Multinomial logit analysis of the effects of five different app‐based incentives to encourage cycling to work

Huang, Bingyuan; Fioreze, Tiago; Thomas, Tom; Berkum, Eric van

doi:10.1049/iet-its.2018.5338

Cited by 9 publications

(9 citation statements)

References 27 publications

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“…In reality, by having a web shop associated with in-kind rewards may make people more enthusiastic about the in-kind reward than about the money, because money has an impersonal character, which would decrease the feeling of enjoyment. [35][36][37]. Challenges and goal-setting are also essential features in gamification.…”

Section: Introductionmentioning

confidence: 99%

Effectiveness of incentives offered by mobile phone app to encourage cycling: A long‐term study

Huang

Thomas

Groenewolt

et al. 2021

IET Intelligent Trans Sys

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Reduction of car use is one of the most effective ways to tackle congestion-related problems. Using positive incentives to stimulate bicycle use is one possibility to reduce car use. Cycling is a sustainable transport mode that uses little space and is healthy. There is evidence that positive incentives may be more effective than punishing travellers for undesirable behaviour, and the emergence of mobile applications for delivering interventions has opened up new opportunities for influencing travellers. So far, few studies have focused on exploring the effectiveness of positive incentives on long-term behavioural change. We used the SMART app to deliver positive incentives to more than 6000 travellers in the Dutch region of Twente. The app automatically tracks users and provides incentives such as challenges with rewards, feedback, and messages. This study covers the period from March 2017 to June 2018, in which more than 1000 SMART users participated in monthly challenges. We evaluated the effects of the challenges and rewards and found that the challenges did encourage cycling and reduced car use in the short term. There is also some evidence for behavioural change over a longer time period. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

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Section: Introductionmentioning

confidence: 99%

Effectiveness of incentives offered by mobile phone app to encourage cycling: A long‐term study

Huang

Thomas

Groenewolt

et al. 2021

IET Intelligent Trans Sys

Self Cite

View full text Add to dashboard Cite

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“…The second phase is to develop a model to achieve an accurate prediction of intercity passenger volume. In the existing studies, multiple logit models, such as the multinomial logit model [22,23], Box-Cox logit model [24], and nested logit model [25], were developed to study the mode choice of intercity trips and deduce the intercity passenger volume of various modes by calculating the intercity travel rate of surveyed samples [26,27]. Moreover, intercity passenger volume was predicted by introducing the impact factors.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Xie et al [30] analyzed the spatiotemporal characteristics of intercity passenger volume and predicted intercity passenger volume on holiday, with a predicted error of 6.43%. Recently, deep learning and machine learning algorithms, represented by various neural networks, have become remarkable at predicting intercity passenger volume by using cellular signaling data and location-based data [4,[22][23][24][25][26][27][28][29][30][31][32]. Numerous studies have shown that predicted accuracy can be significantly improved by deep learning algorithms [33].…”

Section: Literature Reviewmentioning

confidence: 99%

A Two-Phase Approach for Predicting Highway Passenger Volume

Xiang

Chen

et al. 2021

Applied Sciences

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With the continuous process of urbanization, regional integration has become an inevitable trend of future social development. Accurate prediction of passenger volume is an essential prerequisite for understanding the extent of regional integration, which is one of the most fundamental elements for the enhancement of intercity transportation systems. This study proposes a two-phase approach in an effort to predict highway passenger volume. The datasets subsume highway passenger volume and impact factors of urban attributes. In Phase I, correlation analysis is conducted to remove highly correlated impact factors, and a random forest algorithm is employed to extract significant impact factors based on the degree of impact on highway passenger volume. In Phase II, a deep feedforward neural network is developed to predict highway passenger volume, which proved to be more accurate than both the support vector machine and multiple regression methods. The findings can provide useful information for guiding highway planning and optimizing the allocation of transportation resources.

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“…ey reflect that research interests have focused on improving the use of slow modes instead of the information system itself. Between 2010 and 2015, the relatively high frequency of the [70,166,172,178,180,182,183,190,192] Badges Symbolizes rewards to thank riders for their commitment and motivates riders to work on the next challenge [70,172,182,190,202]…”

Section: Bibliometric Investigationmentioning

confidence: 99%

“…Visualizes the standing of a group of riders with regards to certain advocacy topics [178,182] Cluster Mobile Information Systems words "technology acceptance model" and "information" indicates how information design and user adoption have been substantial. On one hand, the research on the time dimension is conducted from a systemic perspective, as "time" and "system" were keywords in 2000 and 2004, respectively.…”

Section: Leaderboardsmentioning

confidence: 99%

Mobile Technology and Studies on Transport Behavior: A Literature Analysis, Integrated Research Model, and Future Research Agenda

Sun

Liu

Zhang

2021

Mobile Information Systems

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The prevalence of mobile technology has been significant in transport research. Despite a growing application spectrum of smartphone uses and interests in mobility inference, little effort has been put into discussing theories, models, and research topics based on a systematic study of scholarly sources rooted in the interdisciplinary area of mobile technology and transport. Therefore, a timely and comprehensive synthesis of the current state of research is deemed to be required. A literature analysis, following PRISMA guidelines, aims to identify the successful development and implementation of the mobile technology that can be employed for behavior studies in transport. A review of the Web of Science Core Collections, JSTOR and SAGE databases, is performed. A rigorous screening process is used to collect key articles to construct the general image of existing knowledge. In addition, this study suggests an integrated research model to summarize how previous studies attain behavioral outcomes and a research agenda to identify unresolved research questions that future research can address. Two hundred fourty-eight papers meet the inclusion criteria. This study demonstrates that mobile technology is helpful for a better understanding of the various types of transport behaviors. They can be categorized according to their system designs and research topics: (1) Smartphone apps in sustainable transport and travel planning were studied in a remarkable collection of articles. (2) As individual’s mobility was under question, cellular signaling data were prominent for the formulation of analytical models. (3) CDRs, WiFi, and GPS data have increasingly been used, but the share of the modeling techniques for all mobile information systems has remained low. It shows that system designers could supply more desirable and appealing features in most areas. However, applications for the movement of goods are limited, although freighting has moved toward digitalization.

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Multinomial logit analysis of the effects of five different app‐based incentives to encourage cycling to work

Cited by 9 publications

References 27 publications

Effectiveness of incentives offered by mobile phone app to encourage cycling: A long‐term study

Effectiveness of incentives offered by mobile phone app to encourage cycling: A long‐term study

A Two-Phase Approach for Predicting Highway Passenger Volume

Mobile Technology and Studies on Transport Behavior: A Literature Analysis, Integrated Research Model, and Future Research Agenda

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