PurposeIn order to better understand how heuristics are used in practice, the authors explore what type of heuristics is used in the managerial domain of financial advisors to small and medium-sized enterprises (SMEs) and what influences the shaping of these heuristics. In doing so, the authors detect possible fast-and-frugal heuristics in day-to-day decision-making of independent financial advisers who help owners of SMEs to acquire capital (e.g. loans, factoring, leasing and equity).Design/methodology/approachThe authors inductively assessed the work of financial advisers of SMEs. Based on group discussions, the authors drew up a semi-structured interview-protocol with descriptive questions about how financial advisers come to a deal for their clients. The interviews of 19 professionals were analysed by relating them to the theory of fast-and-frugal heuristics.FindingsWithin their decision-making, advisers estimate the likelihood of acceptance by a few financial providers they know well in their personal network with a strong bias towards traditional banking products, although there are a large number of alternatives on the Dutch market. “Less is more” seems to be a relevant principle when defined as satisficing. Heuristics help advisers to deal with behavioural and economic limitations. Also, the authors have found that client interaction, previous working experience and the company the adviser is working for influences the shaping of the simple rules the adviser is using.Research limitations/implicationsThe study shows how difficult it is to understand the ecological rationality of a certain group of professionals and to understand the “less is more” principle. Financial advisers to SMEs use cognitive shortcuts and simple rules to advise SME-owners, based on previous experiences, but it is difficult to determine whether that leads to the same or even better solutions for them and their clients than using probability theory and financial optimisation models. Within heuristics, satisficing seems to be a dominant mechanism. Here, heuristics help advisers in recognising possibilities by searching for similarities between a current financing case and previous experiences. The data suggests that if “less is more” is defined as satisficing for one or more stakeholders involved, the principle dominates the decision making of financial advisers of SME's.Practical implicationsThe authors suggest the relevance of a behavioural approach to finance by assessing the day-to-day decisions of financial advisers of SMEs. Also, the authors suggest that financial advisers are guided by previous experiences, and they do not fully assess a wide range of options in their work but need shortcuts to fulfil the needs of their clients.Originality/valueThe study comes close to day-to-day decision-making in finance by assessing how professionals make decisions. The authors try to understand types of heuristics in relation with “ecological rationality” and the less is more principle. The authors assess financial advisers of SME-companies, a group that has gotten little research attention until now. The influence of client interaction and of the company the adviser is working for is remarkable in the shaping of the advisers' simple rules.
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Analyzing historical decision-related data can help support actual operational decision-making processes. Decision mining can be employed for such analysis. This paper proposes the Decision Discovery Framework (DDF) designed to develop, adapt, or select a decision discovery algorithm by outlining specific guidelines for input data usage, classifier handling, and decision model representation. This framework incorporates the use of Decision Model and Notation (DMN) for enhanced comprehensibility and normalization to simplify decision tables. The framework’s efficacy was tested by adapting the C4.5 algorithm to the DM45 algorithm. The proposed adaptations include (1) the utilization of a decision log, (2) ensure an unpruned decision tree, (3) the generation DMN, and (4) normalize decision table. Future research can focus on supporting on practitioners in modeling decisions, ensuring their decision-making is compliant, and suggesting improvements to the modeled decisions. Another future research direction is to explore the ability to process unstructured data as input for the discovery of decisions.
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DISCO aims at fast-tracking upscaling to new generation of urban logistics and smart planning unblocking the transition to decarbonised and digital cities, delivering innovative frameworks and tools, Physical Internet (PI) inspired. To this scope, DISCO will deploy and demonstrate innovative and inclusive urban logistics and planning solutions for dynamic space re-allocation integrating urban freight at local level, within efficiently operated network-of-networks (PI) where the nodes and infrastructure are fixed and mobile based on throughput demands. Solutions are co-designed with the urban logistics community – e.g., cities, logistics service providers, retailers, real estate/public and private infrastructure owners, fleet owners, transport operators, research community, civil society - all together moving a paradigm change from sprawl to data driven, zero-emission and nearby-delivery-based models.
The IMPULS-2020 project DIGIREAL (BUas, 2021) aims to significantly strengthen BUAS’ Research and Development (R&D) on Digital Realities for the benefit of innovation in our sectoral industries. The project will furthermore help BUas to position itself in the emerging innovation ecosystems on Human Interaction, AI and Interactive Technologies. The pandemic has had a tremendous negative impact on BUas industrial sectors of research: Tourism, Leisure and Events, Hospitality and Facility, Built Environment and Logistics. Our partner industries are in great need of innovative responses to the crises. Data, AI combined with Interactive and Immersive Technologies (Games, VR/AR) can provide a partial solution, in line with the key-enabling technologies of the Smart Industry agenda. DIGIREAL builds upon our well-established expertise and capacity in entertainment and serious games and digital media (VR/AR). It furthermore strengthens our initial plans to venture into Data and Applied AI. Digital Realities offer great opportunities for sectoral industry research and innovation, such as experience measurement in Leisure and Hospitality, data-driven decision-making for (sustainable) tourism, geo-data simulations for Logistics and Digital Twins for Spatial Planning. Although BUas already has successful R&D projects in these areas, the synergy can and should significantly be improved. We propose a coherent one-year Impuls funded package to develop (in 2021): 1. A multi-year R&D program on Digital Realities, that leads to, 2. Strategic R&D proposals, in particular a SPRONG/sleuteltechnologie proposal; 3. Partnerships in the regional and national innovation ecosystem, in particular Mind Labs and Data Development Lab (DDL); 4. A shared Digital Realities Lab infrastructure, in particular hardware/software/peopleware for Augmented and Mixed Reality; 5. Leadership, support and operational capacity to achieve and support the above. The proposal presents a work program and management structure, with external partners in an advisory role.
The Dutch floriculture is globally leading, and its products, knowledge and skills are important export products. New challenges in the European research agenda include sustainable use of raw materials such as fertilizer, water and energy, and limiting the use of pesticides. Greenhouse growers however have little control over crop growth conditions in the greenhouse at individual plant level. The purpose of this project, ‘HiPerGreen’, is to provide greenhouse owners with new methods to monitor the crop growth conditions in their greenhouse at plant level, compare the measured growth conditions and the measured growth with expected conditions and expected growth, to point out areas with deviations, recommend counter-measures and ultimately to increase their crop yield. The main research question is: How can we gather, process and present greenhouse crop growth parameters over large scale greenhouses in an economical way and ultimately improve crop yield? To provide an answer to this question, a team of university researchers and companies will cooperate in this applied research project to cover several different fields of expertise The application target is floriculture: the production of ornamental pot plants and cut flowers. Participating companies are engaged in the cultivation of pot plans, flowers and suppliers of greenhouse technology. Most of the parties fall in the SME (MKB) category, in line with the RAAK MKB objectives.Finally, the Demokwekerij and Hortipoint (the publisher of the international newsletter on floriculture) are closely involved. The project will develop new knowledge for a smart and rugged data infrastructure for growth monitoring and growth modeling in the greenhouse. In total the project will involve approximately 12 (teacher) researchers from the universities and about 60 students, who will work in the form of internships and undergraduate studies of interesting questions directly from the participating companies.
