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Über dieses Buch

This book constitutes the refereed proceedings of the 9th International Conference on Software Business, ICSOB 2018, held in Tallinn, Estonia, in June 2018. This year the conference theme was “How Digitalization Impacts Software Business” and focused on digitalization and its impact on the speed of business models and business modeling and the realization of these business models.

The 11 full papers and 1 short paper presented in this volume were carefully reviewed and selected from 34 submissions. They were organized in topical sections named: software ecosystems; software product management and business models; and software start-ups.



Software Ecosystems


Individual People as Champions in Building an Emerging Software Ecosystem

An increasing amount of software service providers tend to evolve their platforms into business ecosystems. In the mainstream of extant literature, the ecosystems have been seen as an interconnected system of organizations, mainly ignoring the individual level. However, some previous studies have suggested that collaboration—such as building a new ecosystem—may be depending on individual key persons who are development-oriented and capable of seeing the ecosystem’s value potential already in its early phases. Based on the results of a single-case study, this short paper proposes a new conversation on an unexplored area of key persons as enablers—‘champions’—for a new ecosystem creation. The empirical analysis was based on a single case study on a recently launched new software business ecosystem. As a result, four different capability areas and six, partly overlapping, roles for a champion, were identified. In future work, the findings on individual’s roles and required capabilities may provide fruitful research avenues to understand better the process of emergence of new ecosystems.
Katariina Yrjönkoski, Marko Seppänen, Sami Hyrynsalmi

Modeling Support for Strategic API Planning and Analysis

APIs provide value beyond technical functionality. They enable and manage access to strategic business assets and play a key role in enabling software ecosystems. Existing work has begun to consider the strategic business value of software APIs, but such work has limited analysis capabilities and has not made use of established, structured modeling techniques from software and requirements engineering. Such modeling languages have been used for strategic analysis of ecosystems and value exchange. We believe these techniques expand analysis possibilities for APIs, and we apply them as part of a cross-company case study focused on strategic API planning and analysis. Results show that goal, value, and workflow modeling provide new, API-specific benefits that include mapping the API ecosystem, facilitating incremental API planning, understanding dynamic API-specific roles, identifying bottlenecks in API change workflows, and identifying API value.
Jennifer Horkoff, Juho Lindman, Imed Hammouda, Eric Knauss, Jamel Debbiche, Martina Freiholtz, Patrik Liao, Stephen Mensah, Aksel Strömberg

Software Ecosystem Health of Cryptocurrencies

Background: Cryptocurrencies are highly valued without understanding the health of the underlying ecosystems. Previous work shows factors which determinate the exchange rate. However, the technological determinants show decreasing significance. Objective: This paper explores whether the Open-source Software Ecosystem Health Operationalization (OSEHO) framework can be used to extend the given technology factors. Method: By conducting the OSEHO in a case-study on three distinct cryptocurrency ecosystems, this paper gives a better insight in the ecosystem’s value, longevity and propensity for growth and the relation of these factors to the cryptocurrency value. Results: The ‘healthiest’ cryptocurrency ecosystem also shows the highest economic health. Two metrics from the OSEHO show strong positive significant correlation with the exchange rate. Conclusion: Metrics from the OSEHO show promising indications to be technological determinants for the exchange rate. This research can be used as a foundation for further econometric tests or research on other aspects of cryptocurrencies.
Matthijs Berkhout, Fons van den Brink, Mart van Zwienen, Paul van Vulpen, Slinger Jansen

Benchmarking Privacy Policies in the Mobile Application Ecosystem

Mobile app providers have access to, and gather, large amounts of personal data. The exact data varies by app provider and is described in lengthy privacy policies with varying levels of transparency. Privacy policies with a low level of transparency hamper users from making educated decisions about the data that they want to share with third parties. In this paper, the Privacy Policy Benchmark Model is presented based on existing literature and applied to a selection of 20 mobile applications and their privacy policies. The Privacy Policy Benchmark Model is used for evaluating the transparency and quantity of data that is collected. The model consists of two aspects: the amount of data mobile app provides collect and the transparency of those privacy policies. The examined providers are transparent about what they collected and how they use it. They are less transparent about other topics such as the location of the stored information and how information is processed after removal, making privacy and usage considerations more difficult for users on those specific matters.
Sharif Adel Kandil, Micha van den Akker, Koen van Baarsen, Slinger Jansen, Paul van Vulpen

Artifact Compatibility for Enabling Collaboration in the Artificial Intelligence Ecosystem

Different types of software components and data have to be combined to solve an artificial intelligence challenge. An emerging marketplace for these components will allow for their exchange and distribution. To facilitate and boost the collaboration on the marketplace a solution for finding compatible artifacts is needed. We propose a concept to define compatibility on such a marketplace and suggest appropriate scenarios on how users can interact with it to support the different types of required compatibility. We also propose an initial architecture that derives from and implements the compatibility principles and makes the scenarios feasible. We matured our concept in focus group workshops and interviews with potential marketplace users from industry and academia. The results demonstrate the applicability of the concept in a real-world scenario.
Yuliyan V. Maksimov, Samuel A. Fricker, Kurt Tutschku

Software Product Management and Business Models


Continuous Software Portfolio Performance Management

Product portfolio decision making is the process of coming to decisions regarding resource division along multiple software products. This process is part of portfolio management, and is an essential task in managing a software company. However, product portfolio decision making is an implicit process, and product managers are too occupied with tactical and operational decision making to execute strategic decisions regarding portfolio management. Academic research has not yet provided a model to adapt intuitive and opportunistic portfolio decision making to an explicit and data-driven cycle. The goal of this research is to make portfolio decision making explicit by modeling this process in the Dutch software industry. Case studies at 6 small to medium-size software companies in the Netherlands evaluate the initial Software Portfolio Decision Making (SPDM) model. We present the SPDM model after adaptation to the findings in the case studies. Using this model enables software companies to move from an intuitive decision making process towards data-driven explicit decision making.
Paul van Vulpen, Sjaak Brinkkemper, Slinger Jansen, Garm Lucassen

Generating Win-Win Strategies for Software Businesses Under Coopetition: A Strategic Modeling Approach

Interorganizational coopetition describes a phenomenon in which businesses cooperate and compete simultaneously. Such behavior is commonplace among software firms wherein vendors concomitantly deal with each other both as partners and as rivals. Sustainable coopetitive relationships are predicated on the logic of win-win strategies. Conversely, win-lose or lose-lose strategies do not lead to durable coopetitive relationships. This aspect of coopetition requires decision-makers in coopeting software businesses to generate and analyze win-win strategies. This paper proposes a strategic modeling approach to systematically search for alternatives and generate win-win strategies. This approach synergistically combines i* goal-modeling to analyze the distributed intentional structures of actors and Game Tree decision-modeling to reason about the moves and countermoves of actors. An illustrative example of a published case study is presented to demonstrate the strengths and weaknesses of this methodology.
Vik Pant, Eric Yu

Exploring Business Model Changes in Software-as-a-Service Firms

This paper reports the findings from research on the changes in the business models of Software-as-a-Service (SaaS) firms. The extant literature defines these firms through the use of cloud computing technologies as part of their products and service. However, current literature is missing consideration of the effects of adopting these technologies on the elements of business model, including value proposition, activities, structure and revenue logic. This paper presents findings from 324 responses to a questionnaire survey on how these business model elements of software firms have changed as a result of adopting cloud computing technologies and competitive pressures, and identifies the differences in changes between the SaaS firms originating from software product and software services business. The findings suggest that the SaaS firms are generally unifying their core product offering and pricing across customers and increasing their sales efforts. Besides, the two types of SaaS firms are different in terms of their software-related activities. The present study therefore provides insights into development of the software market, where SaaS firms are claimed to challenge the proprietary software vendors. The findings also imply that the conceptualization of SaaS in IS adoption and IT outsourcing studies can be improved.
Eetu Luoma, Gabriella Laatikainen, Oleksiy Mazhelis

Software Start-ups


Determinants for the Success of Software Startups: Insights from a Regional Cluster

In recent years, we have seen a growing interest in technology-based companies and intensive knowledge. Several regional clusters have appeared supported in dynamic entrepreneurial ecosystems which, alongside intrinsic aspects of the business, are important determinants of the success of new companies. However, most startups created in these innovation-oriented spaces do not survive the first years of life, due to the high competitiveness of the technological market, due to deficiencies in the business model, due to the support conditions provided by the surrounding ecosystem, and finally due to a weak adjustment between all these dimensions. Among several models available, the Early-Life Decision Model (ELDM) presents itself as an interesting framework for studying the development and success conditions of software companies. This article discusses the application of the ELDM based on a series of interviews conducted to 15 Portuguese software startups installed in a technological cluster located in the northeast of Portugal. Based on the results obtained, it was appropriate to add a new dimension to the ELDM model (learning) and complementing it with the perspectives of the business type and internal versus external determinants.
Paulo Afonso, João M. Fernandes

Opportunity Exploitation in Software Startups. A Human Capital View

Background – Transforming a business opportunity to a valid business case is a crucial process of an early-stage software startups. Prior literature on entrepreneurship defines two types of opportunity exploitations, opportunity discovery and opportunity creation, and proposes models describing the exploitation processes. The factors affecting startups’ abilities to conduct the exploitation are, however, addressed only to a limited extend in prior research. Aim – This research aims at increasing the knowledge on those factors by studying empirically the effects of the available human capital on the opportunity exploitation processes in software startups. Method – We conducted a multiple-case study on a group of software startups in Italy, Norway and Finland. We focused on the founders of the startups, examining their opportunity processes, their human capital, and the interdependencies between the opportunity processes and human capital. Results – Our results are in line with the findings of prior research, which point out that uncertainty is the key differentiator between the opportunity discovery and creation processes. The results reveal, however, that both process types co-exist in the early stages of software startups, independently of how the opportunity was initially recognized, and also highlight missing human capital as a key reason for the uncertainty. We conclude that in software startups the availability of human capital plays a bigger role in the exploitation of opportunities than their types, discovered or created, because even exploitation of a-priori existing opportunities turn to opportunity creation processes in case of human capital shortages.
Pertti Seppänen, Kari Liukkunen, Markku Oivo

Changing and Pivoting the Business Model in Software Startups

In a company, its business strategy and business model undergo changes throughout its life. These changes can be induced or forced externally or they can result from a deliberate strategy to improve the business performance and to achieve success. Certain changes can lead to a major change in the business model of the company (i.e., a pivot). Such change or innovation in the business model can occur in various of its dimensions. According to Osterwalder and Pigneur, there are four epicenters of change and innovation to be taken into consideration. In this manuscript, fifteen Portuguese software startups were studied using essentially semi-structured interviews to gather the information. The data was processed with a software application for qualitative data analysis. The main results are related to a dynamic process of evolution and change of the business model in software startups. In particular, we have identified that the changes in the business elements that support the production of the value proposition (left-hand side of the Business Model Canvas) affect the elements that explain the strategy of delivering the value proposition to customers (right-hand side of the Business Model Canvas).
João M. Fernandes, Paulo Afonso

From MVPs to Pivots: A Hypothesis-Driven Journey of Two Software Startups

Software startups have emerged as an interesting multiper-spective research area. Inspired by Lean Startup, a startup journey can be viewed as a series of experiments that validate a set of business hypotheses an entrepreneurial team make explicitly or inexplicitly about their startup. It is little known about how startups evolve through business hypothesis testing. This study proposes a novel approach to look at the startup evolution as a Minimum Viable Product (MVP) creating process. We identified relationships among business hypotheses and MVPs via ethnography and post-mortem analysis in two software startups. We observe that the relationship between hypotheses and MVPs is incomplete and non-linear in these two startups. We also find that entrepreneurs do learn from testing their hypotheses. However, there are hypotheses not tested by MVPs and vice versa, MVPs not related to any business hypothesis. The approach we proposed visualizes the flow of entrepreneurial knowledge across pivots via MVPs.
Dron Khanna, Anh Nguyen-Duc, Xiaofeng Wang


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