Developing A Digital Contents Valuing Model: How Users Appreciate Their Values

The principal objective of this paper was to propose and verify a digital content valuing model, which is expected to perform a significant role in future research, and provide novel and practical implications. For the efficacy of a model for the evaluation of digital content value, this study reviewed digital content value and categorized it into intrinsic, interaction, and business value. Based on the research model, we attempted to identify and assess the effects of intrinsic digital content value on digital content interaction value, and to characterize the relationship between digital content interaction value and digital content business value. Consequently, this study finds strong interrelations among different types of values and these interactions lead a value addition to digital content usage. We hope that the proposed valuing model of digital contents will prove useful and provide further research insights, and will also increase our understanding of digital content valuing process

Towards an Electronic Commerce Growth Stage Model

The advent of the digital economy and Electronic Commerce (EC) can be seen not as the development of existing commerce but rather as a new commerce pattern caused by Internet technology. There are many possible definitions of EC, but in this research we consider the definition of EC as the buying and selling of information, products, and services via Internet. The application of EC is diffusing into various areas such as merchandising, finance, education, advertising, entertainment and government. To better understand the shaping process of EC and to predict the direction of further diffusion, the growth stage model of EC is required. It is difficult to find a growth stage model in relation to EC. Therefore, in this study, we divide the EC into a series phases, then develop a model explaining the shaping process of EC, regarding major domains of EC such as economic, social, political and technical. To provide a theoretical basis for the growth stage model of the EC, we consider existing literatures about information systems, organization and industry life cycle and then suggest a growth stage model reflecting major characteristics of EC. The growth stage model of EC developed in this research can not only predict the direction of EC growth, but can also provide a useful model as guideline to organizations in planning EC. Key Words: Digital Economy, Electronic Commerce Growth Stage Model, Shaping Process, EC Plannin

Sensor data identification based reagent cabinet management system

Recently, a reagent cabinet is used in a laboratory or a laboratory is required to have a system capable of identifying a dangerous situation through sensor data as various sensors are utilized. The existing system identifies the dangerous situation through various sensor data, but there is a problem that the server performs all the operations and the operation of the device is performed manually. In order to solve this problem, this paper proposes a system that can identify the dangerous situation and automatically operate the equipment through the internal environment data of the reagent cabinet. Identification of the hazardous situation is done through the master node used in the reagent cabinet, not the server. The server can continuously update the sensor data through the master node and monitor the real-time status of the reagent cabinet through the application. In this way, it is expected that the risk situation will be promptly addressed by identifying the dangerous situation in the reagent cabinet and operating the device

How Organizational Resources Influence Benefits of mobile CRM in Organizations?

mCRM (Mobile Customer Relationship Management) system is one of the recent advancements in CRM systems which combines the ubiquitous computing and CRM to enable organizations improve their customer services. This study investigates how various organizational resources influence the benefits organizations gain from their mobile CRM system. Drawing upon resource-based view of the firm and the IS success model proposed by DeLone & McLean, we have proposed a research model linking various resources in an organization to enhance benefits gained from mCRM system. To validate the proposed model, we have developed a survey to collect empirical data from companies using mCRM. We expect that the study help both academic and professionals to understand what organizational resources influence and how organizational benefits of mCRM systems are improved by employing the appropriate resources

Taxonomy of Web-Based Shopping Systems

This paper attempts to address a detailed understanding of the diffusion of WBSS, introducing a classification model of WBSS, analyzing the cases of four categories of WBSS, and providing a characteristics of the four types of WBSS. A model of four types of Web-based shopping systems is suggested: (1) general-direct-sales; (2) generalintermediary-sales; (3) specialized-direct-sales and (4) specialized-intermediary-sales. On the basis of these four categories of WBSS, the paper analyses the distinguishing characteristics of WBSS, which has implications for both theory and practice. We hope that this research will mark the starting point in on-going research towards many unresolved issues on Web-based shopping systems

Use of Online Social Networking Services from a Theoretical Perspective of the Motivation-Participation-Performance Framework

Social networking services (SNS) are platforms to form and manage personal connections and create a foundation for human relationships. Intending to identify why, how, and for what outcome users use SNS, this study contributes to the body of knowledge on SNS by analyzing how motivation, participation, and performance are related to each other in the SNS context. Drawing on a theoretical perspective of the motivation-participation-performance framework, we identify four significant why motivations (i.e., vertical social, horizontal social, hedonic, and utilitarian motivations), two main ways (how) of participation (i.e., sharing and collaboration), and two ultimate benefits (for what outcome) of SNS use (i.e., personal and job performance). The analyzed results of empirical data collected from SNS users indicate that the identified motivations significantly influence participation in sharing and collaboration activities on SNS and that SNS participation significantly affects personal and professional/job-related performance. This study contributes to theory by providing a multidimensional view of SNS use, its predictors, and its consequences

The diffusion of web-based shopping systems: A comparative analysis of the key impact factors in the UK and Korea.

As a major driving force of the global digital economy, Web-Based Shopping Systems (WBSS) are diffusing very rapidly across national boundaries. Though the diffusion of WBSS is recognized as one of the most important issues of electronic commerce, the research on WBSS is just beginning. There is little comprehensive research and only a few examples of empirical research on the topic. This research attempts to examine the phenomenon of WBSS diffusion in different national contexts, based on a combination of qualitative and quantitative approaches. In particular, this dissertation attempts to answer the following questions: What are WBSS. Are WBSS an enabler of new business. What kinds of factors affect the diffusion of WBSS. Are there any distinguishing characteristics of WBSS diffusion in different national contexts. How do organisations tend to enable WBSS diffusion. What kinds of driving forces influence the shaping process of WBSS. In order to answer these questions, this research introduces several research models: a classification model of WBSS, a research model of WBSS diffusion, and a comparison model of key impact factors. On the basis of these models, this dissertation examines and attempts to explain the phenomenon of WBSS diffusion. It does so by relating survey research and interviews in two particular national contexts: the UK and Korea. The findings arising from the quantitative and qualitative data collected are applied to provide guidance as to the further diffusion of WBSS in both countries. Some of the major findings of the dissertation are: o At the macro level, a systemic view of WBSS diffusion is provided by analyzing the characteristics off our types of WBSS. Major characteristics of WBSS associated with each of these types of WBSS - their strengths, critical success factors and suitable strategic options - have also been identified. On the basis of this background knowledge of WBSS, a research model of WBSS diffusion was derived. o At the micro level arising from empirical investigations, key impact factors influencing the diffusion of WBSS in the UK and Korean contexts have been identified. Following cross-national analysis, the diffusion of WBSS was observed as a series of shaping processes being influenced by different cultural issues and similar ICT-related factors in global Web-based shopping circumstances. o The implications emerging from the quantitative survey and qualitative interviews from both countries are: -Theoretical implications were highlighted by comparing the WBSS diffusion model with previous ICT diffusion studies. It was observed that WBSS diffusion in both the UK and Korea is a dynamic, complex, and interactive shaping process being influenced by internal organisation and internal system factors, as well as external market and external technical factors. -Practical implications for further WBSS diffusion in both countries have been suggested in the interests of both promoting e-commerce, and establishing a solid base for the digital economy. Overall, this dissertation has attempted to provide a theoretical foundation for further research relevant to WBSS, electronic commerce and ICT diffusion in different national contexts. It is hoped that this research will serve as a catalyst for triggering new research agendas on e-commerce and ICT innovation diffusion, paving the way for other researchers who wish to build on the research findings of this dissertation

A Strategy for Third-Party Logistics Systems: A Case Analysis Using the Blue Ocean Strategy

One of today’s most frequently discussed topics in the business world is how to escape from the intense Red Ocean and how to create an uncontested Blue Ocean. However, because there are few practical guidelines available on this topic, we will introduce a case study of a third-party logistics (3PL) provider, CJ-Global Logistics Service (CJ-GLS), to show how it aspires to be a leader in the newly introduced 3PL industry in South Korea. CJ-GLS is a latecomer in the logistics industry, and its resources, such as the number of trucks and warehouses, are relatively small in comparison to those of established companies. But, it has achieved a distinct competitive advantage through innovative information technology (i.e., RFID— radio frequency identification), which has enabled it to create an uncontested market space, electronic logistics business. One remarkable fact about CJ-GLS is that its swift growth comes not from attracting competitors’ customers from the existing Red Ocean market but from creating a Blue Ocean market (3PL market), which previously existing incumbents ignored, and also from constructing a new business model founded on a RFID-based, ubiquitous-oriented 3PL system. Analyzed through a Four Actions Framework and characterized as Blue Ocean, this case study provides valuable information on how a company reinforces its competitive advantage from the Red Ocean while it transitions into a Blue Ocean by utilizing advanced information communication technologies

Fruit tree disease classification system using generative adversarial networks

Smart farm refers to a farm that can remotely and automatically maintain proper growth and management of crops and livestock by integrating technology with agriculture. Currently, smart farms are concentrated in the field of smart horticulture, and although spreading research is being conducted in limited spaces. In addition, it is difficult to obtain a sufficient amount of data to be used for learning, and there is a problem that data imbalance occurs because it is difficult to obtain a similar amount for each class. In this paper, we propose a method to amplify a small amount of data and to solve the problems of imbalance data by using a feature that can learn to mimic the data of a generative adversarial network. The proposed method can create dataset of various crops and also show high hit rate. Dataset generated from crops would be used to solve problems of data imbalance by learning