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This study addresses the common occurrence of cell-to-cell variations arising from manufacturing tolerances and their implications during battery production. The focus is on assessing the impact of these inherent differences in cells and exploring diverse cell and module connection methods on battery pack performance and their subsequent influence on the driving range of electric vehicles (EVs). The analysis spans three battery pack sizes, encompassing various constant discharge rates and nine distinct drive cycles representative of driving behaviours across different regions of India. Two interconnection topologies, categorised as “string” and “cross”, are examined. The findings reveal that cross-connected packs exhibit reduced energy output compared to string-connected configurations, which is reflected in the driving range outcomes observed during drive cycle simulations. Additionally, the study investigates the effects of standard deviation in cell parameters, concluding that an increased standard deviation (SD) leads to decreased energy output from the packs. Notably, string-connected packs demonstrate superior performance in terms of extractable energy under such conditions.
The transport sector is a major source of air pollution and thus a major contributor to the changing climate. As a result, in the recent past, driving bans have been imposed on cars with critical pollutant groups. As an international UN campus and self-proclaimed climate capital, the Federal City of Bonn declared a climate emergency in 2019 and participated in a federally funded “Lead City” project to optimise air quality. A key goal of the project is to reduce private motorised transport and strengthen public transport. Among the implemented measures, a “climate ticket” was introduced in 2019 whereby consumers could purchase an annual 365 € ticket for all local public transport. This paper reports on an analysis of that ticket’s changes in travel behavior.
A quantitative survey (n = 1,315) of the climate ticket users as well as the multiple regressions confirm that the climate ticket attracted more customers to the buses and trams and that a modal shift for the period of the measure was recognisable. The multiple regressions showed that the ticket was perceived significantly more positively by full-time employed users than by unemployed people. The results also show that, in addition to the price, it is essential that travel time and reliability are ensured. Furthermore, the eligible groups of people, the area of coverage, and good connecting services should be extended. To sustainably improve air quality, this type of mobility service must be optimised and introduced on a permanent basis.
Improved Thermal Comfort Model Leveraging Conditional Tabular GAN Focusing on Feature Selection
(2024)
The indoor thermal comfort in both homes and workplaces significantly influences the health and productivity of inhabitants. The heating system, controlled by Artificial Intelligence (AI), can automatically calibrate the indoor thermal condition by analyzing various physiological and environmental variables. To ensure a comfortable indoor environment, smart home systems can adjust parameters related to thermal comfort based on accurate predictions of inhabitants’ preferences. Modeling personal thermal comfort preferences poses two significant challenges: the inadequacy of data and its high dimensionality. An adequate amount of data is a prerequisite for training efficient machine learning (ML) models. Additionally, high-dimensional data tends to contain multiple irrelevant and noisy features, which might hinder ML models’ performance. To address these challenges, we propose a framework for predicting personal thermal comfort preferences, combining the conditional tabular generative adversarial network (CTGAN) with multiple feature selection techniques. We first address the data inadequacy challenge by applying CTGAN to generate synthetic data samples, incorporating challenges associated with multimodal distributions and categorical features. Then, multiple feature selection techniques are employed to identify the best possible sets of features. Experimental results based on a wide range of settings on a standard dataset demonstrated state-of-the-art performance in predicting personal thermal comfort preferences. The results also indicated that ML models trained on synthetic data achieved significantly better performance than models trained on real data. Overall, our method, combining CTGAN and feature selection techniques, outperformed existing known related work in thermal comfort prediction in terms of multiple evaluation metrics, including area under the curve (AUC), Cohen’s Kappa, and accuracy. Additionally, we presented a global, model-agnostic explanation of the thermal preference prediction system, providing an avenue for thermal comfort experiment designers to consciously select the data to be collected.
Vehicle emissions have been identified as a cause of air pollution and one of the major reasons why air quality in many large German cities such as Berlin, Bonn, Hamburg, Cologne or Munich does not meet EU-wide limits. As a result, in the recent past, judicial driving bans on diesel vehicles have been imposed in many places since those vehicles emit critical pollutant groups. For the increasing urban population, the challenge is whether and how a change of the modal split in favor of the more environmentally and climate-friendly public transport can be achieved.
This paper presents the case of the Federal City of Bonn, one of five model cities sponsored by the German federal government that are testing measures to reduce traffic-related pollutant emissions by expanding the range of public transport services on offer. We present the results of a quantitative survey (N = 14,296) performed in the Bonn/Rhein-Sieg area and the neighboring municipalities as well as the ensuing logistic regressions confirming that a change in individual mobility behavior in favor of public transport is possible through expanding services. Our results show that individual traffic could be reduced, especially on the city's main traffic axes. To sustainably improve air quality, such services must be made permanently available.
Konsument:innen scheint die Lust vergangen zu sein, individuellen Kleidungsstil auszudrücken, da der Onlinehandel zur Steigerung von Auswahlmöglichkeiten geführt hat. Dies mündet unter anderem in der Nutzung virtueller Stilberatungen. Diese Dienste dienen dazu, Kund:innen möglichst effizient, individuell und authentisch „zu machen“, und sind somit als paradoxaler Demokratisierungsprozess zu verstehen. Eine Erklärung für den Erfolg dieser Dienstleistungen soll mit Reckwitz’ Singularisierungsthese gestützt werden.
Trust-Building in Peer-to-Peer Carsharing: Design Case Study for Algorithm-Based Reputation Systems
(2023)
Peer-to-peer sharing platforms become increasingly important in the platform economy. From an HCI-perspective, this development is of high interest, as those platforms mediate between different users. Such mediation entails dealing with various social issues, e.g., building trust between peers online without any physical presence. Peer ratings have proven to be an important mechanism in this regard. At the same time, scoring via car telematics become more common for risk assessment by car insurances. Since user ratings face crucial problems such as fake or biased ratings, we conducted a design case study to determine whether algorithm-based scoring has the potential to improve trust-building in P2P-carsharing. We started with 16 problem-centered interviews to examine how people understand algorithm-based scoring, we co-designed an app with scored profiles, and finally evaluated it with 12 participants. Our findings show that scoring systems can support trust-building in P2P-carsharing and give insights how they should be designed.
Background
Consumers rely heavily on online user reviews when shopping online and cybercriminals produce fake reviews to manipulate consumer opinion. Much prior research focuses on the automated detection of these fake reviews, which are far from perfect. Therefore, consumers must be able to detect fake reviews on their own. In this study we survey the research examining how consumers detect fake reviews online.
Methods
We conducted a systematic literature review over the research on fake review detection from the consumer-perspective. We included academic literature giving new empirical data. We provide a narrative synthesis comparing the theories, methods and outcomes used across studies to identify how consumers detect fake reviews online.
Results
We found only 15 articles that met our inclusion criteria. We classify the most often used cues identified into five categories which were (1) review characteristics (2) textual characteristics (3) reviewer characteristics (4) seller characteristics and (5) characteristics of the platform where the review is displayed.
Discussion
We find that theory is applied inconsistently across studies and that cues to deception are often identified in isolation without any unifying theoretical framework. Consequently, we discuss how such a theoretical framework could be developed.
Due to expected positive impacts on business, the application of artificial intelligence has been widely increased. The decision-making procedures of those models are often complex and not easily understandable to the company’s stakeholders, i.e. the people having to follow up on recommendations or try to understand automated decisions of a system. This opaqueness and black-box nature might hinder adoption, as users struggle to make sense and trust the predictions of AI models. Recent research on eXplainable Artificial Intelligence (XAI) focused mainly on explaining the models to AI experts with the purpose of debugging and improving the performance of the models. In this article, we explore how such systems could be made explainable to the stakeholders. For doing so, we propose a new convolutional neural network (CNN)-based explainable predictive model for product backorder prediction in inventory management. Backorders are orders that customers place for products that are currently not in stock. The company now takes the risk to produce or acquire the backordered products while in the meantime, customers can cancel their orders if that takes too long, leaving the company with unsold items in their inventory. Hence, for their strategic inventory management, companies need to make decisions based on assumptions. Our argument is that these tasks can be improved by offering explanations for AI recommendations. Hence, our research investigates how such explanations could be provided, employing Shapley additive explanations to explain the overall models’ priority in decision-making. Besides that, we introduce locally interpretable surrogate models that can explain any individual prediction of a model. The experimental results demonstrate effectiveness in predicting backorders in terms of standard evaluation metrics and outperform known related works with AUC 0.9489. Our approach demonstrates how current limitations of predictive technologies can be addressed in the business domain.
Personal-Information-Management-Systeme (PIMS) gelten als Chance, um die Datensouveränität der Verbraucher zu stärken. Datenschutzbezogene Fragen sind für Verbraucher immer dort relevant, wo sie Verträge und Nutzungsbedingungen mit Diensteanbietern eingehen. Vor diesem Hintergrund diskutiert dieser Beitrag die Potenziale von VRM-Systemen, die nicht nur das Datenmanagement, sondern das gesamte Vertragsmanagement von Verbrauchern unterstützen. Dabei gehen wir der Frage nach, ob diese besser geeignet sind, um Verbraucher zu souveränem Handeln zu befähigen.
Damit nachhaltiger Konsum möglich ist, müssen Verbraucherinnen und Verbraucher die Nachhaltigkeit von Produkten angemessen einschätzen können. Ausgehend von der Annahme, dass Greenwashing-Slogans solche Einschätzungen möglicherweise behindern, untersucht dieses zweiteilige quantitative Online-Experiment Schlussfolgerungen von Verbraucherinnen und Verbrauchern, die statische Werbeanzeigen betrachteten. Dabei wurden konkrete, d.h. quantifizierte Umweltaussagen mit vagen Botschaften (Greenwashing-Kondition) bezüglich eines fiktiven TV-Produktes bzw. TV-Herstellers verglichen. Ein Drittel der jungen und gebildeten Stichprobe (N = 163) zog nach Ansicht einer Produktanzeige, die den geringen Stromverbrauch des „Omro UHD-Fernsehers“ bewarb, den Schluss, dass weitere, in der Werbung nicht beobachtbare Umweltmerkmale eher wahrscheinlich als unwahrscheinlich sind. Unternehmensanzeigen zur Energieeffizienz der Produktion von „Nextvision“ entlockten diese Schlussfolgerung sogar 73 Prozent der Probanden. Vage und konkrete Behauptungen unterschieden sich hinsichtlich dieser sog. Halo-Effekte kaum. Dazu berechnete Indizes korrelierten signifikant positiv mit der eingeschätzten Produktqualität, was für die Wirksamkeit eines Gesamteindruckes (General Impression Halos) spricht. Dies galt insbesondere für vage Botschaften. Sie eignen sich daher besonders für Werbetreibende, weil Anzeigen in der Regel nur für kurze Zeit Aufmerksamkeit erhalten. Verbraucherinnen und Verbrauchern kann auf Basis der Ergebnisse geraten werden, stärker auf die theoretische Überprüfbarkeit von Werbeslogans zu achten.
Advocates of autonomous driving predict that the occupation of taxi driver could be made obsolete by shared autonomous vehicles (SAV) in the long term. Conducting interviews with German taxi drivers, we investigate how they perceive the changes caused by advancing automation for the future of their business. Our study contributes insights into how the work of taxi drivers could change given the advent of autonomous driving: While the task of driving could be taken over by SAVs for standard trips, taxi drivers are certain that other areas of their work such as providing supplementary services and assistance to passengers would constitute a limit to such forms of automation, but probably involving a shifting role for the taxi drivers, one which focuses on the sociality of the work. Our findings illustrate how taxi drivers see the future of their work, suggesting design implications for tools that take various forms of assistance into account, and demonstrating how important it is to consider taxi drivers in the co-design of future taxis and SAV services.
Since stationary self-checkout is widely introduced and well understood, previous research barely examined newer generations of smartphone-based Scan&Go. Especially from a design perspective, we know little about the factors contributing to the adoption of Scan&Go solutions and how design enables consumers to take full advantage of this development rather than being burdened with using complex and unenjoyable systems. To understand the influencing factors and the design from a consumer perspective, we conducted a mixed-methods study where we triangulated data of an online survey with 103 participants and a qualitative study with 20 participants. Based on the results, our study presents a refined and nuanced understanding of technology as well as infrastructure-related factors that influence adoption. Moreover, we present several implications for designing and implementing of Scan&Go in retail environments.
Die Bundesrepublik Deutschland erlebt in jüngster Vergangenheit verstärkt Dieselfahrverbote in Großstädten. Gleichzeitig erfahren Großstädte als Lebensmittelpunkt eine steigende Beliebtheit. Für Verkehrsunternehmen gilt es, der Bevölkerung nachhaltige Mobilitätslösungen zu bieten, die ein Höchstmaß an Flexibilität ermöglichen. Moderne Mobility-as-a-Service-Konzepte und Innovationen in der Mobilität stellen den klassischen, planorientierten, öffentlichen Personennahverkehr und damit auch die Existenz von Bushaltestellen infrage. Mittels qualitativer Experten-Interviews lässt sich feststellen, dass sich die Bushaltestelle in den Innenstädten vor dem Hintergrund zunehmender digitaler Vernetzung von Mobilitätsanbietern und daraus resultierender modernen Mobility-as-a-service-Konzepte verändern wird. Die Ergebnisse deuten darauf hin, dass die Bushaltestelle in den Innenstädten auch in Zukunft bestehen bleibt und um „on demand“-Verkehre ergänzt wird. Ein radikaler Wandel, wie eine flächendeckende Einführung von autonom fahrenden Bussen, könnte langfristig eine Runderneuerung der Haltestelle zur Folge haben.
In the context of the Franco-German research project Re(h)strain, this work focuses on a global system analysis integrating both safety and security analysis of international and/or urban railway stations. The Re(h)strain project focuses on terrorist attacks on high speed train systems and investigates prevention and mitigation measures to reduce the overall vulnerability and strengthen the system resilience. One main criterion regarding public transport issues is the number of passengers. For example, the railway station of Paris “Gare du Nord” deals with a bigger number of passengers than the biggest airport in the world (SNCF open Data 2014), the Atlanta airport, but in terms of passengers, it is only around the 23rd rank railway station in the world. Due to the enormous mass of people, this leads to the system approach of breaking out the station into several classes of zones, e.g. entrance, main hall, quays, trains, etc. All classes are analysed considering state-of-the-art parameters, like targets attractiveness, feasibility of attack, possible damage, possible mitigation and defences. Then, safety incidence of security defence is discussed in order to refine security requirement with regard to the considered zone. Finally, global requirements of security defence correlated to the corresponding class of zones are proposed.
Innovations in the mobility industry such as automated and connected cars could significantly reduce congestion and emissions by allowing the traffic to flow more freely and reducing the number of vehicles according to some researchers. However, the effectiveness of these sustainable product and service innovations is often limited by unexpected changes in consumption: some researchers thus hypothesize that the higher comfort and improved quality of time in driverless cars could lead to an increase in demand for driving with autonomous vehicles. So far, there is a lack of empirical evidence supporting either one or other of these hypotheses. To analyze the influence of autonomous driving on mobility behavior and to uncover user preferences, which serve as indicators for future travel mode choices, we conducted an online survey with a paired comparison of current and future travel modes with 302 participants in Germany. The results do not confirm the hypothesis that ownership will become an outdated model in the future. Instead they suggest that private cars, whether conventional or fully automated, will remain the preferred travel mode. At the same time, carsharing will benefit from full automation more than private cars. However, the findings indicate that the growth of carsharing will mainly be at the expense of public transport, showing that more emphasis should be placed in making public transport more attractive if sustainable mobility is to be developed.
A Method for the Sustainable Documentation of Operations Processes in Parcel Distribution Centers
(2018)
There is often no common understanding on operational processes in logistics companies as they are not properly documented. Hence, people execute the same process differently and training is conducted by experienced operators on an ad-hoc basis. Furthermore, continuous process improvement is hampered as neither the ideal process nor current issues in as-is processes are visible. A major reason for the missing documentation is the complexity of existing business process modelling languages. Modelling experts are required for initially describing the processes and also for updating the models after process changes. Furthermore, operations people are usually not used to read complex process models in EPCs or BPMN diagrams. In order to overcome these limitations, a domain-specific modelling language which facilitates maintaining up-to-date process models has been designed with a large logistics company in Germany. The paper at hand briefly describes this language and illustrates the method on how to apply it in operations environments.
The technological development of the digital computer and new options to collect, store and transfer mass data have changed the world in the last 40 years. Moreover, due to the ongoing progress of computer power, the establishment of the Internet as critical infrastructure and the options of ubiquitous sensor systems will have a dramatic impact on economies and societies in the future. We give a brief overview about the technological basics especially with regard to the exponential growth of big data and current turn towards sensor-based data collection. From this stance, we reconsider the various dimensions of personal data and and market mechanisms that have an impact of data usage and protection.
In January 2015, German trade and industry announced to support the national animal welfare initiative "Initiative Tierwohl" (ITW) which stands for a more sustainable and animal-friendly meat production. A web content analysis shows that the ITW initiative has been widely picked up and discussed by online media and that user comments are quite heterogeneous. The current study identifies different types of consumers through factor and cluster analysis and is based on an online survey as well as face-to-face interviews. According to our results, the identified consumer groups demonstrate a rather passive comment behaviour on the internet. In fact, the internet was hardly mentioned as an information source for meat production; consumers more frequently referred to brochures, leaflets and personal contacts with sales personnel.
Das Thema Nachhaltigkeit hat sich in der heutigen Zeit in vielerlei Hinsicht weiterentwickelt. Auch bei der Entwicklung von Produkten ist der Aspekt der Nachhaltigkeit angekommen und wird vermehrt umgesetzt. Dies hat zur Folge, dass auch der Konsument sich mit der Nachhaltigkeit seines Produkts auseinandersetzt.
Die vorliegende Arbeit behandelt die Fragestellung, ob der Aspekt der Nachhaltigkeit auch bei der Kaufentscheidung eine Rolle spielt. Fokussiert wurden besonders die Aspekte: Nachhaltigkeit und Marketing, Wahrnehmung von nachhaltigen Aspekten der Unternehmen, sowie der Produkte, Vertrauen der Konsumenten in Siegel und die soziale Erwartungshaltung der Konsumenten.
Die Analyse resultiert auf der Basis eines durchgeführten Experiments sowie einer schriftlichen Befragung der 73 Probanden, bestehend aus Studenten der Hochschule Bonn-Rhein-Sieg.
Die Ergebnisse dieser Studie zeigen nicht nur den Handlungsbedarf der Unternehmen, sondern auch die Wahrnehmung der Konsumenten zu Produkten und Unternehmen und dass der Aspekt der Nachhaltigkeit auch bei täglichen Kaufentscheidungen eine Rolle spielen kann.
Viele Bereiche des Wirtschaftslebens werden heute durch die Digitalisierung beeinflusst. Sowohl auf Grundlage neuer technischer Möglichkeiten und der damit einhergehenden Vernetzung, als auch mit einem Wandel im Konsumverhalten hat sich die Sharing Economy entwickelt. Auf dem Gebiet der urbanen Mobilität ergibt sich für Anbieter und Nachfrager eine Vielzahl neuer Möglichkeiten im Rahmen der Sharing Economy. Die Arbeit setzt sich sowohl mit den aktuellen Mobilitätstrends, als auch mit dem Wandel im Konsumverhalten auseinander. Im Fokus steht hierbei das Ridesourcing, also die entgeltlichen Personenbeförderung von privaten Fahrern mit eigenem Fahrzeug, bei der der Fahrgast das Fahrziel bestimmt und die Vorteile die ein Markteintritt dieser Anbieter mit sich bringt.
Dieser Beitrag betrachtet den Stand der Entwicklung bei der Vernetzung von Fahrzeugen aus Sicht der IT-Sicherheit. Etablierte Kommunikationssysteme und Verkehrstelematikanwendungen im Automobil werden ebenso vorgestellt und diskutiert wie auch zukünftige Kommunikationstechnologien Car-2-Car und Car-2-X. IT-Sicherheit im Automobil ist ein schwieriges Feld, da es hier um eine Integration von neuen innovativen Anwendungen in eine hochkomplexe bestehende Fahrzeugarchitektur geht, die zu keinen neuen Gefährdungen für die Fahrzeuginsassen führen darf. Zudem bleibt die Funktionsweise dieser Anwendungen mit ihren Auswirkungen auf das informationelle Selbstbestimmungsrecht oft intransparent. Die abschließende Diskussion gibt Handlungsempfehlungen aus Sicht der Verbraucher.
Nachhaltige und zukunftsfähige Mobilität in Städten kann langfristig nur durch die aktive Partizipation ihrer Bürger und Institutionen erreicht werden. Betriebliches Mobilitätsmanagement (BMM) kann dabei einen positiven Beitrag im Hinblick auf Umwelt, Gesundheit und Kosten leisten. Die vorliegende Arbeit beschäftigt sich mit der Wahrnehmung gesundheitlicher und finanzieller Wertschöpfungsaspekte des BMM. Im Rahmen des Forschungsprojekts Betriebe lösen Verkehrsprobleme werden Mobilitätsverhalten und Maßnahmen der Betrieblichen Gesundheitsförderung (BFG) in Bonner Betrieben untersucht. Folgenden Aspekten wird besondere Beachtung geschenkt: Bedeutung Betrieblicher Gesundheitsförderung in Bonner Betrieben, Mobilitätsverhalten von Arbeitnehmern auf dem Weg zur Dienststelle, Wahrnehmung eines unmittelbaren Zusammenhangs zwischen körperlicher Aktivität und Gesundheit bzw. krankheitsbedingter Kosten und Umsatzeinbußen durch Bewegungsmangel. Die Analyse resultiert auf der Basis einer schriftlichen Befragung von 178 Unternehmen, einer Online-Umfrage von 1.341 Mitarbeitern aus 14 Unternehmen sowie auf persönlichen Interviews mit 22 Betriebsleitern bzw. Mobilitäts- und Gesundheitsbeauftragten. Die Ergebnisse der Studie machen sowohl Handlungsbedarf als auch Optimierungspotentiale im Bereich BMM auf Betriebsseite deutlich. Kostensimulationen zeigen darüber hinaus auf, dass durch die Implementierung von BGF-Maßnahmen, explizit der Förderung von Bewegung, auf betriebs- und volkswirtschaftlicher Seite beachtliche Kosten im Gesundheitsbereich eingespart sowie höhere Gewinne im Unternehmen erzielt werden können.
The phenomenon of the deviation between purchase attitudes and actual buying behaviour of responsible consumers is called the attitude-behaviour gap. It is influenced by individual, social and situational factors. The main purchasing barriers for sustainable (organic) food are price, lack of immediate availability, sensory criteria, lack or overload of information as well as the low-involvement feature of food products in conjunction with well-established consumption routines, lack of transparency and trust towards labels and certifications. The last three barriers are mainly of a psychological nature. Especially the low-involvement feature of food products due to daily purchase routines and relatively low prices tends to result in fast, automatic and subconscious decisions based on a so-called human mental system 1, derived from Daniel Kahneman’s (Nobel-Prize laureate in Behavioural Economics) model in behavioural psychology. In contrast, the human mental system 2 is especially important for the transformations of individual behaviour towards a more sustainable consumption. Decisions based on the human mental system 2 are slow, logical, rational, conscious and arduous. This so-called dual action model also influences the reliability of responses in consumer surveys. It seems that the consumer behaviour is the most unstable and unpredictable part of the entire supply chain and requires special attention. Concrete measures to influence consumer behaviour towards sustainable consumption are highly complex. Reviews of interdisciplinary research literature on behavioural psychology, behavioural economics and consumer behaviour and an empirical analysis of selected countries worldwide with a view to sustainable food are presented. The example of Denmark serves as a ‘best practice’ case study to illustrate how sustainable food consumption can be encouraged. It demonstrates that common efforts and a shared responsibility of consumers, business, interdisciplinary researchers, mass media and policy are needed. It takes pioneers of change who succeed in assembling a ‘critical mass’ willing to increase its ‘sustainable’ behaviour. Considering the strong psychological barriers of consumers and the continuing low market share of organic food, proactive policy measures would be conducive to foster the personal responsibility of the consumers and offer incentives towards a sustainable production. Also, further self-obligations of companies (Corporate Social Responsibility – CSR) as well as more transparency and simplification of reliable labels and certifications are needed to encourage the process towards a sustainable development.
Sustainable development needs sustainable production and sustainable consumption. During the last decades the encouragement of sustainable production has been the focus of research and policy makers under the implicit assumption that the observable increasing ‘green’ values of consumers would also entail a growing sustainable consumption. However, it has been found that the actual purchasing behaviour often deviates from ‘green’ attitudes. This phenomenon is called the attitude-behaviour gap. It is influenced by individual, social and situational factors. The main purchasing barriers for sustainable (organic) food are price, lack of immediate availability, sensory criteria, lack or overload of information as well as the low-involvement feature of food products in conjunction with well-established consumption routines, lack of transparency and trust towards labels and certifications.
Sustainability is a key issue in current research activities and programs. In this conjunction three major functions of research have been identified: Basic research, knowledge reservoirs, and knowledge transfer. With regard to a transmission to the private sector, knowledge transfer is the most important factor. In this process, universities of applied sciences can play an important part as they typically have a long-standing experience in linking science and business in their teaching and research. Another important agent in the process of knowledge transfer are networks and clusters. Their strength lies integrating the different competencies of its partners and using them to a mutual benefit.
The International Centre for Sustainable Development (IZNE) – with a major focus on responsible business and sustainable food – takes the advantage of being part of a University of Applied Sciences (Bonn-Rhein-Sieg, BRSU), and being a member of several regional and international clusters and networks. These co-operations aim to establish and strengthen linkages between science and business, in particular by investigating research needs for business and business relevant research activities. Moreover, IZNE established and expanded regional and international co-operations of its own to get more transparency about regional and international value-added chains in the food sector and the issue of responsible business.