This paper presents a Decision Support System (DSS) that helps companies with corporate reputation (CR) estimates of their respective brands by collecting provided feedbacks on their products and services and deriving state-of-the-art key performance indicators. A Sentiment Analysis Engine (SAE) is at the core of the proposed DSS that enables to monitor, estimate, and classify clients’ sentiments in terms of polarity, as expressed in public comments on social media (SM) company channels. The SAE is built on machine learning (ML) text classification models that are cross-source trained and validated with real data streams from a platform like Trustpilot that specializes in user reviews and tested on unseen comments gathered from a collection of public company pages and channels on a social networking platform like Facebook. Such crosssource opinion analysis remains a challenge and is highly relevant in the disciplines of research and engineering in which a sentiment classifier for an unlabeled destination domain is assisted by a tagged source task (Singh and Jaiswal, 2022). The best performance in terms of F1 score was obtained with a multinomial naive Bayes model: 0,87 for validation and 0,74 for testing.
Purpose: Board members and real estate managers (decision makers) play an important role in the decision-making process in nursing home organisations. This study aims to provide an understanding of underlying attributes and benefits sought by decision makers when making nursing home real estate decisions. Design/methodology/approach: Decision makers from seven different nursing home organisations in The Netherlands were interviewed using the laddering technique to determine the individual requirements, the considerations of the decision alternatives, the relevant attributes and benefits and their mutual relationships. Findings: This study details the motivations behind real estate management decisions in nursing home organisations. The findings show that apart from financial considerations, decision makers strive to enhance the quality of life and satisfaction of users with their real estate decisions and seek to include residents and employees in the process. These benefits are connected to the goals of well-being and innovation in health care. Furthermore, functionality, physical and functional flexibility and technology are key considerations when undertaking corporate real estate (CRE) decisions, to ensure that real estate management aligns with the strategic goals of the nursing home organisation. Practical implications: The insights of this study can support decision makers in healthcare facilities to create strategic value with their real estate. Understanding how to obtain certain benefits from nursing home real estate may result in a better realisation of organisational objectives and user needs. Originality/value: This study reveals the decision-making process in a nursing home context. Moreover, the laddering technique is used as a new method to explore and gain a deep understanding of CRE decision-making processes.
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The purpose of this paper is to conceptualise the extent to which partnerships with non-governmental organisations (NGOs) are a necessity for successful efforts of businesses in the area of corporate social responsibility (CSR). The main findings are based on an analysis of existing literature on NGO typologies and strategies for CSR and illustrated with examples from the Dutch National Research Program on CSR. Based on three different strategies towards CSR, the suggestion is that NGOs tend to become involved in partnerships with companies that have an interest in postponing concrete results, while partnerships with companies that have the potential for the biggest contribution to the ambitions of NGOs have the highest risk of diminishing NGO-legitimacy.
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In the last decade, the automotive industry has seen significant advancements in technology (Advanced Driver Assistance Systems (ADAS) and autonomous vehicles) that presents the opportunity to improve traffic safety, efficiency, and comfort. However, the lack of drivers’ knowledge (such as risks, benefits, capabilities, limitations, and components) and confusion (i.e., multiple systems that have similar but not identical functions with different names) concerning the vehicle technology still prevails and thus, limiting the safety potential. The usual sources (such as the owner’s manual, instructions from a sales representative, online forums, and post-purchase training) do not provide adequate and sustainable knowledge to drivers concerning ADAS. Additionally, existing driving training and examinations focus mainly on unassisted driving and are practically unchanged for 30 years. Therefore, where and how drivers should obtain the necessary skills and knowledge for safely and effectively using ADAS? The proposed KIEM project AMIGO aims to create a training framework for learner drivers by combining classroom, online/virtual, and on-the-road training modules for imparting adequate knowledge and skills (such as risk assessment, handling in safety-critical and take-over transitions, and self-evaluation). AMIGO will also develop an assessment procedure to evaluate the impact of ADAS training on drivers’ skills and knowledge by defining key performance indicators (KPIs) using in-vehicle data, eye-tracking data, and subjective measures. For practical reasons, AMIGO will focus on either lane-keeping assistance (LKA) or adaptive cruise control (ACC) for framework development and testing, depending on the system availability. The insights obtained from this project will serve as a foundation for a subsequent research project, which will expand the AMIGO framework to other ADAS systems (e.g., mandatory ADAS systems in new cars from 2020 onwards) and specific driver target groups, such as the elderly and novice.
Nederland kent ongeveer 220.000 bedrijfsongevallen per jaar (met 60 mensen die overlijden). Vandaar dat elke werkgever verplicht is om bedrijfshulpverlening (BHV) te organiseren, waaronder BHV-trainingen. Desondanks brengt slechts een-derde van alle bedrijven de arbeidsrisico’s in kaart via een Risico-Inventarisatie & Evaluatie (RI&E) en blijft het aandeel werknemers met een arbeidsongeval hoog. Daarom wordt er continu geïnnoveerd om BHV-trainingen te optimaliseren, o.a. door middel van Virtual Reality (VR). VR is niet nieuw, maar is wel doorontwikkeld en betaalbaarder geworden. VR biedt de mogelijkheid om veilige realistische BHV-noodsimulaties te ontwikkelen waarbij de cursist het gevoel heeft daar echt te zijn. Ondanks de toename in VR-BHV-trainingen, is er weinig onderzoek gedaan naar het effect van VR in BHV-trainingen en zijn resultaten tegenstrijdig. Daarnaast zijn er nieuwe technologische ontwikkelingen die het mogelijk maken om kijkgedrag te meten in VR m.b.v. Eye-Tracking. Tijdens een BHV-training kan met Eye-Tracking gemeten worden hoe een instructie wordt opgevolgd, of cursisten worden afgeleid en belangrijke elementen (gevaar en oplossingen) waarnemen tijdens de simulatie. Echter, een BHV-training met VR en Eye-Tracking (interacties) bestaat niet. In dit project wordt een prototype ontwikkeld waarin Eye-Tracking wordt verwerkt in een 2021 ontwikkelde VR-BHV-training, waarin noodsituaties zoals een kantoorbrand worden gesimuleerd (de BHVR-toepassing). Door middel van een experiment zal het prototype getest worden om zo voor een deel de vraag te beantwoorden in hoeverre en op welke manier Eye-Tracking in VR een meerwaarde biedt voor (RI&E) BHV-trainingen. Dit project sluit daarmee aan op het missie-gedreven innovatiebeleid ‘De Veiligheidsprofessional’ en helpt het MKB dat vaak middelen en kennis ontbreekt voor onderzoek naar effectiviteit rondom innovatieve-technologieën in educatie/training. Het project levert onder meer een prototype op, een productie-rapport en onderzoeks-artikel, en staat open voor nieuwe deelnemers bij het schrijven van een grotere aanvraag rondom de toepassing en effect van VR en Eye-Tracking in BHV-trainingen.
The Netherlands has approximately 220,000 industrial accidents per year (with 60 people who die). That is why every employer is obliged to organize company emergency response (BHV), including emergency response training. Despite this, only one-third of all companies map out their occupational risks via a Risk Inventory & Evaluation (RI&E) and the share of employees with an occupational accident remains high. That is why there is continuous innovation to optimize emergency response training, for example by means of Virtual Reality (VR). VR is not new, but it has evolved and become more affordable. VR offers the possibility to develop safe realistic emergency response simulations where the student has the feeling that they are really there. Despite the increase in VR-BHV training, little research has been done on the effect of VR in ER training and results are contradictory. In addition, there are new technological developments that make it possible to measure viewing behavior in VR using Eye-Tracking. During an emergency response training, Eye-Tracking can be used to measure how an instruction is followed, whether students are distracted and observe important elements (danger and solutions) during the simulation. However, emergency response training with VR and Eye-Tracking (interactions) does not exist. In this project, a prototype is being developed in which Eye-Tracking is incorporated into a VR-BHV training that was developed in 2021, in which emergency situations such as an office fire are simulated (the BHVR application). The prototype will be tested by means of an experiment in order to partly answer the question to what extent and in what way Eye-Tracking in VR offers added value for (RI&E) emergency response training. This project is therefore in line with the mission-driven innovation policy 'The Safety Professional' and helps SMEs that often lack resources and knowledge for research into the effectiveness of innovative technologies in education/training. The project will include a prototype, a production report and research article, and is open to new participants when writing a larger application about the application and effect of VR and Eye-Tracking in emergency response training.
