Research, advisory companies, consultants and system integrators all predict that a lot of money will be earned with decision management (business rules, algorithms and analytics). But how can you actually make money with decision management or in other words: Which business models are exactly available? In this article, we present seven business models for decision management.
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In mobile robotics, LASER scanners have a wide spectrum of indoor and outdoor applications, both in structured and unstructured environments, due to their accuracy and precision. Most works that use this sensor have their own data representation and their own case-specific modeling strategies, and no common formalism is adopted. To address this issue, this manuscript presents an analytical approach for the identification and localization of objects using 2D LiDARs. Our main contribution lies in formally defining LASER sensor measurements and their representation, the identification of objects, their main properties, and their location in a scene. We validate our proposal with experiments in generic semi-structured environments common in autonomous navigation, and we demonstrate its feasibility in multiple object detection and identification, strictly following its analytical representation. Finally, our proposal further encourages and facilitates the design, modeling, and implementation of other applications that use LASER scanners as a distance sensor.
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Background: Advanced statistical modeling techniques may help predict health outcomes. However, it is not the case that these modeling techniques always outperform traditional techniques such as regression techniques. In this study, external validation was carried out for five modeling strategies for the prediction of the disability of community-dwelling older people in the Netherlands. Methods: We analyzed data from five studies consisting of community-dwelling older people in the Netherlands. For the prediction of the total disability score as measured with the Groningen Activity Restriction Scale (GARS), we used fourteen predictors as measured with the Tilburg Frailty Indicator (TFI). Both the TFI and the GARS are self-report questionnaires. For the modeling, five statistical modeling techniques were evaluated: general linear model (GLM), support vector machine (SVM), neural net (NN), recursive partitioning (RP), and random forest (RF). Each model was developed on one of the five data sets and then applied to each of the four remaining data sets. We assessed the performance of the models with calibration characteristics, the correlation coefficient, and the root of the mean squared error. Results: The models GLM, SVM, RP, and RF showed satisfactory performance characteristics when validated on the validation data sets. All models showed poor performance characteristics for the deviating data set both for development and validation due to the deviating baseline characteristics compared to those of the other data sets. Conclusion: The performance of four models (GLM, SVM, RP, RF) on the development data sets was satisfactory. This was also the case for the validation data sets, except when these models were developed on the deviating data set. The NN models showed a much worse performance on the validation data sets than on the development data sets.
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Particulate matter (PM) exposure, amongst others caused by emissions and industrial processes, is an important source of respiratory and cardiovascular diseases. There are situations in which blue-collar workers in roadwork companies are at risk. This study investigated perceptions of risk and mitigation of employees in roadwork (construction and maintenance) companies concerning PM, as well as their views on methods to empower safety behavior, by means of a mental models approach. We held semi-structured interviews with twenty-two employees (three safety specialists, seven site managers and twelve blue-collar workers) in three different roadwork companies. We found that most workers are aware of the existence of PM and reduction methods, but that their knowledge about PM itself appears to be fragmented and incomplete. Moreover, road workers do not protect themselves consistently against PM. To improve safety instructions, we recommend focusing on health effects, reduction methods and the rationale behind them, and keeping workers’ mental models into account. We also recommend a healthy dialogue about work-related risk within the company hierarchy, to alleviate both information-related and motivation-related safety issues. https://doi.org/10.1016/j.ssci.2019.06.043 LinkedIn: https://www.linkedin.com/in/john-bolte-0856134/
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Organizing entrepreneurial collaboration in small, self-directed teams is gaining popularity. The underlying co-creation processes of developing a shared team vision were analyzed with a core focus on three underlying processes that originate from the shared mental models framework. These processes are: 1) the emergence of individual visions and vision integration, 2) conflict solving, and 3) redesigning the emerging knowledge structure. Key in the analysis is the impact of these three processes on two outcome variables: 1)the perceived strength of the co-creation process, 2) the final team vision. The influence of business expertise and the relationship between personality traits and intellectual synergy was also studied. The impact of the three quality shared mental model (SMM) variables proves to be significant and strong, but indirect. To be effective, individual visions need to be debated during a second conflict phase. Subsequently, redesigning the shared knowledge structure resulting from the conflict solving phase is a key process in a third elaboration phase. This sequence positively influences the experienced strength of the co-creation process, the latter directly enhancing the quality of the final team vision. The indirect effect reveals that in order to be effective, the three SMM processes need to be combined, and that the influence follows a specific path. Furthermore, higher averages as well as a diversity of business expertise enhance the quality of the final team vision. Significant relationships between personality and an intellectual synergy were found. The results offer applicable insights for team learning and group dynamics in developing an entrepreneurial team vision. LinkedIn: https://www.linkedin.com/in/rainer-hensel-phd-8ba44a43/ https://www.linkedin.com/in/ronald-visser-4591034/
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Business rule models are widely applied, standalone and embedded in smart objects. They have become segregated from information technology and they are now a valuable asset in their own right. As more business rule models are becoming assets, business models to monetize these assets are designed. The goal of this work is to present a step towards business model classification for organizations for which its value position is characterized by business rule models. Based on a survey we propose a business model categorization that is aligned to different types of assets and business model archetypes. The results show five main categories of business models: The value adding business rule model, the ‘create me a business rule model’ business model, the KAAS business model, the bait and hook business model and the market place business model.
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New Dutch agrifood business models are emerging in response to economic, social and ecological pressures: new players arrive, new logistical pathways come to the fore and innovative consumer and farmer relationships – food coöperatives – are forged. How do new business models relate to reconfiguring the Dutch agrifood system? Our research combines future exploration (backcasting) and analysis of new business models. We developed three agrifood transition scenarios with various groups of stakeholders. For each scenario, we then analysed a specific, representative business model to explore the different roles of business models in agrifood transition. Business models in the “Added value in and with the countryside” already exist and occupy a niche in the market. However, a breakthrough of these business models require large-scale institutional and behavioural change. Business models in the “New products, specific markets” exist but are rare. They usually concern high-value specialist products that could result in widespread market change, but might require little institutional change. The “Sustainable production methods” most resembles the current system. Some associated business models become successful, but they have difficulty distinguishing themselves from conventional produce, which raises questions about whether business models are able to drive a transition in this direction. Thus, our results lend credence to the hypothesis that different transition pathways offer specific potential for and requirements of new business models.
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Paper presented at the International Sustainability Transitions conference 2018 (12-14 june) Manchester, UK. The Dutch agrifood regime is grinding to a halt. International economic pressures force Dutch farmers to further scale up and intensify their businesses, while food scandals and calamities as well as many and varied negative environmental impacts have led to an all-time low societal acceptance of the agrifood regime as well as a host of legislative measures to stifle further growth. Such a situation, in which regime pressures increasingly undermine the regime, represents a strong call for transition of the Dutch agrifood system.At the same time, new business models emerge: new players arrive, new logistical pathways come to the fore and innovative consumer and farmer relationships – food co-operatives – are forged. In a sense, the transition is already under way (cf. Hermans et al., 2010), with new business models forming an important backbone. However, the way forward is still a matter of great uncertainty and controversy: How do new business models relate to reconfiguring the Dutch agrifood system? We explore the hypothesis that different transition pathways put specific demands on the role of new business models. We studied various new business models in the Dutch agrifood system and their relations to three different transition pathways. Our research combines future exploration (backcasting) and analysis of new business models. In this research, we approach this question from two angles. First, we introduce a transition-oriented business model concept, in order to effectively link new business models to transition. Then we shortly touch upon the transition pathway typology introduced by Geels et al. (2016) and describe three different transition pathways for the Dutch agrifood system. We report on XX business models in each of these transition pathways. The paper ends with a discussion of the role of business models for different types of transition pathways.
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This paper investigates the prospective application of arbitration by Transnational Private Regulation (TPR). It builds on the study of TPR developed by Fabrizio Cafaggi et al. TPR addresses the ever-increasing transfer of regulatory power from national to global levels, and from public to private regulators. TPR entails private regulatory co-operation be-yond the jurisdictional boundaries of States through voluntary standards. The regimes of TPR are built by a variety of actors, such as companies, NGOs, independent experts, and epistemic communities. Examples of TPR can be found in food safety, forestry management, trade, and derivatives, among other fields. More specifically, they concern private actors engaging in transnational coordination of standard setting such as the Forest Stewardship Council (FSC) that was developed to foster responsible management of the world’s forests. There are four main characteristics of TPR: legitimacy, quality, effectiveness, and enforcement. I will describe those four characteristics in brief here. First, the legitimacy of TPR is built around consent through voluntary entry, participation, and exit of regulated entities. Important to this contribution is that the legitimacy of TPR goes beyond its legal dimension, measured by purely legal standards. Hence, the legitimacy of TPR is largely determined by standards developed by social and economic institutions relevant to specific TPR regimes. The role of those institutions in standard settings is higher in private TPR regimes than private-public TPR regimes, where some forms of compliance are mandatory. Second, the quality of TPR corresponds to the ex ante and ex post evaluation cycle of regulatory processes. It is also linked with the transparency of TPR. Third, the effectiveness of TPR is measured according to the extent to which the objectives of TPR (or selected TPR regimes) are met. And finally, enforcement of TPRis understood as ‘ensuring compliance with commitments’. Enforcement of TPR can take place through courts, administrative agencies, and private dispute resolution—including the arbitration at the core of this contribution. Cafaggi’s study identified rather selective use of arbitration in TPR, but also recommended changes to make arbitration law more adaptable to TPR. Furthermore, the study recommended that more specialized dispute resolution institutions are created to exclusively serve TPR. Against this background, I shift the main focus of analysis from TPR to arbitration. Whereas Cafaggi argued that arbitration may be suitable for TPR as a means of private enforcement, in this paper I go even further, arguing that arbitration as a means of informal, out-of-court dispute resolution is well suited to strengthen the normativity of TPR. This is so because private arbitration actors (including, inter alia, arbitrators and arbitral institutions) are already equipped with the tools necessary to facilitate cross-border TPR, which is done through informal standards and procedures with origins in the communitarian values and reputational mechanisms used by different communities before the development of modern States. The roots of most private justice regimes—including arbitration—are informed by communitarian values such as collaboration, participation, and personal trust. Those values, together with other core characteristics of arbitration correspond to all core characteristics of TPR, making both systems comparable and complementary. The analytical framework incorporated in this paper follows the four core characteristics of TPR. Hence, the paper is organized into five sections. The first section contains the introduction. In the second section, I analyze the legitimacy of arbitration vis-à-vis the legitimacy of TPR. In the third section, I investigate the accountability of arbitration as a means of quality signaling vis-à-vis TPR. In the fourth section, I focus on the remedies available to arbitrators in a view of TPR’s effectiveness. Finally, in the fifth section, I analyze enforcement through arbitration and its impact on the exclusiveness versus complementarity of TPR regimes. Conclusions follow, including recommendations for future research. Part of topic "The blurring distinction between public and private in international dispute resolution"
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Mycotoxins are small (MW approximately 700), toxic chemical products formed as secondary metabolites by a few fungal species that readily colonise crops and contaminate them with toxins in the field or after harvest. Ochratoxins and Aflatoxins are mycotoxins of major significance and hence there has been significant research on broad range of analytical and detection techniques that could be useful and practical. Due to the variety of structures of these toxins, it is impossible to use one standard technique for analysis and/or detection. Practical requirements for high-sensitivity analysis and the need for a specialist laboratory setting create challenges for routine analysis. Several existing analytical techniques, which offer flexible and broad-based methods of analysis and in some cases detection, have been discussed in this manuscript. There are a number of methods used, of which many are lab-based, but to our knowledge there seems to be no single technique that stands out above the rest, although analytical liquid chromatography, commonly linked with mass spectroscopy is likely to be popular. This review manuscript discusses (a) sample pre-treatment methods such as liquid-liquid extraction (LLE), supercritical fluid extraction (SFE), solid phase extraction (SPE), (b) separation methods such as (TLC), high performance liquid chromatography (HPLC), gas chromatography (GC), and capillary electrophoresis (CE) and (c) others such as ELISA. Further currents trends, advantages and disadvantages and future prospects of these methods have been discussed.
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