Consumer free riding occurs when consumers gather information about a product through a full-service retailer and then ultimately purchase that product from a limited-service retailer. This phenomenon is becoming more common as consumers have an increasing number of retail channels in which they can evaluate and purchase products. The prevalence of this behavior is causing problems for retailers, particularly small, specialty retailers, as they struggle to deter free riders. The goal of this research is to explore free riding in the context of small, specialty retailers in an attempt to isolate key factors which influence free riding behavior and which may give specialty retailers and managers insights and tools with which to combat this behavior. This is accomplished through three studies, two qualitative and one quantitative. In the two qualitative studies, detailed information regarding free riding motivations and experiences is gained through interviews and open-ended questionnaires. The information gathered in studies one and two is then used in conjunction with the Theory of Reasoned Action to create a model of free riding. The model was tested across four samples and includes firm-controllable factors which may influence free riding. This research yielded many insights into consumer free riding behavior. One of the most illuminating aspects of free riding uncovered through this research is the emotional factor associated with free riding for some consumers. This emotional element, a sense of obligation to purchase from the retailer, was discovered and explored. Factors such as desire to support local merchants, personal connection to the retailer and extra-role service were revealed as firm controllable elements that retailers might be able to use to influence purchase obligation and therefore deter free riders. Other factors, such as subjective norms, were also found to impact free riding attitudes, while the impact of price sensitivity on free riding met with mixed results in this study. The results of this research offer managers possible tools for deterring free riders and offer researchers future areas for research.

This pilot study examined the effect of participation in an equine-assisted activities (EAA) program on the social functioning of participants with autism spectrum disorder (ASD). Pre- and post-assessments via the Naples Equestrian Challenge Participant Initial Evaluation were completed by a trained Certified Therapeutic Riding Instructor prior to and at the conclusion of a 12 week EAA program. 12 individuals (75% male; M age = 10.8; age range 5 – 20 years) participated. Paired-sample t-tests were conducted to examine the impact of EAA on social functioning. Analyses revealed that involvement in the EAA program resulted in a significant improvement in social functioning, but when grouped by age (5 – 10 years old, 10 – 20 years old) the effects were not significant. Lastly, individual analyses indicated that 75% of the sample had improved social functioning scores after participation in the EAA program. Results support EAA as an effective therapy for persons with ASD.

No description available.

Cycling and walking are typical forms of local locomotion. especially common in the urban environment. During the last five years, portable electric scooters were developed and quicldy gained popularity and, at the same time, generated previously unknown challenges associated with safety [1]. Their users compete with pedestrians and cyclists to occupy the same space [2], which may create conflicts and cause accidents. The balance between the safety of pedestrians and ES riders is still being sought [3], while the legislation process lags behind the rapid emergence and popularity of this new micromobility transportation mode [ 4, 5]. Tue aim of this research was a comparison of visual gaze behaviour of cyclists, electric scooter users, and pedestrians passing the same route stretch - a broad busy underpass in city centre. Visual interaction of the test participants with other road users was analysed to understand threats and risks for each of these modes of transport during selection of the path; speeds and behaviour during manoeuvres were also assessed. Differences in perception. depending on the utilized mode of transport, should bring better understanding of their specific needs and may support appropriate regulation. This research work could be considered as an extension of previous study when, in the similar way, behaviours of road-users utilizing a shared road were analysed [ 6]. [From: Introduction]

Bakgrund: Hästunderstödd terapi, HUT, är en sedan länge existerande vårdform för allehanda besvär. Evidensen för HUT som vårdverktyg har framtill nyligen dock varit svag, men allt fler studier har visat att HUT är en effektiv träningsform för balans och gångförmåga hos barn och ungdomar med CP-skador, förmågor som är tätt förknippade med människors livskvalitet. En diagnos som är lik CP och ofta ger liknande symtom är stroke. Trots likheterna mellan stroke och CP finns inte alls samma mängd evidens för effekten av HUT vid stroke som vid CP. Samtidigt råder det brist på effektiv strokerehabilitering i vissa delar av Sverige. Det är därför av intresse att utvärdera huruvida HUT kan vara ännu ett verktyg att använda vid just strokerehabilitering. Syfte: Att systematiskt granska forskningen och gradera evidensen för effekten av HUT på balans, gångförmåga och livskvalitet hos patienter som tidigare drabbats av en stroke. Metod: Systematisk litteraturstudie av randomiserade kontrollerade studier Resultat: Åtta studier hittades och de visade en förbättrande effekt av HUT på de undersökta områdena. Fem av studierna var av tillräckligt hög kvalitet för att graderas via GRADEstud. Graderingen visade att evidensvärdet var mycket låg för effekt av HUT på gångförmåga, låg för effekt av HUT på livskvalitet, och måttligt hög för effekt av HUT på balans.  Konklusion: På grund av begränsat antal studier och begränsade mätmetoder i dem kan ingen fast slutats dras, mer forskning behövs för att svara på frågeställningarna. / Background: Horse-Assisted Therapy, HAT, has since a long time been used as a health-care-tool for an assorted group of problems. The evidence for HAT as a health-care-tool has until recently been weak, however an increasing number of studies has shown HAT to be an effective way to train balance and gait in children and youths with cerebral palsy, abilities that are closely linked to a persons quality of life. A diagnosis that is similar to CP and often gives similar symptoms is stroke. Despite the similarities between stroke and CP there is far less evidence for the effects of HAT on stroke than there is for that on CP. At the same time some parts of Sweden are lacking in0 ways to rehabilitation-train after a stroke, therefore it is of interest to evaluate whether HAT can be yet another tool to use in stroke-rehabilitation.  Purpose: To systematically review and evaluate the evidence for the effect of Horse-Assisted Therapy on balance, gait and quality of life in patients who earlier has suffered a stroke.  Result: Eight studies were found and showed that HAT has an enhancing effect on the examined values. Five studies were of high enough quality to be graded using GRADEstud. The evidence grading showed a very low evidence grade for the effect of HAT on gait, low for the effect on quality of life, and moderately high for the effect on balance.  Conclusion: Due to a limited number of studies, and limitations in the ways to measure the effect no conclusion can be drawn, more research is needed in order to answer the issues in question.

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No description available.

Objectives: Since their introduction in 2019, the use of e-scooters has become widespread in Germany. Concerns about road safety, especially pedestrian safety, have arisen as the popularity of micro-mobility has grown. In light of this context, the present study investigates which types of road infrastructure e-scooter riders use, with a focus on riding on the sidewalk, which is not permitted in Germany. We considered the following infrastructures: (1) off-road bike lane (+ sidewalk and road), (2) on-road bike lane (+ sidewalk and road), and (3) road (+ sidewalk). Methods: Observations at six sites (recording 738 e-scooter riders) and on-site surveys (involving responses from 129 e-scooter riders) were conducted in two German cities in August 2020 and September 2020. Results: Self-reported sidewalk riding was not found to be linked directly to a lack of rule knowledge, a preference for this type of infrastructure, or perceived safety. Observations indicated that using the sidewalk might be related to situational components, such as comfort or convenience, comprising up to 40% of instances of sidewalk riding. Conclusion: Considering the comfort and convenience factor of sites when building or improving cycling infrastructure can help keep e-scooter riders from riding on the sidewalk.

L'objectif de cette thèse est de développer des outils d'analyse de données recueillies sur les deux roues motorisés (2RMs). Dans ce cadre, des expérimentations sont menées sur des motos instrumentés dans un contexte de conduite réelle incluant à la fois des conduites normales dites naturelles et des conduites à risques (presque chute et chute). Dans la première partie de la thèse, des méthodes d'apprentissage supervisé ont été utilisées pour la classification de situations de conduite d'un 2RM. Les approches développées dans ce contexte ont montré l'intérêt de prendre en compte l'aspect temporel des données dans la conduite d'un 2RM. A cet effet, nous avons montré l'efficacité des modèles de Markov cachés. La seconde partie de cette thèse porte sur le développement d'outils de détection et de classification hors ligne des évènements critiques de conduite, ainsi que, la détection en ligne des situations de chute d'un 2RM. L'approche proposée pour la détection hors ligne des évènements critiques de conduite repose sur l'utilisation d'un modèle de mélange de densités gaussiennes à proportions logistiques. Ce modèle sert à la segmentation non supervisée des séquences de conduite. Des caractéristiques extraites du paramètre du modèle de mélange sont utilisées comme entrées d'un classifieur pour classifier les évènements critiques. Pour la détection en ligne de chute, une méthode simple de détection séquentielle d'anomalies basée sur la carte de contrôle MCUSUM a été proposée. Les résultats obtenus sur une base de données réelle ont permis de montrer l'efficacité des méthodologies proposées à la fois pour la classification de situations de conduite et à la détection des évènements critiques de conduite / This thesis aims to develop framework tools for analyzing and understanding the riding of Powered Two Wheelers (PTW). Experiments are conducted using instrumented PTW in real context including both normal (naturalistic) riding behaviors and critical riding behaviors (near fall and fall). The two objectives of this thesis are the riding patterns classification and critical riding events detection. In the first part of this thesis, a machine-learning framework is used for riding pattern recognition problem. Therefore, this problem is formulated as a classification task to identify the class of riding patterns. The approaches developed in this context have shown the interest to take into account the temporal aspect of the data in PTW riding. Moreover, we have shown the effectiveness of hidden Markov models for such problem. The second part of this thesis focuses on the development of the off-line detection and classification of critical riding events tools and the on-line fall detection. The problem of detection and classification of critical riding events has been performed towards two steps: (1) the segmentation step, where the multidimensional time of data were modeled and segmented by using a mixture model with quadratic logistic proportions; (2) the classification step, which consists in using a pattern recognition algorithm in order to assign each event by its extracted features to one of the three classes namely Fall, near Fall and Naturalistic riding. Regarding the fall detection problem, it is formulated as a sequential anomaly detection problem. The Multivariate CUmulative SUM (MCUSUM) control chart was applied on the data collected from sensors mounted on the motorcycle. The obtained results on a real database have shown the effectiveness of the proposed methodology for both riding pattern recognition and critical riding events detection problems

L'objectif de cette thèse est de développer des outils d'analyse de données recueillies sur les deux roues motorisés (2RMs). Dans ce cadre, des expérimentations sont menées sur des motos instrumentés dans un contexte de conduite réelle incluant à la fois des conduites normales dites naturelles et des conduites à risques (presque chute et chute). Dans la première partie de la thèse, des méthodes d'apprentissage supervisé ont été utilisées pour la classification de situations de conduite d'un 2RM. Les approches développées dans ce contexte ont montré l'intérêt de prendre en compte l'aspect temporel des données dans la conduite d'un 2RM. A cet effet, nous avons montré l'efficacité des modèles de Markov cachés. La seconde partie de cette thèse porte sur le développement d'outils de détection et de classification hors ligne des évènements critiques de conduite, ainsi que, la détection en ligne des situations de chute d'un 2RM. L'approche proposée pour la détection hors ligne des évènements critiques de conduite repose sur l'utilisation d'un modèle de mélange de densités gaussiennes à proportions logistiques. Ce modèle sert à la segmentation non supervisée des séquences de conduite. Des caractéristiques extraites du paramètre du modèle de mélange sont utilisées comme entrées d'un classifieur pour classifier les évènements critiques. Pour la détection en ligne de chute, une méthode simple de détection séquentielle d'anomalies basée sur la carte de contrôle MCUSUM a été proposée. Les résultats obtenus sur une base de données réelle ont permis de montrer l'efficacité des méthodologies proposées à la fois pour la classification de situations de conduite et à la détection des évènements critiques de conduite / This thesis aims to develop framework tools for analyzing and understanding the riding of Powered Two Wheelers (PTW). Experiments are conducted using instrumented PTW in real context including both normal (naturalistic) riding behaviors and critical riding behaviors (near fall and fall). The two objectives of this thesis are the riding patterns classification and critical riding events detection. In the first part of this thesis, a machine-learning framework is used for riding pattern recognition problem. Therefore, this problem is formulated as a classification task to identify the class of riding patterns. The approaches developed in this context have shown the interest to take into account the temporal aspect of the data in PTW riding. Moreover, we have shown the effectiveness of hidden Markov models for such problem. The second part of this thesis focuses on the development of the off-line detection and classification of critical riding events tools and the on-line fall detection. The problem of detection and classification of critical riding events has been performed towards two steps: (1) the segmentation step, where the multidimensional time of data were modeled and segmented by using a mixture model with quadratic logistic proportions; (2) the classification step, which consists in using a pattern recognition algorithm in order to assign each event by its extracted features to one of the three classes namely Fall, near Fall and Naturalistic riding. Regarding the fall detection problem, it is formulated as a sequential anomaly detection problem. The Multivariate CUmulative SUM (MCUSUM) control chart was applied on the data collected from sensors mounted on the motorcycle. The obtained results on a real database have shown the effectiveness of the proposed methodology for both riding pattern recognition and critical riding events detection problems