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Business ecosystems are increasingly gaining relevance in research and practice. Because ecosystems progressively change, enterprises are required to analyse their ecosystem, in order to identify and respond to such changes. For gaining a comprehensive picture of the ecosystem, various enterprise stakeholders need to be involved in the analysis process. We use an Action Design Research approach to implement a collaborative process for modelling and visualizing business ecosystems in two case studies. We look at the challenges of the collaborative process and study how a model-driven approach addresses these challenges. We validate and discuss the modelling process along six steps; definition of the business ecosystem focus, model instantiation, data collection, provision of tailored visualizations, model adaption, and using visualizations ‘to tell a story’. In a cross-case analysis, we draw conclusions with respect to process implementation and the role of visualizations.

Business ecosystems are increasingly gaining relevance in research and practice. Because ecosystems progressively change, enterprises are required to analyse their ecosystem, in order to identify and respond to such changes. For gaining a comprehensive picture of the ecosystem, various enterprise stakeholders need to be involved in the analysis process. We use an Action Design Research approach to implement a collaborative process for modelling and visualizing business ecosystems in two case studies. We look at the challenges of the collaborative process and study how a model-driven approach addresses these challenges. We validate and discuss the modelling process along six steps; definition of the business ecosystem focus, model instantiation, data collection, provision of tailored visualizations, model adaption, and using visualizations ‘to tell a story’. In a cross-case analysis, we draw conclusions with respect to process implementation and the role of visualizations.

In this conceptual article, we highlight group modeling and crowd-based modeling as an approach for collectively constructing business ecosystem models. Based on case study examples, we showcase how engaging in the collective activity of crowd-based modeling supports the creation of value propositions in business ecosystems. Such collective activity creates shared, IS-embedded resources on the network level that align the diverse set of ecosystem stakeholders such as firms, public actors, citizens, and other types of organizations. Based on extant research, we describe the roles involved in building ecosystem models that inform and reconfigure shared infrastructures and platforms.

Smart mobility is a central issue in the recent discourse about urban development policy towards smart cities. The design of innovative and sustainable mobility infrastructures as well as public policies require cooperation and innovations between various stakeholders&mdash, businesses as well as policy makers&mdash, of the business ecosystems that emerge around smart city initiatives. This poses a challenge for deploying instruments and approaches for the proactive management of such business ecosystems. In this article, we report on findings from a smart city initiative we have used as a case study to inform the development, implementation, and prototypical deployment of a visual analytic system (VAS). As results of our design science research we present an agile framework to collaboratively collect, aggregate and map data about the ecosystem. The VAS and the agile framework are intended to inform and stimulate knowledge flows between ecosystem stakeholders in order to reflect on viable business and policy strategies. Agile processes and roles to collaboratively manage and adapt business ecosystem models and visualizations are defined. We further introduce basic categories for identifying, assessing and selecting Internet data sources that provide the data for ecosystem models and we detail the ecosystem data and view models developed in our case study. Our model represents a first explication of categories for visualizing business ecosystem models in a smart city mobility context.

Integrated care approaches are becoming increasingly relevant with the current aging population. In the context of an integrated healthcare project, we developed a smart adaptive case management system for professionals that is currently being used for clinical trials. In this paper, we present the modeling requirements for integrated healthcare applications and use them to categorize and compare existing implementation approaches used in practice.

Advances in software and hardware technology open up new potential for context-aware vertical social software. Companies are facing the challenge to incorporate these ideas into their existing software solutions. In this paper, we propose a reference architecture for Context-Aware Vertical Social Software platforms to facilitate reuse and enable synergies across different existing and new social software applications and workflows. This architecture enables external software developers to meet the needs of improving existing products and services of companies. Moreover, we present the lessons we learned from the implementation of such a platform and two case studies in collaboration with a large industry partner.

Conversational interfaces recently gained a lot of attention. One of the reasons for the current hype is the fact that chatbots (one particularly popular form of conversational interfaces) nowadays can be created without any programming knowledge, thanks to different toolkits and so-called Natural Language Understanding (NLU) services. While these NLU services are already widely used in both, industry and science, so far, they have not been analysed systematically. In this paper, we present a method to evaluate the classification performance of NLU services. Moreover, we present two new corpora, one consisting of annotated questions and one consisting of annotated questions with the corresponding answers. Based on these corpora, we conduct an evaluation of some of the most popular NLU services. Thereby we want to enable both, researchers and companies to make more educated decisions about which service they should use.

Today's enterprises have to align their information systems continuously with their dynamic business and IT environment. Collaborative information systems address this challenge by involving diverse users in managing the application's data as well as its conceptual model. In this sense, both the data and the model co-evolve. There are different approaches for aligning data and model evolution, wherein either the data is aligned to the model, or vice versa. In this work, we present a hybrid approach supporting both strategies and elaborate on our experiences of applying the approach in projects for over five years. Thereby, we discuss challenges and issues faced in those projects, and how we addressed them by redesigning and reimplementing the approach. We formulate those issues and respective solutions as lessons learned, which not only hold for the concrete system which was applied in those projects, but which should guide the design and implementation of all software systems supporting the co-evolution of data and model.