• Management & Information Systems Review
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• v.32 no.3
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• pp.107-125
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• 2013

This study deals with a strategic decision making in two level supply chain network design. This study presents more realistic mathematical model than the previous studies by considering simultaneous location of plants and distribution centers, determination of capacity level for both plants and distribution centers, and upper limit condition for numbers of locating plants and distribution centers. This paper tries to help the strategic decision making for two level supply chain network design. For this purpose, three different sized numerical examples are generated and optimal solutions are obtained by applying Excel Solver program. And sensitivity analysis is performed for the biggest sized example problem, which has 10 potential plants, 20 potential distribution centers, and 200 customer zones. After the plants being located are fixed, optimal minimum costs are obtained and compared for each of 7 different numbers of distribution centers to be located. As the number of distribution centers increases, changes in inbound transportation cost and outbound transportation cost can be derived. In case of considering cost as well as customer satisfaction level for two level supply chain network design, the analysis of this changes may help more sophisticated decision making.

• Science of Emotion and Sensibility
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• v.23 no.1
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• pp.57-68
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• 2020

This research investigates how digital design agencies and client companies incorporate design thinking-a human-centered approach to solving difficult problems-into their website development processes. Based on a literature review on the design-thinking-driven web development process, multiple case studies of award-winning website projects were performed by in-depth interviews with key practitioners. Through analyses of these cases, their user-centered approaches for website innovation were identified according to the following four phases: web planning (discovery and defining phases) and web design and development (development and delivery phases). Moreover, distinct approaches of design thinking practices were identified according to two website types: a brand promotion website with a killer brand storytelling approach; and a service channel website with a strategic UI/UX-driven approach. Next, the key success drivers of these website projects were suggested in light of the typical themes of design thinking (i.e., human centeredness, research based, context awareness, and collaboration). Some practical limitations were also found in adopting the design-thinking-driven web development process, such as limited research methods and tools, and insufficient prototyping and experimentation. Along with these limitations, it was also discovered that current digital design agencies still face the following challenges in adopting the design-thinking-driven web development process: building a long-term, playful partnership with clients; leveraging decision-makers' design thinking awareness; and coping with limited resources (design thinking practitioners, budgets, and schedules).

• Asia-Pacific Journal of Business
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• v.12 no.3
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• pp.361-378
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• 2021

Purpose - The purpose of this study is to classify KOSPI listed companies according to their organizational character type based on MBTI. Design/methodology/approach - This study collected 109,989 reviews from an online firm review website, Jobplanet. Using these reviews and the descriptions about organizational character, we conducted document similarity analysis. Doc2Vec technique was hired for the analysis. Findings - First, there are more companies belonging to Extraversion(E), Intuition(N), Feeling(F), and Judging(J) than Introversion(I), Sensing(S), Thinking(T), and Perceiving(P) as organizational character types of MBTI. Second, more companies have EJ and EP as the behavior type and NT and NF as the decision-making type. Third, the top-3 organizational character type of which firms have among 16 types are ENTJ, ENFP, and ENFJ. Finally, companies belonging to the same industry group were found to have similar organizational character. Research implications or Originality - This study provides a noble way to measure organizational character type using firm review big data and document similarity analysis technique. The research results can be practically used for firms in their organizational diagnosis and organizational management, and are meaningful as a basic study for various future studies to empirically analyze the impact of organizational character.

• Journal of Distribution Science
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• v.14 no.9
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• pp.47-64
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• 2016

Purpose - This study reviews the past studies that have researched Vendor Managed Inventory (VMI) as a well-known supply chain collaboration program. The main goals of this study are to figure out how VMI brings significant benefits to the supply chain system and suggest additional areas that future studies would address to discover the true nature of VMI. Research design, data, methodology - This study conducts literature reviews on numerous studies that have researched VMI. The past studies are classified in terms of several main issues that have been commonly addressed by many researchers. This study also identifies three key collaborative features of VMI, which possibly explain why VMI improves the supply chain performance. Results - This study finds out that most past studies focused on a limited research issues about VMI. Many researchers have considered integrated decision making and information sharing to be key features that enables VMI to improve the supply chain performance. Conclusions - Based on the findings from the literature review, this study suggests that future studies on VMI take account of new research issues and pay attention to cost payment that researchers have rarely addressed.

• The Korean Journal of Applied Statistics
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• v.27 no.6
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• pp.1029-1038
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• 2014

Bayesian experimental design is a useful concept in applied statistics for the design of efficient experiments especially if prior knowledge in the experiment is available. However, a theoretical or numerical approach is not simple to implement. We review the concept of a Bayesian experiment approach for linear and nonlinear statistical models. We investigate relationships between prior knowledge and optimal design to identify Bayesian experimental design process characteristics. A balanced design is important if we do not have prior knowledge; however, prior knowledge is important in design and expert opinions should reflect an efficient analysis. Care should be taken if we set a small sample size with a vague improper prior since both Bayesian design and non-Bayesian design provide incorrect solutions.

• Information Systems Review
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• v.4 no.2
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• pp.223-236
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• 2002

In an agent-based system, each agent has its own decision making capability and competes, cooperates, and communicates each other with an agent interface. Virtual manufacturing has characteristics as a typical application area of agent-based system: complex and time-bound decision making and negotiation. The time-boundness influences the choice of decision making models and design of protocols for internal and external negotiation. In this paper, we provide a case study which suggests a time-bound framework for external and internal negotiation between the agents for virtual manufacturing environment. We illustrate decision making model selection strategy and the system architecture of the agent-based system for the complex and time-bound environment.

• Management & Information Systems Review
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• v.5
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• pp.33-59
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• 2000

Problem definition is as important as problem solving in decision making. Decision makers, however, tend to see problem partly or to define it unclearly. The researchers on decision making tend to lay a focus only on the Process of solving the given problem. This dissertation empirically studied the Problem diagnosis and definition in the decision making process. This study developed three kinds of DSS(Decision Support System) for the research and analyzed the effectiveness of the problem diagnosis and definition using DSS developed in this study. The three kinds of DSS are K-T(Kennel and Tregoe) DSS which is a method of table-styled information Presentation, and F-N(Fact-Net) DSS and C-E(Cause and Effect) DSS which are methods of graphic-styled information presentation. The empirical study was conducted twice; the pilot test and the main test. The samples of experiment are 218 students for the pilot test and 259 students for the main test. The author used K-T DSS and F-N DSS for the pilot test, and the revised K-T DSS and C-E DSS for the main test. A questionnaire survey method was included in the main test process The result of the study shows that the group using DSS in problem diagnosis and definition is more effective than the group not using DSS. A table-styled information presentation DSS, K-T, turns out more effective than a graphic-styled information presentation DSS, F-N, K-T DSS and C-E DSS showed no significant differences in the effectiveness in the main test. These results indicate that the use of DSS in the stage of problem diagnosis and definition is very effective and the methods and types of system design are a significant factors for DSS development.

• Fire Science and Engineering
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• v.33 no.5
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• pp.86-93
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• 2019

Previous studies related to evacuation guidance systems are focused on the system construction, and research on manual of the standard evacuation map is insufficient. Therefore, this research is a basic study to establish the standard evacuation map, and analyzed the decision-making time according to the type and size for each component of the evacuation map. Experimental elements were derived through the review of previous studies and legal regulations. After that, decision-making time was analyzed according to the type and size of the component display method. An experiment was conducted to analyze the decision-making time according to the type and size of the component display method. Afterwards, through the statistical test, the evacuation map guidelines for smartphones were proposed.

• Journal of Distribution Science
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• v.11 no.5
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• pp.63-76
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• 2013

Purpose - For the past several decades, behavioral economics or behavioral decision theory has undergone rapid development. This study provides a critical review of the development of behavioral economics with a focus on what are deemed to be core theories in the field. Starting from the utility function proposed by Daniel Bernoulli in the 18th century, the development history of utility functions until the emergence of the prospect theory is thoroughly reviewed. Some of the experimental results violating the traditionally assumed utility function and supporting the prospect theory value function are summarized. The most representative principles of rational choice are transitivity, independence from irrelevant alternatives (IIA), and regularity. The development of behavioral economics has been triggered by finding counter-examples to these principles. Some of the choice behaviors discussed in this study as counter-examples to the traditional theories of rational choice are the St. Petersburg paradox; the Allais paradox; gambling behavior; and the various context effects including the similarity effect, attraction effect, and the compromise effect. The Elimination-by-Aspects (EBA) model, which was proposed as an explanation for the similarity effect, is discussed in detail as well. Based on the literature review and further analysis, this study summarizes the relationship between the context effects, prospect theory, and EBA model. Research design, data, and methodology - This study provides an extensive literature review on several important theories in the field of behavioral decision theory and adds some critical comments to the theories and the relationships among them. This study first reviews the development of utility functions. Daniel Bernoulli introduced the concept of utility function to solve the St. Petersburg paradox. In the mid-20th century, Herbert Simon proposed the "satisficing" heuristic and presented a value function with a shape different from traditional utility functions. This study highlights the strengths and weaknesses of several utility functions proposed until the emergence of the prospect theory value function. Results - This study posits that prospect theory and EBA model are the two most important theories in the field of behavioral decision theory. They can explain various choice behaviors that traditional utility maximization analysis has been unable to. The application of these models to various fields is further increasing nowadays. This study explains how prospect theory and the EBA model can be used to explain the context effects. Conclusions - The traditional economic theory relies on a single variable called "utility" in explaining consumer choice. However, this study argues that, in investigating consumer choice, several other variables should also be considered. These are the similarity among alternatives, an alternative's prototypicality within the category, the dominance relationship between alternatives, and the reference point in evaluating alternatives. Due to the development of behavioral economics, we are now closer to a more complete understanding of consumer choice behavior than in the past when we had only a single tool called utility.

• Journal of Korea Trade
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• v.24 no.7
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• pp.1-28
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• 2020

Purpose - This paper empirically investigates the predictors and main determinants of consumers' ratings of mobile applications in the Google Play Store. Using a linear and nonlinear model comparison to identify the function of users' review, in determining application rating across countries, this study estimates the direct effects of users' reviews on the application rating. In addition, extending our modelling into a sentimental analysis, this paper also aims to explore the effects of review polarity and subjectivity on the application rating, followed by an examination of the moderating effect of user reviews on the polarity-rating and subjectivity-rating relationships. Design/methodology - Our empirical model considers nonlinear association as well as linear causality between features and targets. This study employs competing theoretical frameworks - multiple regression, decision-tree and neural network models - to identify the predictors and main determinants of app ratings, using data from the Google Play Store. Using a cross-validation method, our analysis investigates the direct and moderating effects of predictors and main determinants of application ratings in a global app market. Findings - The main findings of this study can be summarized as follows: the number of user's review is positively associated with the ratings of a given app and it positively moderates the polarity-rating relationship. Applying the review polarity measured by a sentimental analysis to the modelling, it was found that the polarity is not significantly associated with the rating. This result best applies to the function of both positive and negative reviews in playing a word-of-mouth role, as well as serving as a channel for communication, leading to product innovation. Originality/value - Applying a proxy measured by binomial figures, previous studies have predominantly focused on positive and negative sentiment in examining the determinants of app ratings, assuming that they are significantly associated. Given the constraints to measurement of sentiment in current research, this paper employs sentimental analysis to measure the real integer for users' polarity and subjectivity. This paper also seeks to compare the suitability of three distinct models - linear regression, decision-tree and neural network models. Although a comparison between methodologies has long been considered important to the empirical approach, it has hitherto been underexplored in studies on the app market.