Business Model Adaptation: Evidence of Lean Experimentation in Digital Startups

Digital startups frequently adapt their business model, but in doing so they face resource scarcity and need to “make-do” in validating and implementing their design changes at a practical level. We thus argue that digital startups employ a Lean Experimental approach when adapting their BM to contextual conditions. By means of an exploratory multiple-case study on Digital startups, this research investigates the factors driving the deployment of an experimental approach and proposing some factors that may drive differences in its application. Results suggest that most startups dealing with BM adaptation engage in experimentation practices that can be identified with the Lean Startup Approaches (LSAs), although with different extents of application. In this sense, startups move from scarce resource availability in resembling selected elements of the framework, whereas those with higher resource availability seem to be more prone to adopting LSAs in a structured and customized way at the organizational level

The evolution of meanings: an empirical analysis of the social media industry

Purpose – Innovation dynamics have been the object of study of several researchers, focusing in particular on technological innovation and the emergence of a dominant design. However, these models have been challenged by how the pervasiveness of digital technologies is speeding up the pace at which innovation evolves. On the other hand, a growing body of literature in innovation management has started underlining the relevance of new product and service meanings as a source of innovation. Design/methodology/approach – This research aims to study the different innovation dynamics within an industry, investigating not only how companies react to fast-changing functional advancements but rather how their behavior changes as shifts in meaning occur. To properly assess the phenomenon, this longitudinal study analyzes the social media industry, strongly subjected to continuous functional advancements, through a deep dive in the 160 innovations introduced between 2003 and 2017 by the eight leading players in the industry. Findings – Our results illustrate the co-existence of different approaches to innovation within an industry and hint that consequent and fast cycles of innovation in both functionalities and meanings discourage the emergence of a dominant design. Practical implications – Our results help managers and innovators acknowledge the possibility to leverage not just on the technological dimension of innovation but also the reason why people use a given product or service, innovating its meaning. Furthermore, our results recognize the co-existence of different innovation streams upon which innovators can act. Originality/value – This research contributes to the extant literature in innovation management, extending the classical models of innovation dynamics by including the evolution of innovations of meaning in relation to technological innovation

The role of tools, artifacts and instruments in the Experimentation Process: a Boundary Object perspective

Recent literature has focused on the extensive use of experimentation by firms to overcome the hurdles of innovating under uncertainty conditions. However, experimentation encompasses the frequent involvement of different types of tools, artifacts, and instruments to ensure the right conveyance of meanings across stakeholders. However, the current understanding of the role of tools throughout the experimentation process is often limited to mentions and is lacking proper theoretical framing. Previous studies in organizational knowledge sharing defined the concept of boundary object as a means to convey information across individuals. The notion of boundary objects has since been the objects of several studies, related to how companies perform sensemaking, develop new products, or engage in strategic decision-making. Our study aims at investigating the role that tools, artifacts, and instruments play throughout the experimentation process, adopting the lenses of boundary objects to characterize their deployment in the experimentation process. Through a single-case study on a relevant intrapreneurship initiative, we try to disentangle how tools, artifacts, and instruments are employed in the experimentation process. Our study advances the extant understanding in experimentation, by deep diving into the use of tools, artifacts, and instruments across its process. Our study thus contributes to theory in strategic management and innovation, by grounding the role of tools, artifacts, and instruments in the experimentation process into extant theory in management, while better defining and conceptualizing their link to different steps throughout the experimentation process. Finally, our study also contributes to practice by providing managers useful guidelines on the types of tools to employ in specific phases when experimenting for strategy-making

Social Opportunities and Business Model Design: Evidence From Three Social Enterprises

The tremendous pressures of growing social needs pose relevant challenges for governments attempting to allocate resources to deal with deficiencies and failures. At the same time, non-profit organizations, facing rising costs, intense competition over grants and donations, and ever-growing social needs, are struggling to financially sustain their operations. Scholarly research on Social Enterprises has been growing, mainly dealing with Social Enterprises as entrepreneurial endeavors and peculiar types of business models. However, the growing number of Social Enterprises and their relevance within communities is calling for better use of established theories and models from the strategic management and entrepreneurship literatures within the domain of Social Enterprises. The present research aims at addressing the transition that leads Social Enterprises from the identification of the social opportunity to business model design. By means of a series of semi-structured interviews to entrepreneurs from three different Social Enterprises, we lay the foundation for a closer investigation on opportunities in Social Entrepreneurship. We distinguish two composing aspects of Social opportunities: a social aspect, and an economic aspect of the opportunity, the recognition of which does not necessarily happen simultaneously. We then relate this finding to the transition towards business model design and reveal that, while the social aspect is the driving force of the entrepreneur, the recognition of the economic aspect signals the moment of mobilization of the social entrepreneur. Finally, we find that different typologies of social enterprises experience the transition to business model design differently, depending on how intuitive or challenges is the identification and exploitation of the economic aspect of the opportunity. We thus contribute to scholarly theory on entrepreneurship and business models, by extending the discourse on social business model design and social opportunity recognition, as well as provide actionable guidelines to social entrepreneurs struggling with translating the social opportunities, they have recognized into sustainable business models

Business Model Scaling through Experimentation: Growth Hacking in Digital Startups

An ever-growing number of startups is born every year, introducing innovative business models in new and established industries. However, only a limited number of them is able to scale and establish itself as a valid player in the market despite facing the resource constraints that are typical of startups, for which scaling translate into a significantly growth of their user base thanks to the scalability possibilities enabled by digital infrastructures. This phenomenon has called for novel approaches to grow in a sustainable way, while at the same time dealing with the strong resource constraints new ventures face. Several articles have analyzed the use of experimental approaches for startups to design and validate their business model despite their limited resource availability. Extant literature in business model innovation currently fails to investigate the methods and systems startups deploy when transitioning from their innovative and validated business model to a scalable one. However, practitioner literature has underlined the presence of a novel approach going under the name of “Growth Hacking” – to progress beyond a validated business model through continuous testing and experimentation. The aim of this study is to understand the way startups scale their business model, with particular focus on the approach they deploy to do so. This study leverages an exploratory multiple-case study on three Italian fintech startups which have been undergoing business model scaling leveraging Growth Hacking. The findings from the case study have then been supplemented by a series of interviews with a panel of experts in Growth Hacking, aimed at validating the interpretation of the findings. Our findings hint that, once reached a validated business model, startups adopt an experimental approach to business model scaling. In particular, startups use Growth Hacking to experiment in the way they acquire, activate, retain, and monetize customers. Consistently with extant theory, hypothesis building, iteration, and testing constitute the fundamental principles to conduct experiments aimed at growing and engaging the customer base. Furthermore, our findings illustrate the importance of specialization in the experimentation process for business model scaling, where marketing departments are those to carry out the experiments and serve an infrastructural role in gathering data from other departments, designing the experiments and translating their insights into actionable adjustments. This study provides insights for both theory and practice, building theory on the neglected phenomenon of business model scaling and Growth Hacking, while providing managers with guidelines to set up specialized marketing teams who can serve as the owners of the experimentation process for business model scaling