1,720,997 research outputs found
Coniugare passato e futuro: Il ritorno alle origini delle imprese familiari
No full textDopo anni di delocalizzazione e di nuove incertezze, le aziende cercano stabilità. Così le organizzazioni tornano a produrre e investire in Italia. E i vantaggi sono tant
Intellectual Capital Mobilization in the Experimentation Process: Artifacts as Boundary Objects
No full textSocial Opportunities and Business Model Design: Evidence From Three Social Enterprises
No full textThe 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
No full textAn 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
Experimental approaches to entrepreneurship and the scientific method: A critical review and comparison
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Filtering and enabling meaning perception: a business model perspective
No full textThis study aims at expanding the innovation of meaning framework by investigating how a new meaning strategy can be adapted to different contexts, building on a case study based on the comparison between two service companies. The analysis takes into account both the companies' strategy, assessed through interviews with the founder and secondary sources analysis, and the customers' side, combining an ethnographic research with a topic modelling of customer reviews. Findings suggest that companies can convey their overarching meaning strategy in different ways by shaping the way value is delivered to the final users. This study enriches both the innovation of meaning discourse and the literature on the business model by highlighting how to convey an adapted meaning to different contexts. This article provides actionable knowledge to practitioners by suggesting how to contextually adapt a company's meaning strategy to different environments through the intervention on specific business model elements
The evolution of meanings: an empirical analysis of the social media industry
Full text linkPurpose – 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
What happens after market validation? Experimentation for scaling in technology-based startups
Full text linkScaling is one of the most critical phases in the lifecycle of technology-based startups: failure to scale often translates into failure to survive. Entrepreneurial experimentation has emerged as a method to reduce the likelihood of startup failure by anticipating market information. However, previous studies only described experimentation as the means to achieve market validation during the early stages of a startup's lifecycle. In our study, we have inductively investigated experimentation in technology-based startups after they had achieved market validation, conducting a comparative multiple-case study on four technology-based startups operating as digital platforms for financial and marketing services. Our findings conclude that technology-based startups continue to experiment extensively as they scale up. We present a process model of how experimentation for scaling focuses on probing for new customer segments, experimenting on customer relationships and channels, whilst carefully pacing and prioritizing experiments, and selecting the relevant growth metrics to monitor. Our study thus extends the current understanding of entrepreneurial experimentation beyond the accomplishment of market validation to the phase of scaling. This article also provides practical guidelines for technology entrepreneurs to direct their efforts towards experimentation during the challenging scaling phase
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