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INDONESIA
Emerging Science Journal
Published by Ital Publication
ISSN : 26109182     EISSN : -     DOI : -
Core Subject : Social,
Environmental Science
Emerging Science Journal is not limited to a specific aspect of science and engineering but is instead devoted to a wide range of subfields in the engineering and sciences. While it encourages a broad spectrum of contribution in the engineering and sciences. Articles of interdisciplinary nature are particularly welcome.
Arjuna Subject : -
Articles 17 Documents
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Search results for , issue "Vol 6, No 5 (2022): October" : 17 Documents clear
Green Human Resources Practices and Person-Organization Fit: The Moderating Role of the Personal Environmental Commitment Francisco Cesário; Ana Sabino; Ana Moreira; Teresa Azevedo
Emerging Science Journal Vol 6, No 5 (2022): October
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/ESJ-2022-06-05-02

Abstract

Based on the 2030 Agenda of the United Nations (UN), where 17 Sustainable Development Goals (SDGs) are identified, the present study aims to (1) propose a measure for the perception of green human resources management practices; (2) investigate its relationship with the employees’ person-organization fit, and (3) analyze the moderating role of personal environmental commitment in the relationship between the perception of green human resources management practices and employees’ person-organization fit. A quantitative and hypothetical-deductive approach was used, and a sample of 204 Portuguese employees responded to an online questionnaire. The results showed (1) that the proposed measure for the perception of green HR practices was adapted to the Portuguese population and showed excellent internal consistency; (2) a significant and positive relationship between perceived green HR practices and person-organization fit; and (3) that this relationship can be moderated by high personal environmental commitment. The study presents novelty and contributes to the existing literature concerning green HR practices by proposing an adapted measure, relating it to person-organization fit, and verifying the moderated role of personal environmental commitment. Thus, the effective implementation of green HRM practices is highlighted to promote positive consequences in the organization and the employees. Doi: 10.28991/ESJ-2022-06-05-02 Full Text: PDF
Understanding the Socialist-Market Economy in Vietnam Ngoc Anh Nguyen
Emerging Science Journal Vol 6, No 5 (2022): October
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/ESJ-2022-06-05-03

Abstract

The economic reform started in 1986 has transformed Vietnam from one of the world’s poorest countries 35 years ago to a lower middle-income country (MIC) in 2010. Poverty rates dropped from 70% in 1986 to below 2% in 2021. The transition from a central planning system to a socialist market economy is the fundamental underlying factor of Vietnam's success. Using the historical institutional framework that Lee (2018) [1] developed, this study aims to explore the country’s transition from a central planning system to a socialist market economy over the past three decades. The findings demonstrate that the country’s transition to a socialist market economy has been taking a gradualism and dualism path like China. In addition, the study also illustrates how the economic reform and globalization processes pushed the institutional transformation in Vietnam to meet the demands of multiple economic sectors and ownerships as well as accommodate international commitments that the country entered. Finally, Vietnam has been cautious in its political reform over the past few decades. Yet, this is inevitable as a result of the country’s socio-economic development process as well as the global and regional rapid changing context. The implications for Vietnam include: (i) Vietnam needs to transform its growth model toward a knowledge-based, higher-added-value, and more environmentally-friendly pattern; (ii) while there is significant progress in institutional transformation, bottlenecks and challenges remain. This should be addressed effectively to unlock the country’s potential; (iii) political system reform is inevitable as conditions are mature. Domestic demands and international requirements are putting increasing pressure on the changes. However, this process will likely move forward and take place within the political system rather than by civil society or outsiders. Doi: 10.28991/ESJ-2022-06-05-03 Full Text: PDF
Turning Pirates into Subscribers: A Status Quo Bias Perspective on Online Movie Service Switching Intention Panca O. Hadi Putra; Muhammad Imam Santosa; Ika Chandra Hapsari; Achmad Nizar Hidayanto; Sherah Kurnia
Emerging Science Journal Vol 6, No 5 (2022): October
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/ESJ-2022-06-05-06

Abstract

This study aims to analyze the factors that influence a person's intention to use a subscription-based streaming service application using the perspective of the inertia of piracy movie application users. This study investigates the factors that affect the inertia of movie piracy application users. The theory used is a combination of the status quo bias theory and coping theory. This research uses a quantitative approach and an online survey method for data collection. Data collection resulted in 378 responses that were subsequently analyzed using the covariance-based structural equation modeling (CB-SEM) technique. It was found that inertia (the level of user inertia) negatively affects intention to use (the intention to use a subscription-based streaming service application) and convenience. In addition, convenience, perceived controllability (a person's level of control over the application), and morality positively influence intention to use. Furthermore, it was also found that perceived cost and personalization do not affect the intention to use. Inertia is also positively and significantly influenced by the transition cost (effort to move). The factors that have the highest correlation values are transition cost and inertia. Doi: 10.28991/ESJ-2022-06-05-06 Full Text: PDF
Emerging Technological Methods for Effective Farming by Cloud Computing and IoT A. R. Abdul Rajak
Emerging Science Journal Vol 6, No 5 (2022): October
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/ESJ-2022-06-05-07

Abstract

Agriculture provides a solution to the vast majority of problems that threaten human existence. When it comes to agriculture, new or contemporary technology can have a significant impact on a number of factors, including how much food is produced and how long it stays edible. The application of best management practices, for instance, is very common these days in the quest to improve agriculture. New hybrids are resistant to illnesses, use fewer pesticides, have natural defenses against pests, and may be grown in methods that minimize the number of diseases and pests that can affect them. Plants are capable of producing oxygen and medicines in addition to the food that they provide. Consequently, agriculture depends on plants that are in good health. A plant needs water, sunlight, and crucial fertilizer in order to receive the nutrients it needs to have a healthy plant. So, it is necessary to keep an eye on the health of the plant. The article discusses various technological solutions that can be implemented to automate the plant monitoring system. The Internet of Things and cloud computing are two technologies that are contributing to the development of intelligent technology by supplanting traditional agricultural practices. This clever device checks on the well-being of the plants. In order to enable intelligent agriculture, the technology relies on sensors that are dependent on IoT sensors. These sensors monitor the temperature, soil moisture, intensity of the sun's light, air quality value of the soil, vibration, and humidity in the immediate environment of the plant. The networking of these sensors ensures that the plant will continue to be healthy and will function in the appropriate manner. The findings that have been obtained up to this point are encouraging for the continuance of this strategy, which results in the highest possible profit for farmers. Doi: 10.28991/ESJ-2022-06-05-07 Full Text: PDF
Assessing Blockchain Adoption in Supply Chain Management, Antecedent of Technology Readiness, Knowledge Sharing and Trading Need Athapol Ruangkanjanases; Taqwa Hariguna; Ade Maharini Adiandari; Khaled Mofawiz Alfawaz
Emerging Science Journal Vol 6, No 5 (2022): October
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/ESJ-2022-06-05-01

Abstract

The present research aimed to establish a framework integrating the concept of technology readiness with variables that accomplished the blockchain adoption theory to identify the impact of blockchain adoption on supply chain transparency, blockchain transparency, and supply chain performance. The methodology used was quantitative with PLS-SEM as the analysis method. There were 295 validated datasets used. The procedure of data collection involved questionnaires. The key finding of the research confirmed the six proposed hypotheses. It was also confirmed that technology readiness, knowledge sharing, and trading needs were significant for the profitability of blockchain technology adoption in supply chain management. On the other hand, blockchain adoption played a significant role in supply chain transparency, blockchain transparency, and supply chain performance. The novelty of this research is in the integration of technology readiness into blockchain in the field of supply chain management. This research can be used to improve and analyze the success rate of blockchain adoption in supply chain management systems. The findings of this study contribute to several aspects, namely practical and academic implications, by providing more insights that correlate with blockchain integration into supply chain management systems. Doi: 10.28991/ESJ-2022-06-05-01 Full Text: PDF
The Impact of Macroeconomic Factors on Non-performing Loans in the Western Balkans Adelina Gashi; Saranda Tafa; Roberta Bajrami
Emerging Science Journal Vol 6, No 5 (2022): October
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/ESJ-2022-06-05-08

Abstract

This paper analyzes the relationship of macroeconomic factors to the level of non-performing loans (NPLs) using the econometric models GMM, the Fixed Effect model, and the Random Effect model. This study aims to identify macroeconomic factors at the level of non-performing loans in the Western Balkans, measure their impact on non-performing loans, and thus fill the gap that exists between macroeconomic factors (consisting of economic growth) and those with more impact on NPLs. The methodology used to carry out this research was desk research. We used World Bank data from 2000–2019, processed with STATA software. Results show that macroeconomic factors have an impact on non-performing loans. It also proves that even when interacting with other variables, the level of bad debt has not been completely eliminated, despite economic growth in many countries. Third, throughout the study period, fixed effects estimates show that variables are not significant in a static context. According to the findings, the annual rates of GDP growth, final government consumption, the real interest rate, gross domestic savings, and the unemployment rate all have a favorable impact on NPLs. This research contributes to a deeper understanding of the relationship between macroeconomic factors and non-performing loans in the Western Balkans. Based on this, to help reduce loan risk and bad debt by the proper criteria, we propose a series of policy implications. These implications aim to improve the efficiency of banks in particular and the banking system as a whole. Doi: 10.28991/ESJ-2022-06-05-08 Full Text: PDF
Thermal Regeneration and Reuse of Carbon and Glass Fibers from Waste Composites Alexey V. Nistratov; Natalya N. Klimenko; Igor V. Pustynnikov; Long Kim Vu
Emerging Science Journal Vol 6, No 5 (2022): October
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/ESJ-2022-06-05-04

Abstract

This article aims to develop a method for regenerating and reusing carbon and glass fibers extracted from unrecyclable scraps of carbon plastics, printer parts, and laminating coating. A comparison of known methods of fiber regeneration revealed the advantages of thermal treatment: absence of costs of reagents and complex equipment; better preservation of composition; and strength of fibers. Based on the results of thermographic analysis of wastes in nitrogen and air, the destruction temperatures of their organic matrices were determined (200-460°С), and the use of calcination instead of pyrolysis was justified. The appearance and surface quality of the regenerated fibers are characterized by optical and electron microscopy. It has been established that quantitative extraction of pure carbon and glass fibers from waste crushed to 1 cm is efficient by their calcination at 700 °C for 0.5 h and 500 °C for 1 h, respectively. The principle of creating new composites with the obtained fibers based on the similarity of their composition and binding materials (matrices) has been proposed. It was shown that the introduction of 1 wt% of fibers into slag blocks and active carbon pellets considerably increases their compressive strength, but the bending strength does not change due to dispersed reinforcement. Possible improvement of mechanical properties of products requires reagent treatment of the fiber surface or the introduction of binder additives. Calculations show that the developed method of recycling composite waste can produce 2.3 tons/hour of reinforced building materials that are good for the environment and the economy, excluding expenses for landfill waste disposal and reducing the cost of the product by replacing the primary fiber for the secondary one. Doi: 10.28991/ESJ-2022-06-05-04 Full Text: PDF
A YOLO Detector Providing Fast and Accurate Pupil Center Estimation using Regions Surrounding a Pupil Wattanapong Kurdthongmee; Piyadhida Kurdthongmee; Korrakot Suwannarat; Jeremy K. Kiplagat
Emerging Science Journal Vol 6, No 5 (2022): October
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/ESJ-2022-06-05-05

Abstract

Eye-tracking technology has many useful applications, including Virtual Reality (VR) devices, Augmented Reality (AR) devices, and assistive technology. The main objective of eye-tracking technology is to detect eye position and track eye movements. It is possible to determine the eye position when the pupil center is detected. In this paper, a deep learning-based approach to the detection of pupil centers from webcam images is presented. As opposed to all previous approaches to object detection based on training the detector with objects to be detected, our object detector was trained with both the region surrounding a pupil and the region between an eye and the region surrounding a pupil. The latter set of regions has been found to increase the overall detection accuracy. A novel post-processing algorithm is also presented to estimate the pupil center from all the detected regions. To achieve real-time performance, we have adopted the tiny architecture of YOLOv3, which has 23 layers and can be executed without requiring a GPU accelerator. To train the detectors, different variations of regions covering a pupil and an eye were used, as well as expanding regions surrounding a pupil and an eye. The PUPPIE dataset was used as the primary input for training the detector. The setting with the best detection accuracy was applied to all publicly available datasets: I2Head, MPIIGaze, and U2Eyes. In terms of accuracy, the results indicate that pupil center estimation is comparable to the state-of-the-art approach. It achieves pupil center estimation errors below the size of a constricted pupil in more than 98.24% of images. Furthermore, the detection time is 2.8 times faster than the state-of-the-art approach. Doi: 10.28991/ESJ-2022-06-05-05 Full Text: PDF
Deep Learning Based Gait Recognition Using Convolutional Neural Network in the COVID-19 Pandemic Md Shohel Sayeed; Pa Pa Min; Md Ahsanul Bari
Emerging Science Journal Vol 6, No 5 (2022): October
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/ESJ-2022-06-05-012

Abstract

Gait recognition is the behavioral biometric trait that tracks humans based on their walking motion. It has gained attention because of its non-invasive and unobtrusive behaviors and applicable to the different application area. In this paper, we target model-free gait recognition with the deep learning approach for the Muslim community in the COVID-19 pandemic. The different convolutional neural network architectures (CNN) are examined by using the spatio-temporal gait representation called Gait Energy Images (GEI). We explored both the identification and verification problems to determine the suitability of the proposed CNN frameworks. In gait recognition, the intraclass variation is larger than the inter-class variation because of the shooting view, the walking speed, the wearing condition, and so on. To tackle this challenge, the verification framework is more suitable for the 1:1 association of gait recognition. As for the verification problem, we implemented the Siamese network with the parallel CNN architecture. All the proposed methods are tested against the public gait datasets called OUISIR-LP and OUISIR-MVLP to determine the identification and verification performance in terms of recognition accuracy and error rate. Doi: 10.28991/ESJ-2022-06-05-012 Full Text: PDF
Digital Disconnection as an Opportunity for the Tourism Business: A Bibliometric Analysis Juan F. Arenas-Escaso; José A. Folgado-Fernández; Pedro R. Palos-Sanchez
Emerging Science Journal Vol 6, No 5 (2022): October
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/ESJ-2022-06-05-013

Abstract

The aim of this study is to carry out a bibliometric review of the existing research on digital disconnection and Digital Free Tourism (DFT) to discover the extent to which this new trend affects technology users and the tourism market. To do this, a systematic literature review and a bibliometric analysis of the research on digital disconnection contained in the Scopus and Web of Science databases were used. This research includes publications from 2012 to December 2021, which included a total of 37 publications about digital disconnection and digital free tourism in scientific journals indexed in the main scientific databases. The analysis concludes that DFT is a growing economic trend in research and that the phenomenon of digital disconnection is beginning to be a peremptory need for more and more users. This work is original and interesting for researchers specialising in technology addictions, as well as academics and professionals in the tourism sector, because the extensive use of smart devices is becoming a type of addiction in many areas and can be a new opportunity for the tourism market. The DFT phenomenon can improve the response to these types of addictions and be a temporary escape and alternative to technological devices. Doi: 10.28991/ESJ-2022-06-05-013 Full Text: PDF

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