Visualizing Business Ecosystems: Applying a Collaborative Modelling Process in Two Case Studies

Business ecosystems are increasingly gaining relevance in research and practice. Because business ecosystems progressively change, enterprises are interested in analysing their ecosystem, to identify and address such changes. In order to gain a comprehensive picture of the business ecosystem, various stakeholders of the enterprise should be involved in the analysis process. We propose a collaborative approach to model and visualize the business ecosystem and we validate four central roles in the modelling process. The process consists of six steps, namely the definition of the business ecosystem focus, instantiation of the model, data collection, provision of tailored visualizations, collecting feedback and adapting the models, and using the visualization ‘to tell a story’. In this paper, we report case studies of two companies that have instantiated ecosystem models

The impact of Digital Platforms on Business Models: an empirical investigation on innovative start-ups

Digital platforms have the ability to connect people, organizations and resources with the aim of facilitating the core interactions between businesses and consumers as well as assuring a greater efficiency for the business management. New business concepts, such as innovative start-ups, are therefore created based on innovation, scalability and the relationships within the community around them. The purpose of this work is to deeply understand the evolution of business models brought by innovative and dynamic companies operating through online platforms. In order to achieve the objectives set, an exploratory multiple-case study was designed based on in-depth structured interviews. The aim was to conduct a mixed analysis, in order to rely both on qualitative and quantitative data. The structured interview protocol was therefore designed to collect and then analyse data concerning the company profile and managers’ perspectives on the phenomenon of interest. The interview protocol was submitted in advance and then face-to-face interviews were carried out with the following professional figures: Chief Executive Officer (CEO), General Manager, Chief Technology Officer (CTO), Marketing Manager and Developers. Collected data were analysed and processed through the Canvas Business Model in order to clearly outline similarities and differences among the sample. Results can be considered under two viewpoints. On the one hand, this work provides a detailed overview of the companies interviewed, according to the dimensions of: reference market dynamics, type and number of customers, scalability. On the other one, they allow to identify some success patterns regarding key activities, key resources, channel mix strategy, costs management, value proposition, customer segmentation, key partners and the way to obtain revenues. Results from the multiple-case study with 15 Italian start-ups provide interesting insights by comparing the innovative business models developed and highlighting key differences and similarities. verall, the start-ups analyzed, operating in several sectors, showed great growth prospects and the possibility to create value for their customers through innovative products and services offered through digital platforms

Design Fiction Diegetic Prototyping: A Research Framework for Visualizing Service Innovations

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.Purpose: This paper presents a design fiction diegetic prototyping methodology and research framework for investigating service innovations that reflect future uses of new and emerging technologies. Design/methodology/approach: Drawing on speculative fiction, we propose a methodology that positions service innovations within a six-stage research development framework. We begin by reviewing and critiquing designerly approaches that have traditionally been associated with service innovations and futures literature. In presenting our framework, we provide an example of its application to the Internet of Things (IoT), illustrating the central tenets proposed and key issues identified. Findings: The research framework advances a methodology for visualizing future experiential service innovations, considering how realism may be integrated into a designerly approach. Research limitations/implications: Design fiction diegetic prototyping enables researchers to express a range of ‘what if’ or ‘what can it be’ research questions within service innovation contexts. However, the process encompasses degrees of subjectivity and relies on knowledge, judgment and projection. Practical implications: The paper presents an approach to devising future service scenarios incorporating new and emergent technologies in service contexts. The proposed framework may be used as part of a range of research designs, including qualitative, quantitative and mixed method investigations. Originality: Operationalizing an approach that generates and visualizes service futures from an experiential perspective contributes to the advancement of techniques that enables the exploration of new possibilities for service innovation research

UNDERSTANDING MOBILE ECOSYSTEM DYNAMICS: A DATA-DRIVEN APPROACH

The mobile ecosystem consists of a heterogeneous and continuously evolving set of firms that are interconnected through a complex, global network of relationships. However, there is very little theoretical understanding how these networks emerge and evolve and no well-established methodology to study these phenomena. Traditional approaches have primarily utilized alliance data of relatively established firms; however, these approaches ignore the vast number of relevant ecosystem activities that occur at the personal, entrepreneurial, and university level. We argue and empirically illustrate that a data-driven approach, using both alliance and socially-curated datasets, can provide important complementary explanatory insights into the dynamics of the mobile ecosystem. We present our approach through two recently formed mobile ecosystem relationships – the strategic partnership between Nokia and Microsoft and Google’s acquisition of Motorola Mobility. Our analysis is complemented using network visualization techniques. The paper concludes with implications and future research opportunities

ICTs, disruptive forces and the production paradox in tourism: Present and future issues in the Visitor Attraction sector

En el marco de colaboración entre la Glasgow Caledonian University (Escocia, Reino Unido) y la Universidad de Alicante (España) y con el objetivo de dar a conocer la producción investigadora de docentes e investigadores involucrados en el convenio de colaboración entre ambas universidades, publicamos este libro como medio de difusión científica para visibilizar, compendiar y compartir las investigaciones. El valor fundamental de la obra es el carácter internacional y multidisciplinar de las investigaciones en el área de ciencias sociales y económicas, enfocadas en temáticas tan diversas como el marketing, la economía, la comunicación o la moda, entre otras.As part of the cooperation between Glasgow Caledonian University (Scotland, United Kingdom) and the University of Alicante (Spain) and in order to publicize the research production of teachers and researchers involved in the collaboration agreement between the two universities, we publish this book as a means of scientific dissemination to visualize, summarize and share research. The fundamental value of the work is international and multidisciplinary research in the area of social and economic sciences, focused on topics as diverse as marketing, economics, communication and fashion, among others

The Quest for Mobility: Designing Enterprise Application Framework for M-Business Practices

With the advent of the “road warrior,” a growing part of the workforce is mobile and using all sorts of mobile devices to stay in touch and transact business. As the global economy shifts toward the mobile economy, enterprises need to be progressively more flexible and globalize. Mobile businesses open up new opportunities for innovative enterprises and give them new means of communications with customers and employees. In a changing business landscape, mobile business addresses new customer channels and integration challenges. The current transformation is simply the movement of e-business to a mobile environment. It is still a developing concept as are the business models that support it. The usefulness of the mobile channels will be largely driven by new enterprise applications that enhance the overall customer values. This paper provides a broad discussion on the movement of mobile integration strategies. Several issues will be addressed, such as value chain, the data access of mobile computing, m-business application framework, and the future development of mobile computing. All of these efforts attempt to provide an overview and schematics for the integration of modern e-business application strategies into future m-business practices. This paper will show that any proposed system or strategy must recognize the primary value and mechanism of how people “work,” and technological solutions must be devised in order to facilitate people who conduct business. With mobile technologies, enterprise applications will go beyond the four walls of organizations to a workforce on the mov

The influences of user generated ‘Big data’ on urban development

Cities are the nucleus for creativity and ideas, as it has all the potentials for people to work, explore and live. People always come to cities because they want to be part of something, this magnet in the cities created the problem of population (Ericsson: Thinking Cities in the Networked Society, 2012). Approximately 50% of world’s population lives in urban areas, a number which is expected to increase to nearly 60% by 2030. (Mutizwa-Mangiza ND, Arimah B C, Jensen I, Yemeru EA, Kinyanjui MK, 2011). According to the rapid change in cities’ population there exists a need to utilize intelligent prediction tools to deliver a better way of living. Smart cities provide an opportunity to connect people and places using innovative technologies that help in better city planning and management ( Khan, Anjum, Soomro, & Tahir, 2015). Data is never a new thing, but data sources are always in change. The internet made everything easier and more reachable. This wide range of technologies such as IOT (internet of things) and M2M (machine to machine) (Gartner, 2015), is believed to offer a new potential to deliver an analytical framework for urban optimization. The real value of such data is gained by new knowledge acquired by performing data analytics using various data mining, machine learning or statistical methods. According to this technologically mutated, data comes from weather channels, street security cameras, Facebook, Twitter, sensor networks, in-car devices, location-based smartphone apps, RFID tags, smart meters, among other sources (Hinssen, 2012). This massive amount of information that comes from real-time based tools, made the world in front of a new era of data called ‘Big Data’. However, turning an ocean of messy data into knowledge and wisdom is an extremely challenging task. The proposed paper will discuss the IOT developed frameworks which are used to improve cities infrastructure and their vital systems. Analyzing these frameworks will help developing a conceptual proposal of data visualizing software; with the aim of helping urban planners get a better and easier way to comprehend the usage of multi-data sources for city planning and management. The full control of data is an open challenge, however proposing the fundamental bases of framework with the ability to extend and having an application layer above would be very helpful for urban process shifting. The Egyptian case is our main scope to have a smarter city that provides an opportunity to connect people and places using innovative technologies

Business model innovations for the Internet of Things: a focus on the retail setting

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