• Asia pacific journal of information systems
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• v.34 no.1
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• pp.226-247
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• 2024

Most studies on recommender systems to evaluate recommendation performances focus on offline evaluation methods utilizing past customer transaction records. However, evaluating recommendation performance through real-world stimulation becomes challenging. Moreover, such methods cannot evaluate the duration of the recommendation effect. This study measures the personalized recommendation (stimulus) effect when the product recommendation to customers leads to actual purchases and evaluates the duration of the stimulus personalized recommendation effect leading to purchases. The results revealed a 4.58% improvement in recommendation performance in the online environment compared with that in the offline environment. Furthermore, there is little difference in recommendation performance in offline experiments by period, whereas the recommendation performance declines with time in online experiments.

• Journal of Convergence Society for SMB
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• v.5 no.4
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• pp.11-16
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• 2015

In recent years, small businesses are increasing attempt to create better value through a combination of benefits with small and flexible organization of big data. However, until now small businesses are lacking to secure sustainable competitiveness to match the ICT paradigm alteration to focus on improving productivity. This paper propose an efficient small businesses process model which can effectively take advantage of a low cost, identify customer needs, taget marketing, customer management for new product. Proposed model can retain the necessary competitiveness in generating new business for collaboration between companies inside and companies using a massive big data. Also, proposed model can be utilized the overall business activities such as the target customer selection, pricing strategies, public relations and promotional activities and enhanced new product development capabilities using big data.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.05a
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• pp.204-206
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• 2015

Nowadays, many small businesses have experienced the failure of business or hardship. In this point, specific and integrated information for startup business should be required to decrease the rate of failure and to increase the rate of success. This study is to suggest the integration and big data of various data which various public institutions have separately. For this purpose, it is to classify the data types in constructing big-data for start-up business and to suggest a model of analysis in information system for supporting startup businesses.

• Journal of Industrial Convergence
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• v.17 no.3
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• pp.17-22
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• 2019

As the value of big data is recognized as important, it is possible to advance decision making by effectively introducing and improving the development and utilization of JAVA and R programs that can analyze vast amounts of existing and unstructured data to governments, public institutions and private businesses. In this study, news data was collated and analyzed through text mining techniques in order to establish marketing strategies based on consumers' airline preferences. This research is meaningful in establishing marketing strategies based on analysis results by analyzing consumers' airline preferences using high-level big data utilization program techniques for data that were difficult to obtain in the past.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.8
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• pp.3068-3085
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• 2021

The economics of big data knowledge, especially cloud computing and statistical data of consumer preferences, has attracted increasing academic and industry practitioners' attention. Firms nowadays require purchasing not only external private patent knowledge from other firms, but also proprietary big data knowledge to support their new product development. Extant research investigates pricing strategies of external private patent knowledge and proprietary big data knowledge separately. Yet, a comprehensive investigation of pricing strategies of these two types of knowledge is in pressing need. This research constructs an overarching pricing model of external private patent knowledge and proprietary big data knowledge through the lens of firm profitability as a knowledge transaction recipient. The proposed model can help those firms who purchase external knowledge choose the optimal knowledge structure and pricing strategies of two types of knowledge, and provide theoretical and methodological guidance for knowledge transaction recipient firms to negotiate with knowledge providers.

• Asia pacific journal of information systems
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• v.33 no.4
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• pp.1036-1042
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• 2023

• International Journal of Computer Science & Network Security
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• v.24 no.7
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• pp.177-185
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• 2024

Web science, a general discipline of learning is presently at high demand of expertise with ideas to develop software-based WebApps and MobileApps to facilitate user or customer demand e.g. shopping etc. electronically with the access at their smartphones benefitting the business enterprise as well. A worldwide-computerized reservation network is used as a single point of access for reserving airline seats, hotel rooms, rental cars, and other travel related items directly or via web-based travel agents or via online reservation sites with the advent of social-web, e-commerce, e-business, from anywhere-on-earth (AoE). This results in the accumulation of large and diverse distributed databases known as big data. This paper describes a novel intelligent web-based electronic booking framework for e-business with distributed computing and data mining support with the detail of e-business system flow for e-Booking application architecture design using the approaches for distributed computing and data mining tools support. Further, the importance of business intelligence and data analytics with issues and challenges are also discussed.

• Journal of Venture Innovation
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• v.7 no.1
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• pp.1-15
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• 2024

This study aims to elucidate the characteristics of big tech platform companies' sports content business in an environment of rapid digital transformation. Specifically, this study examines the market structure of big tech platform companies with a focus on Amazon, revealing the role of sports content within this structure through an analysis of Amazon's sports marketing business and provides an outlook on the sports content business of big tech platform companies. Based on two-sided market platform business models, big tech platform companies incorporate sports content as a strategy to enhance the value of their platforms. Therefore, sports content is used as a tool to enhance the value of their platforms and to consolidate their monopoly position by maximizing profits by increasing the synergy of platform ecosystems such as infrastructure. Amazon acquires popular live sports broadcasting rights on a continental or national basis and supplies them to its platforms, which not only increases the number of new customers and purchasing effects, but also provides IT solution services to sports organizations and teams while planning and supplying various promotional contents, thus creates synergy across Amazon's platforms including its advertising business. Amazon also expands its business opportunities and increases its overall value by supplying live sports contents to Amazon Prime Video and Amazon Prime, providing technical services to various stakeholders through Amazon Web Services, and offering Amazon Marketing Cloud services for analyzing and predicting advertisers' advertising and marketing performance. This gives rise to a new paradigm in the sports marketing business in the digital era, stemming from the difference in market structure between big tech companies based on two-sided market platforms and legacy global companies based on one-sided markets. The core of this new model is a business through the development of various contents based on live sports streaming rights, and sports content marketing will become a major field of sports marketing along with traditional broadcasting rights and sponsorship. Big tech platform global companies such as Amazon, Apple, and Google have the potential to become new global sports marketing companies, and the current sports marketing and advertising companies, as well as teams and leagues, are facing both crises and opportunities.

• Journal of Digital Convergence
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• v.13 no.10
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• pp.69-80
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• 2015

The Purpose of this study is to establish efficient and balanced development and to make transparent marketing system, environment which is to protect small business, consumer's. This Goal of this study is that focus on development of regional and national economy. Especially, to protect small businessmen, to reserve consumer's buying choice. First of all, to examine causes of distribution maintenance and to will be analysed legal controversy of big distributive markets since local autonomy business limits. It is this study that concentrate on big distributive mart shutdown of business hours, Problems and Countermeasures. The main focus of in this study is as follows: First, to examine the ruling of the court that protest and accept of business hour in big distributive mart' problem and regulation, Second, to understand each of the judgement and problems of distributive shutdown systems, Third, to suggest the good distributive business trade act and the possible collaboration with focus on small and big mart System in Korea. This paper to analyze case of conflict and focus on establishment of transparent distribution since business limits.

• Land and Housing Review
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• v.7 no.1
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• pp.19-29
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• 2016

This study proposes the big data policy and case studies in Korea and the application of land and housing of spatial big data to excavate the future business and to propose the spatial big data based application for the government policy in advance. As a result, at first, the policy and cases of big data in Korea were evaluated. Centered on the Government 3.0 Committee, the information from each department of government is being established with the big-data-based system, and the Ministry of Land, Infrastructure, and Transport is establishing the spatial big data system from 2013 to support application of big data through the platform of national spatial information and job creation. Second, based on the information system established and administrated by LH, the status of national territory information and the application of land and housing were evaluated. First of all, the information system is categorized mainly into the support of public ministration, statistical view, real estate information, on-line petition, and national policy support, and as a basic direction of major application, the national territory information (DB), demand of application (scope of work), and profit creation (business model) were regarded. After the settings of such basic direction, as a result of evaluating an approach in terms of work scope and work procedure, the four application fields were extracted: selection of candidate land for regional development business, administration and operation of rental house, settings of priority for land preservation, and settings of priority for urban generation. Third, to implement the application system of spatial big data in the four fields extracted, the required data and application and analytic procedures for each application field were proposed, and to implement the application solution of spatial big data, the improvement and future direction of evaluation required from LH were proposed.