• The Journal of Asian Finance, Economics and Business
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• v.8 no.3
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• pp.931-941
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• 2021

The study focuses on the relationship between SB, corporate social responsibility (CSR), and the emerging economy. Thereafter it highlights the types, principles, and funding cycle of SB with the evidence from Grameen Bank, which is a globally well-recognized microfinance venture in Bangladesh established by the Nobel Laureate Dr. Muhammad Yunus. This study employs qualitative analysis to illustrate an architectural overview of the SB model by collecting secondary data from various publications related to the topic and published data of Grameen Bank. Finally, this paper illustrates the SB model along with specified characteristics, systematic framework, and main approaches for sustainable context, which could be applied as a conceptual framework for SB in any context of the emerging economy. The findings of this study suggest that the SB model is the workflow having a hierarchy of five phases namely need identification, goal setting, solution-based business plan, business plan assessment, and business plan execution. Analyzing a range of social business interventions in a developing country, Bangladesh, through the lens of five key aspects demonstrates that social business is the most efficient way to sustainably maximize the social benefits and minimize specific social issues poverty of the people affected.

• The Journal of Information Systems
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• v.29 no.4
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• pp.57-76
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• 2020

Purpose Although examining the antecedents of employees' extra-role behavior (i.e. information security participation behavior) in the information security context is significant for researchers and practitioners, most behavioral security studies have focused on employees' in-role behavior (i.e. information security policy compliance). Thus, this research addresses this gap by investigating how organizational information security climate influences information security participation behavior based on social information processing theory and Griffin and Neal's safety model. Design/methodology/approach We developed a research model by applying Griffin and Neal's safety model to the information security context and then tested our research model by conducting an online survey for employees of organizations with information security policies. Structural equation modeling (SEM) with SmartPLS 3.3.2 is used to test the corresponding hypothesis. Findings Our results show that organizational information security climate, information security knowledge, information security motivation are effective in motivating information security participation behavior. Also, we find that organizational information security climate positively influences both information security knowledge and information security motivation. Our findings emphasize the importance of organizational information security climate because it is capable of affecting employees on information security participation behavior. Our study contributes to the literature on information security by exploring the role of organizational information security climate in enhancing employees' information security participation behavior.

• Journal of Information Technology Services
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• v.21 no.5
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• pp.15-28
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• 2022

Recently, government agencies are actively adopting the platform model as a means of public policy. However, existing studies on the public platform are minimal and have focused on user experiences or the possibility of public usage of the platform model. Now the research concerning building governance structure and utilizing network effects of the platform after adopting the platform model in the public sector is keenly required. This study intended to ignite academic dialogue on the governance of public platforms in the context of digital transformation. This study focused on a case of the 'Special delivery,' a public delivery app established by Gyeonggi-do. In order to analyze the characteristics of the public platform and its governance structure, data were collected from press releases, policy reports, and news articles. Data was analyzed using the frame of Hagui's platform design factors and Ansell & Gash's collaborative governance model. The results of the public platform analyses showed 1) incompleteness in the value trade-off accounting, which was designed for platform business based on general cost-benefit analysis, and 2) a closed governance structure that limits direct participation of diverse user groups(i.e., service provider, customer) in order to enhance providers' utility by preventing customers' excessive online activities. The results of this study provided theoretical and policy implications regarding designing the strategy for accounting for value trade-offs and functioning governance structure for public platforms.

• Journal of Distribution Science
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• v.21 no.12
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• pp.23-34
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• 2023

Purpose: The purpose of this study is to identify factors affecting satisfaction as well as the intention of Gen Z customers to reorder food online in the context of a crisis. Research design, data and methodology: Data for this cross-sectional study were collected via the Internet by conducting an online survey of 652 Gen Z respondents, aged 15-25, in the south of Vietnam and using a convenience sampling method. To analyse the reliability of the scales, SPSS was used to run Cronbach's alpha. Then, SmartPLS was used to assess the measurement model, including variable reliability and validity, convergent validity, and discriminant validity of the proposed model, as well as test the hypotheses with partial least squares structural equation modelling (PLS-SEM). Results: Social influence, price value, and convenience all have a positive effect on satisfaction and repurchase intention. Satisfaction not only plays a critical role in mediating the relationship between social influence, price value, convenience and repurchase intention but also has a positive impact on repurchase intention towards buying food online. Conclusions: This study was successful in identifying the factors of repurchase intention in a crisis setting among Gen Z customers by developing a theoretical research model via literature to complete a brief Theory of Planned Behaviour model. This study also took an innovative approach to earlier ones by demonstrating not just the significant effect of social influence on satisfaction and repurchase intention, but also by identifying critical variables that managers should focus on increasing and improving management.

• Journal of the HCI Society of Korea
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• v.7 no.1
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• pp.19-28
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• 2012

Why people share location context information? The purpose of our study is that why users share location context information and which factors is related to co-experiences in LBSNS. Through an exploratory approach, first, we conducted a qualitative study in order to understand experiences among people in LBSNS and analyzed according to Grounded Theory. As a result, we found concepts regarding co-experiences cooperatively and competitively in LBSNS. Second, the theoretical model of co-experience was constructed by mediating perceived empathy based on theoretical foundation. In this study, theoretically, we suggested exploratory research model of co-experiences in LBSNS. Practically, designers could adopt concepts in terms of competition and collaboration among users to build co-experience of LBSNS services as its guidelines.

• Journal of Intelligence and Information Systems
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• v.13 no.3
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• pp.141-160
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• 2007

User interface has been regarded as a crucial issue to increase the acceptance of mobile services. In special, even though to what extent the machine as speaker communicates with human as listener in a timely and polite manner is important, fundamental studies to come up with these issues have been very rare. Hence, the purpose of this paper is to propose a methodology of estimating politeness level in a certain context-aware setting and then to design a context-aware system for polite mobile interface. We will focus on Korean language for the polite level estimation simply because the polite interface would highly depend on cultural and linguistic characteristics. Nested Minkowski aggregation model, which amends Minkowski aggregation model, is adopted as a privacy-preserving similarity evaluation for case retrieval under distributed computing environment such as ubiquitous computing environment. To show the feasibility of the methodology proposed in this paper, simulation-based experiment with drama cases has performed to show the performance of the methodology proposed in this paper.

• Journal of Intelligence and Information Systems
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• v.11 no.3
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• pp.1-23
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• 2005

Personalized reminder systems have to identify the user's current needs dynamically and proactively based on the user's current context. However, need identification methodologies and their feasible architectures for personalized reminder systems have been so far rare. Hence, this paper aims to propose a proactive need awaring mechanism by applying agent, semantic web technologies and RFID-based context subsystem for a personalized reminder system which is one of the supporting systems for a robust ubiquitous service support environment. RescorlaWagner model is adopted as an underlying need awaring theory. We have created a prototype system called NAMA(Need Aware Multi-Agent)-RFID, to demonstrate the feasibility of the methodology and of the mobile settings framework that we propose in this paper. NAMA considers the context, user profile with preferences, and information about currently available services, to discover the user's current needs and then link the user to a set of services, which are implemented as web services. Moreover, to test if the proposed system works in terms of scalability, a simulation was performed and the results are described.

• The Journal of the Korea Contents Association
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• v.11 no.12
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• pp.40-51
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• 2011

The key issues of recommendation systems provide the contents satisfying the interests of users for the huge amounts of contents over internet. The existing recommendation system use the algorithms considering the users' profiles and context information to enhance the exactness of a recommendation. However, the existing recommendation system can't satisfy the requirements of service providers because the business models of service providers is not considered. In this paper, we propose the mobile recommendation system using the composite contexts and the recommendation weights applying the business model of service providers. The proposed system retrieves the contents of the contents providers using composite context information and apply the recommendation weights to recommend the suitable contents for the business models of service providers. Therefore, we provide the contents satisfying the consumption value of users and the business models of service providers to mobile users.

• Journal of Internet Computing and Services
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• v.15 no.6
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• pp.117-124
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• 2014

Cluttered background is a major obstacle in developing salient object detection and tracking system for mobile device captured natural scene video frames. In this paper we propose a context aware feature vector selection model to provide an efficient noise filtering by machine learning based classifiers. Since the context awareness for feature selection is achieved by searching nearest neighborhoods, known as NP hard problem, we apply a fast approximation method with complexity analysis in details. Separability enhancement in feature vector space by adding the context aware feature subsets is studied rigorously using principal component analysis (PCA). Overall performance enhancement is quantified by the statistical measures in terms of the various machine learning models including MLP, SVM, Naïve Bayesian, CART. Summary of computational costs and performance enhancement is also presented.

• Journal of Digital Contents Society
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• v.18 no.3
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• pp.535-542
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• 2017

The ubiquitous computing made it happen to easily take cognizance of context, which includes user's location, status, behavior patterns and surrounding places. And it allows providing the catered service, designed to improve the quality and the interaction between the provider and its customers. The personalized recommendation service needs to obtain logical reasoning to interpret the context information based on user's interests. We researched a model that connects to the practical value to users for their daily life; information about restaurants, based on several mobile contexts that conveys the weather, time, day and location information. We also have made various approaches including the accurate rating data review, the equation of Naïve Bayes to infer user's behavior-patterns, and the recommendable places pre-selected by preference predictive algorithm. This paper joins a vibrant conversation to demonstrate the excellence of this approach that may prevail other previous rating method systems.