Supply Chain Agility and Internal and External Process Connectivity: The Impact of Supply and Product Complexity

The study attempts to analyze the impact of internal and external process connectivity on supply chain agility of manufacturing firms in Thailand. It also examines whether supply and product complexity moderates the impact of internal and external process connectivity on supply chain agility. The study relies on the questionnaire survey to collect the data. Using electronic survey, the respondents working in manager’ positions in Thailand’s manufacturing companies are targeted. Out of 250 survey questionnaires, only 173 responses were found usable with a rate of response of 57.2%. The study focuses on Thai firms because Thai manufacturing sector is one of the strongest players in the globe. The reason to select manufacturing firms is that the manufacturing firms are considered to be very crucial in global supply chains in terms of providing agility and responsiveness while delivering final products to the consumers. Supply chain agility (SCAG) is used as dependent while internal process connectivity (INPC) and external process connectivity (EXPC) are used as independent variables. Moreover, product complexity (PRCX) and supply complexity (SPCX) are used as moderating variables. Findings show that SPCX has negatively significant influence on SCAG while PRCX has insignificant effect on SCAG. INPC and EXPC have positive and significant impact on SCAG. The results state that both INPC and EXPC play vital role in attaining SCAG. The interaction effect of product term (INPC × EXPC) on SCAG is also found to be positively significant. These outcomes are in line with the process theory which states that both INPC and EXPC are significant factor that play important role in attaining SCAG. Both these processes permit companies to better respond to continuous variations

Impact of Corporate Entrepreneurship and Organizational Culture on Business Performance: The Role of Supply Chain Management

With the expanding multifaceted nature and vulnerability of worldwide inventory chains, interruption occasions are as often as possible happening in production network. Commercial condition is separated into two sorts including inner and outer business conditions. In the examination, our inward business condition is organization culture and inside business condition is supply chain performance (SCP). Therefore, the purpose of this study is to quantify the impact of organizational culture (OC), corporate entrepreneurship (CE) and its components on business performance (BP) through SCP in the non-financial sector of Thailand. Research sample comprises of 120 non-financial firms operating in Thailand. The study finds that SCP fully mediates the relationship between work reinforcement BP and time availability and BP. Whereas, SCP is found to have partial mediation in the relationship between CE BP, OC BP, management support BP, organization boundaries BP and reward reinforcement and BP. Findings of study are important for mangers in understanding and implementation of better OC which leads to CE and will ultimately enhance BP

Factors Affecting the Agricultural Restructuration: A Case of Cham Community in Chau Phu District, An Giang Province, Vietnam

The national policy of agricultural restructuring plays a vital role in adapting to climate change's effects and economic development in the Mekong Delta of Vietnam. Unproductive areas have been converted into other crops with higher efficiency. Drawn by the sustainable livelihoods approach, this article explores the current situation and factors challenging the Cham community in implementing the agricultural restructuring. The mixed method included in-depth interviews, focus group discussions, and a questionnaire survey. The results showed that the Xuong Com Vang longan (Dimocarpus longan) variety has occurred in Khanh Hoa commune for a long time as an indigenous fruit tree of this area. In terms of the farming system, the polyculture system combining fruit trees and upland crops brought more income sources than the monoculture system. The asset abilities of the Cham farmers are various from one to the others. Soil and weather conditions are appropriate for planting. But farm size is small, which is one of the difficulties of developing fruit areas. Human and social assets were good since farmers had enough knowledge to manage the gardens, and a close connection existed among the Cham community. It was not a case of the financial status since a lot of money needs to be invested in the starting year. Therefore, the private loan still exists as one of the farmer's choices. For better future development, land management and financial resource should be considered for better agricultural restructuring aims. To increase farmers' incomes, create production chains helping enterprises and farmers work more efficiently for the better life of Cham gardeners in An Giang province in Vietnam

MOTIVATION TO STUDY ENGLISH OF NON-ENGLISH MAJORED FRESHMEN

Motivation is regarded as an influential factor in the success of any activity. It plays a significant role in reaching the desired goals, including learning English. This research aims to analyze the students' motivation and factors affecting their motivation to learn English. The population of this study was 326 freshmen in nine faculties of natural sciences at Tay Do University. The quantitative data was collected through the questionnaire and analyzed by SPSS software. The results show that the students had motivation to learn English, but their motivation levels were not high. Additionally, the students had both intrinsic and extrinsic motivation. However, the latter was higher than the former. Moreover, the results also indicate factors affecting learners’ motivation. The research findings contribute to improving English teaching and learning quality in Vietnam in general and in Tay Do University in particular. Article visualizations

An identification of the tolerable time-interleaved analog-to-digital converter timing mismatch level in high-speed orthogonal frequency division multiplexing systems

High-speed Terahertz communication systems has recently employed orthogonal frequency division multiplexing approach as it provides high spectral efficiency and avoids inter-symbol interference caused by dispersive channels. Such high-speed systems require extremely high-sampling time-interleaved analog-to-digital converters at the receiver. However, timing mismatch of time-interleaved analog-to-digital converters significantly causes system performance degradation. In this paper, to avoid such performance degradation induced by timing mismatch, we theoretically determine maximum tolerable mismatch levels for orthogonal frequency division multiplexing communication systems. To obtain these levels, we first propose an analytical method to derive the bit error rate formula for quadrature and pulse amplitude modulations in Rayleigh fading channels, assuming binary reflected gray code (BRGC) mapping. Further, from the derived bit error rate (BER) expressions, we reveal a threshold of timing mismatch level for which error floors produced by the mismatch will be smaller than a given BER. Simulation results demonstrate that if we preserve mismatch level smaller than 25% of this obtained threshold, the BER performance degradation is smaller than 0.5 dB as compared to the case without timing mismatch

Recommendation Systems: A Systematic Review

This article presents a comprehensive and objective systematic review of existing research on recommendation systems with regards to core theory, latest studies, various applications, current attitudes, and potential future applications. The research is mainly based on exploring professional peer-reviewed studies and articles and using their abstracts to create a comprehensive and unbiased review of existing research. The following search terms were used to identify articles and studies for the research: recommendation systems; recommender systems; core theory of recommender systems; current attitudes towards recommendation systems; latest studies on recommendation systems; applications of recommendation systems; potential studies on recommendation systems; and future potential applications of recommendation systems. The research also used the advanced search filter to locate recent studies for comparison by limiting the search by year to find studies published from 2021 onwards. Most literature on this area highlights the importance of recommendation systems in almost all aspects of modern life. Specifically, recommendation systems have become critical components in business, health care, education, marketing, and social networking domains. Additionally, most studies identified reinforcement of learning and deep learning techniques as significant developments in the field. These techniques form the backbone of most modern recommendation systems. The primary concern that could hinder further evolution systems is their consequent filter bubble effects which many studies showed to be problematic. Healthcare is a central area that shows tremendous potential for these systems. Although recommender systems have been implemented in this domain, there remains a lot of untapped potential that, if unleashed, could revolutionize medicine and healthcare. But the problems facing these systems have to be tackled first to establish trust. Keywords: Recommendation systems, Recommender systems, Deep learning, Reinforcement learning DOI: 10.7176/CEIS/13-4-04 Publication date:August 31st 202

The Nonlinearity of Working Capital and Cross-Sectional Stock Returns: Does Financial Constraints Matter?

This study is the first to examine the impacts of working capital (WC) and financial constraints on cross-sectional stock returns in Taiwan. The findings indicate a non-linear relationship between WC and stock returns. Moreover, the nonlinearity between WC and cross-sectional stock returns is robust after controlling for financial constraints, risk, and growth factors, before the Covid-19 pandemic. In contrast, there is no evidence of nonlinearity between WC and stock returns throughout the Covid-19 outbreak. In addition, the study shows that any deviations from the minimum WC level enhance the stock returns cross-sectionally. It is found that a positive Deviation effect exists in the Taiwan stock exchange before the Covid-19 pandemic by employing portfolio sorting methodologies. The return difference of the long buying highest Deviation and short selling lowest Deviation portfolios earn from 0.6% to 0.9% per month after controlling for financial constraints, risks, and growth factors. Interestingly, it is determined that the deviation effect becomes negative for small stocks during the Covid-19 pandemic, implying that investors prefer small stocks to maintain minimum working capital. The results support the trade-off theory and liquidity preference theory. Finally, the study provides insights into working capital management for managers, and investment strategies for investors during the pandemic

Secrecy performance of underlay cooperative cognitive network using non-orthogonal multiple access with opportunistic relay selection

In this paper, an underlay cooperative cognitive network using a non-orthogonal multiple access (UCCN-NOMA) system is investigated, in which the intermediate multiple relays help to decode and forward two signals x1 and x2 from a source node to two users D-1 and D-2, respectively, under wiretapping of an eavesdropper (E). We study the best relay selection strategies by three types of relay selection criteria: the first and second best relay selection is based on the maximum channel gain of the links Ri-D1, Ri-D-2, respectively; the third one is to ensure a minimum value of the channel gains from the Ri-E link. We analyze and evaluate the secrecy performances of the transmissions x1 and x2 from the source node to the destination nodes D-1, D-2, respectively, in the proposed UCCN-NOMA system in terms of the secrecy outage probabilities (SOPs) over Rayleigh fading channels. Simulation and analysis results are presented as follows. The results of the (sum) secrecy outage probability show that proposed scheme can realize the maximal diversity gain. The security of the system is very good when eavesdropper node E is far from the source and cooperative relay. Finally, the theoretical analyses are verified by performing Monte Carlo simulations.Web of Science113art. no. 38

Gene Family Abundance Visualization based on Feature Selection Combined Deep Learning to Improve Disease Diagnosis

Advancements in machine learning in general and in deep learning in particular have achieved great success in numerous fields. For personalized medicine approaches, frameworks derived from learning algorithms play an important role in supporting scientists to investigate and explore novel data sources such as metagenomic data to develop and examine methodologies to improve human healthcare. Some challenges when processing this data type include its very high dimensionality and the complexity of diseases. Metagenomic data that include gene families often have millions of features. This leads to a further increase of complexity in processing and requires a huge amount of time for computation. In this study, we propose a method combining feature selection using perceptron weight-based filters and synthetic image generation to leverage deep-learning advancements in order to predict various diseases based on gene family abundance data. An experiment was conducted using gene family datasets of five diseases, i.e. liver cirrhosis, obesity, inflammatory bowel diseases, type 2 diabetes, and colorectal cancer. The proposed method provides not only visualization for gene family abundance data but also achieved a promising performance level