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New technologies such as product simulators and virtual reality now allow firms to provide realistic product usage experiences and reduce buyer uncertainty about product quality. We argue that today’s firms should view product design and investments to reduce buyer uncertainty as an integrated process, which is in turn influenced by how much information buyers can obtain from third-party infomediaries. We introduce a game-theoretic model of a competitive market where both quality production and quality disclosure are endogenous decisions, affected by information made available by third parties. We show that quality investment under uncertainty never exceeds the level of quality investment under perfect information. Furthermore, we show that information availability by third parties allows firms to free ride, and it especially favors lower quality firms, who can reduce their information disclosure investments more so than higher-quality firms. Finally, we show that the intuitive argument that firms must improve their product quality when overall information availability in the market improves does not always hold. Instead, improved information availability may enable firms to reduce their quality in some situations. The online appendix is available at https://doi.org/10.1287/mnsc.2016.2634 . This paper was accepted by Chris Forman, information systems.

Purpose To identify the life domains that are most frequently reported to be affected in scoliosis patients undergoing brace treatment. Methods A search within the PubMed database was conducted and a total of 60 publications were selected. We classified the studies based on the methods used to measure patients’ quality of life (QoL) and categorized the life domains reported to be affected. Results Self-image/body configuration was the most reported affected domain of patients’ QoL, identified in 32 papers, whilst mental health/stress was the second most reported affected domain. Mental health was identified in 11 papers, and 11 papers using the BSSQ questionnaire reported medium stress amongst their participants. Vitality was the third most reported affected domain, identified in 12 papers. Conclusions Our review indicates that scoliotic adolescents treated with bracing suffer in their quality of life most from psychological burdens. To improve these patients’ life quality, more attention should be focussed on supporting their mental health.

Design-based learning (DBL) is gaining increasing acceptance as a motivating and practical approach that can be used to prepare young people for the challenges of the twenty-first century. Emotions are known to influence a student’s academic performance in traditional learning, which raises the question as to what role emotions can play in DBL. This article presents a systematic survey of literature published in the last 20 years (searching from 1998 to 2019) and indexed in the Scopus, ERIC, and PsycINFO databases which contribute to our understanding of children’s emotions in DBL. This review coded a total of 34 papers that met the inclusion criteria. Findings that reported on children’s emotions are structured under three themes: (1) the affective DBL components, (2) the labeled emotions, and (3) the impact of emotions in DBL. Based on this evidence, we make recommendations for future research and compile a set of guidelines for designing DBL activities, taking into account students’ emotions that can aid their learning.

Multimodal fusion networks play a pivotal role in leveraging diverse sources of information for enhanced machine learning applications in aerial imagery. However, current approaches often suffer from a bias towards certain modalities, diminishing the potential benefits of multimodal data. This paper addresses this issue by proposing a novel modality utilization-based training method for multimodal fusion networks. The method aims to guide the network’s utilization on its input modalities, ensuring a balanced integration of complementary information streams, effectively mitigating the overutilization of dominant modalities. The method is validated on multimodal aerial imagery classification and image segmentation tasks, effectively maintaining modality utilization within ±10% of the user-defined target utilization and demonstrating the versatility and efficacy of the proposed method across various applications. Furthermore, the study explores the robustness of the fusion networks against noise in input modalities, a crucial aspect in real-world scenarios. The method showcases better noise robustness by maintaining performance amidst environmental changes affecting different aerial imagery sensing modalities. The network trained with 75.0% EO utilization achieves significantly better accuracy (81.4%) in noisy conditions (noise variance = 0.12) compared to traditional training methods with 99.59% EO utilization (73.7%). Additionally, it maintains an average accuracy of 85.0% across different noise levels, outperforming the traditional method’s average accuracy of 81.9%. Overall, the proposed approach presents a significant step towards harnessing the full potential of multimodal data fusion in diverse machine learning applications such as robotics, healthcare, satellite imagery, and defense applications.

In the last years, there have been rapid developments in social robotics, which bring about the prospect of their application as persuasive robots to support behavior change. In order to guide related developments and pave the way for their adoption, it is important to understand the factors that influence the acceptance of social robots as persuasive agents. This study extends the technology acceptance model by including measures of social responses. The social responses include trusting belief, compliance, liking, and psychological reactance. Using the Wizard of Oz method, a laboratory experiment was conducted to evaluate user acceptance and social responses towards a social robot called SociBot. This robot was used as a persuasive agent in making decisions in donating to charities. Using partial least squares method, results showed that trusting beliefs and liking towards the robot significantly add the predictive power of the acceptance model of persuasive robots. However, due to the limitations of the study design, psychological reactance and compliance were not found to contribute to the prediction of persuasive robots’ acceptance. Implications for the development of persuasive robots are discussed.

Neck pain is common among computer workers who may spend too much time in a static posture facing their display. Regular breaks and variety in one’s posture can help to prevent discomfort and pain. In order to understand how to support computer workers to do so regularly, we surveyed a convenience sample of computer workers (N = 130) regarding their work habits and their attitudes towards neck exercises at the workplace. The survey showed that they are highly motivated, but not able to comply with a neck exercise program. To address this challenge, we designed Neckio, a system that is aimed at encouraging posture variation and facilitating neck exercises at work. Neckio consists in an interactive application and a wireless angulation sensing appliance that can be mounted on the headset that office workers often use for reasons of privacy. Next to providing an interactive exercise program suitable for the workplace, its design places emphasis on an engaging user experience. We report a short-term user experience valuation of Neckio in an actual office environment (N = 10). Participants rated the overall user experience positively and reported to be intrinsically motivated to do the neck exercises. These results indicate the potential of the Neckio as a behavior change support technology to reduce the risk of developing neck pain in computer workers.

Coping with stress is crucial for a healthy lifestyle. In the past, a great deal of research has been conducted to use socially assistive robots as a therapy to alleviate stress and anxiety related problems. However, building a fully autonomous social robot which can deliver psycho-therapeutic solutions is a very challenging endeavor due to limitations in artificial intelligence (AI). To overcome AI’s limitations, researchers have previously introduced crowdsourcing-based teleoperation methods, which summon the crowd’s input to control a robot’s functions. However, in the context of robotics, such methods have only been used to support the object manipulation, navigational, and training tasks. It is not yet known how to leverage real-time crowdsourcing (RTC) to process complex therapeutic conversational tasks for social robotics. To fill this gap, we developed Crowd of Oz (CoZ), an open-source system that allows Softbank’s Pepper robot to support such conversational tasks. To demonstrate the potential implications of this crowd-powered approach, we investigated how effectively, crowd workers recruited in real-time can teleoperate the robot’s speech, in situations when the robot needs to act as a life coach. We systematically varied the number of workers who simultaneously handle the speech of the robot (N = 1, 2, 4, 8) and investigated the concomitant effects for enabling RTC for social robotics. Additionally, we present Pavilion, a novel and open-source algorithm for managing the workers’ queue so that a required number of workers are engaged or waiting. Based on our findings, we discuss salient parameters that such crowd-powered systems must adhere to, so as to enhance their performance in response latency and dialogue quality.

Herein, we introduce SONIS, a wearable system to support gait rehabilitation training after a lower extremity trauma, which combines a sensing sock with a smartphone application. SONIS provides interactive, corrective, real-time feedback combining visual and auditory cues. We report the design of SONIS and its evaluation by patients and therapists, which indicates acceptance by targeted users, credibility as a rehabilitation tool, and a positive user experience. SONIS demonstrates how to successfully combine a number of feedback strategies and modalities: graphical, verbal, and music feedback on gait quality during training (knowledge of performance) and verbal and vibrotactile feedback on gait tracking (knowledge of results).

Educational settings are emotional places where students experience diverse emotions in relation to academic activities and their outcomes. Emotions, in turn, greatly influence students’ learning process and engagement. Research on emotions in Design-Based Learning (DBL) has so far been coarse-grained examining how students evaluate their overall feelings towards the DBL project. As yet, little is known regarding how specific DBL activities influence students’ emotional experience. Therefore, we report a three-month field study of a DBL project involving 30 middle school students (aged 13–14) addressing dual research purposes: (1) to faithfully reconstruct the manner and sequence of activities during DBL from a fine-grained perspective; and (2) to examine the relationship between these activities and students’ emotional experience. This study used a mixed research method and collected multiple data sources, including experience sampling surveys, classroom observations, and interviews. The research outcomes in this study are multiple. First, this paper reveals detailed inspection regarding the types of task students performed, the strategies of shifting, and executing tasks during the process student experienced. Second, this paper identifies specific types of activities that have a significant positive or negative relationship with students’ emotional experiences. Derived from reported empirical evidence in the present study, this paper furtherly proposes an Activity-and-Affect model of DBL. This model provides a fine-grained description of DBL activity as continuous along three dimensions: task (design thinking process, project management, social interaction) task strategy (single-tasking vs. multitasking), and collaboration strategy (individual or group). Our analysis highlights the variability in how different DBL activities can be associated with different emotions.

There is a worldwide pursuit to increase children’s interest in STEM (Science, Technology, Engineering, Mathematics) especially in computer science through extra-curricular activities such as coding workshops, hackathons, and FabLab initiatives. However, the underlying reasons for children’s willingness for participation in such activities, and the effect of participation on children’s topic-related knowledge are still not well understood. In order to understand the factors influencing children’s attitude about programming and investigate what effects children’s learning during such activities, we designed a workshop for introducing primary school children to programming, and implemented it for a Dutch primary school class ( n  = 23) as an exploratory case study. We recorded their attitudes towards programming, their state-level emotions, the fun they experienced, and the initial- and final knowledge on the topic and their gender for comparative purposes. Our findings indicate that the coding workshop had a positive effect on children’s state-level emotions, as children felt significantly happier, more excited and more in control at the end of the workshop than at the beginning of it. We also found that children’s attitude toward programming changed significantly and positively during the workshop, and that children’s attitude about programming is influenced by the experienced fun while learning to code regardless their gender. Additionally, we found that the workshop was successful in terms of knowledge acquisition: both the measured and the reported learning indicate that children learned during the activity. Our findings also indicate that children’s reported learning has a positive association with their state-level emotion feeling in control and that the measured learning is negatively influenced by high levels of stress. Accordingly, our results draw attention to the downshifting effect of high arousal emotions on the measured learning. Throughout the paper we discuss gender differences along the study findings and elaborate on further practical implications.