Predicting factors affecting the intention to use a 3PL during the COVID-19 pandemic: A machine learning ensemble approach

Heliyon, Journal Year: 2022, Volume and Issue: 8(11), P. e11382 - e11382

Published: Nov. 1, 2022

The COVID-19 pandemic had brought changes to individuals, especially in consumer behavior. As the government of different countries has been implementing safety protocols mitigate spread virus, people became apprehensive about traveling and going out. This paved way for emergence third-party logistics (3PL). Statistics have proven rapid escalation regarding use 3PL various countries. study utilized Artificial Neural Network Random Forest Classifier validate justify factors that affect intention selecting a service provider during integrating Service Quality Dimensions Pro-Environmental Theory Planned Behavior. findings this revealed attitude is most significant factor affects consumers' behavioral intention. Other such as customer satisfaction, perceived value, environmental concern, assurance, responsiveness, empathy, reliability, tangibility, control, subjective norm, authority support, are all contributing Machine learning algorithms, specifically ANN RFC, resulted be reliable predicting they obtained accuracy rates 98.56% 93%. Results presented attitude, assurance by 3PL, concerns were highly influential choosing package carrier. It was seen would encouraged providers if demonstrate availability catering customers' needs. Subsequently, must assure convenience before, during, after providing ensure continuous patronage consumers. considered first machine ensemble measure logistic sector. framework, analysis tools, could extended applied among other intentions transportation worldwide. Managerial insights discussed.

Language: Английский

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A Machine Learning Ensemble Approach for Predicting Factors Affecting STEM Students’ Future Intention to Enroll in Chemistry-Related Courses

Sustainability, Journal Year: 2022, Volume and Issue: 14(23), P. 16041 - 16041

Published: Dec. 1, 2022

The need for chemistry-related professionals has been evident with the rise of global issues such as pandemic and warming. Studies have indicated how an increase in amount should start within classroom setting, enhancing interest motivation students to pursue higher education related field. This study aimed evaluate predict factors affecting STEM students’ future intention enroll courses. Through use machine learning algorithms a random forest classifier artificial neural network, total 40,782 datasets were analyzed. Results showed that attitude toward chemistry perceived behavioral control represent most influential factors, followed by autonomy affective behavior. demonstrated interest, application real life, development knowledge skills are key indicators would lead positive pursuing course education. is first analyzed intentions using algorithm ensemble. methodology results may be applied extended among other human factor studies worldwide. Lastly, presented discussion analysis considered universities their strategies across different countries.

Language: Английский

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Factors Affecting Flood Disaster Preparedness and Mitigation in Flood-Prone Areas in the Philippines: An Integration of Protection Motivation Theory and Theory of Planned Behavior

Sustainability, Journal Year: 2023, Volume and Issue: 15(8), P. 6657 - 6657

Published: April 14, 2023

Natural hazards are one of the destructive phenomena that pose a significant hazard to humans, property, and economy, among others. One most recurring natural is flooding, which caused by typhoons, monsoons, heavy rainfall has been main concerns Philippines in recent years. The study’s results will provide information on factors affecting flood disaster preparedness integrating Theory Planned Behavior (TPB) Protection Motivation (PMT). A total 509 individuals answered an online survey questionnaire with 52 adapted questions. Structural equation modeling (SEM) revealed risk perception (RP), media (M), personal experience (PE) had effect perceived severity (PS) vulnerability (PV), consequently affected attitude toward behavior (ATB), social norms (SN), behavioral control (PBC). It was determined ATB, SN, PBC significantly (AB), led intention follow (ITF) prevention (PP). After analyzing data, it 56.2% female respondents were said be more resilient compared males. This first study determine mitigation flood-prone areas Philippines. beneficial academicians government officials developing determining affect preparedness. Lastly, deeper understanding how AB variable may further researched improve paper.

Language: Английский

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Classification modeling of intention to donate for victims of Typhoon Odette using deep learning neural network

Environmental Development, Journal Year: 2023, Volume and Issue: 45, P. 100823 - 100823

Published: Feb. 20, 2023

Language: Английский

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The impact of green innovation initiatives on competitiveness and financial performance of the land transport industry

Heliyon, Journal Year: 2023, Volume and Issue: 9(8), P. e19130 - e19130

Published: Aug. 1, 2023

The transportation sector is one of the primary contributors to greenhouse gas emissions that have deteriorating effects on state environment. implementation sustainable practices has become most challenging tasks organizations at present. This study examined effect implementing green innovation initiatives a firm's competitiveness and financial performance motor vehicle companies in Philippines. Data were gathered through an online survey questionnaire with total 206 respondents composed employees various ranks working engaged manufacture, distribution, retail, service vehicles. theoretical framework presented hierarchical latent variable model which was validated using partial least square structural equation modelling (PLS-SEM). fit, measurement, general construct discriminant validity, parameters found acceptable values. findings indicated environmental regulations, market demand, government pressure, competitor corporate social responsibility, employee conduct significant drivers initiatives. also revealed positively affects performance. Motor other types are encouraged demonstrate not only their concern for society or community but environment acquire better leverage position.

Language: Английский

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Expanding integrated protection motivation theory and theory of planned behavior: The role of source of influence in flood and typhoon risk preparedness intentions in Quezon Province, Philippines

Climate Risk Management, Journal Year: 2025, Volume and Issue: unknown, P. 100706 - 100706

Published: April 1, 2025

Language: Английский

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Determining factors affecting perceived effectiveness among Filipinos for fire prevention preparedness in the National Capital Region, Philippines: Integrating Protection Motivation Theory and extended Theory of Planned Behavior

International Journal of Disaster Risk Reduction, Journal Year: 2022, Volume and Issue: 85, P. 103497 - 103497

Published: Dec. 31, 2022

Language: Английский

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“The Big One” Earthquake Preparedness Assessment among Younger Filipinos Using a Random Forest Classifier and an Artificial Neural Network

Sustainability, Journal Year: 2022, Volume and Issue: 15(1), P. 679 - 679

Published: Dec. 30, 2022

Exploring the intention to prepare for mitigation among Filipinos should be considered as Philippines is a country prone natural calamities. With frequent earthquakes occurring in country, “The Big One” has been predicted damage livelihood and infrastructure of capital surrounding cities. This study aimed predict (IP) based on several features using machine learning algorithm ensemble. applied decision tree, random forest classifier, artificial neural network algorithms classify affecting factors. Data were collected convenience sampling through self-administered questionnaire with 683 valid responses. The results this proposed learning-based prediction model could younger prepare. experimental also revealed that tree classifier showed understanding, perceived vulnerability, severity factors highly IP One”. by government promote policies guidelines enhance people’s disasters. utilized determine other disasters, even countries.

Language: Английский

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Utilizing a machine learning ensemble to evaluate the service quality and passenger satisfaction among public transportations

Journal of Public Transportation, Journal Year: 2023, Volume and Issue: 25, P. 100076 - 100076

Published: Jan. 1, 2023

Public transportation is an essential criterion that benefits several social sectors. Hence, most developing countries display increase in the demand for enhanced public utility vehicle (PUV) systems. PUVs are prevalent Philippines; however, research on passenger satisfaction and scarce. This aimed to assess passengers' future intentions regarding through utilizing various latent variables. study utilized online survey with a total of 600 respondents using Philippines who voluntarily answered questionnaire. The data were analyzed different Machine Learning Algorithms (MLA) such as Deep Neural Network (DLNN), Decision Tree (DT), Random Forest Classifier (RFC). indicated people vastly prefer route-efficient way traveling, safety, value money, expectations it highly affected intentions. theoretical basis this provided effective instrument resolving country's emerging traffic issues served foundation forming policy initiatives. Future may look into concentrate more particular types service quality factors provide in-depth analysis subject extend analysis. Researchers also utilize MLA provides efficient accurate factor sector. Finally, managerial insights could be elevated, including domains areas.

Language: Английский

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Geological Hazards and Risk Management

Sustainability, Journal Year: 2024, Volume and Issue: 16(8), P. 3286 - 3286

Published: April 15, 2024

The occurrence of geological hazards is widespread, particularly in mountainous regions [...]

Language: Английский

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