Managing innovation in turbulent environments (e.g., in environments with extreme uncertainty and complexity in market needs and technological opportunities) is a major challenge. A recent stream of studies in the management literature has suggested that when facing turbulent environments, firms should deploy more flexible development processes. This paper approaches this issue by looking at the Italian mobile telecommunications (TLC) industry. Nine in-depth case studies were conducted in five different companies. Data analysis showed some important results. First of all environmental turbulence should be considered to be project specific rather than company or industry specific. Moreover, it can come from both shift in the market needs and in the technology. Nevertheless, it seems clear that having rapid changes is not enough to have environmental turbulence. If rapid changes can be somehow foreseen, there is no turbulence at all. Hence, when approaching projects in potentially turbulent environments, managers should assess both rapidity and unpredictability of the environment. Finally, looking at the in-depth cases, the paper points out what of the main practices to increase flexibility that are described in literature are actually adopted by companies. In case of turbulence (both in the market and/or in the technology) companies delay concept freezing point. Moreover, in the case of technological turbulence, they also leverage on rapid project iterations, whereas in case of market turbulence they more likely adopt early experiments involving customers, formal and cross-functional project teams, and flat organizational structures.

Two-sided markets and digital platforms are becoming increasingly relevant in the modern scenario. Companies like Airbnb and Uber are inspiring many other firms in different fields that share their basic structure: they match two (or more) groups of customers. This research aims at exploring the innovation strategies companies such as these rely on to expand their basic structure towards more complex models. Being inspired by previous models in the field and considering the role that big data seems to play in these businesses, a first conceptual model is presented. Therefore, 100companies-using mobile apps as the empirical setting-are explored in this research to understand the common behaviors concerning evolution. In the end, three strategies are presented: Supply (Side) Expansion, Transactional Advertising, and Data Trading. These strategies are further discussed to highlight two main directions of innovation-ecosystem innovation and data push innovation-which may be merged giving birth to multi-sided epiphanies. The paper contributes to the literature showing various strategies and their implication to foster innovation on two-sided platforms.Moreover, it shows possible ways to exploit the value embedded in the complex ecosystems of the relationships they create.

Purpose The pervasive spread of digital technologies brought an incredible boost in data availability. Companies are dealing with massive amount of data that wait to be exploited. At the same time, scholars are providing different strategies and methods to help companies capture the value embedded in their data to foster innovation and improve the efficiency of existing processes. In these research studies, data are the by-product of something else, and they are a silent asset that needs to be exploited. What if data might be considered the final goal? The paper aims to discuss these issues. Design/methodology/approach The research is based on an exploratory multiple case study analysis, on the basis of three cases used as an illustration for new ideas. In particular, the gathered data are analyzed according to models previously presented in the literature review, building on and expanding them. Findings The research proposes a data-driven approach to innovation, offering a peculiar view of the innovation process. The trigger point is the need of data that let begin the entire development process of a complex system. In this perspective, the application that data are a by-product of the entire innovation process and not the primary output is peculiar since the vast majority of the literature consider data as the by-product of the primary product. Research limitations/implications Future research is needed to assess the replicability of the model outside the mobile app industry and to measure its performances. Nevertheless, this paper provides insights both for scholars and managers, enlarging the discussion on digital innovation and digital business models. Practical implications The results provide a development process to foster innovation relying on the need of data as the trigger point, guiding entrepreneurs and managers in the building process of the entire digital system. Originality/value Previous research studies often considered Big Data (BD) in innovation as a way to enlarge the current product offer or to make the innovation process more effective or efficient; this paper changes the perspective by considering BD as the trigger and the enabler of the entire digital innovation process.

The Open Innovation paradigm has been increasingly considered as a relevant approach to innovation. Among the different sources, the end users are particularly meaningful. Scholars highlighted several methods and strategies to involve them in the innovation process by asking, observing and giving them the chance to actually co-create. Digital technologies are expanding the span of opportunities in this direction, gathering a huge amount and variety of data while the end user enjoy a digital product, these data can be named as User Generated Big Data (UGBD). The aim of this research is to understand whether UGBD can contribute in User Innovation and to highlight the enabled strategies to create value through them.Leveraging on a multiple case study (Twitter, Spotify, Strava and Deliveroo), the paper first classify UGBD among the methods to foster User Centered Innovation, second it defines two strategies to create value relying on UGBD. First, companies can leverage on a Using Data strategy -addressing both the end user or other player in the ecosystem -fostering service innovation through an inbound approach. Second, a Selling data strategy can be pursued, addressing new clients and fostering business model innovation, enlarging the company's value chain in an outbound perspective.

The breakthrough impact of newborn companies over the last years brought to the definition of Big Bang Disruption, a new kind of innovation that relies on an unencumbered development, an unconstrained growth, and an undisciplined strategy. The relevance from a practitioner perspective is straightforward: entire industries have been challenged and disrupted. From a theoretical perspective, the concept is less developed. This research aims to understand it through a Business Model perspective, better highlighting the design variables that may lead to this kind of innovation. Leveraging crisp-set Qualitative Comparative Analysis (csQCA) to define the necessary conditions to be called a Big Bang Disruptor, this paper relies on a rock clustering method-using the Unicorns' list as the sample-to highlight common patterns. Results show two main factors: the chance to innovate the meaning and to rely on a two-sided market structure as key variables to design a Big Bang Disruptor. Results are discussed under the lenses of previous research. Finally, limitations and avenues for further studies are explored.