The Dutch horticultural supply chain is characterised by substantial uncertainty resulting from ongoing organisational changes, such as the transformation from an auction-cooperative system to a sales organisation-based structure. This uncertainty causes strategic behaviour among all supply-chain members (including producers), which often disadvantages primary producers. This study investigates how uncertainty shapes trading behaviour and decision-making using Transaction Cost Theory as a theoretical framework. Specifically, it examines the relationship between environmental and behavioural uncertainty, trading behaviour and strategic responses. Employing a multimethod approach involving interviews, simulation sessions and debriefings to collect data, this study integrates a qualitative and quantitative analysis. The findings reveal: (1) how uncertainty influences trader behaviour and strategic decision-making, and demonstrates the need for more effective coordination mechanisms and strategies to reduce opportunism and inefficiencies in horticultural trade, (2) the diversity of strategic responses to uncertainty and (3) the factors that influence uncertainty and their relationship. These factors, include the current supply-chain structure that upholds uncertainty and strategic behaviour such as the deliberate exploitation of the absence or lack of information (asymmetric information). By combining methodological triangulation with theoretical insight, this study provides a foundational understanding of strategic behaviour under uncertainty in agri-food supply chains.

A lack of self-awareness of communicative behaviours can lead to disadvantages in important interactions. Video recordings as a tool for self-observation have been widely adopted to initiate behaviour change and reflection. Seeing oneself in a recording can lead to negative affect. Forcing an external perspective can lead to cognitive dissonance. Avatars and virtual agents have the advantage that they can copy a human's behaviour while potentially avoiding this dissonance. To explore the design space of mimicking agents, we set up a user study where a video baseline is compared to agent-mediated conditions ranging from idle non-verbal behaviour to complete mimicry of the voice and face. We show that participants gain increased self-awareness from seeing themselves mediated through the virtual agent. We further discuss qualitative observations for the future design of systems that aid in self-reflection, and particularly note that partial mimicry seems to be less appreciated than full mimicry.

Schedule design in the transportation and logistics sector is a widely studied problem. Transport service providers, such as the train industry and aviation, aim for schedules to be on-time according to the planning (i.e., on-time performance or OTP) in order to increase the service level by ensuring that passengers actually make their connections and to reduce costs. Transportation services also aim for schedules that serve a high variety of destinations and frequency of connections (i.e., connectivity). OTP and connectivity are both highly dependent on buffer time: more lucrative connections can often be offered by reducing the buffer time in the schedule, while more delay can be absorbed by more buffer time. Given strict constraints on the minimum turnaround time of aircraft and minimum (and maximum acceptable) transfer times of passengers, assigning buffer time in an already tightly planned schedule to optimize OTP and connectivity simultaneously is a big challenge. This research presents a novel multi-objective formulation of a daily flight schedule where buffer scheduling is used to ensure the optimal balance between OTP of the schedule and the passenger connections as connectivity, given the tight restrictions. This problem formulation is solved using a simulation–optimization framework. Specifically, we use the Multi-Objective Evolutionary Algorithm (MOEA) BORG. As a proof of concept, a daily European flight schedule of a large international airline is optimized on both OTP and connectivity. The results demonstrate that the presented multi-objective formulation and associated solving through simulation–optimization can result in candidate schedules with both better on-time performance and a higher connectivity.

Simplifications of the real world affect the validity and reliability of gaming simulations. This challenges the application of gaming simulations as an instrument for experiential learning, reflective practices and data collection. This study investigates the effects of simplification on extracting tacit knowledge from human behavior by answering the research question: Can tacit knowledge in a simplified design of a gaming simulation be transferred without compromising the validity and reliability corresponding to the real-world complexity? By applying a participatory design a gaming simulation is tested as an instrument to extract tacit knowledge. To test and evaluate the validity of this application, simulation sessions have been performed with experts from the field. In simplifying reality, participants' participation emphasized that the most accurate representation of reality is a prerequisite for capturing tacit knowledge. This in turn contributes again to the validity of the simulation design. The results show that simplification of the real world didn't affect participants' perspective on the use of the gaming simulation as an experiential tool to enable learning processes or create awareness. And that a simplified simulation design, is still valid in addressing the real-world complexity, with minimization of the level of abstraction and maximization of the truthfulness.

Affective aggression is a form of aggression characterized by impulsive reactions driven by strong negative emotions. Despite the extensive research in the area of automatic emotion recognition, affective aggression is a phenomenon that has received less attention. This study investigates the use of head motion as a potential indicator of affective aggression and negative affect. It provides an analysis of head movement patterns associated with various levels of aggression, valence, arousal and dominance, and compares behaviors and recognition performance under speaking and listening conditions. The study was conducted on the Negative Affect and Aggression database - a multimodal corpus of dyadic interactions between aggression regulation training actors and non-actors, annotated for levels of aggression, valence, arousal, and dominance. Results demonstrate that head motion features can serve as promising indicators of affect during both speaking and listening. Valence and arousal prediction achieved better performance during speaking, while aggression and dominance were better predicted during listening. Significant increases in the magnitude of pitch angular acceleration were associated with escalation along all four annotated dimensions. Interestingly, higher escalation was accompanied by a significant increase in the total number of movements during speaking, but a significant decrease of the number of movements was observed as escalation increased along listening intervals. These findings are particularly relevant as head motion can be used solely or potentially as a supplementary modality when other modalities such as speech or facial expressions are unavailable or altered.

The INTERSPEECH 2021 Computational Paralinguistics Challenge addresses four different problems for the first time in a research competition under well-defined conditions: In the COVID-19 Cough and COVID-19 Speech Sub-Challenges, a binary classification on COVID-19 infection has to be made based on coughing sounds and speech; in the Escalation Sub- Challenge, a three-way assessment of the level of escalation in a dialogue is featured; and in the Primates Sub-Challenge, four species vs background need to be classified. We describe the Sub-Challenges, baseline feature extraction, and classifiers based on the 'usual' COMPARE and BoAW features as well as deep unsupervised representation learning using the AUDEEP toolkit, and deep feature extraction from pre-trained CNNs using the DEEP SPECTRUM toolkit; in addition, we add deep end-to-end sequential modelling, and partially linguistic analysis.

Multimodal Sentiment Analysis in Real-life Media (MuSe) 2020 is a Challenge-based Workshop focusing on the tasks of sentiment recognition, as well as emotion-target engagement and trustworthiness detection by means of more comprehensively integrating the audio-visual and language modalities. The purpose of MuSe 2020 is to bring together communities from different disciplines; mainly, the audio-visual emotion recognition community (signal-based), and the sentiment analysis community (symbol-based). We present three distinct sub-challenges: MuSe-Wild, which focuses on continuous emotion (arousal and valence) prediction; MuSe-Topic, in which participants recognise 10 domain-specific topics as the target of 3-class (low, medium, high) emotions; and MuSe-Trust, in which the novel aspect of trustworthiness is to be predicted. In this paper, we provide detailed information on MuSe-CAR, the first of its kind in-the-wild database, which is utilised for the challenge, as well as the state-of-the-art features and modelling approaches applied. For each sub-challenge, a competitive baseline for participants is set; namely, on test we report for MuSe-Wild a combined (valence and arousal) CCC of .2568, for MuSe-Topic a score (computed as 0.34∗UAR + 0.66∗F1) of 76.78 % on the 10-class topic and 40.64 % on the 3-class emotion prediction, and for MuSe-Trust a CCC of .4359.

Background. Revealing tacit knowledge often is seen as very valuable for organizations, although it is usually challenging to enunciate and share this type of knowledge. Methods. This study uses a participatory design and the application of a board gaming simulation as instruments to extract tacit knowledge. To illustrate this application, the gaming simulation is played with entrepreneurs from horticulture. Horticulture represents a complex social system where tacit knowledge plays a major role in the trade process. A participatory design process is used to explore whether the design and play of gaming simulations enable participants to explicate their tacit knowledge. Participants’ participation in designing the gaming simulation explicated that reconstructing reality was a prerequisite for their commitment. Results. The results from playing simulation sessions show that participants were able to: (1) narrow down the anecdotic behaviour to a few factors; (2) to structure these factors; (3) explore how these factors relate to trade barriers and (4) to explain which tactics are applied to foster trade. Conclusion. The educational value of this study is that it helped entrepreneurs in understanding complex real-life situations.