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Context: Organizations are increasingly challenged by dynamic and technical market environments. Traditional product roadmapping practices such as detailed and fixed long-term planning typically fail in such environments. Therefore, companies are actively seeking ways to improve their product roadmapping approach.
Goal: This paper aims at identifying problems and challenges with respect to product roadmapping. In addition, it aims at understanding how companies succeed in improving their roadmapping practices in their respective company contexts.
Method: We conducted semi-structured expert interviews with 15 experts from 13 German companies and conducted athematic data analysis.
Results: The analysis showed that a significant number of companies is still struggling with traditional feature-based product-roadmapping and opinion-based prioritization of features. The most promising areas for improvement are stating the outcomes a company is trying to achieve and making them part of the roadmap, sharing or co-developing the roadmap with stakeholders, and establishing discovery activities.
The question of why individuals adopt information technology has been present in the information systems research since the past quarter century. One of the most used models for predicting the technology usage was introduced by Fred David: The Technology Acceptance Model (TAM). It describes the influence of perceived usefulness and perceived ease of use on attitude, behavioral intention and system usage. The first two mentioned factors in turn are influenced by external variables. Although a plethora of papers exists about the TAM , an extensive analysis of the role of the external variables in the model is still missing. This paper aims to give an overview ove the most important variables. In an extensive literature review, we identified 763 relevant papers, found 552 unique single extenal variables, characterized the most important of them, and described the frequency of their appearance. Additionally, we grouped these variables into four categories (organizational characteristis, system characteristics, user personal characteristics, and other variables). Afterwards we discuss the results and show implications for theory and practice.
Regardless of company size or industry sector, a majority of project teams and companies use customized processes that combine different development methods-so-called hybrid development methods. Even though such hybrid development methods are highly individualized, a common understanding of how to systematically construct synergetic practices is missing. Based on 1,467 data points from a large-scale online survey among practitioners, we study the current state of practice in process use to answer the question: What are hybrid development methods made of? Our findings reveal that only eight methods and few practices build the core of modern software development. This small set allows for statistically constructing hybrid development methods.
A sequence of transactions represents a complex and multi dimensional type of data. Feature construction can be used to reduce the data´s dimensionality to find behavioural patterns within such sequences. The patterns can be expressed using the blue prints of the constructed relevant features. These blue prints can then be used for real time classification on other sequences.
The stimulation of user engagement has received significant attention in extant research. However, the theory of antecedents for user engagement with an initial electronic word-of-mouth (eWoM) communication is relatively less developed. In an investigation of 576 unique user postings across independent Facebook (FB) communities for two German firms, we contribute to the extant knowledge on user engagement in two different ways. First, we explicate senders’ prior usage experience and the extent of their acquaintance with other community members as the two key drivers of user engagement across a product and a service community. Second, we reveal that these main effects differ according to the type of community. In service communities, experience has a stronger impact on user engagement; whereas, in product communities, acquaintance is more important.
Due to rapidly changing technologies and business contexts, many products and services are developed under high uncertainties. It is often impossible to predict customer behaviors and outcomes upfront. Therefore, product and service developers must continuously find out what customers want, requiring a more experimental mode of management and appropriate support for continuously conducting experiments. We have analytically derived an initial model for continuous experimentation from prior work and matched it against empirical case study findings from two startup companies. We examined the preconditions for setting up an experimentation system for continuous customer experiments. The resulting RIGHT model for Continuous Experimentation (Rapid Iterative value creation Gained through High-frequency Testing) illustrates the building blocks required for such a system and the necessary infrastructure. The major findings are that a suitable experimentation system requires the ability to design, manage, and conduct experiments, create so-called minimum viable products or features, link experiment results with a product roadmap, and manage a flexible business strategy. The main challenges are proper, rapid design of experiments, advanced instrumentation of software to collect, analyse, and store relevant data, and integration of experiment results in the product development cycle, software development process, and business strategy. This summary refers to the article The RIGHT Model for Continuous Experimentation, published in the Journal of Systems and Software [Fa17].
Steady growing research material in a variety of databases, repositories and clouds make academic content more than ever hard to discover. Finding adequate material for the own research however is essential for every researcher. Based on recent developments in the field of artificial intelligence and the identified digital capabilities of future universities a change in the basic work of academic research is predicted. This study defines the idea of how artificial intelligence could simplifiy academic research at a digital university. Today's studies in the field of AI spectacle the true potential and its commanding impact on academic research.
The Internet of Things (IoT) refers to the interconnectedness of physical objects, and works by equipping the latter with sensors and actuators as a means to connect to the internet. The number of connected things has increased threefold over the past five years. Consequently, firms expect the IoT to become a source of new business models driven by technology. However, only a few early adopters have started to install and use IoT appliances on a frequent basis. So it is still unclear which factors drive technological acceptance of IoT appliances. Confronting this gap in current research, the present paper explores how IoT appliances are conceptually defined, which factors drive technological acceptance of IoT appliances, and how firms can use results in order to improve value propositions in corresponding business models. lt is discovered that IoT appliance vendors need to support a broad focus as the potential buyers expose a large variety. As conclusions from this insight, the paper illustrates some flexible marketing strategies.
Systemische Betrachtung des therapeutischen Roboters Paro im Vergleich zu dem Haustierroboter AIBO
(2020)
Roboter sind in der heutigen Zeit nicht nur in der Industrie zu finden, sondern werden immer häufiger in privaten Lebensbereichen eingesetzt. Ein Beispiel hierfür ist der soziale Therapie-Roboter Paro. Dieser ist dem Verhalten und Aussehen einer jungen Robbe nachempfunden, drückt Gefühle aus und wird besonders in Pflegeheimen eingesetzt. Dabei zeigt er positive Auswirkungen auf das Wohlbefinden pflegebedürftiger Menschen. Diese Arbeit stellt den Roboter Paro in einer systemischen Analyse dar: hierbei werden Systemkontext, Anwendungsfälle, Anforderungen und Struktur betrachtet. Anschließend erfolgt eine Analyse des Haustierroboters AIBO, welcher einem Welpen ähnelt und verstärkt der Unterhaltung von Privatpersonen dient. Es werden Gemeinsamkeiten und Unterschiede zwischen den Systemen herausgearbeitet. Dabei wird ersichtlich, dass beide Systeme dem Nutzer vorrangig Gesellschaft leisten, jedoch verschiedene Anforderungen besitzen und in unterschiedlichen Anwendungsdomänen eingesetzt werden. Zudem besitzt AIBO vielfältigere Fähigkeiten und einen höheren Bewegungsgrad als Paro. Dies spiegelt sich in einer komplexeren Struktur der Hardware wider.
Software process improvement (SPI) is around for decades: frameworks are proposed, success factors are studied, and experiences have been reported. However, the sheer mass of concepts, approaches, and standards published over the years overwhelms practitioners as well as researchers. What is out there? Are there new emerging approaches? What are open issues? Still, we struggle to answer the question for what is the current state of SPI and related research? We present initial results from a systematic mapping study to shed light on the field of SPI and to draw conclusions for future research directions. An analysis of 635 publications draws a big picture of SPI-related research of the past 25 years. Our study shows a high number of solution proposals, experience reports, and secondary studies, but only few theories. In particular, standard SPI models are analyzed and evaluated for applicability, especially from the perspective of SPI in small-to-medium-sized companies, which leads to new specialized frameworks. Furthermore, we find a growing interest in success factors to aid companies in conducting SPI.
This summary refers to the paper Software process improvement : where is the evidence? [Ku15].
This paper was published as full research paper in the ICSSP’2015 proceedings.
Although still in the early stages of diffusion, smartwatches represent the most popular type of wearable devices. Yet, little is known why some people are more likely to adopt smartwatches than others. To deepen the understanding of underlying factors prompting adoption behavior, the authors develop a theoretical model grounded in technology acceptance and social psychology literature. Empirical results reveal perceived usefulness and visibility as important factors that drive intention. The magnitude of these antecedents is influenced by an individual’s perception of viewing smartwatches as a technology and/or as a fashion accessory. Theoretical and managerial implications are discussed.
Smart meter based business models for the electricity sector : a systematical literature research
(2017)
The Act on the Digitization of the Energy Transition forces German industries and households to introduce smart meters in order to save engery, to gain individual based electricity tariffs and to digitize the energy data flow. Smart meter can be regarded as the advancement of the traditional meter. Utilizing this new technology enables a wide range of innovative business models that provide additional value for the electricity suppliers as well as for their customers. In this study, we followed a two-step approach. At first, we provide a state-of-the-art comparison of these business models found in the literature and identify structural differences in the way they add value to the offered products and services. Secondly, the business models are grouped into categories with respect to customer segmetns and the added value to the smart grid. Findings indicate that most business models focus on the end-costumer as their main customer.
The need for creating digitally enhanced products, services, and experiences as well as the emergence of new or modified business models has a significant impact on the automotive domain. Innovative solutions and new topics such as Smart Mobility or Connectivity require current automotive development processes to undergo major changes. They need to be redesigned in a way that it is possible to learn and adapt continuously at a fast pace. Agile methods are promising approaches to address these new challenges. However, agile methods are not tailored to the specific characteristics of the automotive domain such as software product line (SPLs) development. Although, there have been efforts to apply agile methods in the automotive domain, widespread adoptions have not yet taken place.
In recent years, the rise of the digital transformation received significant importance in Business-to-Business (B2B) research. Social media applications provide executives with a raft of new options. Consequently, interfaces to social media platforms have also been integrated into B2B salesforce applications, although very little is as yet known about their usage and general impact on B2B sales performance. This paper evaluates 1) the conceptualization of social media usage in a dyadic B2B relationship; 2) the effects of a more differentiated usage construct on customer satisfaction; 3) antecedents of social media usage on multiple levels; and 4) the effectiveness of social media usage for different types of customers. The framework presented here is tested cross-industry against data collected from dyadic buyer seller relationships in the IT service industry. The results elucidate the preconditions and the impact of social media usage strategies in B2B sales relations.
Reality mining refers to an application of data mining, using sensor data to drive behavioral patterns in the real world. However, research in this field started a decade ago when technology was far behind today's state of the art. This paper discusses which requirements are now posed to applications in the context of reality mining. A survey has shown which sensors are available in state-of-the-art smartphones and usable to gather data for reality mining. As another contribution of this paper, a reality mining application architecture is proposed to facilitate the implementation of such applications. A proof of concept verifies the assumptions made on reality mining and the presented architecture.
Enterprise architecture management (EAM) is a holistic approach to tackle the complex Business and IT architecture. The transformation of an organization’s EA towards a strategy-oriented system is a continuous task. Many stakeholders have to elaborate on various parts of the EA to reach the best decisions to shape the EA towards an optimized support of the organizations’ capabilities. Since the real world is too complex, analyzing techniques are needed to detect optimization potentials and to get all information needed about an issue. In practice visualizations are commonly used to analyze EAs. However these visualizations are mostly static and do not provide analyses. In this article we combine analyzing techniques from literature and interactive visualizations to support stakeholders in EA decision-making.
The digital transformation of our society changes the way we live, work, learn, communicate, and collaborate. This disruptive change drive current and next 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 with more flexible enterprise information systems through adaptation and evolution of digital architectures. The present research paper investigates the continuous bottom-up integration of micro-granular architectures for a huge amount of dynamically growing systems and services, like microservices and the Internet of Things, as part of a new composed digital architecture. To integrate micro-granular architecture models into living architectural model versions we are extending enterprise architecture reference models by state of art elements for agile architectural engineering to support digital products, services, and processes.
A software process is the game plan to organize project teams and run projects. Yet, it still is a challenge to select the appropriate development approach for the respective context. A multitude of development approaches compete for the users’ favor, but there is no silver bullet serving all possible setups. Moreover, recent research as well as experience from practice shows companies utilizing different development approaches to assemble the best-fitting approach for the respective company: a more traditional process provides the basic framework to serve the organization, while project teams embody this framework with more agile (and/or lean) practices to keep their flexibility. The paper at hand provides insights into the HELENA study with which we aim to investigate the use of “Hybrid dEveLopmENt Approaches in software systems development”. We present the survey design and initial findings from the survey’s test runs. Furthermore, we outline the next steps towards the full survey.
Rapidly growing data volumes push today's analytical systems close to the feasible processing limit. Massive parallelism is one possible solution to reduce the computational time of analytical algorithms. However, data transfer becomes a significant bottleneck since it blocks system resources moving data-to-code. Technological advances allow to economically place compute units close to storage and perform data processing operations close to data, minimizing data transfers and increasing scalability. Hence the principle of Near Data Processing (NDP) and the shift towards code-to-data. In the present paper we claim that the development of NDP-system architectures becomes an inevitable task in the future. Analytical DBMS like HPE Vertica have multiple points of impact with major advantages which are presented within this paper.
Nowadays almost every major company has a monitoring system and produces log data to analyse their systems. To perform analysation on the log data and to extract experience for future decisions it is important to transform and synchronize different time series. For synchronizing multiple time series several methods are provided so that they are leading to a synchronized uniform time series. This is achieved by using discretisation and approximation methodics. Furthermore the discretisation through ticks is demonstrated, as well as the respectivly illustrated results.
Digital companies need information systems to implement their business processes end-to-end. BPM systems are promising candidates for that, because they are highly adaptable due to their business process model-driven operation mode. End-to-end processes contain different types of sub-processes that are either procedural, data-driven or business rule-based. Modern BPM systems support modeling notations for all these types of sub-processes. Moreover, end-to-end processes contain parts of shadow processing, so consequently, they must be supported in a performant way, too. BPMN seems to be the adequate notation for modeling these parts due to its procedural nature. Further, BPMN provides several elements that enable the modeling of parallel executions which are very interesting for accelerating shadow processing parts of the process. The present paper will observe the limitations and potentials of BPM systems for a high-performance execution of BPMN models representing shadow processing parts of a business process.
EAM ist ein holistischer Ansatz, um komplexe IT- und Unternehmensstrukturen darzustellen. Dabei ist es von zentraler Bedeutung, diese Strukturen möglichst komplett und übersichtlich zu visualisieren. Ein Ansatz, dies zu erreichen, ist eine multiperspektivische Darstellung von mehreren Views in einem Architekturcockpit. Dabei können mehrere Views simultan betrachtet und analysiert werden. Dadurch ist es möglich, die Auswirkungen einer Analyse des Views eines Stakeholders simultan aus den Views anderer Stakeholder betrachten zu können, um eventuelle Wechselwirkungen zu erkennen und einen allgemeinen Überblick über die Unternehmensarchitektur zu behalten. In dieser Arbeit zeigen wir, von der Konzeption über die Umsetzung bis zu einem Anwendungsbeispiel, wie ein solches Architekturcockpit realisiert werden kann.
Business processes are important knowledge resources of a company. The knowledge contained in business processes impart procedures used to create products and services. However, modelling and application of business processes are affected by problems connected to knowledge transfer. This paper presents and implements a layered model to improve the knowledge transfer. Thus modelling and understanding of business process models is supported. An evaluation of the approach is presented and results and other areas of application are discussed.
In recent times, enterprises have been increasingly dealing with the use of social media in internal communication and collaboration. In particular, so-called Enterprise Social Networks (ESN) promise meaningful benefits for the nature of work in corporations. However, these platforms often suffer from poor degrees of use. This raises the question of what initiatives enterprise can launch in order to stimulate the vitality of ESN. Since the use of ESN is often voluntary, individual adoption by employees need to be examined to find an answer. Therefore, the Unified Theory of Acceptance and Use of Technology (UTAUT) model was selected for the theoretical foundation of this paper. Following a qualitative research approach, the available research provides an analysis of expert interviews on specific ESN implementation strategies and included factors. In order to extensively conceptualize and generalize these strategic considerations, we conducted an inductive coding process. The results reveal that ESN implementation strategies can be understood as a multi-level construct (individual vs. group vs. organizational level) containing different factors dependent on the degree of documentation and intensity. This research in progress describes a qualitative evaluation as a preliminary study for further quantitative analysis of an ESN adoption model.
Software and system development faces numerous challenges of rapidly changing markets. To address such challenges, companies and projects design and adopt specific development approaches by combining well-structured methods and flexible agile practices. Yet, the number of methods and practices is large and the actual process composition is often carried out in an ad-hoc manner. This paper reports on a survey on hybrid software development approaches. We study which approaches are used in practice, how different approaches are combined, and what contextual factors influence the use and combination of hybrid software development approaches.
The emergence of agile methods and practices has not only changed the development processes but might also have affected how companies conduct software process improvement (SPI). Through a set of complementary studies, we aim to understand how SPI has changed in times of agile software development. Specifically, we aim (1) to identify and characterize the set of publications that connect elements of agility to SPI, (2) to explore to which extent agile methods/practices have been used in the context of SPI, and (3) to understand whether the topics addressed in the literature are relevant and useful for industry professionals. To study these questions, we conducted an in-depth analysis of the literature identified in a previous mapping study, an interview study, and an analysis of the responses given by industry professionals to SPI-related questions stemming from an independently conducted survey study.
Software engineering education is supposed to provide students with industry-relevant knowledge and skills. Educators must address issues beyond exercises and theories that can be directly rehearsed in small settings. A way to experience such effects and to increase the relevance of software engineering education is to apply empirical studies in teaching. In our article, we show how different types of empirical studies can be used for educational purposes in software engineering. We give examples illustrating how to utilize empirical studies, discuss challenges, and derive an initial guideline that supports teachers to include empirical studies in software engineering courses.
Decision-making in the field of Enterprise Architecture (EA) is a complex task. Many organizations establish a set of complex processes and hierarchical structures to enable strategy-driven development of their EA. This leads to slow and inefficient decision-making entailing bad time-to-market and discontented stakeholders. Collaborative EA delineates a lightweight approach to enable EA decisions but often neglects strategic alignment. In this paper, we present an approach to integrate the concept of collaborative EA and goal-driven decision-making through collaborative modeling of goal-oriented information demands based on ArchiMate’s motivation extension to reach a goal-oriented EA decision support in a collaborative EA environment.
The ability to develop and deploy high-quality software at a high speed gets increasing relevance for the comptetitiveness of car manufacturers. Agile practices have shown benefits such as faster time to market in several application domains. Therefore, it seems to be promising to carefully adopt agile practices also in the automotive domain. This article presents findings from an interview-based qualitative survey. It aims at understanding perceived forces that support agile adoption. Particularly, it focuses on embedded software development for electronic control units in the automotive domain.
Location-based services in buildings represent a great advantage for people to search places, products or people. In our paper we examine the feasibility of Bluetooth iBeacons for indoor localization. In the first part we define and evaluate the iBeacon technology through different experiments. In the second part our solution application is described. Our system is able to estimate the position of the user’s smartphone based on RSSI measurements. Therefore we used the built-in smartphone sensor and a building map with required sender information. Trilateration is used as positioning technique in contrast to fingerprinting to minimize beforehand effort. Results are promising but cannot reach the same accuracy level as sensor-fusion or fingerprinting approaches.
Pokémon Go was the first mobile Augmented Reality (AR) game that made it to the top of the download charts of mobile applications. However, very little is known about this new generation of mobile online Augmented Reality (AR) games. Existing media usage and technology acceptance theories provide limited applicability to the understanding of its users. Against this background, this research provides a comprehensive framework that incorporates findings from uses & gratification theory (U>), technology acceptance and risk research as well as flow theory. The proposed framework aims at explaining the drivers of attitudinal and intentional reactions, such as continuance in gaming or willingness to conduct in-app purchases. A survey among 642 Pokémon Go players provides insights into the psychological drivers of mobile AR games. Results show that hedonic, emotional and social benefits, and social norms drive, vice versa physical risks (but not privacy risks) hinder consumer reactions. However, the importance of these drivers differs between different forms of user behavior.
In a world with rapidly changing customer requirements and the increased role of technology, companies need more flexible systems to adapt their processes and react dynamically to changes. Adaptive Case Management (ACM) comes into consideration by providing a concept to adapt to changing business conditions. Within our research project we did a first foundational evaluation of the potential of ACM in supporting unpredictable sales processes. Based on a set of criteria we tested the concept of ACM with the open source tool Cognoscenti. The evaluation gave us the possibility to experience the concept of ACM. Hence we were able to provide a statement about the potential of ACM within the context of an unpredictable sales process, setting the path to further research and discussion of ACM in the area of sales processes.
The digital transformation 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 digital transformation since years. The Internet of Things, social collaboration systems for adaptive case management, mobility systems and services for Big Data in cloud services environments are emerging to support intelligent user-centered and social community systems. They will shape future trends of business innovation and the next wave of information and communication technology. Biological metaphors of living and adaptable ecosystems provide the logical foundation for self-optimizing and resilient run-time environments for intelligent business services and related distributed information systems with service-oriented enterprise architectures. The present research investigates mechanisms for flexible adaptation and evolution of digital enterprise architectures in the context of integrated synergistic disciplines like distributed service-oriented architectures and information systems, EAM - Enterprise Architecture and Management, metamodeling, semantic echnologies, web services, cloud computing and Big Data technology. Our aim is to support flexibility and agile transformations for both business domains and related enterprise systems through adaptation and evolution of digital enterprise architectures. The present research paper investigates digital transformations of business and IT and integrates fundamental mappings between adaptable digital enterprise architectures and service-oriented information systems.
The Internet of Things (IoT) fundamentally influences today’s digital strategies with disruptive business operating models and fast changing markets. New business information systems are integrating emerging Internet of Things infrastructures and components. With the huge diversity of Internet of Things technologies and products organizations have to leverage and extend previous enterprise architecture efforts to enable business value by integrating the Internet of Things into their evolving Enterprise Architecture Management environments. Both architecture engineering and management of current enterprise architectures is complex and has to integrate beside the Internet of Things synergistic disciplines like EAM - Enterprise Architecture and Management with disciplines like: services & cloud computing, semantic-based decision support through ontologies and knowledge-based systems, big data management, as well as mobility and collaboration networks. To provide adequate decision support for complex business/IT environments, it is necessary to identify affected changes of Internet of Things environments and their related fast adapting architecture. We have to make transparent the impact of these changes over the integral landscape of affected EAM-capabilities, like directly and transitively impacted IoT-objects, business categories, processes, applications, services, platforms and infrastructures. The paper describes a new metamodel-based approach for integrating partial Internet of Things objects, which are semi-automatically federated into a holistic Enterprise Architecture Management environment.
Die Energiewende bietet reichlich Fragen für verschiedenste Wissenschaftsdisziplinen einschließlich der Informatik und Wirtschaftsinformatik (WI). Bedauerlicherweise wurde bisher der Bereich der regionalen Energiegenossenschaften und kleinerer Energieversorgungsunternehmen weitgehend von der WI-Forschung vernachlässigt. Der vorliegende Beitrag stellt die aktuelle Situation dieser Organisationen dar und konzentriert sich auf die bestehende Wissenslücke von Geschäftsmodellen (GM) für Energiegenossenschaften (EG) als Zusammenschluss aus Privatpersonen oder kleinen Unternehmen, welche primär regionale, erneuerbare Energie produzieren. Die Modell- und Theorieentwicklung basiert auf der klassischen Literaturrecherche, Fallstudien in der Energiewirtschaft (EW), sowie grafischer Modellierung. Als Ergebnis wird das Referenzgeschäftsmodell einer EG als morphologischer Business Model Canvas vorgestellt. Dieses singuläre GM wird um die Darstellung des Wertschöpfungsnetzwerks, welches die strukturelle Einbindung der Akteure in das digitale Ökosystem der EG berücksichtigt, erweitert. Das aus der Forschung resultierende Referenzmodell dient der kritischen Überprüfung empirisch vorfindbarer GM und zur weiteren Entwicklung von Unternehmensarchitekturen digitaler Unternehmensverbünde.
In this paper we build on our research in data management on native Flash storage. In particular we demonstrate the advantages of intelligent data placement strategies. To effectively manage phsical Flash space and organize the data on it, we utilize novel storage structures such as regions and groups. These are coupled to common DBMS logical structures, thus require no extra overhead for the DBA. The experimental results indicate an improvement of up to 2x, which doubles the longevity of Flash SSD. During the demonstration the audience can experience the advantages of the proposed approach on real Flash hardware.
Im Rahmen der Vernetzung des Autos drängen neue Wettbewerber in die Automobilindustrie. Mittels disruptiver Innovationsmethoden haben Google, Apple, Facebook und Co. bereits Branchen grundlegend verändert und Marktführer wie Nokia oder Otto innerhalb weniger Jahre abgelöst. Die folgende Arbeit befasst sich mit diesen Methoden und der Fragestellung, wie sie in den automotiven Produktentstehungsprozess integriert werden können, um nachhaltig erfolgreiche Geschäftsmodelle am Markt platzieren zu können.
Digitization in the energy sector is a necessity to enable energy savings and energy efficiency potentials. Managing decentralized corporate energy systems is hindered by a non-existence. The required integration of energy objectives into business strategy creates difficulties resulting in inefficient decisions. To improve this, practice-proven methods such as Balanced Scorecard, Enterprise Architecture Management and the Value Network approach are transferred to the energy domain. The methods are evaluated based on a case study. Managing multi-dimensionality, high complexity and multiple actors are the main drivers for an effective and efficient energy management system. The underlying basis to gain the positive impacts of these methods on decentralized corporate energy systems is digitization of energy data and processes.
Neue Modelle für digitale Unternehmensarchitekturen mit Big Data, Services & Cloud Computing, mobilen Systemen, Internet of Things sowie Industrie 4.0 Ökosystemen machen eine enge Kooperation verschiedener Partner aus Wissenschaft, Anwendungsunternehmen, öffentlichen Organisationen, Softwarehersteller und IT- Dienstleister notwendig. Ziel dieser Zusammenarbeit ist die Zusammenführung neuer Konzepte und Möglichkeiten der Informationstechnologie zur bestmöglichen Unterstützung sich verändernder Unternehmensziele und -strategien. Software- und Unternehmensarchitekturen spielen hierbei eine zentrale Rolle. So werden Anforderungen bezüglich Flexibilität und Agilität in digitalen Unternehmen wesentlich durch serviceorientierte Ansätze unterstützt. Der Ordnungsgrad und die kosteneffiziente Gestaltung komplexer IT-Landschaften soll durch Digital Enterprise Architecture Management deutlich verbessert werden – passend zu neuen Möglichkeiten von Services & Cloud Computing, Big Data, sowie kollaborativen Geschäftsprozessen.
Selecting a suitable development method for a specific project context is one of the most challenging activities in process design. To extend the so far statistical construction of hybrid development methods, we analyze 829 data points to investigate which context factors influence the choice of methods or practices. Using exploratory factor analysis, we derive five base clusters consisting of up to 10 methods. Logistic regression analysis then reveals which context factors have an influence on the integration of methods from these clusters in the development process. Our results indicate that only a few context factors including project/product size and target application domain significantly influence the choice. This summary refers to the paper “Determining Context Factors for Hybrid Development Methods with Trained Models”. This paper was published in the proceedings of the International Conference on Software and System Process in 2020.
Der lokale Bekleidungseinzelhandel steht unter immer stärkerem Konkurrenzdruck durch Versandunternehmen. Zusätzlich bestehen durch gewachsene Architekturen eine Reihe von Wachstumshemmnissen. Daher sollen hier eine Reihe von Ansätzen zur Gestaltung datenzentrierter Unternehmensarchitekturen für den Bekleidungseinzelhandel vorgestellt werden. Sie basieren auf dem Einsatz von RFID zur Gewinnung von Kundenprofilen in den Niederlassungen und dem Einsatz von Big-Data basierten Auswertungs- und Analysemechanismen. Mit den vorgestellten Konzepten ist es Unternehmen des Bekleidungseinzelhandels möglich, ähnlich wie Versandunternehmen, individuelle Ansprachen des Kunden und Angebote zu entwickeln
The increasing number of connected mobile devices such as fitness trackers and smartphones define new data for health insurances, enabling them to gain deeper insights into the health of their customers. These additional data sources plus the trend towards an interconnected health community, including doctors, hospitals and insurers, lead to challenges regarding data filtering, organization and dissemination. First, we analyze what kind of information is relevant for a digital health insurance. Second, functional and non-functional requirements for storing and managing health data in an interconnected environment are defined. Third, we propose a data architecture for a digitized health insurance, consisting of a data model and an application architecture.
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.
Converting users into customers : the role of user profile information and customer journey analysis
(2016)
Due to the digital transformation, the importance of web analysis and user profiling for enterprises is increasing rapidly as customers focus on digital channels to obtain information about products and brands. While there exists a lot research on these topics, only a minority of firms use them to their advantage. This study aims to tighten the link between research and business such that experimental methods can be used for the improvement of communication strategies in practice. Therefore, a systematic literature analysis is conducted, workshops are observed and documented and an empirical study is used to integrate single steps into a framework for the
practical usage of user profiling and customer journey analysis.
With the Internet of Things being one of the most discussed trends in the computer world lately, many organizations find themselves struggling with the great paradigm shift and thus the implementation of IoT on a strategic level. The Ignite methodoogy as a part of the Enterprise-IoT project promises to support organizations with these strategic issues as it combines best practices with expert knowledge from diverse industries helping to create a better understanding of how to transform into an IoT driven business. A framework that is introduced within the context of IoT business model development is the Bosch IoT Business Model Builder. In this study the provided framework is compared to the Osterwalder Business Model Canvas and the St. Gallen Business Model Navigator, the most commonly used and referenced frameworks according to a quantitative literature analysis.
This paper investigates the impact of dynamic capabilities (DC) on brand love. From a resource-based view, there is little clarity vis-à-vis the specific capabilities that drive the ability to create brand love. This paper focuses on three research questions: Firstly, which dynamic capabilities are relevant for brand love? Secondly, how strong is the impact of certain dynamic capabilities on brand love? Thirdly, which conditions mediate and moderate the impact of specific dynamic capabilities on brand love? Data from a multi-method research approach have been used to itentify the specific capabilities that corporations need, to enhance brand love. Furthermore, a standardized online survey was conducted on marketing executives and evaluated by structural equation modeling. The results indicate, that customer expertise plays a major role in the relationship between dynamic capabilities and brand love. Furthermore, this relationship is more important in markets that have a low competitive differentiation in products and services.
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.
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.