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Entrepreneurs and small and medium enterprises usually have issues on developing new prototypes, new ideas or testing new techniques. In order to help them, in the last years, academic Software Factories, a new concept of collaboration between universities and companies have been developed. Software Factories provide a unique environment for students and companies. Students benefit from the possibility of working in a real work environment learning how to apply the state of the art of the existing techniques and showing their skills to entrepreneurs. Companies benefit from the risk-free environment where they can develop new ideas, in a protected environment. Universities finally benefit from this setup as a perfect environment for empirical studies in industrial-like environment. In this paper, we present the network of academic Software Factories in Europe, showing how companies had already benefit from existing Software Factories and reporting success stories. The results of this paper can increase the network of the factories and help other universities and companies to setup similar environment to boost the local economy.
Viele Unternehmen befassen sich in jüngster Zeit mit der Nutzung von Social Media für die interne Kommunikation und Zusammenarbeit. So genannte Enterprise Social Networks bieten integrierte Plattformen mit Profilen, Blogs, Gruppen- und Kommentarfunktionen für die unternehmensinterne Anwendung. Sehr häufig sind damit umfangreiche Investitionen verbunden. Die Budgets werden im Kern für die IT verwendet, "weiche Faktoren" bleiben häufig außen vor. Ein schwerer Fehler, wie aktuelle Marktstudien zeigen. Etliche der ambitionierten Projekte drohen daher zu scheitern.
A behavior marker for measuring non-technical skills of software professionals : an empirical study
(2015)
Managers recognize that software development teams need to be developed. Although technical skills are necessary, non-technical (NT) skills are equally, if not more, necessary for project success. Currently, there are no proven tools to measure the NT skills of software developers or software development teams. Behavioral markers (observable behaviors that have positive or negative impacts on individual or team performance) are successfully used by airline and medical industries to measure NT skill performance. This research developed and validated a behavior marker tool rated video clips of software development teams. The initial results show that the behavior marker tool can be reliably used with minimal training.
Managers recognize that software development project teams need to be developed and guided. Although technical skills are necessary, non-technical (NT) skills are equally, if not more, necessary for project success. Currently, there are no proven tools to measure the NT skills of software developers or software development teams. Behavioral markers (observable behaviors that have positive or negative impacts on individual or team performance) are beginning to be successfully used by airline and medical industries to measure NT skill performance. The purpose of this research is to develop and validate the behavior marker system tool that can be used by different managers or coaches to measure the NT skills of software development individuals and teams. This paper presents an empirical study conducted at the Software Factory where users of the behavior marker tool rated video clips of software development teams. The initial results show that the behavior marker tool can be reliably used with minimal training.
In modern times markets are very dynamic. This situation requires agile enterprises to have the ability to react fast on market influences. Thereby an enterprise’ IT is especially affected, because new or changed business models have to be realized. However, enterprise architectures (EA) are complex structures consisting of many artifacts and relationships between them. Thus analyzing an EA becomes to a complex task for stakeholders. In addition, many stakeholders are involved in decision-making processes, because Enterprise Architecture Management (EAM) targets providing a holistic view of the enterprise. In this article we use concepts of Adaptive Case Management (ACM) to design a decision-making case consisting of a combination of different analysis techniques to support stakeholders in decision-making. We exemplify the case with a scenario of a fictive enterprise.
Purpose: This paper aims to conceptualize and empirically test the determinants of service interaction quality (SIQ) as attitude, behavior and expertise of a service provider (SP). Further, the individual and simultaneous effects of SIQ and its dimensions on important marketing outcomes are tested. Design/methodology/approach – The narrative review of extant research helps formulate a conceptual model of SIQ, which is investigated using the univariate and multivariate meta-analysis.
Findings: There are interdependencies between drivers of SIQ that underlines the need to conceptualize service interaction as a dyadic phenomenon; use contemporary multilevel models, dyadic models, non-linear structural equation modeling and process studies; and study new and diverse services contexts. Meta-analysis illustrates the relative importance of the three drivers of SIQ and, in turn, their impact on consumer satisfaction and loyalty.
Research limitations/implications – The meta-analysis is based on existing research, which, unfortunately, has not examined critical services or exigency situations where SIQ is of paramount importance. Future research will be tasked with diversifying to several important domains where SIQ is a critical aspect of perceived service quality.
Practical implications: This study emphasizes that, although the expertise of an SP is important, firms would be surprised to learn that the attitude and behavior of their employees are equally important antecedents. In fact, there is a delicate balance that needs to be found; otherwise, attitudinal factors can have an overall counterproductive effect on consumer satisfaction.
Originality/value: This paper provides an empirical synthesis of SIQ and opens up interesting areas for further research.
Information systems, which support the workflow in the clinical area, are currently limited to organizational processes. This work shows a first approach of an information system supporting all actors in the perioperative area. The first prototype and proof of concept was a task manager, giving all actors information about their task and the task of all other actors during an intervention. Based on this initial task manager, we implemented an information system based on a workflow engine controlling all processes and all information necessary for the intervention. A second part was the development of a perioperative process visualization which was developed based on a user centered approach jointly with clinicians and OR members.
Saving energy and protecting the environment became fundamental for society and politics, why several laws were enacted to increase the energy-efficiency. Furthermore, the growing number of vehicles and drivers leaded to more accidents and fatalities on the roads, why road safety became an important factor as well. Due to the increasing importance of energy-efficiency and safety, car manufacturers started to optimise the vehicle in terms of energy-effciency and safety. However, energy-efficiency and road safety can be also increased by adapting the driving behaviour to the given driving situation. This thesis presents a concept of an adaptive and rule based driving system that tries to educate the driver in energy-efficient and safe driving by showing recommendations on time. Unlike existing driving-systems, the presented driving system considers energy-efficiency and safety relevant driving rules, the individual driving behaviour and the driver condition. This allows to avoid the distraction of the driver and to increase the acceptance of the driving system, while improving the driving behaviour in terms of energy-efficiency and safety. A prototype of the driving system was developed and evaluated. The evaluation was done on a driving simulator using 42 test drivers, who tested the effect of the driving system on the driving behaviour and the effect of the adaptiveness of the driving system on the user acceptance. It has been proven during the evaluation that the energy-efficiency and safety can be increased, when the driving system was used. Furthermore, it has been proven that the user acceptance of the driving system increases when the adaptive feature was turned on. A high user acceptance of the driving system allows a steady usage of the driving system and, thus, a steady improvement of the driving behaviour in terms of energy-efficiency and safety.
Informationstechnische Systeme, die den Arbeitsablauf im klinischen Bereich unterstützen, sind aktuell auf organisatorische Abläufe beschränkt. Diese Arbeit stellt einen ersten Ansatz vor, wie solch ein System in den perioperativen Bereich eingebracht werden kann. Hierzu wurde eine Workflow Engine mit einer perioperativen Prozess-Visualisierung verknüpft. Das System wurde nach Modell-View-Controller-Prinzip implementiert. Als "Controller" kommt die Workflow Engine zum Einsatz; also "Modell" ein Prozessmodell, mit den erforderlichen klinischen Daten. Der "View" wurde durch eine abgekoppelte Anwendung realisiert, welche auf Web-Technologien basiert. Drei Visualisierungen, die Workflow Engine sowie die Anbindung beider über eine Datenbankschnittstelle, wurden erfolgreich umgesetzt. Bei den drei Visualisierungen wurden jeweils eine Ansicht für den OP-Koordinator, den Springer und eine Ansicht für die Übersicht einer OP erstellt.
The character of knowledge-intense processes is that participants decide the next process activities on base of the present information and their expert knowledge. The decisions of these knowledge workers are in general non-deterministic. It is not possible to model these processes in advance and to automate them using a process engine of a BPM system. Hence, in this context a process instance is called a case, because there is no predefined model that could be instantiated. Domain-specific or general case management systems are used to support the knowledge workers. These systems provide all case information and enable users to define the next activities, but they have no or only limited activity recommendation capabilities. In the following paper, we present a general concept for a self-learning system based on process mining that suggests the next best activity on quantitative and qualitative data for a given case. As a proof of concept, it was applied to the area of insurance claims settlement.
Das Provisioning Tool automaIT wurde prototypisch um die Möglichkeit eines Data Discovery erweitert, mit dem Ziel, nicht durch automaIT verwaltete Systeme anbinden und steuern zu können. Daten aus dem Data Discovery werden mittels dem Tool Facter gesammelt und können dynamisch in ausführbare Modelle von automaIT integriert und ausgewertet werden. Dadurch kann der Verlauf weiterer Provisionierungsschritte gesteuert werden, ohne dass es eines manuellen Eingriffs bedarf.
Excellence in IT is a key enabler for the digital transformation of enterprises. To realize the vision of digital enterprises it is necessary to cope with changing business requirements and to align business and IT. In order to evaluate the contribution of enterprise architecture management to these goals, our paper explores the impact of various factors to the perceived benefit of EAM in enterprises. Based on literature, we build an empirical research model. It is tested with empirical data of European EAM experts using a structural equation modelling approach. It is shown that changing business requirements, IT business alignment, the complexity of information technology infrastructure as well as enterprise architecture knowledge of information technology employees are crucial impact factors to the perceived benefit of EAM in enterprises.
Enterprise Architecture (EA) management is an activity that seeks to foster the alignment of business and IT, and pursues various goals further operationalizing this alignment. Key to effective EA management is a framework that defines the roles, activities, and viewpoints used for EA management in accordance to the concerns that the stakeholders aim to address. Consensus holds that such frameworks are organization-specific and hence they are designed in governance activities for EA management. As of today, top-down approaches for governance are used to derive organization-specific frameworks. These usually lack systematic mechanisms for improving the framework based on the feedback of the responsible stakeholders. We outline a bottom-up approach for EA management governance that systematically observes the behavior of the actors to learn user concerns and recommend appropriate viewpoints. With this approach, we complement traditional top-down governance activities.
An ongoing challenge in our days is to lower the impact on the quality of life caused by dysfunctionality through individual support. With the background of an aging society and continuous increases in costs for care, a holistic solution is needed. This solution must integrate individual needs and preferences, locally available possibilities, regional conditions, professional and informal caregivers and provide the flexibility to implement future requirements. The proposed model is a result of a common initiative to overcome the major obstacles and to center a solution on individual needs caused by dysfunctionality.
New business concepts such as Enterprise 2.0 foster the use of social software in enterprises. Especially social production significantly increases the amount of data in the context of business processes. Unfortunately, these data are still an unearthed treasure in many enterprises. Due to advances in data processing such as Big Data, the exploitation of context data becomes feasible. To provide a foundation for the methodical exploitation of context data, this paper introduces a classification, based on two classes, intrinsic and extrinsic data.
The digitization of our society changes the way we live, work, learn, communicate, and collaborate. This disruptive change interacts with all information processes and systems that are important business enablers for the context of digitization since years. Our aim is to support flexibility and agile transformations for both business domains and related information technology and enterprise systems through adaptation and evolution of digital enterprise architectures. The present research paper investigates collaborative decision mechanisms for adaptive digital enterprise architectures by extending original architecture reference models with state of art elements for agile architectural engineering for the digitization and collaborative architectural decision support.
Rapid value delivery requires a company to utilize empirical evaluation of new features and products in order to avoid unnecessary product risks. This helps to make data-driven decisions and to ensure that the development is focused on features that provide real value for customers. Short feedback loops are a prerequisite as they allow for fast learning and reduced reaction times. Continuous experimentation is a development practice where the entire R&D process is guided by constantly conducting experiments and collecting feedback. Although principles of continuous experimentation have been successfully applied in domains such as game software or SAAS, it is not obvious how to transfer continuous experimentation to the business to-business domain. In this article, a case study from a medium-sized software company in the B2B domain is presented. The study objective is to analyze the challenges, benefits and organizational aspects of continuous experimentation in the B2B domain. The results suggest that technical challenges are only one part of the challenges a company encounters in this transition. The company also has to address challenges related to the customer and organizational culture. Unique properties in each customers business play a major role and need to be considered when designing experiments. Additionally, the speed by which experiments can be conducted is relative to the speed by which production deployments can be made. Finally, the article shows how the study results can be used to modify the development in the case company in a way that more feedback and data is used instead of opinions.
Customer services in the digital transformation: social media versus hotline channel performance
(2015)
Due to the digital transformation online service strategies have gained prominence in practice as well as in the theory of service management. This study examines the efficacy of different types of service channels in customer complaint handling. The theoretical framework, developed using complaint handling and social media literature, is tested against data collected from two different channels (hotline and social media) of a German telecommunication service provider. We contribute to the understanding of firm’s multichannel distribution strategy in two ways: a) by conceptualizing and evaluating complaint handling quality across traditional and social media channels, and b) by testing the impact of complaint handling quality on key performance outcomes like customer loyalty, positive word-of-mouth, and cross purchase intentions.
Big Data wird aktuell als einer der Haupttrends der IT-Industrie diskutiert. Big Data d. h. auf Basis großer Mengen unterschiedlich strukturierter Daten die Entscheidungen in Echtzeit oder prognostisch zu treffen. Von hochleistungsfähigen, schnell verfügbaren Prognoseverfahren erhofft man sich eine Risikominimierung für unternehmerische Entscheidungen in hochvolatilen Märkten.
The Seventh International Conference on Advances in Databases, Knowledge, and Data Applications (DBKDA 2015), held between May 24-29, 2015 in Rome, Italy, continued a series of international events covering a large spectrum of topics related to advances in fundamentals on databases, evolution of relation between databases and other domains, data base Technologies and content processing, as well as specifics in applications domains databases. Advances in different technologies and domains related to databases triggered substantial improvements for content processing, information indexing, and data, process and knowledge mining. The push came from Web services, artificial intelligence, and Agent technologies, as well as from the generalization of the XML adoption. High-speed communications and computations, large storage capacities, and loadbalancing for distributed databases access allow new approaches for content processing with incomplete patterns, advanced ranking algorithms and advanced indexing methods. Evolution on e-business, e-health and telemedicine, bioinformatics, finance and marketing, geographical positioning systems put pressure on database communities to push the ‘de facto’ methods to support new requirements in terms of scalability, privacy, performance, indexing, and heterogeneity of both content and technology.