1. INTRODUCTION
During the past two decades, electronic commerce (E-Commerce)
through an internet has been an interesting issue and become an
important business in Thailand. Internet is an important business tool
in helping firms expand their distribution channels, improve business
excellence, build customer satisfaction, increase competitive advantage,
enhance organizational performance and profitability, and sustain in the
competitive markets and environments. Then, the internet can be utilized
to identify, contact and do business directly with potential suppliers
or customers in convenient, flexible and rapid manner without the
services of an intermediary, and becomes a key driver of determining
firms' success, growth and sustainability in local and global
business environments. Thus, E-Commerce businesses in Thailand are a
critical main sample in this study.
With the interests of E-Commerce businesses in Thailand, marketing
effectiveness is an outcome of implementing IT competency, technological
learning, knowledge acquisition, technological complementarity, and
technology acceptance in the business operations, activities and
markets. Here, marketing effectiveness is taken as an ability of firms
to study the market, recognize the numerous opportunities, select the
most appropriate segments of the market to operate in and endeavor to
offer superior value to meet the selected customers' needs and
wants (Kotler, 1977). It includes customer philosophy, integrated
marketing organization, adequate marketing information, strategic
orientation, and operational efficiency. Firms with greater marketing
effectiveness tend to have strong market orientation, enhanced customer
satisfaction, strong market orientation, better competitive advantage,
stable long-term growth, superior firm performance, and outstanding
organizational profitability. Hence, antecedents of increasing marketing
effectiveness in the competitive markets under the E-Commerce aspect are
needed. To clearly understand these antecedents, IT competency,
technological learning, knowledge acquisition, technological
complementarity, and technology acceptance are proposed as significant
factors of explaining marketing effectiveness.
IT competency, technological learning, knowledge acquisition,
technological complementarity, and technology acceptance are the
antecedents of marketing effectiveness. Firstly, IT competency is an
ability to translate a business strategy into long term information
architectures, technology infrastructure, and resourcing plans that
enable the implementation of the strategy and involves improving
information access and coordination across organizational units
(Ussahawanitchakit, 2005a). Secondly, technological learning is a
process by which a technology-driven firm creates, renews, and upgrades
its latent and enacted capabilities based on its stock of explicit and
tacit resources, namely, structural capital, intellectual assets and
human (Carayannis, 1998). Thirdly, knowledge acquisition is the process
of interpretation of new information and its assimilation and
accommodation into schemata (Khalifa and Liu, 2008). Fourthly,
technological complementarity is a unique and symmetric strategic
combination of firm roles, goals, and readiness for the implementation
and use of technology across units and firms (Richey et al., 2007).
Lastly, technology acceptance is the ability to accept new technology
within specific circumstances (Greenfield and Rohde, 2009).
Accordingly, IT competency, technological learning, knowledge
acquisition, technological complementarity, and technology acceptance
are hypothesized to become key determinants of marketing effectiveness.
Both technological complementarity and technology acceptance are also
proposed to be moderators of these relationships. Hence, this study aims
to examine the influences of IT competency, technological learning,
knowledge acquisition, technological complementarity, and technology
acceptance on marketing effectiveness of E-Commerce businesses in
Thailand. In the research model of the relationships, marketing
effectiveness is a dependent variable; IT competency, technological
learning, and knowledge acquisition are independent variables; and
technological complementarity and technology acceptance are both
independent and moderating variables. The key research questions in this
study are how
IT competency, technological learning, knowledge acquisition,
technological complementarity, and technology acceptance have a
relationship with marketing effectiveness; how differences of IT
competency, technological learning, knowledge acquisition, technological
complementarity, and technology acceptance affect marketing
effectiveness; how both technological complementarity and technology
acceptance moderate all aforementioned relationships; and are the
research relationships positive.
This study is organized as follows. A literature review on IT
competency, technological learning, knowledge acquisition, technological
complementarity, technology acceptance, and marketing effectiveness is
firstly addressed. The research model of the relationships among IT
competency, technological learning, knowledge acquisition, technological
complementarity, technology acceptance, and marketing effectiveness is
secondly presented and the hypothesized relationships are also
discussed. The research method used to test these hypotheses is thirdly
discussed. The results of the aforementioned relationships of E-Commerce
businesses in Thailand are fourthly presented. The study lastly ends by
discussing contributions of practice and theory, limitations of the
study, providing directions for future research, and concluding overall
of the study.
2. LITERATURE REVIEWS ON MARKETING EFFECTIVENESS AND ITS
ANTECEDENTS
With respect to the relationships among IT competency,
technological learning, knowledge acquisition, technological
complementarity, technology acceptance, and marketing effectiveness, the
conceptual, linkage, and research model presents the aforementioned
relationships, as shown in Figure 1.
[FIGURE 1 OMITTED]
2.1 Marketing Effectiveness
Marketing effectiveness is an outcome of IT competency,
technological learning, knowledge acquisition, technological
complementarity, and technology acceptance. It is defined as an ability
of firms to study the market, recognize the numerous opportunities,
select the most appropriate segments of the market to operate in and
endeavor to offer superior value to meet the selected customers'
needs and wants (Kotler, 1977). It includes customer philosophy,
integrated marketing organization, adequate marketing information,
strategic orientation, and operational efficiency. Also, marketing
effectiveness refers to the functions of improving how marketers go to
market with the goal of optimizing their marketing spend to achieve even
better results of both the short- and long-term objectives (Nwokah and
Ahiauzu, 2008). Generally, marketing effectiveness positively has a
strong influence on strong market orientation, enhanced customer
satisfaction, strong market orientation, better competitive advantage,
stable long-term growth, superior firm performance, and outstanding
organizational profitability. Higher marketing effectiveness is
positively related to greater customer satisfaction and better firm
performance. Firms have implemented marketing effectiveness in their
marketing activities and business operations in order to achieve their
performance. Thus, marketing effectiveness tends to have a positive
association with firm performance.
To increase the level of firms' marketing effectiveness,
marketing strategy, marketing creation, marketing execution, marketing
infrastructure, and exogenous factors become important main driving
forces of their marketing effectiveness. Similarly, IT competency,
technological learning, knowledge acquisition, technological
complementarity, and technology acceptance have, herein, affected their
excellent marketing effectiveness. Firms with greater IT competency,
technological learning, knowledge acquisition, technological
complementarity, and technology acceptance tend to directly have higher
level of marketing effectiveness and indirectly improve their
performance and profitability. Under the importance of firms'
marketing effectiveness, the aforementioned concepts become key drivers
of determining marketing effectiveness and are hypothesized to be
independent variables of the study. Then, they are likely to have a
positive impact on firms' marketing effectiveness.
2.2 IT Competency
Here, information technology (IT) competency refers to the
abilities of firms to clearly understand and valuably implement the
antecedents and consequences of informational technology in order to
create their efficiency and effectiveness and build organizational
success in business operations. It effectively allows firms to achieve a
competitive advantage and enhances business performance, profitability,
growth, and sustainability (Croteau and Raymond, 2004). It is an outcome
of firms' strategic competencies, namely, shared vision,
cooperation, empowerment, and innovation. Likewise, IT competency
includes connectivity, flexibility and technological scanning. Firstly,
connectivity is the firms' capacity to operate compatible
telecommunications networks and computer systems in support of
enterprise-wide applications (Brown and Magill, 1994). Secondly,
flexibility is an IT capability that can be adapted to strategic changes
within the organization (Byrd and Turner, 2000). Lastly, technological
scanning is the managed acquisition, analysis and diffusion of IT
novelty by members of the information system (IS) department to increase
the competitiveness of the firms (Julien et al., 1999). Higher IT
competency is definitely related to greater use effectiveness and better
management of IT.
IT competency is also defined as the ability to mobilize and deploy
IT-based resources in combination or copresent with other resources and
capabilities (Ussahawanitchakit, 2005a). It is an ability to translate a
business strategy into long term information architectures, technology
infrastructure, and resourcing plans that enable the implementation of
the strategy and involves improving information access and coordination
across organizational units. It consists of (1) the value-added
contribution of IT-assets and routines to the enterprises, (2) comprised
highly interdependent core assets and routines that take on distinctive
profiles in their situational execution, and (3) dynamic in that the
capabilities apply skill sets and routines that evolve very rapidly and
are typically acquired and retired in a discontinuous fashion (Schwarz
and Hirschheim, 2003). IT competency has been recognized for its
potential to contribute to sustained competitive advantage and increased
business performance for firms (Celuch et al., 2007). In this study, IT
competency includes three components, namely, IT infrastructure, human
IT resources, and IT-enabled intangible resources (Bharadwaj, 2000).
Hence, it has become a key driver of enhancing business strategies
through marketing effectiveness that distinctively affects competitive
advantage and firm performance. Therefore, the hypothesis is posited as
below:
Hypothesis 1: IT competency is positively related to marketing
effectiveness.
2.3 Technological Learning
Technological learning is a process by which a technology-driven
firm creates, renews, and upgrades its latent and enacted capabilities
based on its stock of explicit and tacit resources, namely, structural
capital, intellectual assets and human (Carayannis, 1998). It combines
technical with administrative learning processes. It is a strategic role
in achieving successful project and program management, and gaining
competitive advantage and performance. Here, technological learning is
defined as the development of new or novel technological knowledge that
is organizationally accessible for creative problem solving through a
form of organizational learning (Kazanjian et al., 2000). It
outstandingly helps firms create knowledge and learn within the
organizations through the design of new products and services. It is a
process by which firms acquire external technology and accumulate
technology capability to improve their competitive advantage and achieve
business performance (Xie, 2004). Moreover, it generates and manages
strengthened technical changes and technology capabilities. Then,
technological learning becomes the acquisition, assimilation and
improvement upon technologies.
Technological learning is a continuous interactive course between
organizational process and technical path while responding to external
change of environments (Lee, 2004). It has an impact on research and
development (R&D) activities, and operational success and is a
source of firms' decision making and management of uncertainty and
complexity in gaining competitive advantage and achieving firm market
performance in the technology-based environments. Firms have implemented
technological learning to develop their technological knowledge stock
and use that stock to create value (Hitt et al., 2000), and maintain and
exploit dynamic core competencies that are the foundation for
competitive advantages within the technological environments. With
successfully implementing technological learning in business activities,
firms definitely utilize technological learning that is a process of
accumulation of knowledge, information skills, competencies, and
experience in order to generate changes in a productive system and to
sustain competitiveness (Karaoz and Albeni, 2005). Thus, technological
learning becomes a firm's ability to make effective use of
technological knowledge in gaining marketing effectiveness and achieving
business profitability. Then, a greater technological learning is likely
to impact more successful marketing effectiveness. Therefore, the
hypothesis is posited as below:
Hypothesis 2: Technological learning is positively related to
marketing effectiveness.
2.4 Knowledge Acquisition
Beyond IT competency and technological learning as sources of
achieving marketing effectiveness, knowledge acquisition is another main
determinant of explaining marketing effectiveness. It refers to the
process of interpretation of new information and its assimilation and
accommodation into schemata (Khalifa and Liu, 2008). Knowledge
acquisition consists of assimilation: the incorporation of new
information into an already existing schema, and accommodation: the
medication of an existing schema to fit in new information. It is likely
to help firms involve knowledge assessment, knowledge sharing and
knowledge assimilation through transferring and learning knowledge in
order to gain their performance and sustainability. Also, knowledge
acquisition is the process by which tacit knowledge is obtained from
others (Anh et al., 2006). It results from participation and
interactions with tasks, technologies, resources, and people within a
particular context. Higher knowledge acquisition explicitly supports
firms to successfully implement business strategies for having superior
profitability. Likewise, knowledge acquisition is defined as skills
learned and knowledge acquired by a firm from a partner (Norman, 2004).
In the alliance context, a focal firm can learn how to facilitate from
the partners and achieve alliance satisfaction. Then, knowledge
acquisition becomes a significant driver of influencing firms'
success and growth. It can arise from a direct experience of an
organization, its members, and its partners.
For the international aspects, knowledge acquisition is the ability
to acquire knowledge about best practices and local market influences
multinationals' international performance (Zou and Ghauri, 2008).
It is directed toward helping a foreign acquirer evaluate, learn,
accumulate, and leverage complementary knowledge and skills from local
targets, adopt dual management structure, and facilitate communications
with local personnel in order to gain a success of future operations.
Moreover, knowledge acquisition essentially enhances firms to have a
greater foreign development by affecting conditions necessary for a
creation of value abroad (Presutti et al., 2007). It reinforces
knowledge exploitation for an international growth of a start-up by
supporting a level of foreign sales and a number of markets.
Firms with greater knowledge acquisition tend to have better
organizational performance and, thus, gain more business growth in the
international markets through utilizing firm strategies, including
management, marketing and other strategies. Thus, knowledge acquisition
is a key tool that helps firms succeed and sustain. While knowledge
acquisition has an important effect on successfully implementing
business strategies, it is likely to encourage firms' marketing
effectiveness that builds their performance and sustainability. Then,
knowledge acquisition is hypothesized to have a positive association
with marketing effectiveness. Therefore, the hypothesis is posited as
below:
Hypothesis 3: Knowledge acquisition is positively related to
marketing effectiveness.
2.5 Technological Complementarity
In this study, technological complementarity is defined as a unique
and symmetric strategic combination of firm roles, goals, and readiness
for the implementation and use of technology across units and firms
(Richey et al., 2007). It is central to effective management that
supports firms to work together and to complement one another. Firms
with higher technological complementarity tend to successfully create
valuable business strategies, effectively achieve integration,
potentially increase market power, and explicitly gain performance and
other advantages. Technological complementarity arises in any situation
in which the past or present decisions of initiating agents with respect
to their own technologies affect the value of the receiving agents'
existing technologies and/or their opportunities for making further
technological changes (Carlaw and Lipsey, 2002). It plays a crucial role
in explaining sustainable advantages and innovations. Then, firms with
greater technological complementarity are likely to succeed the
implementation of operational strategies, again competitive advantage
and competitiveness, and achieve business performance and
sustainability.
Interestingly, technological complementarity plays a significant
driver in helping firms succeed, grow and sustain through successfully
implementing marketing effectiveness. For the technology complementarity
between firms, it is the degree to which their technological problem
solving focuses on different narrowly defines areas of knowledge within
a broadly defined area of knowledge that they share (Makri et al.,
2010). It has a positive impact on synergistic performance. In this
study, technological complementarity is proposed to become an important
factor that influences firms' marketing effectiveness. Thus, firms
with higher technological complementarity seem to achieve greater
marketing effectiveness. Therefore, the hypothesis is posited as below:
Hypothesis 4: Technological complementarity is positively related
to marketing effectiveness.
Technological complementarity is also a moderator of the
relationships among IT competency, technological learning, knowledge
acquisition, and marketing effectiveness. It tends to help potentially
enhance the stronger aforementioned relationships. Thus, higher
technological complementarity is likely to support the stronger
relationships between IT competency and marketing effectiveness, between
technological learning and marketing effectiveness, and between
knowledge acquisition and marketing effectiveness. Therefore, the
hypothesis is posited as below:
Hypothesis 5: Technological complementarity positively moderates
(a) the IT competency-marketing effectiveness relationships, (b) the
technological learning-marketing effectiveness relationships, and (c)
the knowledge acquisition-marketing effectiveness relationships
2.6 Technology Acceptance
Technology acceptance refers to the ability to accept new
technology within specific circumstances (Greenfield and Rohde, 2009).
It effectively determines a user's intention and attitude to use
technology. For sales force setting, technology acceptance has a
significant positive impact on salesperson performance through enhanced
propensity to practice adaptive selling (Robinson et al., 2005a).
Individual with greater technology acceptance tends to build personal
innovativeness that enhances firms' success and sustainability.
Likewise, technology acceptance is defined as a person's attitude
toward using a technology (Robinson et al., 2005b). It is determined by
internal beliefs, attitudes, and behavioral intentions that can increase
his or her performance. It consists of perceived usefulness and
perceived ease of use. Perceived usefulness refers to the degree to
which an individual considers that employment of a specific system can
improve his or her job performance at work, and perceived ease of use is
defined as the degree to which an individual pays the attention to the
additional effort required to apply a specific technology (Hernandez et
al., 2009). Then, technology acceptance via internal beliefs, attitudes,
and intentions of using technology becomes a critical requirement of
successfully achieving an individual's innovativeness and job
performance.
For the interests of organizational aspect, technology acceptance
is also a key determinant of explaining firm profitability, growth, and
sustainability. It essentially supports firms to implement critical
strategies in order to gain a competitive advantage and achieve their
organizational performance. Similarly, firms with higher technology
acceptance are also likely to utilize greater marketing effectiveness in
order to receive superior corporate outcomes in the competitive markets.
Technology acceptance potentially enhances them to clearly understand
business environments and usefully apply marketing strategies. Then,
technology acceptance has a positive influence on marketing
effectiveness. Therefore, the hypothesis is posited as below:
Hypothesis 6: Technology acceptance is positively related to
marketing effectiveness.
Technology acceptance is also a moderator of the relationships
among IT competency, technological learning, knowledge acquisition, and
marketing effectiveness. It tends to help potentially enhance the
stronger aforementioned relationships. Thus, higher technology
acceptance is likely to support the stronger relationships between IT
competency and marketing effectiveness, between technological learning
and marketing effectiveness, and between knowledge acquisition and
marketing effectiveness. Therefore, the hypothesis is posited as below:
Hypothesis 7: Technology acceptance positively moderates (a) the IT
competency-marketing effectiveness relationships, (b) the technological
learning-marketing effectiveness relationships, and (c) the knowledge
acquisition-marketing effectiveness relationships
3. RESEARCH METHODS
3.1 Sample Selection and Data Collection Procedure
Here, E-Commerce businesses of Thailand are selected as the sample.
In all, 1,204 firms were randomly chosen from the list of the Department
of Business Development, Ministry of Commerce, Thailand. A mail survey
procedure via the questionnaire was used for data collection. The key
participants in this study were chief executive officers, managing
directors or managing executives of E-Commerce businesses of Thailand.
With regard to the questionnaire mailing, 140 surveys were undeliverable
because some firms were no longer in business or had moved to unknown
locations. Deducting the undeliverables from the original 1,204 mailed,
the valid mailing was 1,064 surveys, from which 432 responses were
received. Of the surveys completed and returned, only 399 were usable.
The effective response rate was approximately 37.50%. According to
Aaker, Kumar and Day (2001), the response rate for a mail survey,
without an appropriate follow-up procedure, is less than 20%. Thus, the
response rate of this study is considered acceptable.
To test potential and non-response bias and to detect and consider
possible problems with non-response errors, the assessment and
investigation of non-response-bias was centered on two different
procedures: (1) a comparison of sample statistics and known values of
the population, such as number of employees, number of years in doing
business, and amount of capital funding, and (2) a comparison of first
wave and second wave data recommended by Armstrong and Overton (1977).
The results revealed neither procedure showed significant differences.
3.2 Variables
Here, marketing effectiveness is a dependent variable of the study
and it refers to the function of improving how marketers go to market
with the goal of optimizing their marketing spend to achieve even better
results of both the short- and long-term objectives (Nwokah and Ahiauzu,
2008). Five items were utilized to evaluate the degree to which firms
have focused on customer philosophy, integrated marketing organization,
adequate marketing information, strategic orientation, and operational
efficiency.
The independent variables of the study include IT competency,
technological learning, knowledge acquisition, technological
complementarity, and technology acceptance. Firstly, IT competency is
defined as the ability to mobilize and deploy IT-based resources in
combination or copresent with other resources and capabilities
(Ussahawanitchakit, 2005a). Three items were used to gauge the degree to
which firms invest IT infrastructure, utilize human IT resources, and
create IT-enabled intangible resources in the organization. Secondly,
technological learning refers to the process by which technology-driven
firms create, renew, and upgrade their latent and enacted capabilities
based on their stock of explicit and tacit resources, namely, structural
capital, intellectual assets and human (Carayannis, 1998). Three items
were implemented to investigate the degree to which firms create, renew,
and upgrade their latent and enacted capabilities within a
technology-driven situation. Thirdly, knowledge acquisition is the
process of interpretation of new information and its assimilation and
accommodation into schemata (Khalifa and Liu, 2008). Four items were
implemented to assess the degree to which firms assimilate the
incorporation of new information into an already existing schema, and
accommodate the medication of an existing schema to fit in new
information. Fourthly, technology complementarity is a unique and
symmetric strategic combination of firm roles, goals, readiness for the
implementation and use of technology across units and firms (Richey et
al., 2007). Three items were adapted to evaluate the degree to which
firms are able to combine firm roles, goals, and readiness for the
implementation and use technology across units and firms. Lastly,
technology acceptance refers to the ability to accept new technology
within specific circumstances (Greenfield and Rohde, 2009). Three items
were utilized to measure the degree to which firms perceive internal
beliefs, attitudes, and behavioral intentions of using technology.
In this study, firm size, firm age, and firm capital are control
variables. Firm size may affect the ability to learn and diversify
operations, and to survive in the markets (Arora and Fosfuri, 2000). It
was measured by the number of employees in a firm. Firm age may
influence a firm's technological learning capacity, business
activities, and the profitability of operations (Zahra, Ireland and
Hitt, 2000). It was measured by the number of years a firm has been in
existence. Also, firm capital may impact the capacity of a firm to
implement business strategies in order to achieve superior performance
(Ussahawanitchakit, 2005b). It was measured by the amount of money a
firm has invested in the business.
3.3 Method
Factor analysis was firstly utilized to examine, measure,
investigate, and assess the underlying relationships of a large number
of items and to determine whether they can be reduced to a smaller set
of factors. The factor analyses conducted were done separately on each
set of the items representing a particular scale due to limited
observations. With respect to the confirmatory factor analysis, this
analysis has a high potential to inflate the component loadings. Thus, a
higher rule-of-thumb, a cut-off value of 0.40, was adopted (Nunnally and
Bernstein, 1994). All factor loadings are greater than the 0.40 cut-off
and are statistically significant. The reliability of the measurements
was secondly evaluated by Cronbach alpha coefficients. In the scale
reliability, Cronbach alpha coefficients are greater than 0.70 (Nunnally
and Bernstein, 1994). The scales of all measures appear to produce
internally consistent results; thus, these measures are deemed
appropriate for further analysis because they express an accepted
validity and reliability in this study. Table 1 presents the results for
both factor loadings and Cronbach alpha for multiple-item scales used in
this study.
The ordinary least squares (OLS) regression analysis is used to
test and examine the hypothesized relationships and estimate factors
affecting an e-commerce firm's marketing effectiveness. Because all
dependent variable, independent variables, and control variables in this
study were neither nominal data nor categorical data, OLS is an
appropriate method for examining the hypothesized relationships (Aulakh,
Kotabe and Teegen, 2000). With the need to understand the relationships
in this study, the research model of the aforementioned relationships is
as follows.
Equation 1: Marketing effectiveness = [[beta].sub.01] +
[[beta].sub.1]firm size + [[beta].sub.2]firm age + [[beta].sub.3]firm
capital + [epsilon]
Equation 2: [MATHEMATICAL EXPRESSION NOT REPRODUCIBLE IN ASCII]
Equation 3: [MATHEMATICAL EXPRESSION NOT REPRODUCIBLE IN ASCII]
Equation 4: [MATHEMATICAL EXPRESSION NOT REPRODUCIBLE IN ASCII]
Equation 5: [MATHEMATICAL EXPRESSION NOT REPRODUCIBLE IN ASCII]
4. RESULTS AND DISCUSSION
Table 2 shows the descriptive statistics and correlation matrix for
all variables. With respect to potential problems relating to
multicollinearity, variance inflation factors (VIF) were used to provide
information on the extent to which non-orthogonality among independent
variables inflates standard errors. The VIFs range from 1.37 to 7.51,
well below the cut-off value of 10 recommended by Neter, Wasserman and
Kutner (1985), meaning that the independent variables are not correlated
with each other. Therefore, there are no substantial multicollinearity
problems encountered in this study.
Table 3 shows the results of OLS regression analysis of the
relationships among IT competency, technological learning, knowledge
acquisition, technological complementarity, technology acceptance, and
marketing effectiveness. IT competency has a significant positive
association with marketing effectiveness ([b.sub.4] = 0.30, p < 0.01;
[b.sub.20] = 0.27, p < 0.01). According to the literature, IT
competency is the abilities of firms to clearly understand and valuably
implement the antecedents and consequences of informational technology
in order to create their efficiency and effectiveness and build
organizational success in business operations. It effectively allows
firms to achieve a competitive advantage and enhance business
performance, profitability, growth, and sustainability (Croteau and
Raymond, 2004). Hence, IT competency has become a key driver of
enhancing business strategies through marketing effectiveness that
distinctively affects competitive advantage and firm performance. Then,
it is positively related to marketing effectiveness. Thus, Hypothesis 1
is supported.
Technological learning has an important positive effect on
marketing effectiveness ([b.sub.5] = 0.25, p < 0.01; [b.sub.11] =
0.17, p < 0.06; [b.sub.21] = 0.24, p < 0.01). Here, technological
learning is the development of new or novel technological knowledge that
is organizationally accessible for creative problem solving through a
form of organizational learning (Kazanjian et al., 2000). It
outstandingly helps firms create knowledge and learn within the
organizations through the design of new products and services. It is a
process by which firms acquire external technology and accumulate
technology capability to improve their competitive advantage and achieve
business performance (Xie, 2004), and generate and manage strengthened
technical changes and technology capabilities. Hence, technological
learning becomes a firm's ability to make effective use of
technological knowledge in gaining marketing effectiveness and achieving
business profitability. Then, a greater technological learning is
positively related to impact more successful marketing effectiveness.
Thus, Hypothesis 2 is supported.
Knowledge acquisition has a direct positive impact on marketing
effectiveness ([b.sub.6] = 0.22, p < 0.01; [b.sub.12] = 0.21, p <
0.02; [b.sub.22] = 0.17, p < 0.08; [b.sub.32] = 0.17, p < 0.10).
With the literature of knowledge acquisition, knowledge acquisition is
the process of interpretation of new information and its assimilation
and accommodation into schemata (Khalifa and Liu, 2008). It consists of
assimilation: the incorporation of new information into an already
existing schema, and accommodation: the medication of an existing schema
to fit in new information. It is likely to help firms involve knowledge
assessment, knowledge sharing and knowledge assimilation through
transferring and learning knowledge in order to gaining their
performance and sustainability. Hence, knowledge acquisition enhances
firms' marketing effectiveness to build their performance and
sustainability. Then, it has a positive relationship with marketing
effectiveness. Thus, hypothesis 3 is supported.
Technological complementarity has a positive influence on marketing
effectiveness ([b.sub.13] = 0.26, p < 0.03; [b.sub.33] = 0.23, p <
0.04). It is a unique and symmetric strategic combination of firm roles,
goals, and readiness for the implementation and use of technology across
units and firms (Richey et al., 2007). It is central to effective
management that supports firms to work together and complement one
another. Firms with higher technological complementarity tend to
successfully create valuable business strategies, effectively achieve
integration, potentially increase market power, and explicitly gain
performance and other advantages. Hence, technological complementarity
has a positive impact on synergistic performance. Then, it becomes an
important factor that influences firms' marketing effectiveness.
For a moderating influence of the relationships, technological
complementarity does not moderate the aforementioned relationships.
Thus, hypothesis 4 is supported, but hypotheses 5a-5c are not.
Lastly, technology acceptance has no relationship with marketing
effectiveness ([b.sub.23] = 0.12, p < 0.13; [b.sub.34] = 0.11, p <
0.19). In this study, technology acceptance is the ability to accept new
technology within specific circumstances (Greenfield and Rohde, 2009).
It effectively determines a user's intention and attitude to use
technology. It consists of perceived usefulness and perceived ease of
use. Perceived usefulness refers to the degree to which an individual
considers that employment of a specific system can improve his or her
job performance at work.
Perceived ease of use is defined as the degree to which an
individual pays the attention to the additional effort required to apply
a specific technology (Hernandez et al., 2009). Hence, technology
acceptance potentially enhances them to clearly understand business
environments and usefully apply marketing strategies. Then, technology
acceptance has a positive influence on marketing effectiveness.
Surprisingly, technology acceptance does not affect marketing
effectiveness. This may due to the fact that marketing effectiveness may
only focus on IT competency, technological learning, knowledge
acquisition, and technological complementarity. These factors already
cover the acceptance of technology. For a moderating effect of the
relationships, technology acceptance does not moderate the
aforementioned relationships. Thus, hypotheses 6 and 7a-7c are not
supported.
5. CONTRIBUTIONS AND FUTURE DIRECTIONS FOR RESEARCH
5.1 Theoretical Contributions and Future Directions for Research
This study is intended to provide a clearer understanding of IT
competency, technological learning, knowledge acquisition, and
technological complementarity that has an important positive influence
on marketing effectiveness. The study provides unique theoretical
contributions expanding on previous knowledge and literature of IT
competency, technological learning, knowledge acquisition, and
technological complementarity, and marketing effectiveness. For
advancing the field theoretically, this study is one of the first known
studies to directly link IT competency, technological learning,
knowledge acquisition, and technological complementarity to marketing
effectiveness in the E-Commerce businesses of Thailand. With the results
of the study, the need for further research is apparent. Because only
technology acceptance does not play any significant role in becoming the
antecedent and moderator of the relationships, future research is needed
to review more literature of the technology acceptance-marketing
effectiveness relationships and the role of technology acceptance as a
moderator. To potentially increase more reliability, benefits,
advantages and contributions of the study, future research is also
needed to collect data from a larger population and/or a comparative
population.
5.2 Managerial Contributions
For the managerial contributions of the study, this study helps
managers and executives clearly identify and justify key components that
are more critical in a rigorously competitive market. These components
include IT competency, technological learning, knowledge acquisition,
and technological complementarity. They explicitly enhance firms'
implementing marketing effectiveness that can directly link to superior
competitive advantage and more firm performance. Then, managers need to
focus on IT competency, technological learning, knowledge acquisition,
and technological complementarity and put more emphasis on them to gain
successful implementation of marketing effectiveness in order to enhance
competitive advantage, profitability and sustainability. To maximize the
benefits, advantages and contributions of IT competency, technological
learning, knowledge acquisition, and technological complementarity,
managers must also resort to other resources to support their
operational efficiency and effectiveness, and create an increase new
opportunities in the cyber markets.
6. CONCLUSION
Recently, electronic commerce (E-Commerce) has become an important
business in Thailand. Researchers and managers have attempted to
understand and utilize E-Commerce in order to expand their knowledge and
achieve their competitive advantage and performance. Then, the objective
of this study is to examine the effects of IT competency, technological
learning, knowledge acquisition, technological complementarity, and
technology acceptance on marketing effectiveness of E-Commerce
businesses in Thailand. Both technological complementarity and
technology acceptance are also hypothesized to become moderators of
these relationships. The results show that IT competency, technological
learning, knowledge acquisition, and technological complementarity have
a significant positive impact on marketing effectiveness, but technology
acceptance has no relationship with marketing effectiveness.
Nonetheless, technological complementarity and technology acceptance are
not moderators of the aforementioned relationships. Accordingly, more
literature of the technology acceptance-marketing effectiveness
relationships and the role of technology acceptance as a moderator are
needed to be covered in future research. To effectively increase more
reliability, benefits, advantages and contributions of the study, data
collection from a larger population and/or a comparative population is
recommended.
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Phapruke Ussahawanitchakit, Mahasarakham University, Thailand
Phaithun Intakhan, Lampang Rajabhat University, Thailand
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TABLE 1
RESULTS OF MEASURE VALIDATION
Items Factor Loadings Cronbach Alpha
Marketing effectiveness (ME) .77-.88 0.91
IT competency (IT) .86-.88 0.84
Technological learning (TL) .87-.91 0.86
Knowledge acquisition (KA) .87-.92 0.92
Technological complementarity (TC)) .90-.92 0.90
Technology acceptance (TA) .84-.92 0.85
TABLE 2
DESCRIPTIVE STATISTICS AND CORRELATION MATRIX
Variables ME IT TL
Mean 3.88 4.14 4.09
Standard deviation 0.73 0.67 0.67
Marketing effectiveness (ME)
IT competency (IT) 0.65 ***
Technological learning (TL) 0.64 *** 0.70 ***
Knowledge acquisition (KA) 0.64 *** 0.72 *** 0.73 ***
Technological complementarity (TC) 0.69 *** 0.82 *** 0.78 ***
Technology acceptance (TA) 0.57 *** 0.67 *** 0.63 ***
Firm age (FA) 0.21 *** 0.15 ** 0.10
Firm size (FS) 0.09 0.07 0.04
Firm capital (FC) 0.01 0.07 0.01
Variables KA TC TA
Mean 4.15 3.98 4.32
Standard deviation 0.66 0.75 0.58
Marketing effectiveness (ME)
IT competency (IT)
Technological learning (TL)
Knowledge acquisition (KA)
Technological complementarity (TC) 0.74 ***
Technology acceptance (TA) 0.75 *** 0.67 ***
Firm age (FA) 0.13 0.19 *** 0.09
Firm size (FS) 0.12 0.16 ** 0.07
Firm capital (FC) 0.05 0.12 0.10
Variables FA FS FC
Mean 12.20 43.75 31.40
Standard deviation 5.70 28.25 21.40
Marketing effectiveness (ME)
IT competency (IT)
Technological learning (TL)
Knowledge acquisition (KA)
Technological complementarity (TC)
Technology acceptance (TA)
Firm age (FA)
Firm size (FS) 0.51 ***
Firm capital (FC) 0.41 *** 0.69 ***
** p<.05, *** p<.01
TABLE 3
RESULTS OF OLS REGRESSION ANALYSIS (a)
Independent Dependent Variable
Variables
ME ME ME ME ME
IT 0.30 *** 0.13 0.27 *** 0.13
(0.08) (0.10) (0.08) (0.10)
TL 0.25 *** 0.17 * 0.24 *** 0.15
(0.08) (0.09) (0.08) (0.09)
KA 0.22 *** 0.21 ** 0.17 * 0.17 *
(0.08) (0.09) (0.09) (0.10)
TC 0.26 ** 0.23 **
(0.11) (0.11)
TA 0.12 0.11
(0.08) (0.09)
IT*TC -0.10 -0.11
(0.07) (0.09)
TL*TC -0.01 -0.07
(0.08) (0.10)
KA*TC 0.09 0.12
(0.09) (0.11)
IT*TA -0.06 0.01
(0.08) (0.11)
TL*TA 0.11 0.14
(0.90) (0.10)
KA*TA -0.03 -0.10
(0.09) (0.11)
FA 0.23 *** 0.13 ** 0.15 * 0.14 * 0.17 *
(0.07) (0.05) (0.05) (0.05) (0.05)
FS 0.07 0.04 0.03 0.06 0.04
(0.09) (0.07) (0.07) (0.07) (0.07)
FC -0.13 -0.11 -0.12 -0.13 * -0.17 *
Adj [R.sup.2] (0.09) (0.07) (0.07) (0.07) (0.07)
0.04 0.51 0.52 0.51 0.52
* p<.10, ** p<.05, *** p<.01,
(a) Beta coefficients with standard errors in parenthesis