• Journal of Intelligence and Information Systems
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• v.16 no.4
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• pp.43-65
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• 2010

Facing a complex environment driven by a decade, many companies are adopting new strategic frameworks such as Customer Relationship Management system to achieve sustainable profitability as well as overcome serious competition for survival. In many business areas, CRM system advanced a great deal in a matter of continuous compensating the defect and overall integration. However, pharmaceutical companies in Korea were slow to accept them for usesince they still have a tendency of holding fast to traditional way of sales and marketing based on individual networks of sales representatives. In the circumstance, this article tried to empirically address current status of CRM system as well as the effects of the system on the performance of pharmaceutical companies by applying BSC method's four perspectives, from financial, customer, learning and growth and internal process. Survey by e-mail and post to employers and employees who were working in pharma firms were undergone for the purpose. Total 113 cases among collected 140 ones were used for the statistical analysis by SPSS ver. 15 package. Reliability, Factor analysis, regression were done. This study revealed that CRM system had a significant effect on improving financial and non-financial performance of pharmaceutical companies as expected. Proposed regression model fits well and among them, CRM marketing information system shed the light on substantial impact on companies' outcome given profitability, growth and investment. Useful analytical information by CRM marketing information system appears to enable pharmaceutical firms to set up effective marketing and sales strategies, these result in favorable financial performance by enhancing values for stakeholderseventually, not to mention short-term profit and/or mid-term potential to growth. CRM system depicted its influence on not only financial performance, but also non-financial fruit of pharmaceutical companies. Further analysis for each component showed that CRM marketing information system were able to demonstrate statistically significant effect on the performance like the result of financial outcome. CRM system is believed to provide the companies with efficient way of customers managing by valuable standardized business process prompt coping with specific customers' needs. It consequently induces customer satisfaction and retentionto improve performance for long period. That is, there is a virtuous circle for creating value as the cornerstone for sustainable growth. However, the research failed to put forward to evidence to support hypothesis regarding favorable influence of CRM sales representative's records assessment system and CRM customer analysis system on the management performance. The analysis is regarded to reflect the lack of understanding of sales people and respondents between actual work duties and far-sighted goal in strategic analysis framework. Ordinary salesmen seem to dedicate short-term goal for the purpose of meeting sales target, receiving incentive bonus in a manner-of-fact style, as such, they tend to avail themselves of personal network and sales and promotional expense rather than CRM system. The study finding proposed a link between CRM information system and performance. It empirically indicated that pharmaceutical companies had been implementing CRM system as an effective strategic business framework in order for more balanced achievements based on the grounded understanding of both CRM system and integrated performance. It suggests a positive impact of supportive CRM system on firm performance, especially for pharmaceutical industry through the initial empirical evidence. Also, it brings out unmet needs for more practical system design, improvement of employees' awareness, increase of system utilization in the field. On the basis of the insight from this exploratory study, confirmatory research by more appropriate measurement tool and increased sample size should be further examined.

• 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 Industrial Distribution & Business
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• v.3 no.1
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• pp.7-16
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• 2012

Despite the enforcement of SSM control laws such as 'the Law of Developing the Distribution Industry (LDDI)' and 'the Law of Promoting Mutual Cooperation between Large and Small/medium Enterprises (LPMC)' stipulating the business adjustment system, the number of super-supermarkets (SSMs) has ever been expanding in Korea. In France, however, Super Centers are being regulated most strongly and directly in the whole Europe viewing that there is not a single SSM in Paris, which is emphasized to be the outcome from French government's regulation exerted on the opening of large scale retail stores. In France, the authority to approve store opening is deeply centralized and the store opening regulation is a socio-economic regulation driven by economic laws whereas EU strongly regulates the distribution industry. To control the French distribution industry, such seven laws and regulations as Commission départementale d'urbanisme commercial guidelines (CDLIC) (1969), the Royer Law (1973), the Doubin Law (1990), the Sapin Law (1993), the Raffarin Law (1996), solidarite et renouvellement urbains (SRU) (2000), and Loi de modernisation de l'économie (LME) (2009) have been promulgated one by one since the amendment of the Fontanet guidelines, through which commercial adjustment laws and regulations have been complemented and reinforced while regulatory measures have been taken. Even in the course of forming such strong regulatory laws, InterMarche, the largest supermarket chain in France, has been in existence as a global enterprise specialized in retail distribution with over 4,000 stores in Europe. InterMarche's business can be divided largely into two segments of food and non-food. As a supermarket chain, InterMarche's food segment has 2,300 stores in Europe and as a hard-discounter store chain in France, Netto has 420 stores. Restaumarch is a chain of traditional family restaurants and the steak house restaurant chain of Poivre Rouge has 4 restaurants currently. In addition, there are others like Ecomarche which is a supermarket chain for small and medium cities. In the non-food segment, the DIY and gardening chain of Bricomarche has a total of 620 stores in Europe. And the car-related chain of Roady has a total of 158 stores in Europe. There is the clothing chain of Veti as well. In view of InterMarche's management strategies, since its distribution strategy is to sell goods at cheap prices, buying goods cheap only is not enough. In other words, in order to sell goods cheap, it is all important to buy goods cheap, manage them cheap, systemize them cheap, and transport them cheap. In quality assurance, InterMarche has guaranteed the purchase safety for consumers by providing its own private brand products. InterMarche has 90 private brands of its own, thus being the retailer with the largest number of distributor brands in France. In view of its IT service strategy, InterMarche is utilizing a high performance IT system so as to obtainas much of the market information as possible and also to find out the best locations for opening stores. In its global expansion strategy of international alliance, InterMarche has established the ALDIS group together with the distribution enterprises of both Spain and Germany in order to expand its food purchase, whereas in the non-food segment, it has established the ARENA group in alliance with 11 international distribution enterprises. Such strategies of InterMarche have been intended to find out the consumer needs for both price and quality of goods and to secure the purchase and supply networks which are closely localized. It is necessary to cope promptly with the constantly changing circumstances through being unified with relevant regions and by providing diversified customer services as well. In view of the InterMarche's positive policy for promoting local partnerships as well as the assistance for enhancing the local economic structure, implications are existing for those retail distributors of our country.

• Geophysics and Geophysical Exploration
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• v.9 no.1
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• pp.67-72
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• 2006

Injection of $CO_2$ into underground saline formations, due to their large storage capacity, is probably the most promising approach for the reduction of $CO_2$ emissions into the atmosphere. $CO_2$ storage must be carefully planned and monitored to ensure that the $CO_2$ is safely retained in the formation for periods of at least thousands of years. Seismic methods, particularly for offshore reservoirs, are the primary tool for monitoring the injection process and distribution of $CO_2$ in the reservoir over time provided that reservoir properties are favourable. Seismic methods are equally essential for the characterisation of a potential trap, determining the reservoir properties, and estimating its capacity. Hence, an assessment of the change in seismic response to $CO_2$ storage needs to be carried out at a very early stage. This must be revisited at later stages, to assess potential changes in seismic response arising from changes in fluid properties or mineral composition that may arise from chemical interactions between the host rock and the $CO_2$. Thus, carefully structured modelling of the seismic response changes caused by injection of $CO_2$ into a reservoir over time helps in the design of a long-term monitoring program. For that purpose we have developed a Graphical User Interface (GUI) driven rock physics simulator, designed to model both short and long-term 4D seismic responses to injected $CO_2$. The application incorporates $CO_2$ phase changes, local pressure and temperature changes. chemical reactions and mineral precipitation. By incorporating anisotropic Gassmann equations into the simulator, the seismic response of faults and fractures reactivated by $CO_2$ can also be predicted. We show field examples (potential $CO_2$ sequestration sites offshore and onshore) where we have tested our rock physics simulator. 4D seismic responses are modelled to help design the monitoring program.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.8 no.3
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• pp.113-124
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• 2013

The government strives to create venture ecosystem for realizing creative economy, at the same time, the Mistry of Education is spending huge resources and efforts to spread entrepreneurship education to universities in Korea. Since entrepreneurship education gives motivation to individuals and creates market innovation and these connect to the growth of national economy through increased efficiency, entrepreneurship education is becoming increasingly more important for realizing creative economy. Based on the importance, entrepreneurship education in the universities is now spreading rapidly. However, college students' entrepreneurial intention has still not been improved comparing to spreading entrepreneurship education. To overcome the poor improvement, entrepreneurship education needs to be driven more systematic direction through the study on the effect of students' motivation and environment. In this study, entrepreneurship as a part of careers perspectives, is analyzed on students' career reasons with entrepreneurial intention. For this study, 918 surveys was collected from 7 universities having entrepreneurship courses in Seoul and Gyeonggi regions in 2012 and analyzed 858 surveys in order to prove the hypothesis. The results disclosed the relationship between students' career reasons and entrepreneurial self-efficacy and intention. Motivation factors of self-realization, innovation and role model have positive effect on entrepreneurial self-efficacy following by increased entrepreneurial intention, unlike the common notion financial success and independence factors are not significant with entrepreneurial intention of students. Based on these results having meaningful implication to Korea entrepreneurship education, this study is expected to have contribution to the successful promoting the creative economy realization of our government.

• Journal of Bio-Environment Control
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• v.30 no.4
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• pp.383-392
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• 2021

It has been known that oyster mushrooms cultivated in facilities with thermal insulation have been strongly affected by inner environments. Forced air-circulation fans exert much direct influence on disturbing air inside the facility so the matter is of particular interest. This study is carried out to investigate the measured levels of air uniformity in a cultivation facility for oyster mushroom in the various cases that reversibly controlled air-circulation fans which drove the flow in the upward and reverse direction by turn and unidirectional fans by which the wind blew upwards only were operated from July 1 to 10. The actual survey for the selection of ongoing operation cases presented that farmers, even though there were some discrepancies, have made use of fans in a way that it paused for 5-30min after running for 5-15min by turn. The level of air uniformity in the case of adopting reversible fans revealed a slight difference of 1.4-1.8℃ (Temp.) and 7.8-8.7% (R.H.) under the condition of not using a cooler during the investigation period. By contrast, unidirectional fans showed a noticeable difference of 3.2-3.7℃ and 14.0-15.4%, which meant that air uniformity driven by reversible fans much more increased compared to that for unidirectional fans. Among the twenty operational applications considered for reversible fans, the circumstance that the wind blew upwards for 10-15min and ceased for 5-10min and blew again in the reverse direction for 10-15min in succession gave minor improvements at the level of air uniformity, but at present there was somewhat difficult to make decision on which cases were optimally best. It seems necessary that the effects of reversible fans on air uniformity as well as qualities of oyster mushrooms have to be appraised in the cultivation period and the flow visualization needs to be done to ascertain the performance of air mixture.

• Journal of Intelligence and Information Systems
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• v.27 no.2
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• pp.1-15
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• 2021

If it is difficult for us to make decisions, we ask for advice from friends or people around us. When we decide to buy products online, we read anonymous reviews and buy them. With the advent of the Data-driven era, IT technology's development is spilling out many data from individuals to objects. Companies or individuals have accumulated, processed, and analyzed such a large amount of data that they can now make decisions or execute directly using data that used to depend on experts. Nowadays, the recommender system plays a vital role in determining the user's preferences to purchase goods and uses a recommender system to induce clicks on web services (Facebook, Amazon, Netflix, Youtube). For example, Youtube's recommender system, which is used by 1 billion people worldwide every month, includes videos that users like, "like" and videos they watched. Recommended system research is deeply linked to practical business. Therefore, many researchers are interested in building better solutions. Recommender systems use the information obtained from their users to generate recommendations because the development of the provided recommender systems requires information on items that are likely to be preferred by the user. We began to trust patterns and rules derived from data rather than empirical intuition through the recommender systems. The capacity and development of data have led machine learning to develop deep learning. However, such recommender systems are not all solutions. Proceeding with the recommender systems, there should be no scarcity in all data and a sufficient amount. Also, it requires detailed information about the individual. The recommender systems work correctly when these conditions operate. The recommender systems become a complex problem for both consumers and sellers when the interaction log is insufficient. Because the seller's perspective needs to make recommendations at a personal level to the consumer and receive appropriate recommendations with reliable data from the consumer's perspective. In this paper, to improve the accuracy problem for "appropriate recommendation" to consumers, the recommender systems are proposed in combination with context-based deep learning. This research is to combine user-based data to create hybrid Recommender Systems. The hybrid approach developed is not a collaborative type of Recommender Systems, but a collaborative extension that integrates user data with deep learning. Customer review data were used for the data set. Consumers buy products in online shopping malls and then evaluate product reviews. Rating reviews are based on reviews from buyers who have already purchased, giving users confidence before purchasing the product. However, the recommendation system mainly uses scores or ratings rather than reviews to suggest items purchased by many users. In fact, consumer reviews include product opinions and user sentiment that will be spent on evaluation. By incorporating these parts into the study, this paper aims to improve the recommendation system. This study is an algorithm used when individuals have difficulty in selecting an item. Consumer reviews and record patterns made it possible to rely on recommendations appropriately. The algorithm implements a recommendation system through collaborative filtering. This study's predictive accuracy is measured by Root Mean Squared Error (RMSE) and Mean Absolute Error (MAE). Netflix is strategically using the referral system in its programs through competitions that reduce RMSE every year, making fair use of predictive accuracy. Research on hybrid recommender systems combining the NLP approach for personalization recommender systems, deep learning base, etc. has been increasing. Among NLP studies, sentiment analysis began to take shape in the mid-2000s as user review data increased. Sentiment analysis is a text classification task based on machine learning. The machine learning-based sentiment analysis has a disadvantage in that it is difficult to identify the review's information expression because it is challenging to consider the text's characteristics. In this study, we propose a deep learning recommender system that utilizes BERT's sentiment analysis by minimizing the disadvantages of machine learning. This study offers a deep learning recommender system that uses BERT's sentiment analysis by reducing the disadvantages of machine learning. The comparison model was performed through a recommender system based on Naive-CF(collaborative filtering), SVD(singular value decomposition)-CF, MF(matrix factorization)-CF, BPR-MF(Bayesian personalized ranking matrix factorization)-CF, LSTM, CNN-LSTM, GRU(Gated Recurrent Units). As a result of the experiment, the recommender system based on BERT was the best.

• Journal of Intelligence and Information Systems
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• v.28 no.3
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• pp.237-258
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• 2022

As the global market environment changes, the domestic ICT industry has a growing influence on the world economy. This industry is regarded as an important driving force in the national economy from a technological and social point of view. In particular, small and medium-sized enterprises (SMEs) in the ICT industry are regarded as essential actors of domestic economic development in terms of company diversity, technology development and job creation. However, since it is small compared to large-sized enterprises, it is difficult for SMEs to survive with a differentiated strategy in an incomplete and rapidly changing environment. Therefore, SMEs must make a lot of efforts to improve their own capabilities, and the government needs to provide the desirable help suitable for corporate internal resources so that they can continue to be competitive. This study classifies the types of ICT SMEs participating in government support programs, and analyzes the relationship between resources and performance creation of each type. The data from the "ICT Small and Medium Enterprises Survey" conducted annually by the Ministry of Science and ICT was used. In the first stage, ICT SMEs were clustered based on common factors according to their experiences with government support programs. Three clusters were meaningfully classified, and each cluster was named "active participation type," "initial support type," and "soloist type." As a second step, this study compared the characteristics of each cluster through profiling analysis for each cluster. The third step carried out in this study was to find out the mechanism of R&D performance creation for each cluster through regression analysis. Different factors affected performance creation for each cluster, and the magnitude of the influence was also different. Specifically, for "active participation type", "current manpower", "technology competitiveness", and "R&D investment in the previous year" were found to be important factors in creating R&D performance. "Initial support type" was identified as "whether or not a dedicated R&D organization exists", "R&D investment amount in the previous year", "Ratio of sales to large companies", and "Ratio of vendors supplied to large companies" contributed to the performance. Lastly, in the case of "soloist type", "current workforce" and "future recruitment plan", "technological competitiveness", "R&D investment", "large company sales ratio", and "overseas sales ratio" showed a significant relationship with the performance. This study has practical implications of showing what strategy should be established when supporting SMEs in the future according to the government's participation in the startup program and providing a guide on what kind of support should be provided.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.18 no.5
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• pp.91-107
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• 2023

Lean startup is a concept that combines the words "lean," meaning an efficient way of running a business, and "startup," meaning a new business. It is often cited as a strategy for minimizing failure in early-stage businesses, especially in software-based startups. By scrutinizing the case of a startup L, this study suggests that lean startup methodology(LSM) can be useful for hardware and manufacturing companies and identifies ways for early startups to successfully implement LSM. To this end, the study explained the core of LSM including the concepts of hypothesis-driven approach, BML feedback loop, minimum viable product(MVP), and pivot. Five criteria to evaluate the successful implementation of LSM were derived from the core concepts and applied to evaluate the case of startup L . The early startup L pivoted its main business model from defecation alert system for patients with limited mobility to one for infants or toddlers, and finally to a smart bottle for infants. In developing the former two products, analyzed from LSM's perspective, company L neither established a specific customer value proposition for its startup idea and nor verified it through MVP experiment, thus failed to create a BML feedback loop. However, through two rounds of pivots, startup L discovered new target customers and customer needs, and was able to establish a successful business model by repeatedly experimenting with MVPs with minimal effort and time. In other words, Company L's case shows that it is essential to go through the customer-market validation stage at the beginning of the business, and that it should be done through an MVP method that does not waste the startup's time and resources. It also shows that it is necessary to abandon and pivot a product or service that customers do not want, even if it is technically superior and functionally complete. Lastly, the study proves that the lean startup methodology is not limited to the software industry, but can also be applied to technology-based hardware industry. The findings of this study can be used as guidelines and methodologies for early-stage companies to minimize failures and to accelerate the process of establishing a business model, scaling up, and going global.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.19 no.2
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• pp.197-214
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• 2024

This study aimed to investigate students' perceptions at science and technology specialized universities towards entrepreneurship support policies and to derive policy improvement measures by applying a bottom-up approach to reflect the requirements of the policy beneficiaries, i.e., the students. Specifically, the research explored effective execution strategies for student entrepreneurship support policies through a survey and analysis of KAIST students. The findings revealed that KAIST students recognize the urgent need for improvement in sharing policy objectives with the student entrepreneurship field, reflecting the opinions of the campus entrepreneurship scene in policy formulation, and constructing an entrepreneurship-friendly academic system for nurturing student entrepreneurs. Additionally, there was a highlighted need for enhancement in the capacity of implementing agencies, as well as in marketing and market development capabilities, and organizational management and practical skills as entrepreneurs within the educational curriculum. Consequently, this study proposes the following improvement measures: First, it calls for enhanced transparency and accessibility of entrepreneurship support policies, ensuring students clearly understand policy objectives and can easily access information. Second, it advocates for student-centered policy development, where students' opinions are actively incorporated to devise customized policies that consider their needs and the actual entrepreneurship environment. Third, there is a demand for improving entrepreneurship-friendly academic systems, encouraging more active participation in entrepreneurship activities by adopting or refining academic policies that recognize entrepreneurship activities as credits or expand entrepreneurship-related courses. Based on these results, it is expected that this research will provide valuable foundational data to actively support student entrepreneurship in science and technology specialized universities, foster an entrepreneurial spirit, and contribute to the creation of an innovation-driven entrepreneurship ecosystem that contributes to technological innovation and social value creation.