tsai, Hsieh, and Hultink 2011;
Kang, Jo, and Kang 2015; Fartash et al. 2018) that have
confirmed a positive relationship between technology
management (as measured by technology acquisition
and absorption) and innovation (product, process, and
method).
Moreover, technology transfer has a significant posi-
tive influence on the three innovation constructs –
process, product, and method innovations –suggesting
it is an important driver of innovation. This implies that
the practice of firms with respect to the internal flow of
Figure 5: Effect of technology management (i.e., technology absorption and technology transfer) on innovation.
Table 5: Structural model 2 results.
Variable Standardized coefficient Std. Error t-value R-square
TECHABS -> PCI 0.08 0.081 0.97 0.79
TECHTR -> PCI 0.87 0.099 8.75**
TECHABS -> PDI 0.17 0.077 2.19* 0.88
TECHTR ->PDI 0.81 0.10 8.03**
TECHABS ->MI 0.11 0.083 1.27 0.78
TECHTR ->MI 0.77 0.11 7.29**
Where, TECHABS-technology absorption, TECHTR-technology transfer, PCI-process innovation; PDI-product innovation; MI-method innovation;
RMSEA-Root Mean Square Error of Approximation; NFI-Normed Fit Index; NNFI-Non-Normed Fit Index; CFI-Comparative Fit Index; IFI-
Incremental Fit Index; RFI-Relative Fit Index; GFI- Goodness of Fit Index. Note: ** and * denote a significant level at 1% and 5%, respectively.
RMSEA = 0.072 NFI = 0.95 NNFI = 0.97 CFI = 0.98 IFI =0.98 RFI = 0.95 GFI = 0.87.
African Journal of Science, Technology, Innovation and Development 11
know-how, technical knowledge, equipment, data, and
information (intellectual property) from government
units, universities, technology providers, and other exter-
nal parties is essential to scale-up firms’innovative
capacity. It also suggests that a firm with better techno-
logical capacity (skilled human resources, expertise,
experience) can more easily achieve the maximum
benefits from transferred technology than those that
have less capacity. This result supports the general view
of the extant literature (Li-Hua and Khalil 2006; Chan
and Daim 2011; White and Bruton 2011; García-Vega
and Vicente-Chirivella 2020) that indicates technology
transfer is a key antecedent for innovation. Furthermore,
this finding is also consistent with Liang and Zhang’s
(2012)finding that technology transfer is an effective
source of technological product and process innovation
in Chinese high technology industries.
The current study contributes to the theoretical notion
that technology is a source of competitive advantage,
which is achieved through encouraging technological
innovation. Technology management is a critical strategy
that assists businesses in identifying, selecting, acquiring,
exploiting, and protecting technology (Gregory 1995;
Durrani et al. 1998). However, achieving effective tech-
nological management would be difficult for firms with
low-skilled labour, insufficient knowledge of technology,
and inadequate investment in R&D because the technol-
ogy base cannot be built in a single process; rather, it
requires time and large capital investment. In addition,
policymakers should support firms in their efforts to
improve technology, which will help them increase pro-
ductivity and become more innovative.
Conclusion
The current highly impulsive and rapid change in the
business environment changes the way firms have to
operate and deliver products or services. Technology is
a resource that can provide a competitive advantage if uti-
lized well for the intended purpose. Technology pro-
cesses, acquisition, absorption, and transfer are valuable
indicators of technology management in the manufactur-
ing sector. They show that firms engaging in developing
technology in-house via R&D, acquiring, learning and
exploiting, and transferring technology simultaneously
would have a higher technology management capacity.
It is further noted that innovation can be operationalized
adequately through process, product, and method inno-
vations. Thus, a firm’s innovation strategy should con-
sider these factors as important sources of innovation.
Furthermore, technology management is an appropriate
resource to be used in conjunction with appropriate tech-
nology management policies and strategies to enhance
firm performance, particularly innovation and creativity,
which in turn, are sources of competitive advantage.
It is noted that technology transfer is the most impor-
tant driver of product, process, and method innovations.
This indicates that the more a firm shares, transmits, and
converts technology, data, and information with outside
parties (universities, government units, firms, or others),
the better its innovation performance. The result confirms
the general view that technology transfer is a means for
innovation and productivity where human creativity has
not been well developed and the existing system is not
capable of creating technology (Li-Hua and Khalil
2006; Chan and Daim 2011). The study also found tech-
nology processes, acquisitions, and absorption are valu-
able factors in explaining innovation. Overall, the
results add to the body of knowledge that manufacturing
innovation can best be driven through strengthened tech-
nological capacity. Finally, we conclude that building
technological or innovative capacity requires a huge
amount of resources (human and financial) and takes a
long time to attain the optimum benefits. However, if a
firm needs to operate a business (deliver products or ser-
vices), there is no alternative but to elevate its technologi-
cal innovation capability through investing in research
and development, learning, and exploiting existing or
new knowledge.
Availability of data and materials
Data are available from the authors upon reasonable request.
Acknowledgments
We acknowledge with appreciation the helpful and constructive
comments of Prof. Angathevar Baskaran (Editor-in-Chief) and
two anonymous reviewers.
Disclosure statement
No potential conflict of interest was reported by the authors.
Funding
The authors gratefully acknowledge the financial support for this
study from Tomas Bata University in Zlin [grant number IGA/
FaME/2020/003] and Hawassa University.
ORCID iDs
Mesfin Mala Kalko http://orcid.org/0000-0001-5153-
4764
Obsa Teferi Erena http://orcid.org/0000-0003-4304-
5359
Sara Adugna Debele http://orcid.org/0000-0002-9832-
7049
References
Aghion, P., and P. Howitt. 1996.“Research and Development in
the Growth Process.”Journal of Economic Growth 1 (1):
49–73. doi:10.1007/bf00163342.
Akcigit, U., D. Hanley, and N. Serrano-Velarde. 2020.“Back to
Basics: Basic Research Spillovers, Innovation Policy and
Growth.”The Review of Economic Studies 88 (1): 1–43.
doi:10.1093/restud/rdaa061.
Appiah-Adu, K., B. K. Okpattah, and J. G. Djokoto. 2016.
“Technology Transfer, Outsourcing, Capability, and
Performance: A Comparison of Foreign and Local Firms
in Ghana.”Technology in Society 47 (1): 31–39. doi:10.
1016/j.techsoc.2016.07.002.
Autio, E., and T. Laamanen. 1995.“Measurement and
Evaluation of Technology Transfer: Review of Technology
Transfer Mechanisms and Indicators.”International
Journal of Technology Management 10 (7/8): 643–664.
doi:10.1504/IJTM.1995.025647.
Becker, W., and J. Peters. 2000.“Technological opportunities,
absorptive capacities, and innovation.”The Eighth
International Joseph A. Schumpeter Society Conference
Centre for Research in Innovation and Competition
(CRIC), University Manchester, Manchester.
12 Kalko, Erena and Debele
Belderbos, B., S. Kelchtermans, and R. Leten. 2021.“How Does
Basic Research Improve Innovation Performance in the
World’s Major Pharmaceutical Firms?”Industry and
Innovation, doi:10.1080/13662716.2021.1997723.
Bentler, P., and D. Bonett. 1980.“Significance Tests and
Goodness of fit in the Analysis of Covariance Structures.”
Psychological Bulletin 88 (3): 588–606. doi:10.1037/
0033-2909.88.3.588.
Bentler, P. M. 1990.“Comparative fit Indexes in Structural
Models.”Psychological Bulletin 107 (2): 238–246. doi:10.
1037/0033-2909.107.2.238.
Boudreau, M.-C., K. D. Loch, D. Robey, and D. Straud. 1998.
“Going Global: Using Information Technology to
Advance the Competitiveness of the Virtual Transnational
Organization.”Academy of Management Perspectives 12
(4): 120–128. doi:10.5465/AME.1998.1334008.
Bozeman, B. 2000.“Technology Transfer and Public Policy: A
Review of Research and Theory.”Research Policy 29 (4):
627–655. doi:10.1016/S0048-7333(99)00093-1.
Calantone, R. J., and M. A. Stanko. 2007.“Drivers of
Outsourced Innovation: An Exploratory Study.”Product
Innovation Management 24 (3): 230–241. doi:10.1111/j.
1540-5885.2007.00247.x.
Cardamone, P., V. Pupo, and F. Ricotta. 2015.“University
Technology Transfer and Manufacturing Innovation: The
Case of Italy.”Review of Policy Research 32 (3): 297–
322. doi:10.1111/ropr.12125.
Cassiman, B., and R. Veugelers. 2006.“In Search of
Complementarity in Innovation Strategy: Internal R&D
and External Knowledge Acquisition.”Management
Science 52 (1): 68–82. doi:10.1287/mnsc.1050.0470.
Cepeda-Carrion, G., J. G. Cegarra-Navarro, and D. Jimenez-
Jimenez. 2012.“The Effect of Absorptive Capacity on
Innovativeness: Context and Information Systems
Capability as Catalysts.”British Journal of Management
23 (1): 110–129. doi:10.1111/j.1467-8551.2010.00725.x.
Chan, L., and T. U. Daim. 2011.“Technology Transfer in China:
Literature Review and Policy Implications.”Journal of
Science and Technology Policy in China 2 (2): 122–145.
doi:10.1108/17585521111155192.
Charmjuree, T., Y. F. Badir, and U. Safdar. 2021.“External
Technology Acquisition, Exploitation and Process
Innovation Performance in Emerging Market Small and
Medium-Sized Enterprises: The Moderating Role of
Organizational Slack.”European Journal of Innovation
Management Vol. ahead-of-print No. ahead-of-print,
doi:10.1108/EJIM-07-2020-0263.
Chebo, A. K., and Y. F. Wubatie. 2020.“Commercialisation of
Technology Through Technology Entrepreneurship: The
Role of Strategic Flexibility and Strategic Alliance.”
Technology Analysis & Strategic Management 33 (4): 1–
12. doi:10.1080/09537325.2020.1817367.
Cheung, G. W., and R. B. Rensvold. 2002.“Evaluating
Goodness-of-Fit Indexes for Testing Measurement
Invariance.”Structural Equation Modeling: A
Multidiscplinary Journal 9 (2): 233–255. doi:10.1207/
s15328007sem0902_5.
Cinar, O., S. Altuntas, and M. A. Alan. 2021.“Technology Transfer
and its Impact on Innovation and Firm Performance: Empirical
Evidence from Turkish Export Companies.”Kybernetes 50
(7): 2179–2209. doi:10.1108/k-12-2019-0828.
Cohen, W. M., and D. A. Levinthal. 1989.“Innovation and
Learning: The Two Faces of R&D.”The Economic
Journal 99 (397): 56–59. doi:10.2307/2233763.
Cohen, W. M., and D. A. Levinthal. 1990.“Absorptive
Capacity: A New Perspective on Learning and
Innovation.”Administrative Science Quarterly 35 (1):
128–152. doi:10.2307/2393553.
Cresswell J.W. 2014.Research Design: Qualitative, Quantitative,
and Mixed Approaches. Los Angeles: Sage Publications, Inc.
CSA. 2018.“Report on Large and Medium Scale Manufacturing
and Electricity Industries Survey.”Addis Ababa: The FDRE
Statistical Bulletin.
Davenport, T. H., and L. Prusak. 1998.Working Knowledge:
How Organizations Manage What They Know. Boston,
MA: Harvard Business School Press.
Durrani, T. S., S. M. Forbes, C. Broadfoot, and A. S. Carrie.
1998.“Managing the Technology Acquisition Process.”
Technovation 18 (8/9): 523–587. doi:10.1016/s0166-4972
(98)00047-9.
Engelman, R., S. Schmidt, C. Froehlich, and E. M. Fracasso.
2018.“The Influence of Absorptive Capacity on Product
Innovation in Southern Brazilian Industries.”International
Journal of Innovation and Learning 24 (3): 345–365.
doi:10.1504/IJIL.2018.094713.
Erena, O. T., M. M. Kalko, and S. A. Debele. 2021.“Technical
Efficiency, Technological Progress and Productivity Growth
of Large and Medium Manufacturing Industries in Ethiopia:
A Data Envelopment Analysis.”Cogent Economics &
Finance 9(1): 1–38. doi:10.1080/23322039.2021.1997160.
Fartash, K., S. M. M. Davoudi, T. A. Baklashova, N. V.
Svechnikova, Y. V. Nikolaeva, S. A. Grimalskaya, and A.
V. Beloborodova. 2018.“The Impact of Technology
Acquisition & Exploitation on Organizational Innovation
and Organizational Performance in Knowledge-Intensive
Organizations.”EURASIA Journal of Mathematics,
Science and Technology Education 14 (4): 1497–1507.
doi:10.29333/ejmste/84835.
Fornell, C., and D. F. Larcker. 1981.“Evaluating Structural
Equation Models with Unobservable Variables and
Measurement Error.”Journal of Marketing Research 18
(1): 39–50. doi:10.1177/002224378101800104.
Fosfuri, A., and J. A. Tribo. 2008.“Exploring the Antecedents of
Potential Absorptive Capacity and its Impact on Innovation
Performance.”Omega 36 (2): 173–187. doi:10.1016/j.
omega.2006.06.012.
Gao,S.,K.Xu,andJ.Yang.2008.“Managerial Ties, Absorptive
Capacity, and Innovation.”Asia Pacific Journal of
Management 25 (3): 395–412. doi:10.1007/s10490-008-9096-1.
Garcia-Morales, V. J., A. Ruiz-Moreno, and F. J. Llorens-Montes.
2007.“Effects of Technology Absorptive Capacity and
Technology Proactivity on Organizational Learning,
Innovation and Performance: An Empirical Examination.”
Technology Analysis & Strategic Management 19 (4): 527–
558. doi:10.1080/09537320701403540.
García-Vega, M., and Ó Vicente-Chirivella. 2020.“Do
University Technology Transfers Increase Firms’
Innovation?”European Economic Review 123: 1–20.
doi:10.1016/j.euroecorev.2020.103388.
Gebreeyesus, M. 2009.Innovation and Microenterprise Growth
in Ethiopia. Tokyo: United Nations University.
Goedhuys, M., and R. Veugelers. 2012.“Innovation Strategies,
Process and Product Innovations and Growth: Firm-Level
Evidence from Brazil.”Structural Change and Economic
Dynamics 23 (4): 516–529. doi:10.1016/j.strueco.2011.01.004.
Grant, R. M. 1996.“Toward a knowledge-based theory of the
firm.”Strategic Management Journal 17 (2): 109–122.
doi:10.1002/smj.4250171110
Gregory, M. J. 1995.“Technology Management: A Process
Approach.”ARCHIVE: Proceedings of the Institution of
Mechanical Engineers, Part B: Journal of Engineering
Manufacture 1989-1996 (Vols 203-210) 209 (52): 347–
356. doi:10.1243/PIME_PROC_1995_209_094_02.
Guan, J. C., C. K. Mok, R. C. M. Yam, K. S. Chin, and K. F. Pun.
2006.“Technology Transfer and Innovation Performance:
Evidence from Chinese Firms.”Technology Forecasting &
Social Change 73 (6): 666–678. doi:10.1016/j.techfore.
2005.05.009.
Hair, J. F., W. C. Black, B. J. Babin, and R. E. Anderson. 2019.
Multivariate Data Analysis. 8th ed. Hampshire, UK:
Cengage Learning EMEA.
Henard, D. H., and M. A. McFadyen. 2005.“The
Complementary Roles of Applied and Basic Research: A
Knowledge-Based Perspective.”The Journal of Product
Innovation Management 22 (6): 503–514. doi:10.1111/j.
1540-5885.2005.00146.x.
African Journal of Science, Technology, Innovation and Development 13
Hitt, M. A., R. D. Ireland, and H.-u. Lee. 2000.“Technological
Learning, Knowledge Management, Firm Growth and
Performance: An Introductory Essay.”Journal of
Engineering and Technology Management 17 (3/4): 231–
246. doi:10.1016/s0923-4748(00)00024-2.
Hoegl, M., and S. M. Wagner. 2005.“Buyer-Supplier
Collaboration in Product Development Projects.”Journal
of Management 31 (4): 530–548. doi:10.1177/
0149206304272291.
Hsiao, Y. C., C. J. Chen, B. W. Lin, and C. I. Kuo. 2017.
“Resource Alignment, Organizational Distance, and
Knowledge Transfer Performance: The Contingency Role
of Alliance Form.”The Journal of Technology Transfer 42
(3): 635–653. doi:10.1007/s10961-016-9505-4.
Hsu, C-C., K. C. Tan, J. Jayaram, and T. Laosirihongthong.
2014.“Corporate Entrepreneurship, Operations Core
Competency and Innovation in Emerging Economies.”
International Journal of Production Research 52 (18):
5467–5483. doi:10.1080/00207543.2014.915069.
Hung, K.-P., and C. Chou. 2013.“The Impact of Open
Innovation on Firm Performance: The Moderating Effects
of Internal R&D and Environmental Turbulence.”
Technovation 33 (10/11): 368–380. doi:10.1016/j.
technovation.2013.06.006.
Hussen, M. S., and M. Çokgezen. 2019.“Analysis of Factors
Affecting Firm Innovation: An Empirical Investigation for
Ethiopian Firms.”Journal of African Business 21 (2): 1–
24. doi:10.1080/15228916.2019.1625020.
Jeon, J., S. Hong, J. Ohm, and T. Yang. 2015.“Causal
Relationships among Technology Acquisition, Absorptive
Capacity, and Innovation Performance: Evidence from the
Pharmaceutical Industry.”PLOS ONE 10 (7): 1–14.
doi:10.1371/journal.pone.0131642.
Jöreskog, K. 2005.Structural Equation Modeling with Ordinal
Variables Using LISREL. Chicago: Scientific Software
International. Accessed June 10, 2020. http://www.
ssicentral.com/lisrel/advancedtopics.html.
Jöreskog, K., and D. Sörbom. 1989.LISREL VII. Analysis of
Linear Structural Relationships by Maximum Likelihood,
Instrumental Variables, and Least-Squares Methods.
Mooresville, Indiana: Scientific Software.
Kang, K. H., G. S. Jo, and J. Kang. 2015.“External Technology
Acquisition: A Double-Edged Sword.”Asian Journal of
Technology Innovation 23 (1): 35–52. doi:10.1080/
19761597.2015.1010265.
Kessler, E. H., P. E. Bierly, and S. Gopalakrishnan. 2000.
“Internal vs. External Learning in New Product
Development: Effects on Speed, Costs and Competitive
Advantage.”R&D Management 30 (3): 213–224. doi:10.
1111/1467-9310.00172.
Kneller, R., and P. A. Stevens. 2006.“Frontier Technology and
Absorptive Capacity: Evidence from OECD Manufacturing
Industries.”Oxford Bulletin of Economics and Statistics 68
(1): 1–20. doi:10.1111/j.1468-0084-2006.00150.x.
Kostopoulos, K., A. Papalexandris, M. Papachroni, and G.
Ioannou. 2011.“Absorptive Capacity, Innovation, and
Financial Performance.”Journal of Business Research 64
(12): 1335–1343. doi:10.1016/j.jbusres.2010.12.005.
Lewin, A. Y., S. Massini, and C. Peeters. 2011.
“Microfoundations of Internal and External Absorptive
Capacity Routines.”Organization Science 22 (1): 81–98.
doi:10.1287/orsc.1100.0525.
Liang, H., and Z. Zhang. 2012.“The Effects of Industry
Characteristics on the Sources of Technological Product
and Process Innovation.”The Journal of Technology
Transfer 37 (6): 867–884. doi:10.1007/s10961-011-9206-y.
Lichtenthaler, U. 2005.“External Commercialization of
Knowledge: Review and Research Agenda.”International
Journal of Management Reviews 7 (4): 231–255. doi:10.
1111/j.1468-2370.2005.00115.x.
Lichtenthaler, U. 2007.“The Drivers of Technology Licensing:
An Industry Comparison.”California Management Review
49 (4): 67–89. doi:10.2307/41166406.
Lichtenthaler, U. 2009.“Absorptive Capacity, Environmental
Turbulence, and the Complementarity of Organizational
Learning Processes.”Academy of Management Journal 52
(4): 822–846. doi:10.5465/AMJ.2009.43670902.
Lichtenthaler, U., and H. Ernst. 2007.“External Technology
Commercialization in Large Firms: Results of a
Quantitative Benchmarking Study.”R&D Management 37
(5): 383–397. doi:10.1111/j.1467-9310.2007.00487.x.
Lichtenthaler, U., and H. Ernst. 2009.“Opening up the
Innovation Process: The Role of Technology
Aggressiveness.”R&D Management 39 (1): 38–54.
doi:10.1111/j.1467-9310.2008.00522.x.
Li-Hua, R., and T. M. Khalil. 2006.“Technology Management
in China: A Global Perspective and Challenging Issues.”
Journal of Technology Management in China 1 (1): 9–26.
doi:10.1108/17468770610642731.
Lim, K. 2004.“The Relationship Between Research and
Innovation in the Semiconductor and Pharmaceutical
Industries (1981–1997).”Research Policy 33 (2): 287–
321. doi:10.1016/j.respol.2003.08.001.
Lin, Y., Y. Qin, and Z. Xie. 2020.“Does Foreign Technology
Transfer Spur Domestic Innovation? Evidence from the
High-Speed Rail Sector in China.”Journal of
Comparative Economics 49 (1): 212–229. doi:10.1016/j.
jce.2020.08.004.
Malhotra, N. K., D. Nunan and D. F. Birks. 2017.Marketing
Research: An Applied Approach. 5th ed. Edinburgh:
Prentice Hall Inc.
Masa’deh, R. E., B. Y. Obeidat, and A. Tarhini. 2016.“A
Jordanian Empirical Study of the Associations among
Transformational Leadership, Transactional Leadership,
Knowledge Sharing, job Performance, and Firm
Performance: A Structural Equation Modelling
Approach.”Journal of Management Development 35 (5):
681–705.
Montoya, P. V., R. S. Zárate, and L. A. G. Martín. 2007.“Does
the Technological Sourcing Decision Matter?: Evidence
from Spanish Panel Data.”R&D Management 37 (2):
161–172. doi:10.1111/j.1467-9310.2007.00465.x.
Nelson, R. R. 1959.“The Simple Economics of Basic Scientific
Research.”Journal of Political Economy 67 (3): 297–306.
doi:10.1086/258177.
Nieto, M. J., and L. Santamaría. 2007.“The Importance of
Diverse Collaborative Networks for the Novelty of
Product Innovation.”Technovation 27 (6/7): 367–377.
doi:10.1016/j.technovation.2006.10.001.
Nonaka, I. 1994.“ADynamic Theory of Organizational
Knowledge Creation.”Organization Science 5 (1): 14–37.
doi:10.1287/orsc.5.1.14.
Novickis, L., A. Mitasiunas, and V. Ponomarenko. 2017.
“Information Technology Transfer Model as a Bridge
Between Science and Business Sector.”Procedia Computer
Science 104 (1): 120–126. doi:10.1016/j.procs.2017.01.083.
Oqubay, A. 2018.The Structure and Performance of the
Ethiopian Manufacturing Sector. Working Paper Series N°
299. Abidjan, Côte d’Ivoire: African Development Bank.
Ortega, M. J. R. 2010.“Competitive Strategies and Firm
Performance: Technological Capabilities’Moderating
Roles.”Journal of Business Research 63 (12): 1273–1281.
doi:10.1016/j.jbusres.2009.09.007.
Phaal, R., C. J. P. Farrukh, and D. R. Probert. 2001.“Technology
Management Process Assessment: A Case Study.”
International Journal of Operations & Production
Management 21 (8): 1116–1132. doi:10.1108/
EUM0000000005588.
Pinheiro, J., L. F. Lages, G. M. Silva, A. L. Dias, and M. T.
Preto. 2021.“Effects of Absorptive Capacity and
Innovation Spillover on Manufacturing Flexibility.”
International Journal of Productivity and Performance
Management. Advance online publication. doi:10.1108/
IJPPM-04-2020-0156.
Pradana, M., A. Pérez-Luño, and M. Fuentes-Blasco. 2020.
“Innovation as the key to Gain Performance from
14 Kalko, Erena and Debele
Absorptive Capacity and Human Capital.”Technology
Analysis & Strategic Management 32 (7): 822–834.
doi:10.1080/09537325.2020.1714578.
Rajan, R., Dhir, S., and Sushil. 2021.“Technology Management
for Innovation in Organizations: An Argumentation-Based
Modified TISM Approach.”Benchmarking: An
International Journal 28 (6): 1959–1986. doi:10.1108/BIJ-
01-2020-0019
Shenkoya, T., and E. Kim. 2020.“The Impact of Technology
Transfer/Policies on the Economic Catch-up of the Korean
National Innovation System and its Implications for
Nigeria.”African Journal of Science, Technology,
Innovation and Development 13 (6): 685–699. doi:10.
1080/20421338.2020.1799536.
Simon, H. A. 1991.“Bounded Rationality and Organizational
Learning.”Organization Science 2 (1): 125–134. doi:10.
1287/orsc.2.1.125.
Small, A., and D. Wainwright. 2014.“SSM and Technology
Management: Developing Multimethodology Through
Practice.”European Journal of Operational Research 233
(3): 660–673. doi:10.1016/j.ejor.2013.08.049.
Sözbilir F. 2018.“Innovation Capacity and Innovation
Performance in Terms of Educational Level of Managers.”
Journal of Business Research-Turk 10 (2): 1–12. https://
www.ceeol.com/search/journal-detail?id=329.
Steiger, J., and J. Lind. 1980.“Statistically Based Tests for the
Number of Common Factors.”Paper presented at the
annual meeting of the psychometric society, Iowa City, IA.
Thornhill, S. 2006.“Knowledge, Innovation, and Firm
Performance in High- and Low-Technology Regimes.”
Journal of Business Venturing 21 (5): 687–703. doi:10.
1016/j.jbusvent.2005.06.001.
Todorova, G., and B. Durisin. 2007.“Absorptive Capacity:
Valuing a Reconceptualization.”Academy of Management
Review 32 (3): 774–786. doi:10.5465/amr.2007.25275513.
Tsai, K.-H., and J.-C. Wang. 2007.“Inward Technology
Licensing and Firm Performance: A Longitudinal Study.”
R&D Management 37 (2): 151–160. doi:10.1111/j.1467-
9310.2007.00464.x.
Tsai, K.-H., and J.-C. Wang. 2008.“External Technology
Acquisition and Firm Performance: A Longitudinal
Study.”Journal of Business Venturing 23 (1): 91–112.
doi:10.1016/j.jbusvent.2005.07.002.
Tsai, K.-H., and J.-C. Wang. 2009.“External Technology
Sourcing and Innovation Performance in LMT Sectors: An
Analysis Based on the Taiwanese Technological
Innovation Survey.”Research Policy 38 (3): 518–526.
doi:10.1016/j.respol.2008.10.007.
Tsai, K.-H., M.-H. Hsieh, and E. J. Hultink. 2011.“External
Technology Acquisition and Product Innovativeness: The
Moderating Roles of R&D Investment and Configurational
Context.”Journal of Engineering and Technology
Management 28 (3): 184–200. doi:10.1016/j.jengtecman.
2011.03.005.
UNDP. 2018.“Understanding African Experiences in
Formulating and Implementing Plans for Emergence: A
Case Study of Growing Manufacturing Industry in
Ethiopia.”Addis Ababa: UNDP. https://www.et.undp.org/
content/ethiopia/en/home/library/poverty/understanding-
african-experiences-in-formulating-and-implementin.html.
Utterback, J. M. 1971.“The Process of Technological
Innovation Within the Firm.”Academy of Management
Journal 14 (1): 75–88. doi:10.5465/254712.
Vanhaverbeke, W., G. Duysters, and N. Noorderhaven. 2002.
“External Technology Sourcing Through Alliances or
Acquisitions: An Analysis of the Application-Specific
Integrated Circuits Industry.”Organization Science 13 (6):
714–733. doi:10.1287/orsc.13.6.714.496.
Wakeford, J. J., M. Gebreeyesus, T. Ginbo, K. Yimer, O.
Manzambi, C. Okereke, B. Mairi, and M. Yacob. 2017.
“Innovation for Green Industrialization: An Empirical
Assessment of Innovation in Ethiopia’s Cement, Leather
and Textile Sectors.”Journal of Cleaner Production 166
(1): 503–511. doi:10.1016/j.jclepro.2017.08.067.
Wheaton, B., B. Muthén, D. F. Alwin, and G. F. Summers. 1977.
“Assessing Reliability and Stability in Panel Models.”
Sociological Methodology 8: 84–136. doi:10.2307/270754.
White, M. A., and G. D. Bruton. 2011.The Management of
Technology and Innovation: A Strategic Approach. 2nd ed.
Ohio, USA: Cengage Learning, Natorp Boulevard (Mason).
Williamson, O. E. 1975.Markets and Hierarchies: Analysis and
Antitrust Implications. New York: Free press.
Williamson, O. E. 1991.“Comparative Economic Organization:
The Analysis of Discrete Structural Alternatives.”
Administrative Science Quarterly 36 (2): 269–296. doi:10.
2307/2393356.
World Bank. 2014.“Doing Business: Understanding
Regulations for Small and Medium-Size Enterprises.”
Washington, DC: World Bank.
World Economic Forum. 2019.“The Global Competitiveness
Report.”Geneva: World Economic Forum.
Wu, W. W., Y. Yang, Q. Deng and B. Yu. 2010.“Technology
Management Capability and New Product Development
Performance: The Mediating Role of Absorptive
Capacity.”In PICMET 2010 Technology Management for
Global Economic Growth. Proceedings of Portland
International Conference on Management of Engineering
and Technology, Phuket, Thailand, 18-22 July 2010.
Zahra, S. A., and G. George. 2002.“Absorptive Capacity: A
Review, Reconceptualization, and Extension.”Academy of
Management Review 27 (2): 185–203. doi:10.5465/amr.
2002.6587995.
Appendix 1. Technology management and innovation constructs and measurement items.
Item code Constructs and measurement items Standardized loading (λ)
Technology Process
TP1 The amount of basic research done so far to support the
company’s goal towards technology was enough.
0.73
TP2 The company has given higher priority to basic research to
promote the company’s performance.
0.75
TP3 The company considers basic research as its main competitive
and developmental advantage.
0.75
TP4 Several indigenous ideas and technologies have emerged as a
result of the company’s basic and applied research.
0.75
(Continued)
African Journal of Science, Technology, Innovation and Development 15
Continued.
Item code Constructs and measurement items Standardized loading (λ)
TP5 The willingness of the organization’s research and development
division to involve and collect relevant ideas from different
levels of workers.
0.72
TP6 The extent to which the company relied on applied research to
support the company’s growth and development in technology
and innovation
0.76
TP7 The company’s priorities towards basic research are to promote
the product features and equip laboratories with the necessary
supporting equipment and inputs.
0.72
TP8 The extent to which your company regards basic research as its
primary competitive and developmental advantage, as well as its
inclusion in its strategic plans.
0.74
TP9 As a result of applied research done in the company, several
indigenous ideas and technologies have been obtained.
0.74
TP10 Different technologies resulting from basic and applied research
were identified properly for development phases regularly.
0.75
TP11 Development of technologies was done in accordance with the
company’s policies by screening those that have promising
rewards, enhancing growth and development.
0.79
TP12 Sounding numbers of technologies from research output were
identified for further screening and to have more alternatives for
flexibility and decisions.
0.74
Technology Acquisition
TAC1 Several technologies and innovative ideas and outputs have been
used and marketed diligently in the past five years.
0.71
TAC2 The management of imitated technologies or innovative ideas
for further research and analysis to be used as a basis to improve
the existing knowledge and creativity.
0.73
TAC3 Initiation and commitment of top management and other staff in
engaging themselves in imitative innovations.
0.72
TAC4 Culture has developed throughout the company in the creation of
an innovative and technology-responsive society
0.65
TAC5 How do you rate the number of adopted and/or adapted
technologies that have been developed and used so far in your
company?
0.71
TAC6 To what extent have the adapted technologies, innovative ideas,
processes, and/or products have been used so far to enhance the
company’s performance?
0.74
TAC7 Attempts have been made to have a strong relationship between
technology providers in order to facilitate further training and
joint work with them.
0.80
TAC8 The number of technologies adopted so far that have been
patented and/or registered as intellectual property in the last 3
years was satisfactory.
0.76
Technology Absorption
TAB1 The integration of basic and applied research was made to
innovatively enhance the company’s growth and development.
0.82
TAB2 Efforts were made to exploit the existing abilities to create and
use technologies to the maximum level.
0.63
TAB3 The company had devoted its efforts to technology exploitation
from other industries through technology transfer.
0.74
TAB4 To what degree did the gains obtained from technology enhance
the company’s performance?
0.68
Technology Transfer
TT1 The company’s strategic goals associated with technology
transfer have been designed to spur innovation and get
acceptance at all levels and implemented/executed accordingly.
0.70
TT2 The company performs technology planning and reviews with
respect to technology transfer and innovation and makes
improvements on a continuous basis.
0.72
TT3 The number of technologies transferred internally aligns with
the targeted quantities of technology transfer and strategies
towards technology transfer to enhance innovation.
0.73
TT4 The trend and practice of your company to monitor the
technologies owned by competitors.
0.70
(Continued)
16 Kalko, Erena and Debele
Continued.
Item code Constructs and measurement items Standardized loading (λ)
TT5 The company tracks the technologies transferred across
industries and makes important amendments and improvements
to improve innovation.
0.75
TT6 The company reviews important technology information
periodically, and certain measures/actions are taken according to
the information obtained to inspire creativity and innovation.
0.83
TT7 The company assesses technology needs across industries and
tries to fill the gap with any endeavour.
0.82
TT8 The company has allotted a budget to develop one or more of its
core technologies internally to transfer to another organization.
0.75
TT9 The number of technologies that were identified to be transferred
to other organizations was decided in advance.
0.73
TT10 The company has a clear policy and viable strategy towards
technology transfer at the firm level for strengthening new
product development and managing the innovation process.
0.69
Process Innovation
PCI1 To what extent does process innovation streamline the internal
manufacturing process/activities and simplify them?
0.83
PCI2 To what extent does process innovation contribute to reducing
production cycle time and/or lead time and setup times?
0.77
PCI3 How do you rate the contribution of process innovation that has
been made in your organization to increase productivity?
0.73
PCI4 To what extent did the process innovation contribute to creating
a conducive working environment and simplifying tasks in the
company?
0.84
PCI5 To what extent did the process innovation endeavour enhance
the product features and add value to the customers?
0.74
Product Innovation
PDI1 How do you evaluate the product innovations made in your
organization in the past 3–5 years?
0.71
PDI2 Is there a policy and practice towards product innovations? If so,
how can you rate the level of engagement in your company?
0.82
PDI3 To what extent does the product innovation process contribute to
producing products with multifunctionality, attractive design,
and appearance?
0.73
PDI4 Differentiation and variety, such as new designs introduced or
improved existing designs of the product, were created as a
result of product innovation.
0.76
PDI5 Enhancement of existing brands regarding user-friendliness,
simplified operation, and safety.
0.72
Method Innovation
MI1 The practice and know-how of the company towards method
improvement are through innovative activities.
0.76
MI2 Methods of performing internal production activities have
improved as a result of innovative thinking and practice.
0.75
MI3 Contributions of methodological innovations to create a
conducive working environment reduced defects and reworks.
0.86
MI4 The extent that innovative methods played a role in cutting costs
by avoiding non-value-adding activities.
0.77
MI5 The contribution of innovative methodologies to improve
delivery times and methods enhances customers’experience
with the company.
0.79
Note: All items are measured on a five-point scale, ranging from 1 (nothing was done) to 5 (very good).
African Journal of Science, Technology, Innovation and Development 17
