In 2012 in Italy it was introduced the Decreto Crescita 2.0 (Growth Decree 2.0), a policy measure in support of the emerging Italian startup ecosystem. The aim of the Decree consists in sustaining the new entrepreneurial ecosystem and promoting technological advancement and innovation, highly achievable by new ventures. Nowadays, Italy counts of 9,525 startups . The startups community has registered an increasing trend since the introduction of the Decree and it is expected to furtherly grow in next years. The aim of this thesis is to investigate which are the most recurrent business models adopted by the Italian startup ecosystem, focusing on enterprises presenting digital and technological innovation. Thus, it is examined which architectures and values are mostly pursued by entrepreneurs who launch a new venture. In the past, as reported in the literature review of this thesis, many renowned scholars have proposed their own business model categorizations, both for established firms (such as Osterwalder and Morris et al.) and, more rarely, for startups (such as Croll & Yoskovitz). The novelty of this research lies on its focus on Italian digital startups, thus business ventures with limited initial capital compared to incumbents, and born in a Country which is still far behind other foreign ecosystems in terms of number of startups, investments and innovation. The research is conducted throughout the examination of data released by the Chamber of Commerce, which includes 8,897 innovative startups of the Business Register . Since the focus of the analysis is on startups presenting digital content, the list of startups is skimmed by considering only enterprises that have been incubated or financed by some incubators, accelerators and venture capitalists of our Country. In this manner, I have obtained a sample of 175 innovative digital startups, which I have furtherly analysed to investigate additional variables, fundamental for the creation of business model categories. In particular, the variables considered to find the main startups’ trends and define the categories are: - the type of product - the type of customer connection - the role and the importance of technology. This analytical research is additionally integrated by interviews to proponents of two incubators based in Milan, PoliHub and Innovits. The interviews have actively contributed to obtain further insights about startups key success factors and most recurrent business model categories within incubators’ startup portfolio. Hence, after qualitative and quantitative analysis, four clusters of business model are depicted: - Product innovation, containing startups characterized by a high technological intensity embedded in the final product, which is then commercialized mainly to business customers; - Client service, containing startups focusing on the delivery of a service to business customers. Services vary from software, cloud platform and consulting activities; - Sale of product, containing startups which sell products and services to the final consumers, using principally the online channel; - Multi-sided platform, containing startups which connect two or more groups of people through an online platform with the aim of exchanging product and service, thus making monetary transaction, or exchanging content and information, like in a social media site. All the startups of the sample have been assigned to their corresponding category through a methodology able to sort all the enterprises according to the three variables presented above, which present different weight in each cluster. Once outlined the most common business models, each of them is described in terms of major characteristics and strategies adopted. Furthermore, they are analysed and compared in terms of capital raised and turnover generated, which are data already provided by the Chamber of Commerce database. The latter analysis permits to discover which of the business models depicted show greater potential in raising more funds and generating higher turnover and employment. Thus, precisely, the main contribution of the thesis is to propose to potential investors an additional method for startup evaluation, based on the way through which startups develop their value proposition, thus their business model.
Il Decreto Crescita 2.0, una politica a supporto dell’emergente ecosistema di startup italiane, è stato introdotto in Italia nel 2012 con l’obiettivo di sostenere il nuovo quadro imprenditoriale e promuovere lo sviluppo tecnologico ed innovativo del paese. Dall’introduzione del Decreto, il numero di startup in Italia è cresciuto, fino a raggiungere oggi un ecosistema di 9,525 aziende. L’obiettivo della tesi è quello di individuare quali sono i modelli di business più utilizzati dalle startup italiane, circoscrivendo l’analisi alle aziende che sviluppano idee innovative con contenuto tecnologico e digitale. In passato, come viene riportato dall’analisi della letteratura, noti studiosi hanno presentato diverse categorizzazioni di modelli di business, ideate sia per aziende già affermate sul mercato (come proposto dagli studi di Osterwalder e di Morris et al.) sia, più raramente, per sole startup (come proposto da Croll & Yoskocitz). Il contributo di questa tesi consiste nel proporre una categorizzazione in modelli di business delle startup italiane con contenuto tecnologico, che si discosta dalle classificazioni esistenti per il suo focus sulle startup tecnologiche, aziende con un capitale iniziale limitato, che avviano la loro attività in Italia, un paese che registra risultati ancora lontani rispetto ad altri ecosistemi esteri. La ricerca è stata svolta esaminando un database rilasciato dalla Camera di Commercio contenente dati di 8,897 startup innovative registrate al Registro Imprese. Siccome l’analisi si concentra su startup digitali, è stato considerato un campione di 175 aziende ottenuto selezionando solo startup iscritte ad un programma di incubazione, accelerazione o Venture Capital. Le startup del campione sono state quindi analizzate sulla base di ulteriori indicatori, fondamentali per la creazione delle categorie di modelli di business. In particolare, le variabili considerate per definire i modelli sono: - La tipologia di prodotto; - La tipologia di connessione con il cliente; - Il ruolo e il livello della tecnologia. La ricerca analitica è stata integrata con dati qualitativi ottenuti tramite interviste a esponenti di due incubatori di Milano, PoliHub e Innovits. Le interviste hanno contribuito ad ottenere informazioni riguardo i fattori critici di successo e i business model più ricorrenti tra le startup appartenenti al portfolio degli incubatori. Dopo analisi qualitative e quantitative, sono state delineate quattro classi di modelli di business: - Prodotto innovativo: contenente startup che sviluppano prodotti ad alto contenuto tecnologico e distribuiti principalmente a clienti business; - Servizio al cliente: contenente startup che si focalizzano principalmente sullo sviluppo di un servizio, come un software, una piattaforma cloud o attività di consulenza, da distribuire principalmente a clienti business; - Vendita di prodotto: contenente startup che vendono prodotti o servizi a consumatori finali, utilizzando piattaforme online; - Piattaforme multi-sided: contenente startup che svolgono un ruolo da intermediario tra due o più gruppi di persone che si scambiano prodotti, servizi o informazioni attraverso una piattaforma online gestita dalla stessa startup. Tutte le startup del campione sono state assegnate al proprio modello di business attraverso una metodologia in grado di smistare le aziende a seconda dei valori delle tre variabili considerate, che presentano un peso differente per ogni modello di business. In seguito, ogni business model viene descritto considerando ulteriori indicatori, con lo scopo di presentare le caratteristiche e le strategie di mercato adottate da ognuno. Infine, i quattro business model sono confrontati in termini di capitale raccolto, ricavi registrati e livello di occupazione generato. Quest’ultima analisi permette di individuare quali modelli hanno registrato performance più elevate e proporre a investitori e imprenditori italiani un metodo per valutare e stimare il potenziale successo di una startup.
Business model classification of Italian hi-tech and digital startups. An empirical research
LONGHITANO, ALESSIA
2017/2018
Abstract
In 2012 in Italy it was introduced the Decreto Crescita 2.0 (Growth Decree 2.0), a policy measure in support of the emerging Italian startup ecosystem. The aim of the Decree consists in sustaining the new entrepreneurial ecosystem and promoting technological advancement and innovation, highly achievable by new ventures. Nowadays, Italy counts of 9,525 startups . The startups community has registered an increasing trend since the introduction of the Decree and it is expected to furtherly grow in next years. The aim of this thesis is to investigate which are the most recurrent business models adopted by the Italian startup ecosystem, focusing on enterprises presenting digital and technological innovation. Thus, it is examined which architectures and values are mostly pursued by entrepreneurs who launch a new venture. In the past, as reported in the literature review of this thesis, many renowned scholars have proposed their own business model categorizations, both for established firms (such as Osterwalder and Morris et al.) and, more rarely, for startups (such as Croll & Yoskovitz). The novelty of this research lies on its focus on Italian digital startups, thus business ventures with limited initial capital compared to incumbents, and born in a Country which is still far behind other foreign ecosystems in terms of number of startups, investments and innovation. The research is conducted throughout the examination of data released by the Chamber of Commerce, which includes 8,897 innovative startups of the Business Register . Since the focus of the analysis is on startups presenting digital content, the list of startups is skimmed by considering only enterprises that have been incubated or financed by some incubators, accelerators and venture capitalists of our Country. In this manner, I have obtained a sample of 175 innovative digital startups, which I have furtherly analysed to investigate additional variables, fundamental for the creation of business model categories. In particular, the variables considered to find the main startups’ trends and define the categories are: - the type of product - the type of customer connection - the role and the importance of technology. This analytical research is additionally integrated by interviews to proponents of two incubators based in Milan, PoliHub and Innovits. The interviews have actively contributed to obtain further insights about startups key success factors and most recurrent business model categories within incubators’ startup portfolio. Hence, after qualitative and quantitative analysis, four clusters of business model are depicted: - Product innovation, containing startups characterized by a high technological intensity embedded in the final product, which is then commercialized mainly to business customers; - Client service, containing startups focusing on the delivery of a service to business customers. Services vary from software, cloud platform and consulting activities; - Sale of product, containing startups which sell products and services to the final consumers, using principally the online channel; - Multi-sided platform, containing startups which connect two or more groups of people through an online platform with the aim of exchanging product and service, thus making monetary transaction, or exchanging content and information, like in a social media site. All the startups of the sample have been assigned to their corresponding category through a methodology able to sort all the enterprises according to the three variables presented above, which present different weight in each cluster. Once outlined the most common business models, each of them is described in terms of major characteristics and strategies adopted. Furthermore, they are analysed and compared in terms of capital raised and turnover generated, which are data already provided by the Chamber of Commerce database. The latter analysis permits to discover which of the business models depicted show greater potential in raising more funds and generating higher turnover and employment. Thus, precisely, the main contribution of the thesis is to propose to potential investors an additional method for startup evaluation, based on the way through which startups develop their value proposition, thus their business model.| File | Dimensione | Formato | |
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https://hdl.handle.net/10589/142453