Explore the vast range of titles available.

Platform sponsors typically have both incentive and opportunity to manage the overall value of their ecosystems. Through selective promotion, a platform sponsor can reward successful complements, bring attention to underappreciated complements, and influence the consumer’s perception of the ecosystem’s depth and breadth. It can use promotion to induce and reward loyalty of powerful complement producers, and it can time such promotion to both boost sales during slow periods and reduce competitive interactions between complements. We develop arguments about whether and when a platform sponsor will selectively promote individual complements and test these arguments on data from the console video game industry in the United Kingdom. We find that platform sponsors do not simply promote “best in class” complements; they strategically invest in complements in ways that address complex trade-offs in ecosystem value. Our arguments and results build significant new theory that helps us understand how a platform sponsor orchestrates value creation in the overall ecosystem.

Families often face financial and geographical barriers to services for children with autism. The current study explored the effectiveness of a parent-supported adaptation of the computer game-based social skills program Secret Agent Society (SAS). Seventy child-parent dyads were randomized to SAS ( n  = 35) or a caregiver-supported cognitive skills training game (CIA—control comparison; n  = 35), both completed over 10 weeks. Child participants were on the autism spectrum and aged seven to 12 years (60 boys, 10 girls). SAS participants improved more than CIA participants on parent-rated social skills and problem behaviors and teacher-rated social skills. Findings suggest the intervention may be a convenient, cost-effective therapeutic approach, especially during times of restricted face-to-face service access, such as COVID-19.

Video game technology is changing from 2D to 3D and virtual reality (VR) graphics. In this research, we analyze how an identical video game that is either played in a 2D, stereoscopic 3D or Head-Mounted-Display (HMD) VR version is experienced by the players, and how brands that are placed in the video game are affected. The game related variables, which are analyzed, are presence, attitude towards the video game and arousal while playing the video game. Brand placement related variables are attitude towards the placed brands and memory (recall and recognition) for the placed brands. 237 players took part in the main study and played a jump'n'run game consisting of three levels. Results indicate that presence was higher in the HMD VR than in the stereoscopic 3D than in the 2D video game, but neither arousal nor attitude towards the video game differed. Memory for the placed brands was lower in the HMD VR than in the stereoscopic 3D than in the 2D video game, whereas attitudes towards the brands were not affected. A post hoc study (n = 53) shows that cognitive load was highest in the VR game, and lowest in the 3D game. Subjects reported higher levels of dizziness and motion-sickness in the VR game than in the 3D and in the 2D game. Limitations are addressed and implications for researchers, marketers and video game developers are outlined.

Gaming disorder (GD) is a clinical addiction to video or internet games. This study investigated whether GD symptoms are heightened in adults with autism spectrum disorder (ASD) in comparison to a control group, and explored predictors of GD in 230 adults with ASD and 272 controls. The relationship between GD and gelotophobia was examined. Measures included the Ten-Item Internet Gaming Disorder Test, GELOPH < 15 >, Autism Spectrum Quotient-10 items, Inventory of Parent and Peer attachment, Emotional Regulation Questionnaire, Social Functioning Questionnaire (SFQ) and the NEO-FFI-3. Individuals in the ASD group showed significantly higher symptoms of GD. Peer-attachment, emotional regulation and extraversion significantly predicted GD scores. Gelotophobia and GD were related to each other with a small effect size.

The merger of game-based approaches and Virtual Reality (VR) environments that can enhance learning and training methodologies have a very promising future, reinforced by the widespread market-availability of affordable software and hardware tools for VR-environments. Rather than passive observers, users engage in those learning environments as active participants, permitting the development of exploration-based learning paradigms. There are separate reviews of VR technologies and serious games for educational and training purposes with a focus on only one knowledge area. However, this review covers 135 proposals for serious games in immersive VR-environments that are combinations of both VR and serious games and that offer end-user validation. First, an analysis of the forum, nationality, and date of publication of the articles is conducted. Then, the application domains, the target audience, the design of the game and its technological implementation, the performance evaluation procedure, and the results are analyzed. The aim here is to identify the factual standards of the proposed solutions and the differences between training and learning applications. Finally, the study lays the basis for future research lines that will develop serious games in immersive VR-environments, providing recommendations for the improvement of these tools and their successful application for the enhancement of both learning and training tasks.

Video games have become a ubiquitous part of demographically diverse cultures. Numerous studies have focused on analyzing the cognitive aspects involved in game playing that could help in providing an optimal gaming experience by improving video game design. To this end, we present a framework for classifying the game player’s expertise level using wearable electroencephalography (EEG) headset. We hypothesize that expert and novice players’ brain activity is different, which can be classified using frequency domain features extracted from EEG signals of the game player. A systematic channel reduction approach is presented using a correlation-based attribute evaluation method. This approach lead us in identifying two significant EEG channels, i.e., AF3 and P7, among fourteen channels available in Emotiv EPOC headset. In particular, features extracted from these two EEG channels contributed the most to the video game player’s expertise level classification. This finding is validated by performing statistical analysis (t-test) over the extracted features. Moreover, among multiple classifiers used, K-nearest neighbor is the best classifier in classifying game player’s expertise level with a classification accuracy of up to 98.04% (without data balancing) and 98.33% (with data balancing).

This study examines how an organization can redefine its core process when faced with a major crisis of creative efficiency. We analyze the case of the experimentation of the “Always Playable” project at Ubisoft Montreal, a leading video game development studio, where a crisis of creativity triggered an active reconfiguration of routines and their artifacts. To address this crisis, the organization attempted to restore a balance between efficiency and flexibility by modifying the generative relationship among the ostensive aspect, the performative aspect, and artifacts of routines. Our study shows that one way to reach this balance is by deliberately breaking, partitioning, and recombining aspects from different routines.

This article considers players’ experiences seeking out new games to play, and their use of the Australian National Classification Scheme in doing so. The global video game industry is booming, with hundreds of games being released each month across numerous platforms. As a result, players have an unprecedented number of games available when choosing what games to purchase. However, a number of confounding issues around the emergent content of games and the subjective nature of game reviewing makes it difficult to relate what kinds of experiences a given game will facilitate. In this study, we surveyed game players in order to find their game platform and acquisition preferences; strategies and experiences when choosing games; and attitudes towards classification systems. Our findings suggest that players find it difficult to choose what games to purchase, and that existing classification systems are mostly only beneficial when choosing games for minors.

Constructing agents with planning capabilities has long been one of the main challenges in the pursuit of artificial intelligence. Tree-based planning methods have enjoyed huge success in challenging domains, such as chess 1 and Go 2 , where a perfect simulator is available. However, in real-world problems, the dynamics governing the environment are often complex and unknown. Here we present the MuZero algorithm, which, by combining a tree-based search with a learned model, achieves superhuman performance in a range of challenging and visually complex domains, without any knowledge of their underlying dynamics. The MuZero algorithm learns an iterable model that produces predictions relevant to planning: the action-selection policy, the value function and the reward. When evaluated on 57 different Atari games 3 —the canonical video game environment for testing artificial intelligence techniques, in which model-based planning approaches have historically struggled 4 —the MuZero algorithm achieved state-of-the-art performance. When evaluated on Go, chess and shogi—canonical environments for high-performance planning—the MuZero algorithm matched, without any knowledge of the game dynamics, the superhuman performance of the AlphaZero algorithm 5 that was supplied with the rules of the game. A reinforcement-learning algorithm that combines a tree-based search with a learned model achieves superhuman performance in high-performance planning and visually complex domains, without any knowledge of their underlying dynamics.

Anecdotal reports suggest that motion sickness may occur among users of contemporary, consumer-oriented head-mounted display systems and that women may be at greater risk. We evaluated the nauseogenic properties of one such system, the Oculus Rift . The head-mounted unit included motion sensors that were sensitive to users’ head movements, such that head movements could be used as control inputs to the device. In two experiments, seated participants played one of two virtual reality games for up to 15 min. In Experiment 1, 22% of participants reported motion sickness, and the difference in incidence between men and women was not significant. In Experiment 2, motion sickness was reported by 56% of participants, and incidence among women (77.78%) was significantly greater than among men (33.33%). Before participants were exposed to the head-mounted display system, we recorded their standing body sway during the performance of simple visual tasks. In both experiments, patterns of pre-exposure body sway differed between participants who (later) reported motion sickness and those who did not. In Experiment 2, sex differences in susceptibility to motion sickness were preceded by sex differences in body sway. These postural effects confirm a prediction of the postural instability theory of motion sickness. The results indicate that users of contemporary head-mounted display systems are at significant risk of motion sickness and that in relation to motion sickness these systems may be sexist in their effects.