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With the aid of naturalistic simulations, this paper aims to investigate human behavior during manual and autonomous driving modes in complex scenarios.

The simulation environment is established by integrating virtual reality interface with a micro-simulation model. In the simulation, the vehicle autonomy is developed by a framework that integrates artificial neural networks and genetic algorithms. Human-subject experiments are carried, and participants are asked to virtually sit in the developed autonomous vehicle (AV) that allows for both human driving and autopilot functions within a mixed traffic environment.

Not surprisingly, the inconsistency is identified between two driving modes, in which the AV’s driving maneuver causes the cognitive bias and makes participants feel unsafe. Even though only a shallow portion of the cases that the AV ended up with an accident during the testing stage, participants still frequently intervened during the AV operation. On a similar note, even though the statistical results reflect that the AV drives under perceived high-risk conditions, rarely an actual crash can happen. This suggests that the classic safety surrogate measurement, e.g. time-to-collision, may require adjustment for the mixed traffic flow.

Understanding the behavior of AVs and the behavioral difference between AVs and human drivers are important, where the developed platform is only the first effort to identify the critical scenarios where the AVs might fail to react.

This paper attempts to fill the existing research gap in preparing close-to-reality tools for AV experience and further understanding human behavior during high-level autonomous driving.

This work aims to systematically analyze the inconsistency in driving patterns between manual and autopilot modes in various driving scenarios (i.e. multiple scenes and various traffic conditions) to facilitate user acceptance of AV technology.

A close-to-reality tool for AV experience and AV-related behavioral study. A systematic analysis in relation to the inconsistency in driving patterns between manual and autonomous driving. A foundation for identifying the critical scenarios where the AVs might fail to react.

An individual’s driving style significantly affects overall traffic safety. However, driving style is difficult to identify due to temporal and spatial differences and scene heterogeneity of driving behavior data. As such, the study of real-time driving-style identification methods is of great significance for formulating personalized driving strategies, improving traffic safety and reducing fuel consumption. This study aims to establish a driving style recognition framework based on longitudinal driving operation conditions (DOCs) using a machine learning model and natural driving data collected by a vehicle equipped with an advanced driving assistance system (ADAS).

Specifically, a driving style recognition framework based on longitudinal DOCs was established. To train the model, a real-world driving experiment was conducted. First, the driving styles of 44 drivers were preliminarily identified through natural driving data and video data; drivers were categorized through a subjective evaluation as conservative, moderate or aggressive. Then, based on the ADAS driving data, a criterion for extracting longitudinal DOCs was developed. Third, taking the ADAS data from 47 Kms of the two test expressways as the research object, six DOCs were calibrated and the characteristic data sets of the different DOCs were extracted and constructed. Finally, four machine learning classification (MLC) models were used to classify and predict driving style based on the natural driving data.

The results showed that six longitudinal DOCs were calibrated according to the proposed calibration criterion. Cautious drivers undertook the largest proportion of the free cruise condition (FCC), while aggressive drivers primarily undertook the FCC, following steady condition and relative approximation condition. Compared with cautious and moderate drivers, aggressive drivers adopted a smaller time headway (THW) and distance headway (DHW). THW, time-to-collision (TTC) and DHW showed highly significant differences in driving style identification, while longitudinal acceleration (LA) showed no significant difference in driving style identification. Speed and TTC showed no significant difference between moderate and aggressive drivers. In consideration of the cross-validation results and model prediction results, the overall hierarchical prediction performance ranking of the four studied machine learning models under the current sample data set was extreme gradient boosting > multi-layer perceptron > logistic regression > support vector machine.

The contribution of this research is to propose a criterion and solution for using longitudinal driving behavior data to label longitudinal DOCs and rapidly identify driving styles based on those DOCs and MLC models. This study provides a reference for real-time online driving style identification in vehicles equipped with onboard data acquisition equipment, such as ADAS.

To advance marketing research and practice, this study aims to examine the application of the innovative, mobile-applicable neuroimaging method – mobile functional near-infrared spectroscopy (mfNIRS) – in the field of marketing research, providing comprehensive guidelines and practical recommendations.

A general review and investigation of when and how to use mfNIRS in business-to-consumer and business-to-business marketing settings is used to illustrate the utility of mfNIRS.

The research findings help prospective marketing and consumer neuroscience researchers to structure mfNIRS experiments, perform the analysis and interpret the obtained mfNIRS data.

The application of mfNIRS offers opportunities for marketing research that allow the exploration of neural processes and associated behaviour of customers in naturalistic settings.

The application of mfNIRS as a neuroimaging method enables the investigation of unconscious neural processes that control customer behaviour and can act as process variables for companies.

This is one of the first studies to provide comprehensive guidelines and applied practical recommendations concerning when and how to apply mfNIRS in marketing research.

This paper aims to review the existing literature about consumers’ evaluation of products in virtual reality (VR), provide an accurate overview of this field, systematise the knowledge developed so far, identify the research gaps and propose a future research agenda.

A systematic literature review was performed on Scopus and Web of Science, resulting in a final pool of 31 articles.

Four main themes were identified, and a detailed research agenda is proposed based on the findings and following the theory, context, characteristics, methodology framework.

The provision of formal inclusion and exclusion criteria may have resulted in additional potentially relevant articles not indexed in the data set under consideration.

The paper highlights how products are perceived in VR, the consumers’ responses, the peculiarities of VR compared to other conditions and VR as a product test environment. To the best of the authors’ knowledge, this paper seems to represent the first systemic review that focusses solely on how consumers assess products in VR. The results lead to a broad proposal of directions for future research that can expand knowledge on VR in marketing. Practical implications concern the use of VR to design product strategies and as a testing and prototyping environment.

Este artículo revisa la literatura existente sobre la evaluación de los consumidores de productos en Realidad Virtual, proporciona una visión precisa de este campo, sistematiza el conocimiento desarrollado hasta el momento, identifica las lagunas en la investigación y propone una agenda de investigación futura.

Se realizó una revisión sistemática de la literatura en Scopus y Web of Science, que dio como resultado un conjunto final de 31 artículos.

Se identificaron cuatro temas principales y se propone una agenda de investigación detallada basada en las conclusiones y siguiendo el marco Teoría, Contexto, Características, Metodología.

La provisión de criterios formales de inclusión y exclusión puede haber dado lugar a artículos adicionales potencialmente relevantes no indexados en el conjunto de datos considerado.

El artículo destaca cómo se perciben los productos en la Realidad Virtual, las respuestas de los consumidores, las peculiaridades de la Realidad Virtual en comparación con otras condiciones y la Realidad Virtual como entorno de prueba de productos. Esta parece representar la primera revisión sistémica que se centra exclusivamente en cómo los consumidores evalúan los productos en la Realidad Virtual. Los resultados conducen a una amplia propuesta de direcciones para futuras investigaciones que puedan ampliar los conocimientos sobre la Realidad Virtual en el marketing. Las implicaciones prácticas se refieren al uso de la Realidad Virtual para diseñar estrategias de producto y como entorno de prueba y creación de prototipos.

本文回顾了现有的关于消费者对虚拟现实产品评价的文献, 提供了这个领域的准确概述, 系统化了迄今为止的知识, 确定了研究差距, 并提出了一个未来的研究议程。

在Scopus和Web of Science上进行了系统的文献综述, 最终形成了31篇文章的资料库。

确定了四个主要的主题, 并根据研究结果, 按照理论、背景、特征、方法框架提出了详细的研究议程。

提供正式的纳入和排除标准可能会导致更多潜在的相关文章没有被收录到所考虑的数据集中。

文章强调了产品在虚拟现实中是如何被感知的, 消费者的反应, 与其他条件相比虚拟现实的特殊性, 以及虚拟现实作为产品测试环境。这似乎代表了第一个只关注消费者如何在虚拟现实中评估产品的系统性评论。研究结果为未来的研究方向提出了一个广泛的建议, 可以扩展营销中的虚拟现实知识。实际意义在于使用虚拟现实技术来设计产品策略, 并作为测试和原型设计环境。

This study aims to illuminate the contribution of neurophysiological techniques in the field of marketing and consumer decision-making and to highlight avenues and research questions that marketing researchers can take advantage of from neuroscience and psychology to inform marketing phenomena.

The authors first reviewed the roots and definition of consumer neuroscience. Then, the authors outlined the main characteristics of the most commonly used neurophysiological tools (namely, skin conductance, facial electromyography, electrocardiogram, eye-tracking, electroencephalography, functional magnetic resonance imaging, functional near-infrared spectroscopy, magnetoencephalography and transcranial magnetic stimulation) with a special emphasis on their advantages and weaknesses. Finally, the authors propose the development of research lines that could be implemented by marketing researchers with an appropriate application and understanding of tools and theories of neuroscience and psychology.

The authors propose research questions to be addressed within four thematic areas: opportunities in product decisions (predicting product purchasing decisions, consumer responses to branding efforts and packaging), pricing, communication and retailing scenarios. The authors also incorporate insights into the complementarity of neurophysiological tools to traditional ones and situations in which these tools are useful for enhancing marketing theory. The authors finally shed light on the moral–ethical criticisms of this new branch of marketing.

To the best of the authors’ knowledge, this research constitutes the first study in identifying the research opportunities that marketing researchers could take advantage from neuroimaging and physiological tools to inform marketing theory and practice.

Esta investigación tiene como objetivo esclarecer la contribución de las técnicas neurofisiológicas en el campo del marketing y la toma de decisiones de los consumidores y destacar las vías y preguntas de investigación que los investigadores de marketing pueden aprovechar de la neurociencia y la psicología para informar sobre los fenómenos del marketing.

En primer lugar, revisamos el origen y la definición de la neurociencia del consumidor. A continuación, esbozamos las principales características de las herramientas neurofisiológicas más utilizadas (a saber, la conductancia, la electromiografía facial, el electrocardiograma, el seguimiento ocular, la electroencefalografía, la resonancia magnética funcional, la espectroscopia funcional en el infrarrojo cercano, la magnetoencefalografía y la estimulación magnética transcraneal), haciendo especial hincapié en sus ventajas y debilidades. Finalmente, se propone el desarrollo de líneas de investigación que podrían ser implementadas por los investigadores de marketing con una adecuada aplicación y comprensión de las herramientas y teorías de la neurociencia y la psicología.

Proponemos preguntas de investigación para ser abordadas dentro de cuatro áreas temáticas: oportunidades en las decisiones de producto (predicción de las decisiones de compra de productos, respuestas de los consumidores a los esfuerzos de marca y envasado), precios, comunicación y distribución. También incorporamos ideas sobre la complementariedad de las herramientas neurofisiológicas con las tradicionales y las situaciones en las que estas herramientas son útiles para mejorar la teoría del marketing. Por último, arrojamos luz sobre las críticas ético-morales a esta nueva rama del marketing.

本研究旨在阐明神经生理学技术在营销和消费者决策领域的贡献, 并强调营销研究人员可以从神经科学和心理学中利用的途径和研究问题, 以告知营销现象。

我们首先回顾了消费者神经科学的根基和定义。然后, 我们概述了最常用的神经生理学工具（即皮肤电导率、面部肌电图、心电图、眼球追踪、脑电图、功能性磁共振成像、功能性近红外光谱、脑磁图和经颅磁刺激）的主要特点, 特别强调了它们的优势和劣势。最后, 我们提出了研究路线的发展, 这些路线可以由营销研究人员通过适当的应用和理解神经科学和心理学的工具和理论来实施。

我们提出了四个主题领域的研究问题：产品决策中的机会（预测产品购买决策、消费者对品牌推广工作的反应和包装）、定价、沟通和零售场景。我们还纳入了对神经生理学工具与传统工具的互补性的见解, 以及这些工具对加强营销理论有用的情况。最后, 我们对这个新的营销分支的道德伦理批评进行了说明。

纸张类型 – 研究论文

The purpose of this paper is to design a unified operational design domain (ODD) monitoring framework for mitigating Safety of the Intended Functionality (SOTIF) risks triggered by vehicles exceeding ODD boundaries in complex traffic scenarios.

A unified model of ODD monitoring is constructed, which consists of three modules: weather condition monitoring for unusual weather conditions, such as rain, snow and fog; vehicle behavior monitoring for abnormal vehicle behavior, such as traffic rule violations; and road condition monitoring for abnormal road conditions, such as road defects, unexpected obstacles and slippery roads. Additionally, the applications of the proposed unified ODD monitoring framework are demonstrated. The practicability and effectiveness of the proposed unified ODD monitoring framework for mitigating SOTIF risk are verified in the applications.

First, the application of weather condition monitoring demonstrates that the autonomous vehicle can make a safe decision based on the performance degradation of Lidar on rainy days using the proposed monitoring framework. Second, the application of vehicle behavior monitoring demonstrates that the autonomous vehicle can properly adhere to traffic rules using the proposed monitoring framework. Third, the application of road condition monitoring demonstrates that the proposed unified ODD monitoring framework enables the ego vehicle to successfully monitor and avoid road defects.

The value of this paper is that the proposed unified ODD monitoring framework establishes a new foundation for monitoring and mitigating SOTIF risks in complex traffic environments.

The purpose of this paper is to describe the components, structure and theoretical underpinnings of a cognitive remediation intervention that was delivered within a supported education program for mental health survivors.

In total, 21 participants enrolled in the course Strengthening Memory, Concentration and Learning (PREP 1033 at George Brown College (GBC)) with the diagnosis of depression, anxiety, PTSD, ED and substance use disorder were included in the research. After a baseline assessment, participants completed 14 week cognitive remediation training (CRT) protocol that included six essential components that were integrated and implemented within the course structure of the supported education program at GBC. This was followed by a post-training assessment.

Analysis of the participants’ performance on CRT protocol using computerized games showed little significant progress. However, the research found a positive change in the self-esteem of the participants that was statistically significant and the findings also aligned with the social and emotional learning framework.

One of the limitations in the research was the use of computer-assisted cognitive remediation in the form of the HappyNeuron software. The value and relevance of computer assisted needs are to be further examined. It seems that the implementation of the course that explicitly address cognitive challenges creates a supportive environment can be helpful.

Despite the mixed results and the few limitations associated with the CRT intervention reported in the research, the study offers reminders of the complexity of cognitive remediation and all the factors involved that need to be taken into consideration.

This research created explicit space for addressing some of the implicit assumptions about the cognitive abilities when in post-secondary education.

This work is based on author’s previous work on cognitive remediation research within the supported education setting.

Despite a fast-growing interest in leadership development programs, there is limited research on the impacts of leadership development and a narrow focus on professional competencies as outcomes. The authors’ aim was to test whether authentic leadership development (ALD), an identity-based leadership development approach, is associated with positive changes in leaders' psychological well-being.

In a large sample of leaders (N = 532) from five different ALD programs, the authors conducted a pre-registered outcome-wide analysis and tested within-person changes in key indicators of psychological well-being and explored individual differences moderating these changes.

Results showed significant increases in self-concept clarity, sense of purpose in life and personal growth about two to three weeks after the programs ended. Changes in stress and health were not consistent. These changes did not differ across socio-demographic status (gender, age), work-related factors (leadership, industry and tenure) and most personality factors (extraversion, agreeableness, openness to experience). Those with high emotional variability experienced greater improvements in some outcomes of well-being while individuals with higher income and conscientiousness (who had high baseline self-concept clarity) experienced smaller improvements. Longer follow-up assessments were associated with smaller changes.

As one of the most comprehensive assessments of ALD outcomes to date, this study shows the potential of ALD for improving outcomes beyond leadership skills, the well-being of leaders, highlighting the return on value in leadership development and pointing to learning and development as a workplace well-being intervention.

Metaverse, that is extended reality (XR)-based technologies such as augmented reality (AR) and virtual reality (VR), are increasingly believed to facilitate fundamental human practice in the future. One of the vanguards of this development has been the consumption domain, where the multi-modal and multi-sensory technology-mediated immersion is expected to enrich consumers' experience. However, it remains unclear whether these expectations have been warranted in reality and whether, rather than enhancing the experience, metaverse technologies inhibit the functioning and experience, such as cognitive functioning and experience.

This study utilizes a 2 (VR: yes vs no) × 2 (AR: yes vs no) between-subjects laboratory experiment. A total of 159 student participants are randomly assigned to one condition — a brick-and-mortar store, a VR store, an AR store and an augmented virtuality (AV) store — to complete a typical shopping task. Four spatial attention indicators — visit shift, duration shift, visit variation and duration variation — are compared based on attention allocation data converted from head movements extracted from recorded videos during the experiments.

This study identifies three essential effects of XR technologies on consumers' spatial attention allocation: the inattention effect, acceleration effect and imbalance effect. Specifically, the inattention effect (the attentional visit shift from showcased products to the environmental periphery) appears when VR or AR technology is applied to virtualize the store and disappears when AR and VR are used together. The acceleration effect (the attentional duration shift from showcased products to the environmental periphery) exists in the VR store. Additionally, AR causes an imbalance effect (the attentional duration variation increases horizontally among the showcased products).

This study provides valuable empirical evidence of how VR and AR influence consumers' spatial bias in attention allocation, filling the research gap on cognitive function in the metaverse. This study also provides practical guidelines for retailers and XR designers and developers.

This study aims to validate a model for estimating platoon delay due to pedestrian crossing for use in Kuwait City.

The model was modified slightly for the scenario used in Kuwait, in which the presence of raised crosswalk meant that all incoming traffic would slow down automatically. Using video footage to observe the site, several variables were collected, and a model was used to calculate the delays suffered by the vehicles because of pedestrian crossing. The model was validated using the actual footage and manual observation to measure the delays.

The model showed a good match fit to the observed data, as the average delays differed by 22.5% between the two methods. Following the comparison, a sensitivity analysis was made on three variables: the acceleration rate, deceleration rate, as well as the pedestrian walking time. The analysis has shown that deceleration rate has approximately twice the effect on the model than the acceleration rate has. It has also shown that the pedestrian walking time has a major effect on the model, in an almost one-to-one correlation. A 50% change of the pedestrian walking time is associated with approximately 50% change in the model’s output delay.

A model for estimating platoon delay because of pedestrian crossing was validated for use in Kuwait City. The model was modified slightly for the scenario used in Kuwait, in which the presence of raised crosswalk meant that all incoming traffic would slow down automatically.