A Modeling Framework to Assess Strategies Alignment based on Collaborative Network Emotions

[DE] The Collaborative Networks (CN) discipline has been largely studied in last decades, addressing different problems and proposing solutions for the robust establishment of collaborative processes, within the enterprises willing to collaborate. The main aim of CN research is, therefore, to generate approaches that enable creating effective relationships in the long term, to achieve stable and agile alliances. The concept of alignment among the CN partners has been considered since the beginning of CN research. Nevertheless, novel perspectives of study in CN, such as the consideration of collaborative emotional states, within the CN, have been introduced in recent years. This paper connects the research area of strategies alignment and the CN emotion models. Accordingly, a modelling framework to assess strategies alignment considering the emotional environment within the CN is proposed. The modelling framework allows representing how the enterprises emotions affect in the selection and alignment of formulated enterprises¿ strategiesAndres, B.; Ferrada, F.; Poler, R.; Camarinha-Matos, L. (2018). A Modeling Framework to Assess Strategies Alignment based on Collaborative Network Emotions. IFIP Advances in Information and Communication Technology. 534:349-361. https://doi.org/10.1007/978-3-319-99127-6_30S349361534Camarinha-Matos, L.M.: Collaborative networks in industry and the role of PRO-VE. Int. J. Prod. Manag. Eng. 2(2), 53–57 (2014)Andres, B., Poler, R.: Models, guidelines and tools for the integration of collaborative processes in non-hierarchical manufacturing networks: a review. Int. J. Comput. Integr. Manuf. 2(29), 166–201 (2016)Bititci, U., Martinez, V., Albores, P., Parung, J.: Creating and managing value in collaborative networks. Int. J. Phys. Distrib. Logist. 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C-EMO: A Modeling Framework for Collaborative Network Emotions

Recent research in the area of collaborative networks is focusing on the social and organizational complexity of collaboration environments as a way to prevent technological failures and consequently contribute for the collaborative network’s sustainability. One direction is moving towards the need to provide “human-tech” friendly systems with cognitive models of human factors such as stress, emotion, trust, leadership, expertise or decision-making ability. In this context, an emotion-based system is being proposed with this thesis in order to bring another approach to avoid collaboration network’s failures and help in the management of conflicts. This approach, which is expected to improve the performance of existing CNs, adopts some of the models developed in the human psychology, sociology and affective computing areas. The underlying idea is to “borrow” the concept of human-emotion and apply it into the context of CNs, giving the CN players the ability to “feel emotions”. Therefore, this thesis contributes with a modeling framework that conceptualizes the notion of “emotion” in CNs and a methodology approach based on system dynamics and agent-based techniques that estimates the CN player’s “emotional states” giving support to decision-making processes. Aiming at demonstrating the appropriateness of the proposed framework a simulation prototype was implemented and a validation approach was proposed consisting of simulation of scenarios, qualitative assessment and validation by research community peers.Recentemente a área de investigação das redes colaborativas tem vindo a debruçar-se na complexidade social e organizacional em ambientes colaborativos e como pode ser usada para prevenir falhas tecnológicas e consequentemente contribuir para redes colaborativas sustentáveis. Uma das direcções de estudo assenta na necessidade de fornecer sistemas amigáveis “humano-tecnológicos” com modelos cognitivos de factores humanos como o stress, emoção, confiança, liderança ou capacidade de tomada de decisão. É neste contexto que esta tese propõe um sistema baseado em emoções com o objectivo de oferecer outra aproximação para a gestão de conflitos e falhas da rede de colaboração. Esta abordagem, que pressupõe melhorar o desempenho das redes existentes, adopta alguns dos modelos desenvolvidos nas áreas da psicologia humana, sociologia e affective computing. A ideia que está subjacente é a de “pedir emprestado” o conceito de emoção humana e aplicá-lo no contexto das redes colaborativas, dando aos seus intervenientes a capacidade de “sentir emoções”. Assim, esta tese contribui com uma framework de modelação que conceptualiza a noção de “emoção” em redes colaborativas e com uma aproximação de metodologia sustentada em sistemas dinâmicos e baseada em agentes que estimam os “estados emocionais” dos participantes e da própria rede colaborativa. De forma a demonstrar o nível de adequabilidade da framework de modelação proposta, foi implementado um protótipo de simulação e foi proposta uma abordagem de validação consistindo em simulação de cenários, avaliação qualitativa e validação pelos pares da comunidade científica

Current Challenges and Visions in Music Recommender Systems Research

Music recommender systems (MRS) have experienced a boom in recent years, thanks to the emergence and success of online streaming services, which nowadays make available almost all music in the world at the user's fingertip. While today's MRS considerably help users to find interesting music in these huge catalogs, MRS research is still facing substantial challenges. In particular when it comes to build, incorporate, and evaluate recommendation strategies that integrate information beyond simple user--item interactions or content-based descriptors, but dig deep into the very essence of listener needs, preferences, and intentions, MRS research becomes a big endeavor and related publications quite sparse. The purpose of this trends and survey article is twofold. We first identify and shed light on what we believe are the most pressing challenges MRS research is facing, from both academic and industry perspectives. We review the state of the art towards solving these challenges and discuss its limitations. Second, we detail possible future directions and visions we contemplate for the further evolution of the field. The article should therefore serve two purposes: giving the interested reader an overview of current challenges in MRS research and providing guidance for young researchers by identifying interesting, yet under-researched, directions in the field

Automatic Context-Driven Inference of Engagement in HMI: A Survey

An integral part of seamless human-human communication is engagement, the process by which two or more participants establish, maintain, and end their perceived connection. Therefore, to develop successful human-centered human-machine interaction applications, automatic engagement inference is one of the tasks required to achieve engaging interactions between humans and machines, and to make machines attuned to their users, hence enhancing user satisfaction and technology acceptance. Several factors contribute to engagement state inference, which include the interaction context and interactants' behaviours and identity. Indeed, engagement is a multi-faceted and multi-modal construct that requires high accuracy in the analysis and interpretation of contextual, verbal and non-verbal cues. Thus, the development of an automated and intelligent system that accomplishes this task has been proven to be challenging so far. This paper presents a comprehensive survey on previous work in engagement inference for human-machine interaction, entailing interdisciplinary definition, engagement components and factors, publicly available datasets, ground truth assessment, and most commonly used features and methods, serving as a guide for the development of future human-machine interaction interfaces with reliable context-aware engagement inference capability. An in-depth review across embodied and disembodied interaction modes, and an emphasis on the interaction context of which engagement perception modules are integrated sets apart the presented survey from existing surveys

Optimizing Partnership Impact: Prioritizing High-Quality Social-Emotional Learning In A Sports Enrichment Out-Of-School Time Program

Research demonstrates that out-of school time (OST) programs featuring physical activity positively impact students\u27 social-emotional learning (SEL) competencies, including self-regulation and collaboration skills. However, financial barriers prevent low-income students access to OST and sports opportunities. Grant-funded OST partnerships seeking to improve student well-being, emotional safety, and connection need ways to measure their value. A systems view indicates that OSTs play an interactive role within a school\u27s complex system. Guided by the Improvement Science Framework, this Dissertation-in-Practice aimed to strengthen the SEL quality of 2-4-1 TOP Self Sports, a physical literacy-informed sports enrichment OST program serving primarily elementary school students. Using an action research methodology and a mixed-methods sequential explanatory design, the study used the Forum for Youth Investment\u27s SEL PQA, a research-validated program evaluation tool measuring the quality of OS T\u27s SEL practices and opportunities. The researcher collaborated with the OST, 2- 4-1 CARE, to design and implement a job-embedded curriculum-based SEL intervention at two mban-based magnet schools. The researcher analyzed pre- and post-intervention scores and transcripts from semi-structured focus groups with 2-4-1 instructors to determine the extent of the intervention\u27s impact. Post-intervention data indicate high-quality SEL in 2-4-1 TOP Self improvement in three of the four domains and two of the three focus areas. 2-4-1 instructors indicated the SEL intervention increased their intentionality to promote self-awareness and selfregulation skills. They observed student SEL growth during and beyond the sports enrichment time, suggesting the potential for 2-4-1 TOP Self to improve school climate

Models and tools for value systems analysis in collaborative environments

Dissertation to obtain the degree of Doctor in Electrical and Computer Engineering, specialization of Collaborative NetworksParticipation in collaborative networks is vital for small and medium-sized enterprises to survive in the current market, bringing them several benefits. However,participation in collaborative networks also involves risks and often consortia fail due to internal conflicts. Conflicts can be originated by different prioritization of values and different perceptions of outcomes. The perception of outcomes is, to some extent, subjective given that it depends on the preferences of the subject and how exchanges are evaluated. Therefore, the establishment of a common Value System or the effort to align the Value Systems of network members can play an important role in the collaboration sustainability. Although the topic of values and values alignment has been studied within the scope of various scientific disciplines, there is still no common understanding on these concepts and the literature does not include any suitable models to formally represent and analyze Value Systems within the scope of collaborative networks. This thesis proposes a set of models and formal mechanisms for specifying and analyzing Value Systems in collaborative networks. The development of models and methods followed a hybrid approach, where qualitative and quantitative techniques are used in order to represent and analyze the Value System. A web application was designed and a prototype developed in order to show that the models and methods proposed can be implemented by a computer program and can be integrated into a single framework in order to support Value Systems management within the scope of collaborative networks. The application of a multifaceted and systematic validation strategy, supported by the “Square Validation Framework” brought together a set of preliminary results that attest the theoretical and practical relevance of the proposed approach and allow us to conclude that: (i) it is possible to define and analyze Value Systems in collaborative networks, considering the economic and sociologic approach, in an integrated and unambiguous way, (ii) the potential impacts between Value Systems in collaborative environments can be inferred if the typical influences among core values are known and the preferences of the actors, regarding those values, are identified; (iii) the identification and assessment of Value Systems misalignments would be improved if qualitative and quantitative assessment methods integrating the notion of shared-values, potential for conflict and positive impacts were developed