In a recent official statement, Google highlighted the negative effects of fake reviews on review websites and specifically requested companies not to buy and users not to accept payments to provide fake reviews (Google, 2019). Also, governmental authorities started acting against organisations that show to have a high number of fake reviews on their apps (DigitalTrends, 2018; Gov UK, 2020; ACM, 2017). However, while the phenomenon of fake reviews is well-known in industries as online journalism and business and travel portals, it remains a difficult challenge in software engineering (Martens & Maalej, 2019). Fake reviews threaten the reputation of an organisation and lead to a disvalued source to determine the public opinion about brands. Negative fake reviews can lead to confusion for customers and a loss of sales. Positive fake reviews might also lead to wrong insights about real users’ needs and requirements. Although fake reviews have been studied for a while now, there are only a limited number of spam detection models available for companies to protect their corporate reputation. Especially in times with the coronavirus, organisations need to put extra focus on online presence and limit the amount of negative input that affects their competitive position which can even lead to business loss. Given state-of-the-art derived features that can be engineered from review texts, a spam detector based on supervised machine learning is derived in an experiment that performs quite well on the well-known Amazon Mechanical Turk dataset.
MULTIFILE
Little is known about the role of organizational culture regarding management control systems (MCS) that focus on corporate sustainability. To enhance our understanding of this phenomenon, this study of MCS shows how social and technical forms of control can be used to embedded sustainability in the corporate culture. When companies are founded with a sustainable purpose, then sustainability at the core of their endeavors. In these cases, social controls have the main focus and have a substitutive role to technical controls. In contrast, social and technical controls are complementary to effectively embed sustainability in the culture for companies transitioning to sustainability. We empirically inform our study with a multiple exploratory case-study design, using interviews, desk research, and observations, investigating a variety of twenty companies in The Netherlands that aim to corporate sustainability. In this paper, we respond to the need in a literature for further empirical research regarding the design of MCS aimed at sustainability, and the role of culture in particular. We also contribute to the discussion in the literature about complementarity versus substitution of controls. Besides contributing to the academic literature, we believe this paper can also help practitioners design MCS to create sustainable value for their organization.
A considerable amount of literature has been published on Corporate Reputation, Branding and Brand Image. These studies are extensive and focus particularly on questionnaires and statistical analysis. Although extensive research has been carried out, no single study was found which attempted to predict corporate reputation performance based on data collected from media sources. To perform this task, a biLSTM Neural Network extended with attention mechanism was utilized. The advantages of this architecture are that it obtains excellent performance for NLP tasks. The state-of-the-art designed model achieves highly competitive results, F1 scores around 72%, accuracy of 92% and loss around 20%.
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.
Many companies struggle with their workplace strategy and corporate real-estate strategy, especially when they have a high percentage of knowledge workers. How to balance employee satisfaction and productivity with the cost of offices.This project focused on developing methods and tools to design customer journeys and predict the impact of investments and changes on user satisfaction with the work environment. The tools, including a game and simulation tool, allowed to focus on the needs of particular subgroups of employees while at the same time keeping an overview on the satisfaction and perceived productivity of all employees and guests. We applied Quality Function Deployment techniques to understand how needs of different types of users of (activity-based) office environments can catered for in smart customer-centric office design.
Advances in technology are opening up new learning opportunities, consequently having an impact on conventional teaching and learning concepts. The roles of teachers, students and universities are also being transformed worldwide. The Academy for Leisure & Events of BUas has always been part of the above quest.Therefore, it is crucial that teaching methods and learning experiences in higher education are dynamic and continuously incorporate innovative approaches as well as integrate new technologies. After all, it is essential to be prepared for the way students learn nowadays and for the future demand coming.It is now more important than ever, especially considering the challenging coronavirus times we are in, for Breda University of Applied Sciences – as a partner of this project – to actively contribute to strengthening staff capacities in innovative teaching and learning methods and digital skills. For instance by offering training courses in a blended model, combining face-to-face teacher training with MOOCs and e-learning.As designing meaningful experiences has always been at the heart of the mission and work ofthe Academy for Leisure & Events, this project builds upon further extension of networks in teaching and learning innovation in national and international higher education contexts.Partners:FH Joanneum University of Applied Sciences, Universidad Carlos III de Madrid, Universidad de Lima, Universidad Catolica San Pablo, Universidad de Piura, Universidad Austral de Chile, Universidad de Santiago de Chile, Universidad Vina del Mar
