• 유통과학연구
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• 제20권6호
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• pp.109-123
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• 2022

Purpose: This research presents a practical tool aimed at increasing collaboration between designers and marketers for effective retail space branding. We present a design-related information processing model (DIP Model), which is a schematic map that includes cognitive theories which have design applications to retail space branding. Research design, data and methodology: Through literature review and practitioner opinion survey, 43 theories pertaining to the brand communication in retail spaces were selected, and design applications of the theories were analysed through field trips to stores of global brands. Results: The DIP Model consists of two axes: the information processing axis (i.e., encoding vsretrieval) and the regulatory focus axis(i.e., promotion vs prevention). Theories related to information processing axis are theories that facilitate the encoding and retrieval of information as intended by the company. Theories related to regulatory focus axis are theories that reinforce positive cognition and prevent negative cognition regarding the brand. Conclusions: The DIP Model is developed as a tool to categorise cognitive theories that are applicable to the design of brand communication in retail spaces. As such, the model can provide a better understanding of the role of behavioural design, with the aim of building stronger brands in retail spaces.

• The Journal of Asian Finance, Economics and Business
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• 제9권9호
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• pp.105-114
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• 2022

Financial markets have long been known to be prone to behavioral biases. One such behavioural bias that is consequential yet pervasive in financial markets is the herd effect. The objective of this study is to determine whether or not there exist herd behaviour in the new and bourgeoning Decentralized Finance (DeFi) Tokens market. This is accomplished by using daily returns of 22 DeFi tokens from January 29, 2017 to August 19, 2021, and the Cross-sectional Absolute Deviation (CSAD) of market returns to capture herd behavior. The results fail to provide any evidence of herding in the DeFi token market on bullish days, that is days for which the average market returns is positive. For bearish days however, that is days for which the market returns is negative, our empirical findings point to the presence of adverse herding in the DeFi token market. This phenomenon can be explained to some extent by the investor composition of the DeFi market. The DeFi token space is a growth market dominated by experts and/or enthusiasts who are insulated against the temptation and panic of negative market swings by the level of market and technical information they possess on the assets they invest.

• The Journal of Asian Finance, Economics and Business
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• 제9권2호
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• pp.395-407
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• 2022

This study examines the emotional undercurrents of individual investors. Earlier finance theory was based on the assumption that investors would act rationally. According to the findings, it is the investors' collective expectations and anxieties that have an impact on their investment fortunes. This necessitates a high level of emotional stability on the side of the investors. Investors must have a firm foundation in financial literacy to have the requisite level of emotional stability. This study aims to add to existing theory and practice by analyzing whether investors who have received business-related education are less emotional than those who have not. For the survey inquiry of individual investors, 'fear' and 'love' are considered among the emotional undercurrents of individual investors. The research is based on a survey of 875 individual investors in India, 342 of whom had a business background and the others have none. It has been discovered that no investor, regardless of their level of business education, is emotion-free. Investors with and without a business education display emotional stability in many behavioral aspects of fear and love to varying degrees.

• 생물정신의학
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• 제29권1호
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• pp.1-8
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• 2022

Objectives In regard to the social competition hypothesis, depression is viewed as an involuntary defeat strategy. A previous study has demonstrated that adaptation in microenvironments can result in a wide range of behavioural patterns including defense activation disorders. Using a simulation model with evolutionary ecological agents, we explore how the fitness of various defence activation traits has changed over time in different environments with high and low social mobility. Methods The Evolutionary Ecological Model of Defence Activation Disorder, which is based on the Marginal Value Theorem, was used to examine changes in relative fitness for individuals with defensive activation disorders after adjusting for social mobility. Results Our study examined the effects of social mobility on fitness by varying the d-values, a measure of depression in the model. With a decline in social mobility, the level of fitness of individuals with high levels of defense activation decreased. We gained insight into the evolutionary influence of varying levels of social mobility on individuals' degrees of depression. In the context of a highly stratified society, the results support a mismatch hypothesis which states that high levels of defence are detrimental. Conclusions Despite the fact that niche specialization in habitats composed of multiple microenvironments can result in diverse levels of defensive activation being evolutionary strategies for stability, decreased social mobility may lead to a decrease in fitness of individuals with highly activated defence modules. There may be a reason behind the epidemic of depression in modern society.

• International Journal of Computer Science & Network Security
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• 제23권8호
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• pp.190-198
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• 2023

To enhance customer satisfaction for higher profits, an e-commerce sector can establish a continuous relationship and acquire new customers. Utilize machine-learning models to analyse their customer's behavioural evidence to produce their competitive advantage to the e-commerce platform by helping to improve overall satisfaction. These models will forecast customers who will churn and churn causes. Forecasts are used to build unique business strategies and services offers. This work is intended to develop a machine-learning model that can accurately forecast retainable customers of the entire e-commerce customer data. Developing predictive models classifying different imbalanced data effectively is a major challenge in collected data and machine learning algorithms. Build a machine learning model for solving class imbalance and forecast customers. The satisfaction accuracy is used for this research as evaluation metrics. This paper aims to enable to evaluate the use of different machine learning models utilized to forecast satisfaction. For this research paper are selected three analytical methods come from various classifications of learning. Classifier Selection, the efficiency of various classifiers like Random Forest, Logistic Regression, SVM, and Gradient Boosting Algorithm. Models have been used for a dataset of 8000 records of e-commerce websites and apps. Results indicate the best accuracy in determining satisfaction class with both gradient-boosting algorithm classifications. The results showed maximum accuracy compared to other algorithms, including Gradient Boosting Algorithm, Support Vector Machine Algorithm, Random Forest Algorithm, and logistic regression Algorithm. The best model developed for this paper to forecast satisfaction customers and accuracy achieve 88 %.

• Asia Marketing Journal
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• 제17권4호
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• pp.43-61
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• 2016

This paper has identified some theoretical reasons and empirical evidence for negative scores that occur in Japan and Korea or unstable NPS scores that can be experienced. A psychological analysis of NPS results sheds light on the validity of the negative NPS scores that are often found in Japan and Korea. Usually customer experience surveys utilize a "single stimulus" such as the "company" or the "company's products / services." However, in the case of the "recommendation to friend" question of the NPS system there are two stimuli namely the "company product/service" and the influence of "friends." Hence, the survey outcomes from this question can be very different when compared with other single stimulus questions such as "overall satisfaction" or "repurchase." Japanese and Korean people may have a positive attitude towards the company but they will provide low NPS scores because they are reflecting that they would not run the risk of ruining their relationships with their friends by making a recommendation. As a result, in the NPS system these people will be labeled as "detractors" when in fact they are "ambivalent customers." Using several Japanese and Korean based marketing research industry examples and case studies, different strategies are proposed to address the issue of negative scores in the NPS system in Japan and Korea. The Customers Psyche appears to be the key determinant factors for both types of behavioural items (items with a single stimulus as well as items with two stimuli).

• Physical Therapy Rehabilitation Science
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• 제11권4호
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• pp.535-545
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• 2022

Objective: This study was conducted to identify predictive factors of physical activity in total hip arthroplasty patients, and to provide basic data for the developing physical activity promotion program for total hip arthroplasty patients. Design: Descriptive correlational research. Methods: Data were collected from August 2017 to May 2018. Surveys were distributed to 60 patients in a G university hospital located at J city, Gyeongsangnam-do. Data were analyzed by frequency, mean, standard deviation, t-test, ANOVA, Pearson's correlation coefficient, multiple regression analysis using SPSS 24 Win program. Results: The variables affecting the 4-week physical activity after discharge were age (β=.07), residence after discharge (β=-.22), cerebrovascular disease (β=-.13), mental and behavioural disease (β=-.11), taking antibiotic (β=-.26), walking ability (β=.41), nutritional status (β=.25), depression (β=.05). The eight variables accounted for 39.4% in the 4-week physical activity (F=4.49 p=.001). The variables affecting the 8-week physical activity after discharge were age (β=.06), waking ability (β=.34), nutritional status (β=.20), exercise self-efficacy (β=.05), depression (β=-.05). The six variables accounted for 28.0% in the 8-week physical activity (F=4.58, p<.001). Conclusions: The walking ability in discharge important to improve the physical activity, there is a need to develop an program to improve walking ability before discharge, in total hip arthroplasty. There is a need to develop a physical activity program to consistently participate in a community.

• 유통과학연구
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• 제20권6호
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• pp.75-86
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• 2022

Purpose: This research aims to provide empirical evidence on the impact of digital literacy on behavioural intention regarding using technology for distribution of higher education. Design, Methodology, and Approach: Quantitative analysis was carried out using Covariance-Based Structural Equation Model with data collected from 901 students who fully experienced 2-year study online at different universities in Vietnam. The structural model was built with digital literacy as the primary indicator and other variables were included based on modified version of Unified Theory of Acceptance and Use of Technology (UTAUT2) by adopting performance expectancy, effort expectancy, social influence, habit, and hedonic motivation variables specifically for education sector. Self-efficacy was added to eliminate possible bias in technology acceptance. Results: From the results of model estimation, digital literacy presented positive impact on the online distribution of higher education in Vietnam. The mediating effects of various indicators such as performance expectancy, effort expectancy, social influence, habit, hedonic motivation, and self-efficacy are significantly determined by research model. Conclusion: The higher level of digital literacy of the students, the more likely that they will use technology in higher education study, especially online learning. Additionally, the mediating effects of indicators from the UTAUT2 theoretical model were also evident to be positively significant.

• Structural Engineering and Mechanics
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• 제86권4호
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• pp.503-518
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• 2023

In tall constructions, the outriggers are regarded as a structural part capable of effectively resisting lateral loads. This study analyses the efficacy of hybrid outrigger system in high rise RCC building for various structural parameters identified. For variations in α, which is defined as the ratio of the relative flexural stiffness of the core to the axial rigidity of the column, static and dynamic analyses of hybrid outrigger system having a virtual and a conventional outrigger at two distinct levels were conducted in the present study. An investigation on the optimal outrigger position was performed by taking the results from absolute maximum inter storey drift ratio (ISD_max), roof acceleration (acc_roof), roof displacement (disp_roof), and base bending moment under both wind and seismic loads on analytical models having 40, 60 and 80 storeys. An ideal performance index parameter was introduced and was utilized to obtain the optimal position of the hybrid outrigger system considering the combined response of ISD_max, acc_roof, disp_roof and, criteria required for the structure under wind and seismic loads. According to the behavioural study, increasing the column area and outrigger arm length will maximise the performance of the hybrid outrigger system. The analysis results are summarized in a flowchart which provides the optimal positions obtained for each dependent parameter and based on ideal performance index which can be used to make initial suggestions for installing a hybrid outrigger system.

• Coupled systems mechanics
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• 제12권2호
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• pp.167-181
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• 2023

The determination of the blast protection level and the corresponding minimum load-bearing capacity for a laminated glass (LG) window is of crucial importance for safety and security design purposes. In this paper, the focus is given to the window response under near-field blast loading, i.e., where relatively small explosives would be activated close to the target, representative of attack scenarios using small commercial drones. In general, the assessment of the load-bearing capacity of a window is based on complex and expensive experiments, which can be conducted for a small number of configurations. On the other hand, nowadays, validated numerical simulations tools based on the Finite Element Method (FEM) are available to partially substitute the physical tests for the assessment of the performance of various LG systems, especially for the far-field blast loading. However, very little literature is available on the LG window performance under near-field blast loads, which differs from far-field situations in two points: i) the duration of the load is very short, since the blast wavelength tends to increase with the distance and ii) the load distribution is not uniform over the window surface, as opposed to the almost plane wave configuration for far-field configurations. Therefore, the current study focuses on the performance assessment and structural behaviour of LG windows under near-field blasts. Typical behavioural trends are investigated, by taking into account possible relevant damage mechanisms in the LG window components, while size effects for target LG windows are also addressed under a multitude of blast loading configurations.