October 2018 Download this article as a PDF

Welcome to the October 2018 issue of the Technology Innovation Management Review. The authors in this issue share insights on using machine learning for customer foresight and service design, enhancing industry–academia collaboration, and understanding the impacts on incumbents when new digital platforms enter existing markets.

The articles in this issue were selected and developed from papers presented at the ISPIM Innovation Conference in Stockholm, Sweden, from June 17–20, 2018. ISPIM – the International Society for Professional Innovation Management – is a network of researchers, industrialists, consultants, and public bodies who share an interest in innovation management.

Next year’s event in North America – ISPIM Connects Ottawa – will be held in Ottawa, Canada, from April 7–10, 2019. The TIM Review and its associated academic program at Carleton University, the TIM Program, are proud to be the local hosts of the event in collaboration with other partners. See Box 1 for further details about this event, and please note that the deadline for submissions of outlines is December 1, 2018.

Box 1. ISPIM Connects Ottawa

ISPIM Connects Ottawa is a three-day event that will bring together world-renowned innovation managers, researchers, and business and thought leaders to share insights on specific local and global innovation challenges. Hosted by local universities in partnership with industry and the public sector, ISPIM Connects Ottawa seeks participation, submissions and presentations from academia, industry, research organizations, consultants, intermediaries, and policy makers.

Ottawa is Canada’s Capital City and it boasts a highly educated and skilled technology workforce, world-class research and higher-education institutions, strong startup ecosystems, and nearly 2,000 knowledge-based businesses. But, it takes more than that to stand out on the global stage. Invest Ottawa – the city’s leading economic development agency – recently completed its new strategic plan, which focuses on the city’s need to create local capability to be competitive in global markets, with the ultimate goal of cementing Ottawa’s status as a global technology hub. With this goal in mind, ISPIM Connects Ottawa will highlight three local innovation challenges that are also of global importance:

  • Scaling Startups: How can we design and sustain a startup ecosystem in a way that enables new ventures to grow early, rapidly, and securely? How can we help startups quickly reach a scale where they can make a real impact on the local economy and in global markets?
  • Adopting AI and Analytics: How can we move from hype to real customer value and competitive advantage? How can we transform the use of AI and machine learning to enable SME innovation and growth? How do we encourage adoption while navigating ethical issues?
  • Innovating with Government: How can we encourage collaboration between industry and government to drive innovation and provide benefit to citizens? How we can use this as an opportunity to develop advanced capacity and capability in startups, SMEs, and large companies?

ISPIM Connects Ottawa will also feature various other innovation management topics, as detailed in the call for submissions.


About this issue

In the first article, Daniel Gentner, Birgit Stelzer, and Bujar Ramosaj from Ulm University in Germany and Leo Brecht from the University of Liechtenstein present a case study in strategic foresight using machine learning algorithms to analyze a customer database. Using the CRISP-DM data mining methodology, they supported a manufacturing company’s efforts to obtain a profile of high-potential customers and their need for a new technology. The case study shows how quantitative customer foresight based on machine learning can help identify weak signals in a customer database, which, in turn, can be translated into specific actions for sales teams.

Next, Jyrki Koskinen, founder of Avaamo Konsultointi in Finland, shares lessons learned from a coaching program to help companies develop the data analysis and design thinking competencies needed to develop new, data-driven services. The coaching courses and supporting innovation platform of processes, methods, tools were developed and delivered by a consortium of Finnish universities and other organizations. Following a six-week course, participating companies undertook an eight-week case project to develop a new service or product by leveraging machine learning for predictive analysis. The article share details of the program’s development and insights gained from its implementation and outcomes.

Then, Els De Maeijer, Tom Van Hout, Mathieu Weggeman, and Ger Post from universities in the Netherlands and Belgium examine how the changing role of academics is reflected in the interaction between industry and academia, specifically during meetings. The authors closely studied project meetings in collaborative industrial–academic settings, mostly serving the semi-conductor field. They sought to understand how the choice of linguistic features shapes social and interpersonal relations in industry–academia collaborations by focusing on open innovation as a socially contingent process. Their findings challenge the typical industry–academia dichotomy implied by much of the literature, and they suggest practical approaches to stimulating open innovation in such collaborations.

Finally, Andreas J. Steur from Ulm University in Germany examines the impacts on incumbents when a new digital platform enters a market. The results of a time series analysis of the impacts on the taxi industry in New York City following Uber’s market entry show that new platforms must overcome a chicken-or-egg problem because their platform’s success depends on network effects, whereas the business models of incumbents typically do not. The analysis shows that the time needed for a new platform to reach a critical mass – at least one year in this case – can give incumbents a relatively brief but potentially critical chance to react to the new entrant.

For future issues, we are accepting general submissions of articles on technology entrepreneurship, innovation management, and other topics relevant to launching and growing technology companies and solving practical problems in emerging domains. Please contact us with potential article topics and submissions.

Chris McPhee

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Keywords: customer foresight, data analysis, data mining, design thinking, digital platforms, industry–academia collaboration, machine learning, market entry, Open innovation, service design