• Journal of Digital Convergence
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• v.10 no.11
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• pp.403-418
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• 2012

In this paper, we attempted to theorize the synergy effect between the value creating attributes for digital convergence model in the service industry. Our investigation is based upon contingency fit theory to understand the strategic fit for the two inherent value attributes of fixed and mobile value, as well as resolving fundamental limitations of service processes. Empirical validation of the derived research model is analyzed using hierarchical regression method. The results indicate that the relative advantage of each value creating attributes are strongly associated with the characteristics of domain service industries, and compatibility is critical to user adoption of convergent service model. Moreover, the less significant statistical impact of the synergy between mobile and fixed value attributes and others implies that each value attribute uniquely contributes to particular IT convergence model, which thereby offers critical insight that focusing the convergent value in conjunction with specific application domain is the most appealing managerial focus. The findings provide useful insight for the further research in IT based industry convergent business model areas.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.19 no.3
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• pp.53-68
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• 2024

Generative AI is receiving a lot of attention around the world, and ways to effectively utilize it in the business environment are being explored. In particular, since the public release of the ChatGPT service, which applies the GPT-3.5 model, a large language model developed by OpenAI, it has attracted more attention and has had a significant impact on the entire industry. This study focuses on the emergence of Generative AI, especially ChatGPT, which applies OpenAI's GPT-3.5 model, to investigate its impact on the startup industry and compare the changes that occurred before and after its emergence. This study aims to shed light on the actual application and impact of generative AI in the business environment by examining in detail how generative AI is being used in the startup industry and analyzing the impact of ChatGPT's emergence on the industry. To this end, we collected company information of generative AI-related startups that appeared before and after the ChatGPT announcement and analyzed changes in industry, business content, and investment information. Through keyword analysis, topic modeling, and network analysis, we identified trends in the startup industry and how the introduction of generative AI has revolutionized the startup industry. As a result of the study, we found that the number of startups related to Generative AI has increased since the emergence of ChatGPT, and in particular, the total and average amount of funding for Generative AI-related startups has increased significantly. We also found that various industries are attempting to apply Generative AI technology, and the development of services and products such as enterprise applications and SaaS using Generative AI has been actively promoted, influencing the emergence of new business models. The findings of this study confirm the impact of Generative AI on the startup industry and contribute to our understanding of how the emergence of this innovative new technology can change the business ecosystem.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.16 no.1
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• pp.55-69
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• 2021

For the national economic development, the participation of women in the social and economic activities is crucial. The popularization of start-ups, digital transformation, and WEconomy trends have lowered the barriers to opportunities for women to start a business and provide an environment in which women can grow faster. This paper examines the significance and process of success of women entrepreneurs and the characteristics of innovation strategies and achievements by linking the recently changing business environment of a company, factors influencing the success of women entrepreneurship, and innovation activities. To this end, four companies' cases were analyzed in the fields of distribution/service and consumer products/services, which are areas of large investment among female startups. The result shows that women entrepreneurs recognize the meaning of success as creating and continuing to create a 'corporate value through establishing a trust relationship with customers' within the 'balance between personal life and work.' In terms of the business ecosystem, women entrepreneurs strive for 'business activities based on the win-win growth of consumers, producers and sellers' for success, and rather 'focus on the process with a problem-solving approach' rather than achieving performance-oriented goals. Also through excellent power of observation, flexibility, and execution power, women entrepreneurs conduct business by adapting to changing trends. In terms of innovation activities, the innovation strategy of women-led companies puts priority on 'creating the value customers want' and focuses on innovation in the 'customer-centric business model' rather than technological innovation. As such, women-led companies show several differentiated characteristics, which enable them to create corporate value and achieve sustainable growth. The barriers to challenges and opportunities for women to start a business have been lowered, and an ecosystem has been created for female startups to grow. But why are there still so few women entrepreneurs, and the answer to where we need to close these gaps is ultimately a close analysis and investigation of the field. We must present milestones for growth steps through the accumulation of case studies of women startups that have exited. In addition, women can stand as economic agents only when the policy targets are subdivided and specific approaches to child-rearing and childcare for women entrepreneurs must be taken. This paper expects to serve as basic data for follow-up studies and become the basis of research for women entrepreneurs to grow as economic agents.

• Management & Information Systems Review
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• v.39 no.1
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• pp.93-114
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• 2020

Platform is considered as an alternative strategy to the traditional linear pipeline based business. Moreover, in the 4th industrial revolution period, efficiency driven pipeline business model needs to be changed to platform business. We have such success stories about platform as Apple, Google, Amazon, Uber, and so on. However, for those smaller corporations, it is not easy to find out the transformation strategy. The essence of platform business is to leverage network effect in management. Thus platform based management can be rephrased as network management across the business functions. Research on platform business is popular and related to diverse facets. But few scholars cover what the research trend of the domain is. The main purpose of this paper is to identify the research trend on platform business in Korea. To do that we first propose the analytical model for platform architecture whose components are consumers, suppliers, artifacts, and IT platform system. We conjecture that mapping of the research work on platform to the components of the model will make us understand the hidden domain of platform research. We propose three hypotheses regarding the characteristics of research and one proposition for the transitional path from pipeline to platform business model. The mapping is based on the research articles filtered from the Korea Citation Index, using keyword search. Research papers are searched through the keywords provided by authors using the word of "platform". The filtered articles are summarized in terms of the attributes such as major component of platform considered, platform type, main purpose of the research, and research method. Using the filtered data, we test the hypotheses in exploratory ways. The contribution of our research is as follows: First, based on the findings, scholars can find the areas of research on the domain: areas where research has been matured and territory where future research is actively sought. Second, the proposition provided can give business practitioners the guideline for changing their strategy from pipeline to platform oriented. This research needs to be considered as exploratory not inferential since subjective judgments are involved in data collection, classification, and interpretation of research articles.

• The Journal of the Korea Contents Association
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• v.17 no.7
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• pp.1-11
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• 2017

The best business strategy leading to innovation and productivity can be achieved by carefully analyzing internal and external environments of a company. Many companies often require, but difficult to find a tool to determine their own internal/external environmental factors including strengths, weaknesses, opportunities and threats(SWOT). SWOT is one analytical base model that is utilized in this research to design semi-automated environmental analysis process. This study investigates on SWOT generation system that is built on existing analysis database created by experts in each field. Companies can search and choose their best expressing environmental elements that are stored in the database. This semi-automated SWOT tool is expected to contribute that companies can recognize their internal capabilities more accurately, and help consider external environment changes around them.

• The Journal of Information Technology
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• v.5 no.1
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• pp.157-171
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• 2002

The evolution of transaction-based business model is upon us. The business models of many e-Marketplace in their early stages have typically been based on transaction fees. Many e-Marketplaces have even called out transaction revenues as a core element of their business plans. The transaction business represents the most simple of business models, but it does not provide a long-term sustain able advantage. For buyer's convenience, wide selection and test price hold appeal. For suppliers, the extended global market reach and direct access to customers and consortiums of customers is powerful. To maxmize leverage of these new e-marketplace, you must from both a buyer perspective as well as a supplier perspective. Also required is a strategy that takes in account all of the various e-Marketplace transaction standards and one that allows the easy accomodation to new e-marketplace as the market change. These new e-marketplace will need to be factored into the sales channel strategies. To be successful, integration with these e-marketplaces should occur at a complete business process level. This study explored independent and industry-backed current and future business models that are emerging in the B2B electronic market industry, as well as value -added service models for the Net market maker industry. E-Marketplaces will evolve into digital work environments in which real industry collaboration can occur.

• The Journal of Information Technology
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• v.7 no.1
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• pp.23-41
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• 2004

It is estimated that electronic commerce facilitates international trade and lower transaction cost and help firms make the best of the opportunities of market access. The comprehensive programs had been implemented to provide better electronic commerce environments by international organizations such as OECD, UNCITRAL, APEC, ICC and etc. Especially, WTO plays the most important role to implement efficient forms and rules on electronic commerce after Doha Ministerial Conference. Member countries recognize the need to conduct the electronic commerce in compliance with the principles and rules of WTO. However, there are many issues to be solved such as the clarifications of concepts and definitions, the possibility of adaptation of technological neutrality in GATS, the imposition of taxation in electronic commerce transactions and the methods of protecting copying as well as trademark. The Implementation of concrete forms and rules of electronic commerce in the WTO will be influential to international trade as the member countries have to adapt them in their transactions. Considering that further discussion will be continued in GATS, we need to analyze the problems and strategies for electronic commerce. As there are not concrete international laws for e-commerce, the existing laws must be revised and changed and each country need to present the enactment direction of e-commerce law to streamline e-commerce and to prevent trading partners from conflicting due to legal problems.

• Journal of Fashion Business
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• v.19 no.2
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• pp.69-84
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• 2015

The objective of this study is to investigate the intention to adopt smart wear, based on extended UTAUT model. We examined the effects of performance expectancy (PE), effort expectancy (EE), hedonic motivation (HE), social influence (SI), facilitating conditions (FC), and price value (PV) on the intended adoption of smart watch and smart shoes, respectively. In addition, moderating effects of gender, age, and innovation resistance were examined. An online survey was conducted, comprised of 2030 consumers who were aware of smart watch or smart shoes. In total, 393 responses were analyzed. About 50.4% were male, and 44.8% were in their 20's. An exploratory factor analysis generated five factors - PE & HM, EE, SI, FC, and PV- which were employed as independent variables in the multiple regression models. PE & HM, PV, and SI influenced on the intention to use both smart devices. FC showed the significant effect only on the intention to adopt the smart watch. In terms of gender differences, SI and PV were the important predictors of the intention to adopt the smart watch in the female group only. With respect to age difference, SI was very effective in explaining the intention of individuals in their 30's to adopt smart wear. Among the low innovation resistance group, SI was significant predictor, while PE & HE and PV were significant among the high resistance group. The findings provide useful information about the possibility of the adoption of smart wear, and new insight into market segmentation.

• Industry Promotion Research
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• v.8 no.3
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• pp.201-210
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• 2023

This study is based on data ecology theory and takes Chinese local governments' open public data as the research object. Data asset value assessment methods are compared from a new perspective of data business operations. The results show that the assessment model constructed using the hierarchical analysis method (AHP) can more objectively reflect the commercial value of government open data assets than the traditional cost, revenue and market methods, has the advantage of a comprehensive assessment of data value index, and better reflects the findings of a comprehensive index of regional data value. The data show that the local government data value assessment index is positively proportional to the region's digital economy development index, highlighting the driving effect on the digital economy. The results of the study provide a good help for the identification of local government data value rights. The research and practice of promoting the construction of data innovation and data business operation models, improving social well-being and promoting the rapid development of the digital economy to achieve data realisation provides a good reference.

• Advanced Industrial SCIence
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• v.3 no.2
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• pp.17-22
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• 2024

Recently, as the ICT field has been used in various environments, it has become possible to analyze pests by crops, use robots when harvesting crops, and predict by big data by utilizing ICT technologies in a sustainable agricultural environment. However, in a sustainable agricultural environment, efforts to solve resource depletion, agricultural population decline, poverty increase, and environmental destruction are constantly being demanded. This paper proposes an artificial intelligence-based big data processing analysis method to reduce the production cost and increase the efficiency of crops based on a sustainable agricultural environment. The proposed technique strengthens the security and reliability of data by processing big data of crops combined with AI, and enables better decision-making and business value extraction. It can lead to innovative changes in various industries and fields and promote the development of data-oriented business models. During the experiment, the proposed technique gave an accurate answer to only a small amount of data, and at a farm site where it is difficult to tag the correct answer one by one, the performance similar to that of learning with a large amount of correct answer data (with an error rate within 0.05) was found.