• The Journal of Asian Finance, Economics and Business
• /
• 제8권3호
• /
• pp.717-729
• /
• 2021

This paper examines the efficacy of the default risk factor in an emerging market context using the Fama-French five-factor model. Our aim is to test whether the Fama-French five-factor model augmented with a default risk factor improves the predictability of returns of portfolios sorted on the firm's characteristics as well as on industry. The default risk factor is constructed by estimating the probability of default using a hybrid version of dynamic panel probit and artificial neural network (ANN) to proxy default risk. This study also provides evidence on the temporal stability of risk premiums obtained using the Fama-MacBeth approach. Using a sample of 3,806 firm-year observations on non-financial listed companies of Pakistan over 2006-2015 we found that the augmented model performed better when tested across size-investment-default sorted portfolios. The investment factor contains some default-related information, but default risk is independently priced and bears a significantly positive risk premium. The risk premiums are also found temporally stable over the full sample and more recent sample period 2010-2015 as evidence by the Fama-MacBeth regressions. The finding suggests that the default risk factor is not a useless factor and due to mispricing, default risk anomaly prevails in the Pakistani equity market.

• The Journal of Asian Finance, Economics and Business
• /
• 제9권4호
• /
• pp.381-389
• /
• 2022

Studies examining the interplay between brand transgression and brand forgiveness is notably sparse especially in the context of Southeast Asian banking customers. The purpose of this research is to add to the existing literature by examining the impact of brand transgression, which is represented by negative past experience image incongruence, and corporate wrongdoing on brand forgiveness among Islamic banking customers in Malaysia. The increasing surge in interest in unfavorable brand relationships has sparked concerns about its impact on brand forgiveness. As a result, this theoretical argument, which lacks empirical proof, has to be statistically tested. The current study was conducted utilizing a non-probability purposive sampling technique among clients in the Klang Valley who had poor experiences with Islamic banking services. Data analysis included descriptive statistics, exploratory factor analysis, and multiple regression on a total of 211 valid replies. The findings show that two elements of brand transgression, image inconsistency, and corporate wrongdoing, have a major impact on brand forgiveness. However, the other dimension namely negative past experience was found to be non-significant to brand forgiveness. Research implications and directions for future studies are also discussed in this paper.

• 아태비즈니스연구
• /
• 제12권1호
• /
• pp.25-39
• /
• 2021

Purpose - This study aims to examine whether family firm governance is related to long-term corporate survival. To find out whether and why family firms have higher chances of long-term survival compared to non family firms, this study analyzes the relationship between some governance characteristics that are prevalent in family firms and corporate long-term viability. Design/methodology/approach - This study utilizes a sample of 285 family firms listed on the Korea Stock Exchange (KSE) to probe the influence of governance characteristics on corporate survival. This study conducts Cox proportional hazard regression analysis to estimate the influences on the survival duration. Findings - The results indicate that firms with particular governance characteristics show higher long-term survivability. Specifically, the probability of firm's long-term survival is increased when the CEO is the largest shareholder, which may be related to CEO's stewardship attitudes. Research implications or Originality - This study has significance in that it examines the direct causal variables that enhance long-term corporate viability through a large scale empirical examination. Also, the study findings provide some clues as to why certain family firms outlive non-family firms.

• Journal of Multimedia Information System
• /
• 제8권4호
• /
• pp.259-266
• /
• 2021

Security vulnerabilities have been reported in major design software systems such as Adobe Photoshop and Illustrator, which are recognized as de facto standard design tools in most of the design industries. Companies need to evaluate and manage their risk levels posed by those vulnerabilities, so that they could mitigate the potential security bridges in advance. In general, security vulnerabilities are discovered throughout their life cycles repeatedly if software systems are continually used. Hence, in this study, we empirically analyze risk levels for the three major graphical design software systems, namely Photoshop, Illustrator and GIMP with respect to a software vulnerability discovery model. The analysis reveals that the Alhazmi-Malaiya Logistic model tends to describe the vulnerability discovery patterns significantly. This indicates that the vulnerability discovery model makes it possible to predict vulnerability discovery in advance for the software systems. Also, we found that none of the examined vulnerabilities requires even a single authentication step for successful attacks, which suggests that adding an authentication process in software systems dramatically reduce the probability of exploitations. The analysis also discloses that, for all the three software systems, the predictions with evenly distributed and daily based datasets perform better than the estimations with the datasets of vulnerability reporting dates only. The observed outcome from the analysis allows software development managers to prepare proactively for a hostile environment by deploying necessary resources before the expected time of vulnerability discovery. In addition, it can periodically remind designers who use the software systems to be aware of security risk, related to their digital work environments.

• 응용통계연구
• /
• 제35권3호
• /
• pp.347-356
• /
• 2022

본 논문에서는 금융 시계열 비대칭 변동성을 모형화하기 위해서 다중 임계점을 가진 비대칭-ARCH 점화식(A-ARCH(1))을 제안하고 있다. 특히 임계점이 두 개인 간단한 모형에 초점을 맞추어 설명하고 있으며 미국 S&P500 자료 분석을 통해 예시하였다. 다양한 A-ARCH(1) 모형의 예측력 비교를 위해 모수적-붓스트랩을 활용하여 예측오차의 평가 및 예측구간의 정확도를 설명하였다.

• The Journal of Asian Finance, Economics and Business
• /
• 제9권9호
• /
• pp.205-216
• /
• 2022

This study investigates the effect of serv-qual and reputation on customer loyalty through the trust of deposit customers in Micro Finance Institutions. The population was deposit customers at BMT distributed into 5 provinces of the Special Region of Yogyakarta, and a survey was conducted from January 2021 to February 2022. The probability random sampling technique was used to select the final sample, and a total of 221 responses were collected using a questionnaire. Technical data analysis was done using the Structural Equation Modeling (SEM), supported by AMOS 22.0 program. The results showed that serv-qual and reputation have a positive and significant impact on the trust and loyalty of deposit customers at BMT. Customers positively and significantly impact the relationship between serv-qual and reputation on customer loyalty. The biggest contribution to loyalty was generated by the variable customer trust (0.399), followed by service quality (0.359) and reputation (0.166). Micro Finance Institution needs to improve the management of deposit customers by improving serv-qual, reputation, and customer trust and conduct comparative research between conventional financial institutions and other informal financial service institutions.

• 산경연구논집
• /
• 제13권11호
• /
• pp.1-10
• /
• 2022

Purpose: This study measures the influence of facilitating conditions on employees' attitudes towards the adoption of big data analytics by selected medical aid organizations in Durban. In the health care sector, there are various sources of big data such as patients' medical records, medical examination results, and pharmacy prescriptions. Several organizations take the benefits of big data to improve their performance and productivity. Research design, data, and methodology: A survey research strategy was conducted on some selected medical aid organizations. A non-probability sampling and the purposive sampling technique were adopted in this study. The collected data was analysed using version 23 of Statistical Package for Social Science (SPSS) Results: the results show that the "facilitating conditions" have a positive influence on employees' attitudes in the adoption of big data analytics Conclusions: The findings of this study provide empirical and scientific contributions of the facilitating conditions issues regarding employee attitudes toward big data analytics adoption. The findings of this study will add to the body of knowledge in this field and raise awareness, which will spur further research, particularly in developing countries.

• 반도체디스플레이기술학회지
• /
• 제22권2호
• /
• pp.50-55
• /
• 2023

Due to the unavailability of global positioning system (GPS) indoors, various indoor pedestrian positioning methods have been designed to estimate the position of the user using received signal strength (RSS) measurements from radio beacons, such as wireless fidelity (WiFi) access points and Bluetooth low energy (BLE) beacons. In indoor environments, radio-frequency (RF) signals are unpredictable and change over space and time because of multipath associated with reflection and refraction, shadow fading caused by obstacles, and interference among different devices using the same frequencies. Therefore, the outliers in the positional information obtained from the indoor positioning method based on RSS measurements occur often. For this reason, the performance of the positioning method can be degraded by the characteristics of the RF signal. To resolve this issue, a map-matching (MM) algorithm based on maximum probability (MP) estimation is applied to the indoor positioning method in this study. The MM algorithm locates the aberrant position of the user estimated by the positioning method within the limits of the adjacent pedestrian passages. Empirical experiments show that the positioning method can achieve higher positioning accuracy by leveraging the MM algorithm.

• 융합경영연구
• /
• 제3권4호
• /
• pp.5-11
• /
• 2015

The study examined the socio-economic factors influencing the participation of rural farming households in barter trade in Ondo State, Nigeria. The objectives were to compare the socio-economic characteristics of the participants and non-participants in barter trade, analyze the preference for barter trade and identify the constraints to it. Also, the factors affecting respondents' participation in barter trade were identified. Empirical results indicated that there were significant differences in the socio-economic characteristics of the participants and non-participants in barter trade. The SWOT analysis showed that possession of agrarian attributes by the locality where the trade is practiced was the strongest factor ensuring the survival of barter in the study area. Double coincidence of wants was found to be the most prevailing weakness associated with barter while the major reason for participation by some households was that the quantity of commodities received is usually higher compared with cash transactions. Transportation cost to barter markets was found to be the greatest threat to the continued existence of barter trade in the area. The results of the Probit model showed that age, household size, transportation cost to cash markets, farm size, distance to barter markets, and formal education significantly affected the probability participating in barter trade.

• 국제학술발표논문집
• /
• The 4th International Conference on Construction Engineering and Project Management Organized by the University of New South Wales
• /
• pp.58-65
• /
• 2011

Construction Productivity is one of the most important elements in construction management. It is used in construction process scheduling and cost management, which are significant sector in construction management. It is important to make appropriate schedule and monitor how works are done within schedule. But construction project contains uncertainty and inexactitude, modifying construction schedule is being an issue to manage construction works well. Even though prediction and monitoring of productivity can be principal activity, it is hard to predict productivity with manager's experience and a standard of estimate. A large number of factors influencing productivity, such as drawing, construction method, weather, labor, material, equipment, etc. But current calculation of productivity depends on empirical probability, not consider difference of each influencing factor. In this research, the aim is to present a productivity predicting regression model of form work, which includes effectiveness of influences factors. 5 variables existed inside form work are selected by interview and site research based on literature review of existed various productivity influencing factors. The effectiveness and correlation of productivity influencing factors are analyzed by statistical approach, and it is used to make productivity regression model. The finding of this research will improves monitoring and controlling of project schedule in construction phase.