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Marketing effectiveness and the antecedents: evidence from e-commerce businesses in Thailand.
Abstract:
This study aims to test the effects of IT competency, technological learning, knowledge acquisition, technological complementarity, and technology acceptance on marketing effectiveness of E-Commerce businesses in Thailand. Also, both technological complementarity and technology acceptance are hypothesized to become moderators of these relationships. The results indicate that IT competency, technological learning, knowledge acquisition, and technological complementarity have a significant positive impact on marketing effectiveness. However, technological complementarity and technology acceptance are not moderators of the aforementioned relationships. Surprisingly, technology acceptance does not play an important determinant of explaining firms' marketing effectiveness. Giving potential discussion is efficiently implemented in the study. Theoretical and managerial contributions are explicitly provided. Conclusion and suggestions and directions of the future research are described.

Keywords: E-Commerce, IT Competency, Technological Learning, Knowledge Acquisition, Technological Complementarity, Technology Acceptance, Marketing Effectiveness

Article Type:
Report
Subject:
Electronic commerce (Evaluation)
Advertising (Evaluation)
Advertising (Analysis)
Authors:
Ussahawanitchakit, Phapruke
Intakhan, Phaithun
Pub Date:
05/01/2011
Publication:
Name: Journal of International Business and Economics Publisher: International Academy of Business and Economics Audience: Academic Format: Magazine/Journal Subject: Business, international; Computers Copyright: COPYRIGHT 2011 International Academy of Business and Economics ISSN: 1544-8037
Issue:
Date: May, 2011 Source Volume: 11 Source Issue: 2
Topic:
Computer Subject: Electronic commerce
Geographic:
Geographic Scope: Thailand Geographic Code: 9THAI Thailand
Accession Number:
272616511
Full Text:
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

Dr. Phapruke Ussahawanitchakit earned his Ph.D. at Washington State University, USA in 2002. Currently he is an associate professor of accounting and a dean of Mahasarakham Business School, Mahasarakham University, Thailand.

Dr. Phaithun Intakhan earned his Ph.D. at Mahasarakham University, Thailand in 2009. Currently he is a lecturer of accounting at the Faculty of Management Science, Lampang Rajabhat University, Thailand.
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
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