A multi-group analysis of the behavioral intention to ride in autonomous vehicles: evidence from three U.S. metropolitan areas

2022 ◽  
Author(s):  
Christos Gkartzonikas ◽  
Lisa Lorena Losada-Rojas ◽  
Sharon Christ ◽  
V. Dimitra Pyrialakou ◽  
Konstantina Gkritza
Keyword(s):  
Behavioral Intention ◽  
Autonomous Vehicles ◽  
Metropolitan Areas ◽  
Group Analysis

scholarly journals What drives you to use a driverless car?

2020 ◽  
Author(s):  
Sándor Huszár ◽  
Zoltán Majó-Petri
Keyword(s):  
Technology Acceptance ◽  
Influencing Factors ◽  
Behavioral Intention ◽  
Autonomous Vehicles ◽  
Structural Equation ◽  
Technological Development ◽  
Perceived Safety ◽  
Psychological Models ◽  
Acceptance Model ◽  
Self Driving Cars

The investigation of driverless car from the economic perspective is one of the most discussed topics nowadays. Although it can be approached from various perspectives there is still a lack of studies focusing on the behavioral intention to use self-driving cars and its influencing factors. Over the last few decades, various psychological models have been developed to investigate the influencing factors of usage of certain technologies, but most of them cannot provide clear answers on consumer attitudes and intentions with regard to autonomous vehicles. Thus, new models have appeared to better describe the psychological factors of this new technological development that will revolutionize the future of mobility. In our research CTAM (Car Technology Acceptance Model) was used to measure intention to using self-driving cars. In 2019, 314 participants responded to our questionnaire and provided answers to the given questions. We used structural equation modelling to investigate the linkages between the behavioral intention and influencing factors revealed during the literature review. According to the results, the most important influencing factors of intention are attitude, perceived safety and social norms, while anxiety (of using the technology), effort expectancy, performance expectancy, and self-efficacy have not been proven important factors. The model used in our investigation explains behavioral intention to a great extent (63%).

Using the UTAUT Model to Explore University Student Acceptance towards Moodle Reader

2013 ◽  
Vol 765-767 ◽  
pp. 1541-1545 ◽  
Author(s):  
Hsin Ke Lu ◽  
Peng Chun Lin ◽  
Shu Mei Fan
Keyword(s):  
Information Systems ◽  
Individual Differences ◽  
Language Learning ◽  
Direct Effect ◽  
Behavioral Intention ◽  
English Language ◽  
User Behavior ◽  
Group Analysis ◽  
Obvious Effect ◽  
Use Of Technology

With the advances in information systems and the Internet, universities have developed various e-learning platforms and blended courses that enable students to learn in a variety of ways. For system users, the acceptance and adoption of the system affects their learning processes and results. This research applied the United Theory of Acceptance and Use of Technology (UTAUT), proposed and validated by Venkatesh et al (2003), to explore factors that affect the acceptance of Moodle Reader, a system that supports English language learning. The results show that the constructs, performance expectancy and social influence have significant effects on behavioral intention, and facilitating conditions has a direct effect on user behavior and system usage. However, effort expectancy does not have an obvious effect on behavioral intention. Users intentions are dominant factors that consequently lead to gains in information systems performance. Furthermore, researchers classified students into different groups by gender, age and English learning experiences to study how individual differences affect adoption of the system. Multi-group analysis with PLS was used to examine the groups, and the results suggest that individual differences have no direct effect.

scholarly journals Using Car to Infrastructure Communication to Accelerate Learning in Route Choice

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Guilherme D. dos Santos ◽  
Ana L. C. Bazzan ◽  
Arthur Prochnow Baumgardt
Keyword(s):  
Autonomous Vehicles ◽  
Metropolitan Areas ◽  
Route Choice ◽  
Learning Processes ◽  
Traffic Situation ◽  
The Road ◽  
Road Users ◽  
Learning Tasks ◽  
Infrastructure Network ◽  
Near Future

The task of choosing a route to move from A to B is not trivial, as road networks in metropolitan areas tend to be over crowded. It is important to adapt on the fly to the traffic situation. One way to help road users (driver or autonomous vehicles for that matter) is by using modern communication technologies.In particular, there are reasons to believe that the use of communication between the infrastructure (network), and the demand (vehicles) will be a reality in the near future. In this paper, we use car-to-infrastructure (C2I) communication to investigate whether the road users can accelerate their learning processes regarding route choice by using reinforcement learning (RL). The kernel of our method is a two way communication, where road users communicate their rewards to the infrastructure, which, in turn, aggregate this information locally and pass it to other users, in order to accelerate their learning tasks. We employ a microscopic simulator in order to compare this method with two others (one based on RL without communication and a classical iterative method for traffic assignment). Experimental results using a grid and a simplification of a real-world network show that our method outperforms both.

scholarly journals Predicting Academic Staffs Behaviour Intention and Actual Use of Blended Learning in Higher Education: Model Development and Validation

2021 ◽  
Author(s):  
Bokolo Anthony ◽  
Adzhar Kamaludin ◽  
Awanis Romli
Keyword(s):  
Higher Education ◽  
Blended Learning ◽  
Content Knowledge ◽  
Behavioral Intention ◽  
Technology Use ◽  
Group Analysis ◽  
Pedagogical Practices ◽  
Intention To Use ◽  
Course Content ◽  
Actual Use

AbstractBlended Learning (BL) has been implemented by lecturers in higher educations for promoting effective pedagogical practices. However, intention to use and actual usage of BL by lecturers in higher education seems to be a major setback for successful BL implementation. Therefore, this study developed a model to examine the factors that influences lecturers’ behavioral intention and actual use of BL based on the Unified Theory of Acceptance and Use of Technology and Technological, Pedagogical and Content Knowledge model. Accordingly, survey questionnaire was employed to collect data from 544 academic staffs across universities, colleges, and polytechnics. Results indicate that performance expectancy, effort expectancy, and social influence significantly impact lecturers’ behavioral intention to use BL for teaching. Additionally, results confirm that facilitating condition positively influence actual BL usage. Likewise, technological, pedagogical, and content knowledge initiatives employed by lecturers in teaching positively influences actual BL usage. Results from multi-group analysis indicate that gender, age, experience, and voluntariness of use do not predict the behaviour of lecturers to use BL. Also, this study provides insights as to how higher education can enhance lecturers’ usage of BL to improve teaching effectiveness. This study provides a better understanding of lecturers’ views of knowledge in relation to course content, pedagogy, and technology use in improving teaching. The developed model can significantly be used by academic staffs to monitor and improve their current BL activities in measuring their knowledge about teaching regarding teaching improvement. Practically, lecturers can adopt the developed model to improve teaching pedagogies and course content.

Exploring the Adoption of Sports Brand Apps

2021 ◽  
pp. 75-91
Author(s):  
Hyun Byun ◽  
Weisheng Chiu ◽  
Jung-sup Bae
Keyword(s):  
Technology Acceptance ◽  
Behavioral Intention ◽  
Structural Equation ◽  
Group Analysis ◽  
Age Groups ◽  
Ease Of Use ◽  
Perceived Usefulness ◽  
Actual Behavior ◽  
Perceived Ease Of Use ◽  
Acceptance Model

The purpose of this article was to apply the modified technology acceptance model (TAM) to examine factors influencing consumers' intention and actual behavior in using sports brand apps. Convenience sampling was conducted for Korean consumers (N = 261) of sports brand apps. Data were analyzed by partial least squares structural equation modeling (PLS-SEM) using SmartPLS 3.0. The results found that the level of enjoyment had a significantly positive effect on the perceived ease of use, while perceived ease of use also positively affected perceived usefulness. Behavioral intention to use sports brand apps was most significantly influenced by perceived enjoyment, followed by perceived usefulness, and then perceived ease of use. Moreover, behavioral intention positively affected actual behavior. In addition, a multi-group analysis carried out found differences between three age groups (20s, 30s, and 40+) regarding the use of sports brand apps. The findings provide a better understanding of consumer behavior when using sports brand apps.

scholarly journals Internet of Things Adoption Among Micropreneurs in Regional Coast of Sabah

2021 ◽  
Author(s):  
NONA M NISTAH ◽  
HADZARIAH ISMAIL ◽  
JONATHAN LIKOH ◽  
SYED NASIRIN ◽  
SUAINI SURA
Keyword(s):  
Internet Of Things ◽  
Behavioral Intention ◽  
Qualitative Data ◽  
Group Analysis ◽  
Moderating Effects ◽  
Farming Communities ◽  
Expected Outcome ◽  
Preliminary Study ◽  
Usage Level ◽  
The Internet Of Things

Abstract This study aimed to determine the awareness and usage of the internet of things (IoT) technologies in aquafarming within the coastal community of Sabah. The UTAUT approach was applied in identifying the acceptance and usage level among these farmers. In conducting the research, both quantitative and qualitative data were collected during the fieldwork from 4 different coastal locations, which specialize in 4 different aqua-farming products. For this preliminary study, the expected outcome of the research project is a UTAUT framework for Aquafarming for the community. The main objective of the study is to determine the awareness (hearing and seeing) and usage (use, time and purpose) of IoT technologies (smartphones, computers and tablets) in aqua-farming communities in Sabah and the moderating effects of age and experience linked between predictors and behavioral intention based on the multi-group analysis. The result of this research is expected to benefit the community in devising new IoT-based policies, which may assist aqua-farmers in their business.

Scenario Modeling of Autonomous Vehicles with Trip-Based Models

2019 ◽  
Vol 2673 (10) ◽  
pp. 261-270
Author(s):  
Vincent L. Bernardin ◽  
Theodore Mansfield ◽  
Benjamin Swanson ◽  
Hadi Sadrsadat ◽  
Sumit Bindra
Keyword(s):  
South Carolina ◽  
Travel Behavior ◽  
Autonomous Vehicles ◽  
Metropolitan Areas ◽  
Scenario Planning ◽  
Modeling Framework ◽  
Fundamental Parameters ◽  
Scenario Modeling ◽  
Modeling Analysis ◽  
Comprehensive Framework

While a range of methods have been employed to quantify certain anticipated impacts of connected and autonomous vehicles (CAVs), a comprehensive framework for integrating CAVs into trip-based models, like those used by many metropolitan areas today, is lacking. Without real-world CAV usage data, integrating CAVs into trip-based models today requires speculative modeling assumptions; however, incorporating fundamental parameters into existing travel modeling frameworks is timely for two reasons. First, understanding the range of possible futures from scenario planning or exploratory modeling analysis can assist metropolitan areas anticipate and manage the potential risks and benefits of CAVs. Second, data on the travel behavior of early CAV adopters will become available during the lifespan of many models currently in use or development. This paper summarizes an enhanced trip-based modeling framework incorporating uncertainties related to CAVs initially developed in support of the Michigan Department of Transportation’s statewide model. This framework is now being applied in statewide and metropolitan scale models in Michigan, Illinois, Virginia, Indiana, and South Carolina. An important contribution of this framework is its typology of and methods for representing zero-occupant vehicle (ZOV) trips. Additionally, this paper details an exploratory analysis of CAV scenarios in Vermont using a trip-based model incorporating several elements of the framework. In this application, reasonable assumptions related to induced CAV demand, including ZOV trips, resulted in substantial increases in vehicle miles traveled, vehicle hours traveled, and delay despite capacity increases, demonstrating how relatively basic trip-based scenario modeling of CAVs can be a valuable tool for informing and encouraging public policy discussions.

scholarly journals Can Climate Change Awareness Predict Pro-Environmental Practices in Restaurants? Comparing High and Low Dining Expenditure

2019 ◽  
Vol 11 (23) ◽  
pp. 6777 ◽  
Author(s):  
Myung Ja Kim ◽  
C. Michael Hall
Keyword(s):  
Climate Change ◽  
Theory Of Planned Behavior ◽  
Planned Behavior ◽  
Behavioral Intention ◽  
Behavioral Control ◽  
Group Analysis ◽  
Waste Reduction ◽  
Equation Modeling ◽  
Perceived Behavioral Control ◽  
Extended Theory

The purpose of this study is to develop a better understanding of what makes consumers reduce waste in order to address climate change, particularly when dining out. To accomplish this goal, this research constructs an extended theory of planned behavior model, using four main constructs of attitude, subjective norm, perceived behavioral control, and behavioral intention and incorporating climate change awareness and mitigation pursuing actions, anticipated pride and guilt, and high and low levels of dining expenses. An online survey was conducted of 482 respondents aged 20 years old or over who had dined in restaurants in the previous month in 2019. A partial least squares-structural (PLS) equation modeling analysis has been utilized with multi-group analysis. Results reveal that climate change awareness has significant effects on attitude and behavior intention, and climate change mitigation pursuing actions positively influence attitude and behavioral intention to reduce waste. Consumers’ anticipated emotions lead to their behavioral intention. Diners’ behavioral intention to reduce waste is significantly influenced by their attitude, subjective norms, and perceived behavioral control on waste reduction in restaurants. The levels of dining expenses significantly moderate seven out of nine hypotheses. Research on consumers’ waste reduction in relation to climate change is not sufficiently conducted in the foodservice sector. Using an extended theory of planned behavior (TPB) to understand diner behavior related to waste reduction and climate change, this study therefore makes an important contribution to improving sustainability in foodservices, especially in the Asian context.

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