With the recent development of manufacturing technology and the diversification of consumer needs, not only the process and quality control of production have become more complicated but also the kinds of information that manufacturing facilities provide the user about process have been diversified. Therefore the importance of big data analysis also has been raised. However, most small and medium enterprises (SMEs) lack the systematic infrastructure of big data management and analysis. In particular, due to the nature of domestic manufacturing companies that rely on foreign manufacturers for most of their manufacturing facilities, the need for their own data analysis and manufacturing support applications is increasing and research has been conducted in Korea. This study proposes integrated analysis platform for process and quality analysis, considering manufacturing big data database (DB) and data characteristics. The platform is implemented in two versions, Web and C/S, to enhance accessibility which perform template based quality analysis and real-time monitoring. The user can upload data from their local PC or DB and run analysis by combining single analysis module in template in a way they want since the platform is not optimized for a particular manufacturing process. Also Java and R are used as the development language for ease of system supplementation. It is expected that the platform will be available at a low price and evolve the ability of quality analysis in SMEs.

This study focuses on the value of social platform and investigates the relationships between knowledge sharing and customer value. The study examines the effects of social network attributes on knowledge sharing in social platforms, and the effects of knowledge sharing on customer value in social platforms. In the context of social platform, this study clarifies the concept of customer value, the role of knowledge sharing, and the relationships between knowledge sharing and customer value. The study builds a theoretical model regarding social platforms and customer value that offers implications for advertising & PR practitioners.

Introduction In order to solve the information asymmetry and make full use of resources (unused goods, spare capacity and so on), the sharing economy, which based on the application of mobile internet technology and focused on the consumption of the right to use, is developing rapidly. Lack of trust is considered to be one of the important problems hindering the development of sharing economy. Möhlmann (2015) said that trust is a fundamental determinant of sharing economy development and ensuring shared satisfaction. At present, sharing economy enterprises have established product evaluation system and docked a third party credit rating system (i.e. Zhima Credit) to promote consumers’ trust. However, with most enterprises are becoming more and more consistent in evaluation and credit rating system, there is a new problem emerged: how to further deepen consumers’ trust in order to promote consumers’ intention to participate continuously (Zucker, 1986; Lewis & Weigert, 1985). Granovetter (1985) mentioned that trust is the product of social relationships. Botsman and Rogers (2011) made it clear that social networks play an important role in building trust in sharing economy. And people are always more willing to accept the opinions of people who have social relations with them (Lu, Zhao, & Wang, 2010). Hence, with the feature of participant of everyone in sharing economy, it is necessary to further strengthen consumers’ trust through the social interaction among consumers and between consumers and sharing platforms. Theoretical Development Sharing economy is based on LBS and other new technologies to realize the matching of supply and demand information across time and space. And to a certain extent, it solves the problem of information asymmetry in the era of e-commerce. Yet consumer have new requirements for product information. For example, consumers are more concerned about whether the utility of products and services can meet their needs (i.e. some consumers are more concerned about when to reach their destination than the performance of the car). But it is difficult for company to understand each everyone of consumers’ utility preference and publish product utility information based on these preferences (Xie & Gerstner, 2007). Because this kind of utility preference has the characteristic of timeliness and personalization. Therefore, consumers’ perceived uncertainty about the utility of the product will also affect the consumers’ trust. In summary, we then address these research questions:(1) can the promotion of trust between consumers and sharing platforms be achieved through the socializing of sharing platforms and then affect consumers’ intention to participate continuously; (2) if so, which type of privacy protection method and social information can promote consumer trust; and (3) does the impact of sharing platform socialization on consumer trust vary according to consumers’ concerns about the perceived utility uncertainty of the product. Research Design We then address these issues using experiment data. The first experiment was a 2 (social media: have, not have) x 2 (individual trust propensity: trust, not trust) between-subject design on the intention to trust sharing platform and participant continuously. Perceived utility uncertainty was added to this design as a moderator. Moreover, the second experiment was a 2 (social information type: hedonic, utilitarian) x 2 (degree of privacy protection: week, strong) between-subject design on the intention to trust sharing platform. Our scales come from existing scales and optimize it according to the characteristics of sharing economy (Schneider, 1999; Dhar & Wertenbroch, 2000; McKnight, Choudhury, & Kacmar, 2002). Results and Conclusion The results of the first experiment show that whether or not the social platform has no significant impact on the consumer trust if the individual tends to trust others. And for individuals who tends to do not trust others, they are more likely to trust socialized sharing platforms. The higher the consumer perceived utility uncertainty is, the higher (lower) trust of the consumer platform in the socialized (not socialized) sharing platform. For the second experiment results, in the context of sharing economy, the utilitarian information has a greater positive impact on the consumer trust than the hedonic information. In addition, the stronger the privacy protection of sharing platforms, the higher the trust of consumes. This study makes several academic contributions. First, we extend the topic of socialization to sharing economy context. Second, we add the perceived utility uncertainty as a moderator, and supplement the role of perceived uncertainty. This research also provides several practical implications. First, sharing platform can promote their consumers’ trust by establishing their own social platform. This platform can be used as a differentiated competitive strategy for sharing platform. Second, sharing platform should guide consumers to share utilitarian information (i.e. weather for specific place or real time traffic) to improve consumer satisfaction. Third, sharing platform can access consumer preference information through this social platform for further product development and classification.

The number of individuals using peer-to-peer and access-based services through collaborative consumption platforms (CCP) has been grown dramatically for a few reasons. CCP makes consumers convenient because it enables individuals trade directly without contacting each other. Thus, CCP, a digital platform, encourages more consumers to use access-based. CCP is temporal access-based service to a good. A good is usually accessed and traded in the absence of a service provider representative through CCP, and thus, misbehavior can occur and then be diffused into other consumers. Most of CCPs are based on digital platform, which provides participants with space where they can trade. Because the interactions in CCP is usually non-face to face communication and the participants tend to have similar interests and chat with task-oriented and low socio-emotional content, they can feel submerged in a crowd and indistinguishable from others. That is, participants feel like the sense of deindividuation which means to lose all sense of individuality. When participants face misbehavior of multiple previous customers, such deindividuation makes them conform social norm that they think that others do misbehavior as well. Based on social identity theory and deindividuation, this research examines the mediating effect of deindividuation on the relationship between previous misbehavior and misbehavior and the moderating effect of the self-disclosure on the relationship between previous misbehavior and deindividuation.

Since more and more consumers rely on online consumer reviews in their purchase decision making, we have observed the emergence of empirical studies on online reviews in different contexts. Such studies look at various dimensions surrounding online reviews; nevertheless, none of them actually gives a more comprehensive picture as to the rating differences across online rating platforms and/or across time, let alone explains such differences. This study aims to address these understudied but managerially relevant issues. In our empirical study, we focus on hotel ratings across platforms and across time (i.e., across identified change point in time), and explain such differences by review text associating with the ratings. We investigated San Francisco hotels that were rated on both Tripadvisor and Expedia, and utilized the General Inquirer dictionary to identify the categories of words in a review. Regressions analyses were then conducted for the explanation of rating differences. We found that rating differences, in both the cross-platform and the longitudinal cases, are substantially associated with the number of words (in a negative relationship). Furthermore, word tags identified from the review text associated with ratings also explain the rating differences. To conclude, the research reveals that for a specific service provider, online ratings may vary significantly in both the cross-platform and the longitudinal senses. It demonstrates that adopting a systematic approach and utilizing an established semantic dictionary, information extracted from review text can substantially explain such differences.

Introduction In order to solve the information asymmetry and make full use of resources (unused goods, spare capacity and so on), the sharing economy, which based on the application of mobile internet technology and focused on the consumption of the right to use, is developing rapidly. Lack of trust is considered to be one of the important problems hindering the development of sharing economy. Möhlmann (2015) said that trust is a fundamental determinant of sharing economy development and ensuring shared satisfaction. At present, sharing economy enterprises have established product evaluation system and docked a third party credit rating system (i.e. Zhima Credit) to promote consumers’ trust. However, with most enterprises are becoming more and more consistent in evaluation and credit rating system, there is a new problem emerged: how to further deepen consumers’ trust in order to promote consumers’ intention to participate continuously (Zucker, 1986; Lewis & Weigert, 1985). Granovetter (1985) mentioned that trust is the product of social relationships. Botsman and Rogers (2011) made it clear that social networks play an important role in building trust in sharing economy. And people are always more willing to accept the opinions of people who have social relations with them (Lu, Zhao, & Wang, 2010). Hence, with the feature of participant of everyone in sharing economy, it is necessary to further strengthen consumers’ trust through the social interaction among consumers and between consumers and sharing platforms. Theoretical Development Sharing economy is based on LBS and other new technologies to realize the matching of supply and demand information across time and space. And to a certain extent, it solves the problem of information asymmetry in the era of e-commerce. Yet consumer have new requirements for product information. For example, consumers are more concerned about whether the utility of products and services can meet their needs (i.e. some consumers are more concerned about when to reach their destination than the performance of the car). But it is difficult for company to understand each everyone of consumers’ utility preference and publish product utility information based on these preferences (Xie & Gerstner, 2007). Because this kind of utility preference has the characteristic of timeliness and personalization. Therefore, consumers’ perceived uncertainty about the utility of the product will also affect the consumers’ trust. In summary, we then address these research questions:(1) can the promotion of trust between consumers and sharing platforms be achieved through the socializing of sharing platforms and then affect consumers’ intention to participate continuously; (2) if so, which type of privacy protection method and social information can promote consumer trust; and (3) does the impact of sharing platform socialization on consumer trust vary according to consumers’ concerns about the perceived utility uncertainty of the product. Research Design We then address these issues using experiment data. The first experiment was a 2 (social media: have, not have) x 2 (individual trust propensity: trust, not trust) between-subject design on the intention to trust sharing platform and participant continuously. Perceived utility uncertainty was added to this design as a moderator. Moreover, the second experiment was a 2 (social information type: hedonic, utilitarian) x 2 (degree of privacy protection: week, strong) between-subject design on the intention to trust sharing platform. Our scales come from existing scales and optimize it according to the characteristics of sharing economy (Schneider, 1999; Dhar & Wertenbroch, 2000; McKnight, Choudhury, & Kacmar, 2002). Results and Conclusion The results of the first experiment show that whether or not the social platform has no significant impact on the consumer trust if the individual tends to trust others. And for individuals who tends to do not trust others, they are more likely to trust socialized sharing platforms. The higher the consumer perceived utility uncertainty is, the higher (lower) trust of the consumer platform in the socialized (not socialized) sharing platform. For the second experiment results, in the context of sharing economy, the utilitarian information has a greater positive impact on the consumer trust than the hedonic information. In addition, the stronger the privacy protection of sharing platforms, the higher the trust of consumes. This study makes several academic contributions. First, we extend the topic of socialization to sharing economy context. Second, we add the perceived utility uncertainty as a moderator, and supplement the role of perceived uncertainty. This research also provides several practical implications. First, sharing platform can promote their consumers’ trust by establishing their own social platform. This platform can be used as a differentiated competitive strategy for sharing platform. Second, sharing platform should guide consumers to share utilitarian information (i.e. weather for specific place or real time traffic) to improve consumer satisfaction. Third, sharing platform can access consumer preference information through this social platform for further product development and classification.

Introduction With the opening of the 4th revolution era, platform business started to come into the spotlight. It was in the early 2000s that academics started full-scale research on platform based on the two-sided market theory but in fact the two-sided market is a business model that has existed around us since before. Examples include credit card industry, real estate brokering, and auctions. These industries are creating value through the interaction of two markets of different needs through a company that provides a specific platform (Rochet and Tirole, 2003, 2006). Recently, with the widespread use of services and products based on high technology, platform business is pouring into our lives at an amazing speed. With a single ID, you can shop, pay for, and receive shipping from a variety of online stores, without having to go through a lot of memberships. You do not have to search every single hotel for the best price, best location. You can even find a room in the house and see the reviews of customers who have stayed there. Compared to traditional pipeline business, one of the key differentiating features of the platform business is a two-sided network effect where consumers and consumers, producers and producers, and consumers and producers interact with each other. This two-sided network effect, with a positive feedback loop, has become a major driver of platform company growth. In the two-sided market, the platform‟s value to any given user largely depends on the size of the users on the other side of the platform due to the indirect network effect (Evans, 2003; Parker & Van Alstyne, 2005). Therefore, increasing the size of one side market, including the issue of „chicken or egg‟, is an indispensable task for the platform managers to maximize platform performance. But more important than increasing the size of one side of the market is transforming the new customers to loyal customers and creating positive feedback loops. This study explores the process of online payment platform users signing up, forming user loyalty, and spreading the loyalty to the sellers and platform providers. More specifically, this study examines (1) what causes the consumers to join the online payment platform at the beginning (2) what are the drivers that lead new members to the active, loyal users (3) whether the loyalty to the payment platform has a positive effect on the attitude toward the sellers (the other side market) and the platform company (platform provider). Theoretical Background and Hypotheses Two- Sided Markets and the Platform The definition of the two-sided market is varied by scholars. Chakravoti and Roson (2006) defines the two-sided market as a market where two different groups of users interact through the platform and the value created at this time is influenced by the indirect externalities of the network. Here, the platform is a physical, virtual, or institutional environment that allows different groups of users to facilitate transactions or interactions. According to Evans (2003), three necessary conditions for two sided platform markets are: (1) there are two distinct groups of customers; (2) there are externalities associated with customer A and B becoming connected or coordinated in some fashion; (3) an intermediary can facilitate that coordination efficiently than bi-lateral relationships between the members of the group. For example, we can think of a credit card company. There is a group of card holders and merchants and the demands of these two groups are very different. There is also a network effect between the two groups. Customers will not use credit cards with fewer merchants. The greater the number of merchants, the greater the benefits the customers have. Likewise, the more cardholders there are, the more profitable the merchants can generate. The intermediary role of the two groups of users to interact is a credit card company. Perceived value and Loyalty to the Online Payment Platform The loyalty to the online payment system can be expressed as the level of participation and commitment the member has over other similar payment systems. O‟Brien and Jones (1995) argue the value perception as an important prerequisite factor in developing brand loyalty; that is, only after the customer has perceived the online payment system as valuable, then would the customer become loyal to the system. The expectations that the perceived value can affect the loyalty to the online payment platform may be explained in terms of “Social Exchange Theory” (Thibaut and Kelly 1959). Within this framework, the customer will remain in the platform only when he or she perceives the value, which is defined as a trade-off between costs and benefits (Woodruff and Gardial 1996) is sufficient. Overall, perceived value of the online payment platform would affect customer loyalty. More specifically, it is expected that non-economic values such as simplicity in account setting, convenience in use will have a more meaningful effect than the economic value including sign-up grant at the stage of attracting new customers. But in the process of new customers becoming active and loyal users, the economic value including mileage points, discount coupons and free trial coupons will play a more important role in addition to this convenience. For example, benefit of being able to use the accumulated mileage or discount coupon on any online store within the platform will make consumers to stay on this payment platform and become loyal customers. Based on such argument, we put forward the following hypothesis. H1: Non economic value has a positive effect on online payment platform loyalty H2: Economic value has a positive effect on online payment platform loyalty. Loyalty Transfer According to Eisenmann et al. (2006), the platforms exhibit two types of network effects: A same-side effect, in which increasing the number of users on one side of the network makes it either more or less valuable to users on the same side; and a cross-side effect, in which increasing number of users on one side makes it either more or less valuable to the users on the other side. In case of online payment platform, it is expected that there will be a positive cross-side network effect. As the number of consumers using a specific online payment platform increases, the number of partner shops participating in the platform will increase, allowing consumers to shop in more diverse online stores. Once customers experienced the value of a specific online payment system, they would insist on paying by this method when shopping online (Parker, Alstein and Choudary, 2016), that is, becoming a loyal customer. Oliver (1999) defines customer loyalty as a deeply held commitment to re-buy or re-patronize a preferred product or service consistently in the future, thereby causing repetitive same brand purchasing. The loyal customers will be among the many online stores selling the same products/services at a same price, shopping at stores that show their favorite online payment system logo, and encouraging friends and family to use the payment system. The frequent transactions will affect consumer‟s attitude towards a certain brand or store and diffuse their loyalty. The customers that are loyal to the payment platform will not only actively try to earn points but also be willing to go and shop at the stores participating in the platform. Some customers may prefer a store among many even though they have not used it before because it belongs to the platform. The loyalty to the platform also can be transferred to the loyalty on the platform provider. Customers will have a favorable attitude when the platform providers do other business (for example, online banking, debit card business, etc.). Given the above, we put forward the following 3 hypotheses. H3: Platform loyalty has a positive effect on the loyalty toward the sellers, the other side market. H4: Positive attitude toward the sellers within the platform has a positive effect on attitude toward the platform company H5: Platform loyalty has a positive effect on the attitude toward the platform company. Conceptual Framework Data Analysis and Results The data used in this study were obtained from a survey of 562 online payment platform users. Data analysis shows that non-economic values such as simplicity, convenience, and platform reliability have a more significant impact on platform loyalty than economic values such as sign-up bonus. However, it was found that economic factors such as mileage points, and discount coupons are more influential factors in the process of converting new members to active users. In addition, loyalty to the payment system has a positive effect on attitudes towards sellers where one can use the means of payment. Also, it can be seen that the customer loyalty to the platform and the favorable attitude toward the sellers make a favorable attitude toward the platform company providing and managing the two-sided market. Conclusion and Discussion This study may contribute to a better understanding of platform business in three particular ways. First, understanding the loyalty diffusion mechanisms within the platform can support platform companies to develop effective strategies to attract new consumers to the platform and to transform them into active users. Second, even though the study uses the data collected from individual consumer level, the findings may provide some inspiration for B2B relationships. For example, as the number of loyal buyers and sellers sharing the platform increases, the value of the platform increases and the platform company can use it as a powerful bargaining power when it comes to third business. Third, the study may help us to understand the role of Platform in two-sided market and how the customer loyalty becomes diffused. Although this study explored the loyalty formation and diffusion using the sample of the major payment systems in Korea, it may be premature to generalize the findings at this stage. It is important to note that there may be negative network effects. They need to be evaluated further through careful research.

With the recent development of manufacturing technology and the diversification of consumer needs, the process and quality control of production have become more complicated. In particular, due to the nature of domestic manufacturing companies that rely on foreign manufacturers for most of their manufacturing facilities, the need for their own data analysis and manufacturing support applications is increasing and research has been conducted in Korea. This study proposes integrated process and quality analysis platform supporting analysis template considering manufacturing big data DB interworking and data characteristics. In addition, the platform is implemented in two versions, web and CS, in consideration of user accessibility.

RNA interference (RNAi) has been considered as an alternative strategy to control agricultural pest whereby double-stranded RNA triggers a potent and specific inhibition of its homologous mRNA. Since small dsRNAs are required for various RNAi applications, there is a need for cost-effective methods for producing large quantities of high-quality dsRNA. In this study, Bacillus thuringiensis (Bt) based dsRNA production platform was established under control of sporulation-dependent promoter and vp1 gene of Sacbrood virus (SBV) was introduced. The dsRNA against vp1 gene produced from the Bt suppressed the replication of SBV. In addition, the dsRNA was assembled into inulin coated-nanoparticle to increase stability of dsRNA in environment.

The virus-like particle (VLP) is similar to a pathogenic virus and has a high immunogenicity. However, in the selection of various structural proteins to form VLP, all expression systems commonly consume most of the time and suffer from various difficulties. Therefore, there is a need for a system that can rapidly determine the structural proteins required for effective VLP production. This study aims to construct a transient expression platform using insect cells to solve this problem. Plasmid-based expression vectors and baculovirus-inducible expression vectors were constructed. The vectors were evaluated for overexpression using EGFP. We also confirmed the formation of virus like particles through overexpression of virus structural proteins.

본 연구는 농업 및 정보 통신 기술의 융합을 기반으로 국내외 스마트 농장 서비스 모델을 검토하고 한국의 스마트 온실을 개선하기 위해 필요한 다양한 요인을 조사 하기 위해 수행되었다. 국내 스마트 온실의 작물 생육모델 및 환경모델에 관한 연구는 제한적이었고, 연구를 위한 인프라를 구축하는 데는 많은 시간이 필요하다. 이러한 문제의 대안으로 클라우드 기반 연구 플랫폼이 필요하다. 제안된 클라우드 기반 연구 플랫폼은 통합 데이터, 생육 환경모델, 구동기 제어 모델, 스마트 온실 관리, 지식 기반 전문가 시스템 및 농가 대시보드 모듈을 통해 통합적 데이터 저장 및 분석을 위한 연구 인프라를 제공한다. 또한 클라우드 기반 연구 플랫폼은 작물 생육환경, 생산성 및 액추에이터 제어와 같은 다양한 요인들 간의 관계를 정량화하는 기능을 제공하며, 연구자는 빅데이터, 기계 학습 및 인공지능을 활용하여 작물 생육 및 생장 환경 모델을 분석할 수 있다.

More people travel oversea as the economic size of Korea is getting larger and more new jobs are requested to be created by the society. To respond to these trend and request, Incheon International Airport Corporation (IIAC) is about to expand its processing capability with a new terminal; 54 million passengers to 72 million. IIAC is also introducing new strategies such as open innovation (OI) and creating shared value (CSV). With these changes, IIAC faces new challenges of restructuring its business and organization with new ideas. Most organizations including IIAC are becoming more dependent on external resources to keep their competitive advantages under the turbulence of global business environmental changes. Therefore, they focus on the OI paradigm which is reported as a convincing strategy to improve competitiveness in terms of budget and time-to-market. OI is to quickly react to the rapidly changing business environment and is adopted to support startup incubation. In the previous research with IIAC, three major tasks were defined; utilizing the IIAC brand power for external vendors, building a technology road-map, and introducing a collaboration support system. This paper deals with the collaboration system as proposed in the previous research. We focused on the collaboration process for startup incubation. Cases were studied; the K-startup model by the government, a university model to explore youth startups, and a R&D institute model to study professional startups. Based on the case studies, we defined an IIAC model and proposed issues to take care of. The model is distinguished from the other studied models since IIAC is a prospective customer of new technology.

Compared to the early 2000s, the number of tourists in Korea has increased significantly. Approximately 40 million tourists visit Korea each year. In line with this trend, various technologies for developing tourism content have reached a very high level. Therefore, adding experience-oriented AR (Augmented Reality) game based on LBS (Location-Based System) to existing tourist contents will create a new tourism content platform that can give new experience to tourists . This paper proposes a tourism contents platform based on Suwon Hwaseong Fortress which can give such a new experience.

본 연구는 온라인 큐레이션 플랫폼을 이용한 외현적 정보의 제공이 현대미술에 대한 일반대중의 진입장벽을 낮추는 효과를 가지는지 알아보았다. 현대미술은 일반대중이 접근하기 난해한 장르로 여겨져 왔다. 한편, 미술 감상에 대한 연구들은 외현적인 정보의 제공이 미학적 감상 경험에 긍정적인 영향을 줄 수 있음을 밝혔다. 따라서 본 연구에서는 작품에 대한 구체적 정보를 제공하는 것이 현대미술을 감상하는 데에 긍정적인 영향을 미칠 수 있는지 알아보았으며 감상 경험을 심리학적으로 분석한 Leder et al.(2004)의 이론적 모델에 기초하여 외현적 정보가 어떠한 인지적 처리과정을 도와주는지 분석하였다. 더 나아가 최근의 전시 트렌드를 반영하여 온라인 플랫폼 환경을 적용하였다. 실험 1에서는 작품과 설명문이 제공되었고 작품에 대한 이해도, 관람의향을 보고하였다. 실험 결과, 해설이 제시된 조건에서 작품에 대한 이해도가 더 높았다. 또한, 긴 해설이 제시된 조건에서 해설 이해도와 관람의향을 작품이해도가 완전매개하는 매개모형이 나타났다. 실험 2에서는 ARS 설문을 추가하고 온라인 큐레이션의 능동적인 조작 환경을 재현했다. 실험결과, 해설이 제공된 조건들에서 관람의향, 작품이해도가 더 높았다. 예술사적 의미, 자아성찰, 창의성 등 Leder et al.(2004) 모델의 후기 단계에 해당하는 지표들 역시 해설조건에서 더 높은 것으로 나타났다. 종합하면, 온라인 큐레이션 환경에서의 정보전달이 일반대중의 현대미술 작품에 대한 인지적 처리와 판단에 도움을 줄 수 있었다.

This study introduces coding education using functional computer game and board game. We direct compare two different types of the educational game for coding education and their learning achievements. The purpose of this study is mainly to compare the effect of the difference of game type on the learner's attitude, learning immersion, education satisfaction and preference for elementary school and junior high school students. In this study, we considered the effect of game platform type on learning and we suggested that when designing an educational game for coding, the proper combination of these platforms are important.