Comparison between EMA and transmissibility-based OMA.
\r\n\tSolar radiation is the radiant energy that originated from the sun in the form of electromagnetic radiation at various wavelengths. Solar radiation is the source of renewable energy and can be captured and converted into various forms of energy (e.g. electricity and heat) using different technologies.
\r\n\tA very vast amount of solar energy reaches the atmosphere and surface of the earth and solar energy has been used for heating purposes for a very long-time and after solar cells’ invention in 1954, solar cells have also been used widely for electricity generation. Solar cells convert the sunlight into electricity by the creation of voltage and electric current through the so-called photovoltaic effect.
\r\n\tPhotovoltaic (PV) solar energy has attracted significant attention in the recent decade as a reliable source for power generation due to various merits such as the free source of energy, abundant materials resources, environmentally friendly and noise-free, longtime service life, requiring low maintenance, technological advancements, market potential, and very importantly, low cost. The growth of using photovoltaic (PV) solar energy as a promising renewable energy technology, is being increased more and more worldwide. Therefore, much further research is needed for possible future developments in the field of solar photovoltaic energy.
\r\n\tThe aim of this book is to provide detailed information about solar radiation as the source of photovoltaic (PV) solar energy for a broad range of readership including undergraduate and postgraduate students, young or experienced researchers and engineers.
\r\n\tThis should be accomplished by addressing the various technical and practical aspects of solar radiation fundamentals, modeling and the measurement for photovoltaic (PV) solar energy applications.
\r\n\tThe majority of this book should describe the basic, modern, and contemporary knowledge and technology of extraterrestrial and terrestrial solar irradiance for photovoltaic (PV) solar energy.
\r\n\tThe book covers the most recent developments, innovation and applications concerning the following topics:
\r\n\t• Fundamental of solar radiation and photovoltaic solar energy
\r\n\t• Solar radiation and photovoltaic solar energy potential
\r\n\t• Solar irradiance measurement: techniques, instrumentation and uncertainty analysis
\r\n\t• Solar radiation modeling for photovoltaic solar energy applications
\r\n\t• Solar monitoring and data quality assessment
\r\n\t• Solar resource assessment and photovoltaic system performance
\r\n\t• Solar energy and photovoltaic power forecasting
\r\n\tThese are accompanied with other useful research topics and material.
",isbn:"978-1-83968-859-1",printIsbn:"978-1-83968-858-4",pdfIsbn:"978-1-83968-860-7",doi:null,price:0,priceEur:0,priceUsd:0,slug:null,numberOfPages:0,isOpenForSubmission:!1,hash:"4c3d1319d7286e81bfb15c1f4b20460a",bookSignature:"Dr. Mohammadreza Aghaei",publishedDate:null,coverURL:"https://cdn.intechopen.com/books/images_new/9862.jpg",keywords:"Solar Radiation Modeling, Solar Data Assessment, Solar Monitoring, Solar Radiation Forecasting, Solar Irradiance Measurements, Solar Instruments, Solar Spectral Distributions, Uncertainty Analysis, Solar Cell Technologies, Photovoltaics (PV), Solar Resource Assessment, Photovoltaics Power Forecasting",numberOfDownloads:null,numberOfWosCitations:0,numberOfCrossrefCitations:null,numberOfDimensionsCitations:null,numberOfTotalCitations:null,isAvailableForWebshopOrdering:!0,dateEndFirstStepPublish:"September 17th 2020",dateEndSecondStepPublish:"October 15th 2020",dateEndThirdStepPublish:"December 14th 2020",dateEndFourthStepPublish:"March 4th 2021",dateEndFifthStepPublish:"May 3rd 2021",remainingDaysToSecondStep:"5 months",secondStepPassed:!0,currentStepOfPublishingProcess:5,editedByType:null,kuFlag:!1,biosketch:"A senior researcher in the field of photovoltaic solar energy, a postdoctoral scientist at Eindhoven University of Technology (TU/e), Chair of the WG2: reliability and durability of PV in EU COST PEARL PV.",coeditorOneBiosketch:null,coeditorTwoBiosketch:null,coeditorThreeBiosketch:null,coeditorFourBiosketch:null,coeditorFiveBiosketch:null,editors:[{id:"317230",title:"Dr.",name:"Mohammadreza",middleName:null,surname:"Aghaei",slug:"mohammadreza-aghaei",fullName:"Mohammadreza Aghaei",profilePictureURL:"https://mts.intechopen.com/storage/users/317230/images/system/317230.jpg",biography:"Mohammadreza Aghaei is a senior researcher in the field of photovoltaic solar energy, Eindhoven University of Technology (TU/e), The Netherlands. He is chair of the Working Group 2: reliability and durability of PV in European Cooperation in Science and Technology, COST Action PEARL PV.\nHe received the M.S. degree in electrical engineering from the Universiti Tenaga Nasional (UNITEN), Selangor, Malaysia, in 2013, and the Ph.D. degree in electrical engineering from the Politecnico di Milano, Milan, Italy, in 2016.\nHe was a Postdoctoral Scientist with Fraunhofer ISE and Helmholtz-Zentrum Berlin (HZB)-PVcomB, Germany, in 2017 and 2018, respectively. He is a Guest Scientist with the Department of Microsystems Engineering (IMTEK), Solar Energy Engineering, University of Freiburg since 2017. He is currently a Postdoctoral Scientist with the Design of Sustainable Energy Systems Group, Eindhoven University of Technology (TU/e), The Netherlands. He has authored numerous publications in international refereed journals, book chapters, and conference proceedings. The main his research interests include Solar Energy, Photovoltaic systems, PV monitoring, LSC PV, solar cells, machine learning, and UAVs.\nDr. Aghaei is a member of the International Energy Agency, PVPS program-Task 13 and International Solar Energy Society, and also an MC member in EU COST Action PEARL PV.",institutionString:"Eindhoven University of Technology",position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"0",totalChapterViews:"0",totalEditedBooks:"0",institution:{name:"Eindhoven University of Technology",institutionURL:null,country:{name:"Netherlands"}}}],coeditorOne:null,coeditorTwo:null,coeditorThree:null,coeditorFour:null,coeditorFive:null,topics:[{id:"10",title:"Earth and Planetary Sciences",slug:"earth-and-planetary-sciences"}],chapters:null,productType:{id:"1",title:"Edited Volume",chapterContentType:"chapter",authoredCaption:"Edited by"},personalPublishingAssistant:{id:"247865",firstName:"Jasna",lastName:"Bozic",middleName:null,title:"Ms.",imageUrl:"https://mts.intechopen.com/storage/users/247865/images/7225_n.jpg",email:"jasna.b@intechopen.com",biography:"As an Author Service Manager, my responsibilities include monitoring and facilitating all publishing activities for authors and editors. 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Venkateswarlu",coverURL:"https://cdn.intechopen.com/books/images_new/371.jpg",editedByType:"Edited by",editors:[{id:"58592",title:"Dr.",name:"Arun",surname:"Shanker",slug:"arun-shanker",fullName:"Arun Shanker"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"878",title:"Phytochemicals",subtitle:"A Global Perspective of Their Role in Nutrition and Health",isOpenForSubmission:!1,hash:"ec77671f63975ef2d16192897deb6835",slug:"phytochemicals-a-global-perspective-of-their-role-in-nutrition-and-health",bookSignature:"Venketeshwer Rao",coverURL:"https://cdn.intechopen.com/books/images_new/878.jpg",editedByType:"Edited by",editors:[{id:"82663",title:"Dr.",name:"Venketeshwer",surname:"Rao",slug:"venketeshwer-rao",fullName:"Venketeshwer Rao"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"4816",title:"Face Recognition",subtitle:null,isOpenForSubmission:!1,hash:"146063b5359146b7718ea86bad47c8eb",slug:"face_recognition",bookSignature:"Kresimir Delac and Mislav Grgic",coverURL:"https://cdn.intechopen.com/books/images_new/4816.jpg",editedByType:"Edited by",editors:[{id:"528",title:"Dr.",name:"Kresimir",surname:"Delac",slug:"kresimir-delac",fullName:"Kresimir Delac"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}}]},chapter:{item:{type:"chapter",id:"67609",title:"Introductory Chapter: Some Insights into Bridge Structural Condition Monitoring",doi:"10.5772/intechopen.85742",slug:"introductory-chapter-some-insights-into-bridge-structural-condition-monitoring",body:'\nBridge structural condition monitoring has become a hot spot in both research and engineering fields. Bridges, serving as a connection between cliffs, shallow rivers, or special environmental conditions, have a lot of forms in functionality, economy, and art consideration. For instance, concrete bridge, steel bridges, cable stayed bridge, suspension bridges shown in Figure 1, and so on have been served in various cities [1]. The initial use of bridge is for functionality like footbridge [2], and then other considerations are included. As shown in Figure 1, both the suspension bridge and cable-stayed bridge are extending for long span and large area application in civil engineering.
\nDiagram for (a) suspension bridge; (b) cable-stayed bridge.
Since the bridges provide the convenient transportation for passengers and vehicles, the in-service safety shall be the most essential issue in the lifecycle service of bridges, providing timely early stage warning and suggestion for the possible maintenance [3, 4, 5, 6, 7]. For instance, fiber optic sensors are applied for full-scale destructive bridge condition monitoring [3]. A comprehensive discussion on bridge instrumentation and monitoring for structural diagnosis is conducted in [4], expressing the general steps for bridge management system for condition monitoring including experimental tests, nondestructive tests, performance evaluation, and so on; in [5], the temperature effect is studied between the temperature and the frequency ratio for model plate-girder bridges under uncertain temperature conditions; and also the modal strain energy is extended to predict the location and severity of the damages; in [6], the acoustic emission is applied for monitoring the prestressed concrete bridges health condition after constructing a reference-signals database; in [7], Poisson process is applied to simulate the arrival of vehicles traversing a bridge, and a stochastic model of traffic excitation on bridges is constructed to be incorporated in a Bayesian framework, to assess the properties and update the uncertainty for condition evaluation of the bridge superstructure.
\nSensing techniques include a lot of conventional technologies and advanced technologies developed in recent decades. The conventional technologies include impact echo testing, dye penetration, strain gage, electrical magnetic testing, piezoelectric gages, acoustic emission, leakage testing, magnetic testing, ultrasonic testing, radiographic testing, eddy current testing, infrared thermography testing, microwave testing, and so on. Advanced technologies include phased array ultrasonic testing, eddy current array testing, microelectromechanical sensors, air-coupled sensors, vision sensors with cameras, radar sensors, and so on. In [8], the condition monitoring system for Tsing Ma Bridge is thoroughly introduced: the wind and structural health monitoring (WASHMS) in the Tsing Ma Bridge used about 300 sensors: anemometers, temperature sensors, accelerometers, strain gauges, displacement transducers, weigh-in-motion sensors, and so on. The Global Positioning System-On-Structure Instrumentation System (GPS-OSIS) was installed to improve the bridge displacement response monitoring. In [9], the Global Navigation Satellite System (GNSS): BeiDou Navigation Satellite System (BDS) and Global Positioning System (GPS) are applied to monitoring the bridge displacement responses. In [10], image processing is applied to construct a vision-based monitoring system for cable tension estimation under various weather conditions in the cable-stayed bridge, proving that the natural frequencies can be obtained up to the third and fifth modes. In [11], the radar sensor techniques were employed to predict the changes in the natural frequencies of bridge girders with certain characteristics that control the structural performance with being incorporated with computational modeling. In [12], commercially available remote sensors for Highway Bridge condition evaluation such as ground penetrating radar (GPR), optical interferometry, digital image processing (DIC), and so on are summarized.
\nDamage identification, part of structural health monitoring (SHM), has appealed lots of attention since the occurrence of defect/damage demands repairing and maintenance, simultaneously leading to economic loss. Damage identification techniques can be summarized into two categories: model based and data based, and this has been discussed in [1].
\nModal testing serves as the fundamental and most essential technique in SHM, and along with the development of technology, modal testing underwent experimental modal analysis (EMA) and operational modal analysis (OMA). The key difference between them is EMA needs, while OMA does not demand the measurement of excitation. During the last decades, new measurement techniques also arise in engineering application. For instance, ultrasonic testing, eddy current, magnetic particle testing, acoustic emission, and so on are all imposed in SHM.
\nComparing with the model-based techniques, data based, especially the output only based damage identification suggests a wide applicable potential since its merit relying on structural responses solely. Transmissibility is a typical output only based technique [13], which has been developed in the past decades for system identification, damage detection, localization, quantification, and assessment [14]. Review can refer to [14]. Even a lot of investigations about transmissibility can be accessed to [15, 16, 17, 18, 19], for instance, transmissibility coherence (TC) is raised [14, 17]; cosine-based indicator is constructed from the modal assurance criterion (MAC) and incorporated with transmissibility for damage detection and quantification relatively [15]; Mahalanobis distance is also applied to transmissibility for damage detection [16]; transmissibility is extended to apply in the responses analysis of ultrasonic testing [19]; the transmissibility still encounters difficulty in both theory development and engineering application. This study tries to extend the transmissibility theory for estimating and reconstructing mode shape from structural responses solely. Remaining work can be summarized as follows: Section 2 gives the theoretical development of transmissibility mode shape (TMS) and comparison between transmissibility-based OMA and frequency response functions (FRFs) based EMA, Section 3 gives the possible damage indicators, and Section 4 gives the numerical case study; conclusions are finally summarized.
\nTransmissibility has several kinds of definitions with existing reviews [14], while the fundamental concept is the ratio between two structural responses, which can be expressed as
\nwhere i, s mean the response locations, while Xi and Xj represent the frequency spectrum of dynamic response xi and xs in time domain.
\nTransmissibility can be assessed with several ways, for instance, to use FRFs if available,
\nwhere r denotes the excitation location (assuming single load). H represents the FRFs.
\nSimilar to the application of coherence in FRFs analysis, TC is also raised and defined as
\nwhere G means the auto- and cross spectrum. TC is initially developed for damage/small nonlinearity detection and quantification, and later it is advanced for natural frequency extraction.
\nFor a single load linear elastic structural system, the FRF can also be expressed as
\nwhere p denotes the pth mode, n means the number of modes considered. kp, mp, and cp mean modal stiffness, mass, and damping, respectively, ϕ means the mode shape, and ω represents the frequency.
\nThen, the transmissibility illustrated above can be further expressed as
\nNote, this relation shall be better if obtained by using Laplace transform. As to Eq. (5), if fixing s, transmissibility will allow assessing the mode shape, or scalar mode shape. For each mode, transmissibility will express the scalar mode shape at each location, if further obtaining the direction of the scalar mode shape in each measurement location, and then the transmissibility-based mode shape TMS (full-unscaled mode shape ϕ1s, ϕ 2s, ϕ 3s, …, ϕNs, N is the number of measured responses) will be obtained. A general definition can be denoted as
\nwhere B denotes the frequency boundary [B1, B2] around the natural frequency, and f indicates the frequency domain. TMSp means pth TMS. All the TMSs will later contribute for further OMA [14].
\nTable 1 illustrates the comparison between EMA and transmissibility-based OMA, and it can be found that transmissibility has been developed by analog of FRF, where transmissibility can also perform the same function as FRF, like in damage detection, system identification, and so on. Note that transmissibility has not been thoroughly investigated; and further study is still needed to unveil new features.
\nModal analysis | \nEMA | \nTransmissibility-based OMA | \n
---|---|---|
Kernel | \nFRF | \nTransmissibility | \n
Coherence | \nFRF coherence | \nTC [17] | \n
Modal parameters | \nMode shape | \nTMS | \n
Frequency extraction techniques like SSI | \nFrequency extraction techniques like TC based [14] | \n
Comparison between EMA and transmissibility-based OMA.
Since transmissibility can assess TMS and natural frequencies, then, the extended parameters based on modal parameters can later similarly be applied in transmissibility-based OMA.
\nDamage identification includes several stages: detection, locating, quantification, and remaining life assessment. All damage identifications follow the same procedure, (1) operational evaluation; (2) data acquisition, fusion, and cleansing; (3) feature extraction and information condensation; and (4) statistical mode development for feature discrimination [20]. The most essential step is feature extraction. Generally, feature means the property associated with the structural internal change. For instance, the cross section reduction will result in stiffness reduction, which later changes the structural dynamic responses. Then, features can be constructed from structural dynamic responses to assess the stiffness reduction (kind of damage).
\nCertainly, damage has more kinds, like spalling in concrete structures, corrosion induced defects, and so on. These kinds of defects at initial stage may not cause a clear change in stiffness reduction; thus, special techniques like acoustic emission should be adopted in further investigation.
\nFor the damage illustrated in this study-stiffness reduction related damage, vibration-based techniques are taken into consideration. To construct damage indicator, the change of feature is the commonest, and one may use MAC for achieving a comparable indicator without needing normalization, which can be denoted as
\nwhere (TMS)u and (TMS)d denote the value under undamaged and damaged states, respectively.
\nOf course, herein, more indicators can be constructed, since TMS and natural frequencies are assessed by transmissibility in OMA, curvature, higher order derivative, and so on, and all these modal parameters based indicators can further be applied in damage detection [23].
\nIn order to illustrate the feasibility of the proposed methodology, a pined-pined beam is numerically analyzed. Young’s modulus is 185.2 GPa, dimension is 0.005 × 0.006 × 1.000 m, density is 7800 Kg/m3, and a vertical impulse is excited in the node 7 with 10 elements discretized on average in the whole beam. Dynamic responses are considered in the further OMA. The schematic diagram in Figure 2 shows the beam. Different damage levels are simulated with reducing the stiffness in element 3, and for damage level D1, D2, D3, and D4, the stiffness reduced from 5, 10, 15, to 20% accordingly.
\nSchematic diagram of the pined-pined beam.
Results for the aforementioned methodology is computed and discussed in this section. Figure 3 illustrates the mode shapes for first four modes, while Figure 4 demonstrates the TMSs for first four modes, where one can find that both mode shapes and TMSs share the similar shapes, and their well agreement implies the potential use of TMS in damage identification.
\nMode shapes of the beam for first four modes.
TMSs of the beam for first four modes.
Figure 5 gives the structural detection results from the constructed damage indicator DI. From this figure, it can be found that all damage levels are detected. It should also be noted that the change of DI for all the four modes are not very much, this suggests that TMSs vary small before and after the occurrence of damage, and further enhancement should be conducted in order to achieve a better damage detection performance.
\nDI for first four modes.
This study tries to discuss some insights for bridge condition monitoring, also extends the mode shape into transmissibility-based OMA, and by using transmissibility, TMS is assessed by analog of mode shape in EMA, which paves the way for further investigation of extending the mode shape-based indicators to TMS-based analysis [21, 22]. MAC is used to construct a damage indicator with being verified by a pined-pined beam. The damage detection performance implies further necessary investigation for obtaining a better and deeper understanding.
\nSince 1980s, in many western countries, the focus of industrial choices has changed substantially as consequence of the transition from SMEs policies to entrepreneurship policies. More recently, to react to the deep economic and financial crisis of 2008 and to sustain the diffusion of ICT, industrial policy measures have been fundamentally finalized at providing instruments increasing starting-up and the emergence of the self-employment in general, by spreading entrepreneurial culture and stimulating the direct participation of citizens in entrepreneurial process.
\nNew ventures have been believed as a pathway for increase employment, especially for youth suffering from a disproportionate lack of job opportunities [1, 2, 3], while the startups, considered as innovation-based new ventures, have been spurred by the ambition of accelerating the adoption and diffusion of border line technologies, in doing so counteracting the competition of Eastern countries benefiting of lower production costs [4, 5].
\nThese purposes have been sustained by measures improving the business environments, trying to make them economically conducive for firm emergence. Among these new measures, there are R&D grants and tax benefits, business accelerators and incubators, incentives and facilities for university-based spin-offs, financing of risk initiatives, and so on.
\nNevertheless, this strategy has often led to unsatisfactory results, notably as regard to the contribution to territorial economic growth, innovations spreading, and dissemination of skills and competencies. Even in local contexts where high ventures birth rates were registered, there have been no relevant increases of key economic indicators, such as gross income, firms’ survival, or profit level (e.g., [6, 7, 8]). A managerial and business research stream [9, 10, 11] argues that the weak impact of the mentioned measures on local economy development could be linked to three main aspects.
\nFirstly, a nebula idea of the entrepreneurship concept exists. A wide range of economic activities is used to be included in this term, even if the scientific literature has been clarifying its real meaning since many decades [12, 13], as detailed later.
\nSecondly, usually new firms are considered in a similar manner and often equated at startups. But not all new firms necessarily are startup, as well as startups are dissimilar in terms of value generation or job creation [14, 15]. A basilar matter is that too few startups are able to become high growth firms, which are able to assure a tangible contribution to the territorial context in terms of employment, income, investment, knowledge, and competencies [16, 17]. Indeed, startups are unsteady activities, with high probability of failure or destined to remain small business, when not simple micro-firms or self-employment activities. In the last circumstances, the contribution to regional growth is rather limited, if it exists [18, 19].
\nThirdly, an excessive emphasis on technological innovation exists. Technological innovation in itself is not a panacea as it is risky and normally takes a long time to deploy its effects and to be fully appreciated. These peculiarities contrast with the typical weaknesses of new ventures, when they are not able to evolve in more established societal or legal forms [20, 21, 22]. The overwhelming focus on technologies innovation might acquire an ambiguous meaning when related to startups [23]. Firms operating into the so-called traditional sectors (automotive, domestic appliances, furnishings, etc.) of Western countries often exhibit higher growth rates than firms placed at the technological border. The capacity to propose, over the time, more and more effective business models could, therefore, overcome the prominence of technological factor [24]. Hence, all high growth firms are neither necessarily high-tech startups nor a new business in general.
\nWith this in mind, the incoming of digital technologies in the realm of entrepreneurship represents a new challenge for entrepreneurs and policy makers [25]. When applied to manufacturing, digital technologies (such as social media, mobile computing, data analytics, 3d printing, cloud, and cyber solutions) lead to a remodeling of productive patterns originating new market opportunities, higher revenue streams, faster time-to-market, enhanced service provision, and increased productivity [25, 26]. Moreover, digital technologies also deeply modify the boundaries of products and processes, in doing so transforming the nature of uncertainty inherent entrepreneurial processes and outcomes, as well as the ways of dealing with such uncertainty [27]. All these changings are shifting the traditional way of creating and doing business, determining the emergence of a new specific type of entrepreneurship, the digital entrepreneurship (Nambisan, 2017).
\nBroadly defined as creating new ventures and transforming existing businesses by developing novel digital technologies and/or novel usage of such technologies [27], digital entrepreneurship needs to be properly fueled and enabled in many directions. Among these, European Commission [25] suggests the creation of specific digital knowledge base and ICT markets, the creation of digital business environments, an easier access to finance facilitations, the diffusion of digital skills, the creation of e-leadership, and the creation of entrepreneurial culture. These complex aims assume a heuristic and wide-ranging approach that, presumably, requests a reconsideration of the logic that leads to the emergence and development of startups operating in the digital setting.
\nThis chapter aims primarily to discuss how the current focus on startups could be addressed, so that the digital era becomes a source of opportunities more than risks. Specifically, the paper is consistent with an up-warding audience of scholars [28, 29, 30, 31] according to the best answer for collecting the business opportunities and channeling the benefits for local areas appears the creation of ecosystems able to support scale ups; that is, startups with high potentiality to grow-up [32].
\nThe debate on the importance of these companies for local development and growth is really dated. The novelty is that, instead of an undifferentiated starting-up, a selective approach centered on startups with the better potentialities is now explored by creating specific business environments aligned to the purpose of systematizing, promoting, and sustaining their growth [3, 33, 34].
\nThe chapter is organized as follows. After this introduction, Section 2 specifies the concept of entrepreneurship oriented for the purpose of the regional economic development. Afterward, the notions of startup and scale ups are clarified in Section 3. Section 4 deepens the dynamic meaning of an entrepreneurial ecosystem functional to scale ups development. Section 5 identifies the link existing among the challenges linked to digital technologies and the advantages provided by ecosystems. Some conclusive remarks are showed in the last section.
\nAn aspect systematically ignored by policies concerns the concept of entrepreneurship, often considered as an undifferentiated phenomenon whose only evaluable output is the birth of new ventures. This is because, on one side, a shared definition of entrepreneurship is missing, as well as a precise knowledge of its boundaries and factors from which it originates. On the other side, it descends from the fact that, by logic, this concept can only derive from that of entrepreneur [13]. In turn, the figure of entrepreneur is ambiguous, confused with other economic roles such as the owner or the capitalist, not always easy to identify inside the firm, and whose assignments and tasks are not easily framed. Not by chance, the Huffalump metaphor, the imaginary animal impossible to capture [35], was introduced.
\nHowever, more recently, entrepreneurship literature has shed much light on these aspects. But these advances do not seem fully absorbed in determining policy measures. So that, even if a propulsive thrust of economy is expected from the entrance in the digital economy ([27], Nambisan, 2017), there is a real possibility that not all contexts will be able to benefit from the emerging opportunities.
\nIn this view, this chapter emphasizes the thesis for which standardized policy actions addressed to support an undifferentiated starting-up risk to obtain limited, when not counterproductive effects. Investigations on firms’ turnover have showed that an increasing birth rate is often accompanied by an almost similar increase of death rate. This faster turnover has not a positive impact on the social and economic context if the surviving ventures remain micro or individual firms [1, 2, 36]. In other words, just favoring a high entrepreneurial activity—the percentage of adults involved in the process of the creation or management of an enterprise—does not necessarily ensure the emergence of a sufficient share of companies that are able to succeed in the medium or long term with a positive impact on local context.
\nThis assumption is coherent with the supposed U-shaped relationship between the entrepreneurial activity of a country and its per-capita Gross National Product (GNP). Leading scholars belonging to the Global Entrepreneurship Monitoring [4, 37] explain that the entrepreneurship activity is higher for countries with either a low or a high GNP per capita.
\nIn countries with low GNP per capita, entrepreneurship activity is higher owing to the lack of professional alternatives and other revenue sources—‘necessity’ driven entrepreneurship rather than ‘opportunity’ [38]. When GNP per capita grows, countries with middle-income, activity gradually decrease up to a certain minimum point. That is because the emergence of scale-intensive firms operating in mid-technology sectors offers stable employment perspectives, which reduce the motivation toward starting up. After this point, activity newly increases. In areas with a higher GNP per capita, the presence of advanced technology and scale economies allows larger and established companies to meet the growing demand of expanding markets, exerting a positive attraction to would-be entrepreneurs. In these circumstances, high startups rates are predictable. They could begin an economic virtuous circle.
\nThis theory, therefore, supports the existence of an equilibrium rate of entrepreneurial activity, which varies consistently in line with the degree of national development. This rate is considered “an ‘optimal’ industry structure, operationalized either in terms of the number of business owners or in terms of the small-firm share in value-of shipments” ([1], p. 3). Deviations from the equilibrium rate caused by cultural forces, institutional changes, and economic trends risk to cause negative consequences for national growth, since “economies can have both too few and too many businesses and both situations can imply a growth penalty” ([36], p. 285). A too low equilibrium rate may imply few stimuli toward innovation and change. A too high rate could determinate the failure to exploit scale and scope economies, a reduction in R&D expenditure, or an excess of price-based competition, forcing firms to reduce output/input quality or resorting to shadow economy. Consequently, regions deviating from the level of entrepreneurial activity compatible with their GNP, risk to obtain lower rates of overall economic growth.
\nThe optimal equilibrium rate is dependent on both the weight of sectors, —dynamism in services business is statistically much greater than in manufacturing industry—and the type of entrepreneurship created. Hence, generic starting up policies could not be a panacea for local economic and social troubles, neither present nor future. This statement is supported by many evidences.
\nOne of the most quoted scholar of entrepreneurship states that new firms do not always have an innovation propensity higher than incumbent firms, “even for a developed country such as the United States, only a very small fraction of new startups is really innovative” ([39], p. 8). Without innovative capacity, in a contestable market, these firms have limited chance to growth.
\nLikewise, usually the large majority of incumbents firms are destined to remain a small firm or even a self-employment venture. This possibility is more likely when the entrepreneurs’ teams that manage such firms do not possess an adequate level of entrepreneurship, but only business entrepreneurialism, that is, a generic spirit or state of acting in an entrepreneurial manner in the broader sense [38]. A pioneer in the field of entrepreneurship research and education [40] explains that there is a “continuum” along which each entrepreneur or aspiring entrepreneur has a different increasing subjective level of entrepreneurial capabilities. In addition, the more the business is small, the more the relationship among entrepreneur’s potentialities and firm’s performance tends to be stronger.
\nGenerally, policies do not care or are not able to select aspiring entrepreneurs with the better potentialities. Hence, it is surprising to discover neither high failure rates nor large share of micro-firms from policies directed to favor undifferentiated startups. While firms which are unable to grow and develop rarely can disseminate knowledge or innovations, high failure rates are associated with a possible dispersion of public funds and sunk costs.
\nThese contingencies introduce the specific problem regarding the quality of the arising entrepreneurship: “business ownership and entrepreneurship are not synonymous … entrepreneurs are a small fraction of the business owners” ([36], p. 275). It is worth to underline that a seminal article on the nature and quality of entrepreneurship goes back to Carland et al. [12].
\nAuthors distinguish entrepreneurs with the highest level of entrepreneurship and capabilities, identified as true entrepreneurs in the Schumpeterian sense, from other typologies of entrepreneurs with a lower level of entrepreneurship. Among the latter, there is the small business owner (“an individual who establishes for the principal purpose of furthering personal goals … the owner perceives the business as an extension of his/her personality, intricately bound with family needs and desire”) ([12], p. 358) and the self-employer, a personal response to the lack of professional alternatives, implying a low entrepreneurial level [38]. Businesses undertaken by small business owners and self-employers who “are not dominant in their field, and don’t engage in any new marketing or innovative practices” ([12], p. 358) usually exhibit a low propensity for expansion, change, and knowledge adoption, while we have a high probability of failure. Often these entrepreneurs “have incomes below the poverty line” (Stam, 2015, p. 123).
\nOn the contrary, a true entrepreneur is an individual who creates an entrepreneurial venture in Schumpeterian sense. That is a venture “characterized by innovative strategic practices … employ strategic management practices in the business” ([12], p. 358). An entrepreneurial venture does not necessarily mean a large firm, but a business able to develop and to reach profitability and success, thereby having a relevant and stable impact on local growth. The ability to found and manage an entrepreneurial venture mirrors entrepreneurs’ subjective predispositions, personal traits, experiences, knowledge and competences, innate or acquired, that shape their capabilities in a business’s management, as well as in lifestyle [41].
\nThe logic of this brief exposition concerns the opportunity, in some circumstances, to abandon policies that aim to support generic entrepreneurial activity by proposing top-down measures, such as granting subsidies or facilitations. The simple improving of the environmental framework risks to favor an undifferentiated creation of new businesses and/or startups, as well as the survival of incumbents no more competitive.
\nAs researchers agree to sustain that the entrepreneurial process is the result of a complex interaction between individuals, cultural, social, and environmental factors, the alternative that is intended to endorse is to concentrate efforts on entrepreneurs/aspiring entrepreneurs who show the best business plans, the preeminent entrepreneurial features, and the ability to withstand market difficulties [3, 28, 34, 42]. These entrepreneurs have the higher probability of founding and managing entrepreneurial ventures.
\nA focus of entrepreneurship policies has been, as explained, increasing the number of startups and spreading the entrepreneurial culture by providing tangible (grants, real services, and facilitations) and intangible tools (training, incubators, consultancies). The corner stone of this policy sinks its roots in the belief that the startups are a powerful tool for spreading innovations and knowledge locally [21].
\nIt is therefore essential to clarify what the startups are. Alike other social and economic phenomena based on individual or collective behaviors, different interpretations of startup exist. Each one offers a viewing angle for reading, analyzing, and evaluating the startup process.
\nThis chapter follows and deepens one of the best known definitions of startup: “a temporary organization searching for a repeatable and scalable business model [32].” Although extremely concise, this definition is very widespread and effective.
\nA startup is an “organization” that is a systematic complex of human, material, and financial resources, tangible and intangible assets, coordinated by someone with a rough business idea for reaching a unitary scope. Often, it is a venture which is trying to become something to evolve in a steady enterprise. There is no certainty about a happy end of this process. This organization is designed to create a new product or service works under conditions of extreme uncertainty; hence, it is “searching.” Statistically, it is more likely that the founders decide to abandon the project or to sell the idea they were working on. Then, a startup can and must evolve into an enterprise, or fail, or dissolve. This is why it is “temporary.” Behind the possibility of becoming a company, however, there must be the perspective of transforming a business idea into a business model. Of course, this contingency does not imply that a startup will become a big company. It can remain a small firm with few employees or even an individual firm.
\nConsistent with the pillar of Schumpeterian theories, the focus of a startup is expected to be on innovation. Innovation understood as a positive change compared to a pre-existing situation, therefore not only technological but also managerial, organizational, productive, or technical, who allows and sustains a company in the proposition of a profitable business model. The latter has to be “repeatable.” It means that the way in which company creates, delivers, and captures value has to be sustainable with recurring profit. Startup also has to be “scalable.” It implies that the company must be able to serve profitably an increasing number of customers. Some business models can be repeatable but not scalable or scalable but not repeatable; but only when they are in the meantime both repeatable and scalable, they can catch the interest of venture capitalists [32]. The role of venture capitalists is essential for the startup dynamic because, often, traditional banks have neither the instruments to finance the starting-up processes nor competencies to judge business model potentialities.
\nAs reminded by Blank [32], a scalable startup created from the very beginning by founders who believe that their proposal could change the world is different from a startup created by people just aspiring to become self-employed or to satisfy family need through a small business which is not designed to scale. In short, scalability is the basilar feature which distinguishes a startup with potentialities from other types of enterprises generically defined newborn ventures. This potentiality to profitably expand their boundaries is a crucial aspect which allows to clarify some doubt about the overall startups policies efficacy for the territorial development.
\nSome researchers [9, 14, 23] are quite skeptical about the advantages of the starting-up in general, describing a blanket policy focus on startups as “bad public policy.” It occurs when startups born, thank to public facilitations and supports, and limit themselves at crowding-out existing companies that have not benefited from support or when they replicate existing business model taking advantage of greater operational and management slenderness by virtue of learning by others mistakes (“copycat”) or if they absorb all the resources allocated for policy measures. Moreover, high startups death rate could determinate relevant sunk costs for society and aspiring entrepreneurs. In these circumstances, “evidence suggests the contribution of entrepreneurial startups to the economy is limited and in some cases can be potentially damaging” ([15], p. 136).
\nMoreover, some types of startups normally offer a lower contribution to local economy development. Among them, there are [32] buyable startups, namely startups born to be bought; large company startups, for answering to changes in customer preferences, new technologies, legislation issues, competitors pressure; or social startups, whose mission is to make the world a better place for a welfare purpose. Hence, to consider startups in a similar and undifferentiated way is a limit of industrial policy.
\nIf entrepreneurship literature is rather skeptical about the effectiveness of startups, it agrees to sustain that the so-called high growth firms (henceforth HGFs) have significant spill-over effects: “small businesses that become middle-sized and ultimately large businesses, over a comparatively short period of time, are central to economic prosperity” ([14], p. 208). That is because HGFs are the preferential channel in the net jobs creation [6] and are beneficial to the development of other enterprises placed in the same context [43], as well as in industrial clusters [44], as they provide meaningful stimulus within economies by increasing competition, promoting innovation, and improving the efficient allocation of resources [23]. Not by chance, HGFs tend to exhibit high levels of productivity, innovation, export-orientation, internationalization, and investments in human capital [29, 43, 45]. Consequently, “the ability of a country to nurture the growth of such businesses is probably the most important element in enterprise development” ([14], p. 208).
\nHGFs are neither exclusively young businesses [18] nor predominantly in high tech sectors [6], and just few are venture capital backed [8]. Moreover, only episodically exhibit a linear growth, while they can expand organically or with external acquisition [23]. In line with these assumptions, a thriving stream of research stresses the necessity to favor the emerging of scale ups [22, 28, 29].
\nA univocal definition of scale up company still does not exist since the metrics, that is, the characteristics that distinguish it from the startup, vary according to the size of the reference context, the type of sector in which they operate, and the business model (usually b2c or b2b) [46]. Consistent with Blank [32], a scale ups can be framed as fast growing startups that have already overcome some phases on which the activity of the startup is focused. In particular, the scale up is a company that has developed its product or service, has defined its business model (scalable and repeatable), and can therefore focus on its growth on the market to take it forward in a controlled and sustainable manner. Hence, terminologically and consistent with the previous startup definition, only startups can become scale ups, while incumbent ventures can become HGFs; often just for a limited period of time [16].
\nA scale up stands out for some parameters attesting its success like market traction, 1–10 million € turnover annually, at least 1 million users (in the b2c), 20% growth in revenues or headcount for 3 years running after at least 10 people and $ 1 million in revenues, and 20% of the turnover from the foreign market [47]. Their highest ambition is to become a “centaurus”—valued more than 100 million dollars—or an “unicorns”—valued over 1 billion dollars.
\nAs other entrepreneurial ventures, the possibility that scale ups come to light is strictly linked to their intrinsic capacity to discover, to exploit, and to successfully manage economic opportunities. The incoming of digital era certainly is a source of uncountable opportunities. A new wave of economic openings linked to the Industry 4.0, where digital platforms will be coupled and connected with sophisticated infrastructures of sensors, cyber-physical systems, and robots, is expected [48]. Furthermore, digital innovations are bringing substantial new challenges on how to handle with technology, management, government policies, stakeholders’ engagement, and so on [49]. Hence, the digital economy represents for ventures both a challenge and a requirement for conformity. It is a challenge, if they wish to set out a developmental pathway; it is a duty, if ventures are forced to adapt their organizational and productive pattern in order to remain competitive.
\nTo look for strategies that are able to increase the presence of scale ups engaged into digital economy should be a primary aim for researchers and policy makers of many western countries. In this perspective, literature (Brown and Mason, 2012) [19, 34] specifies that this possibility is linked to the capacity to create a specific business environment consistent with scale ups needs. Only when effectively planned, this framework provides consistent outcomes. In Italy, for instance, the low number of scale ups created is not believed to depend on the lack of quality startups but mainly on their need to move abroad to find sufficient risk capital investments for tackling scaling, as well as for the shortage of connections with external actors [47].
\nHence, new policy measures are requested, as the environments in which scale ups prosper are distinct from those which have high rates of startups [17, 21] (Brown and Mason, 2013). Scale ups also need to access to specialized resources that differ significantly from those supporting new firms [28, 32] (Brown and Mason, 2012).
\nTo this purpose, the necessity to create a distinctive type of supportive economic and social framework emerges. It should be planned to captivate entrepreneurs with wide economic potential [16, 19, 42]; to establish steady and productive relationships among all the local stakeholders; to provide relational forms of support (such as network building, institutional alignment of priorities, strategic guidance, leadership development, and mentoring) ([20], p. 2016), instead of money-based facilities (from grants to tax incentives or subsidies) that have showed limited impact [10]; to attract different businesses funding resource (such as debt finance, crowd-funding, and peer to peer) targeted to the specific requirements of the businesses [43]; to nurture the developing of the innovation system joining local customers end users, suppliers, universities, and so on [50]; to guarantee the recognition of unprotected and open sources innovations, respect on technological innovations and the protection of intellectual property rights [46]; and to limit its action at regional or local level [33].
\nThe specific environments and the specialized resources scale ups and HGFs need are usually defined ecosystems (Napier and Hansen, 2011) [24].
\nIn the last decade, the entrepreneurship ecosystem approach has emerged as response for the propagation of scale ups and HGFs in general (e.g. [11, 28]). An ecosystem encloses the “set of interconnected entrepreneurial actors (both potential and existing), entrepreneurial organizations (e.g. firms, venture capitalists, business angels, banks), institutions (universities, public sector agencies, financial bodies) and entrepreneurial processes (e.g. the business birth rate, numbers of high growth firms, levels of ‘blockbuster entrepreneurship’, number of serial entrepreneurs, degree of sell-out mentality within firms and levels of entrepreneurial ambition) which formally and informally coalesce to connect, mediate and govern the performance within the local entrepreneurial environment” ([8], p. 5).
\nThere are more models of entrepreneurial ecosystems, but each one is unique, that emerge under an inimitable set of conditions and circumstance and only where it finds fertile soil [31]. However, ecosystems usually share some common crucial features.
\nFirstly, an ecosystem cannot come to light in a vacuum [24] but generally arises where there are place-based assets, such as a previous strategic location of other industrial activities, even if of traditional type, or cluster [8]. This is not a surprising assumption, as researches indicate that firms that are located in “clusters” exhibit higher growth than those in other locations [44], and that in clusters usually have high number of graduates in technical disciplines who support the adoption of innovations [50]. However, the entrepreneurial ecosystem approach offers a distinctive perspective on the clustering of economic activities respect to the original concept of Porter [51].
\nNotably, the core of a thriving ecosystem is the presence of one or more large successful established businesses, preferably knowledge based. Their primary role is to deliberately cultivate the ecosystem itself [31]. Large companies provide outcomes of their R&D, are magnets of skilled workers, provide a market for local subcontractors, and shape specialized personnel who can decide to leave the firm to assume other roles (entrepreneur, mentor, angel investor, etc.) in the same context. These companies also invest in the local territory financing universities, research centers, and social initiatives and attract specialized suppliers that fertilize the context spreading knowledge [8, 11].
\nAbout the cross-fertilization process, it is crucial to underline the so-called entrepreneurial recycling process. It is fostered by entrepreneurs whose successful business idea/startup (blockbusters) was taken over from another firms or who, having already reached entrepreneurial significant goals, decide to remain in the cluster reinvesting their profit, time, wealth, experience, and expertise in supporting new entrepreneurial activities as serial entrepreneurs, venture investors, advisors, or manager of other firms [52]. The spillover effect of these entrepreneurs is particularly significant in the developmental process of the ecosystem, and these businesses in turn are the source of further waves of spinoff activity (Mason, 2009) [29]. Hence, potential entrepreneurs are themselves important players in creating the ecosystem and keeping it healthy [53].
\nAnother key role is played by deal-makers, “individuals with valuable social capital, who have deep fiduciary ties within regional economies and act in the role of mediating relationships, making connections and facilitating new firm formation” ([54], p. 24). They can be entrepreneurs, investors, or service providers who are well-connected, qualified, and experienced who informally or with a fidelity role offer support to young firms and startups, helping them to develop their potential [29]. Deal-makers also support information sharing process. This is consistent with a relevant feature of the ecosystem, that is, an information-rich environment in which knowledge is both accessible and shared according to the principle of open innovation and cooperation for tacit dissemination. For successful entrepreneurship, the presence of dealmakers is more important than the measures supporting local entrepreneurship or investors networks, and it is a valid predictor of the health state of the regional entrepreneurial economy [54].
\nFor the effectiveness of an entrepreneurship ecosystem, a prominent role is also due to the presence of universities and other research centers. The most significant lapel is not as much the research output transfers as the predictable presence of innovative spinoffs and startups that spread knowledge in the ecosystem itself. Evidence shows that ecosystems have typically emerged in places that already have an established and highly regarded knowledge base which employs significant numbers of scientists and engineers. Universities and research and corporate R&D laboratories are a primary source of skilled personnel who can found innovative startups [55]. Anyway, sometimes the substantive disconnection between universities and their surrounding local entrepreneurial and innovation ecosystem belittles entrepreneurial spillovers from universities [50].
\nAnother propulsive role is played by services providers that perform no-core activities which are outsourced. Three types of services facilitating the process of business startup and growth by enabling new firms to focus on their area of expertise can be highlighted: (1) specialist business services (law, marketing, accountability, management, consultants familiar with the unique needs of technology startups, technology marketing and assessment consultants, and PR firms), (2) technical services offering precision machining, prototyping, testing, and so on, (3) finance providers, such as venture capital firms or investment banks.
\nFrom financial perspective, the most important aspect concerns the availability of a critical mass of seeds and connections with local and foreign investors and venture capital funds [10], while the importance attributed to venture capitalists tends to be minor, as most firms are initially funded through a combination of self-financing, loans from family and friends, and bootstrapping. Despite a cluster is likely to stagnate or decline without these actors [44], in ecosystems venture capital seems lags, rather than stimulate, the emergence of entrepreneurial activity (Mason, Brown, 2014). This type of financing is more suitable for high growth technology-based firms [10].
\nAn ecosystem has to be planned and managed. Often traditional decision makers of political origin have not suitable and enough technical and economic competencies to follow the implementation of the ecosystem: “however challenging the encouragement of entrepreneurship may seem, it is truly too important to be left to policy specialists” ([10], p. 264). In this regard, Isenberg [28] argues it would be better to establish new organizations with a ‘sell-by date’ composed of experts with specific entrepreneurial competencies—entrepreneurial enablers.
\nThe tasks of these temporary organizations are to assure a holistic approach that considers especially bottom-up measures, as the major needs for the firms belonging to the entrepreneurial ecosystem do not concern the offering of grant and subsidies. The latter could have self-defeating effects respect on a Darwinist natural and spontaneous selection of the best firms and business models [5, 28]. As explained, ecosystem is chiefly founded on the active input coming from the entrepreneurial community. Hence, the involved firms require relational rather than transactional assistance during the different stages they run across, with the provision of intensive support and mentoring, as well as facilitations for startups through business incubators. The latter provides business advice, networking with mentors, business angels, banks, and service providers. The purpose is to build “bridges” between different actors through the creation of communities of best practices or entrepreneurial networks [8, 21]. Therefore, it is important primarily to establish steady and effective connections among all the involved actors and networking linkages.
\nThese tools answer to the essential presence of startups which aspire to expand and develop. Sometimes, in the early stages of establishing an ecosystem, to stress on supporting the starting up processes helping these ventures with organizational and human capital development, internationalization support and access to growth capital could be necessary. But a mature ecosystem needs to focus its efforts on companies with the greatest potential. Entrepreneurial enablers should possess the ability to understand the right moment to shift the focus of their intervention. In addition, as the creation of an ecosystem occurs by phases which evolve over time, the organization’s experts have to be able to determinate metric to evaluate strength, weakness, and bottlenecks of the ecosystem through a continue monitoring, identifying whether and how to intervene, and verifying over time the effectiveness of such interventions. Consistent with the described selective approach, they should also have the political strength to concentrate resources (public and/or private) primarily on a small number of high-potential early stage firms to accelerate their development [6, 46]. As success breeds, resources have to be granted in a selective way and not equally distributed [28].
\nAmong the enablers duties, another vital aspect concerns the creation and diffusion of a specific culture. There is the necessity to plan initiatives acting on the cultural pattern of the territory, stimulating universities and school to focus on entrepreneurial education and promoting events which celebrate local entrepreneurship and innovation. The purpose is to valorize the entrepreneurial choice among citizens favoring a mentality changing and stimulating imitation. In this perspective, it would be significant to already have in the ecosystem HGFs or other successful examples to imitate. In parallel, as basic informal rule, an ecosystem should be characterized by the acceptance of failure as a normal outcome of entrepreneurial activity. The consequence is that there is no diffidence to employ workers coming from other companies, even if they have failed [11]. Being based on largely trustworthy relationships, the ecosystem has also to be pervaded by the typical optimistic and positive business climate which feeds of self-confidence among entrepreneurs [41].
\nLast but not least, a prosperous ecosystem also depends on innovations diffusion and industry conditions. For instance, even if riskier, technological advances of disruptive nature, which create “discontinuities,” are believed to produce the largest opportunities [27, 50]. Consequently, often the emergence of an entrepreneurial ecosystem depends on the development of markets for newer technologies [8, 55]. Digital technologies are a remarkable example of this type, with a lot of opportunity that could be disclosed for new would-be entrepreneurs and the local context [48]. From this last perspective, entrepreneurial enablers have a great responsibility in connecting the ecosystem to the technological and innovation dynamics. To collect all these changes and challenges, the business environment has to show a high social capital [54], while firms show a high level of intellectual capital, in form of the three interrelated human, relational, and organizational components [56].
\nThe overture described is in line with the increasingly widespread theses according to which economic behavior can be better understood within its historical, temporal, institutional, spatial, and social contexts. Contexts provide individuals with opportunities and set boundaries for their actions and influence entrepreneurial choices, helping to understand who, when, how, and why someone becomes involved. But also entrepreneurship impacts on context, modifying its features [3]. Consistent with some influential experts [57], the next shift in policies will lead from “regional entrepreneurship policy” to “policy for an entrepreneurial regional economy,” that is the ecosystem approach.
\nObserving the transformations taking place in the industrial system, it is clearer how, on the one hand, technology becomes much more pervasive by entering more and more directly and intensely in production processes, products, and services. From the other hand, the technology-based competition is intensified, with new comer countries that force Western countries to continuously renew the bases of their technological and competitive advantage. This dynamic makes R&S activity and the related ability to propose innovations increasingly necessary [49].
\nWith specific regard to digital technologies, “the biggest transformation in business the world has seen in over a century” ([48], p. 5), they are radically changing the way people live, work, communicate, and play. Their pervasive diffusion is also causing significant repercussions on the dynamics of companies in European countries: 2.6 new digital job for each job destroyed is expected, manufacturing can achieve growth from 15 to 20% by 2030 if digitalized, revenue coming from digital technologies will growth of 2% for year, big data technology and services are expected to grow worldwide to USD 16.9 billion in 2015 at a compound annual growth rate of 40%, while companies using that data become 5–6% more productive [48]. Also, the way of carrying out many of the traditional production processes is modifying considerably, as well as consolidated theoretical approaches regarding the methods of supplying resources, the product management, and service offered are questioned. Indeed, the possibility of constantly introducing new functionalities for a product or service, even in remotely, would seem to alter the validity of theories on the product life cycle, on the genesis of the innovation, or on the product development process [25, 26].
\nConsequently, by proceeding with digital technologies adoption and implementation, an almost infinite number of economic opportunities for existing or new ventures is emerging, waiting to be grasped. Even more by considering that the boundaries of digital technologies in the three interrelated components of digital artifacts, platforms, and infrastructures are still unexplored, and every innovation such as cloud computing, data analytics, online communities, social media, 3D printing, and digital makerspaces contains indefinite applications.
\nThe magnitude of this change is so significant and visible that a specialized literature has arisen—the digital entrepreneurship. It analyzes the effects of digitalization on the traditional methods of conducting a business to success. For instance, about the digital artifacts (the digital components, applications or media content that are part of a new product/service and offers a specific functionality or value to the end-user), the decoupling of information from its related physical form or device has led to the gradual infusion of such digital artifacts into a wide range of products and services and discloses a plethora of business occasions for different industrial sectors [58]. Digital artifacts are continually embedded in wider and constantly shifting ecosystems, such that they become increasingly editable, interactive, reprogrammable, and distributable [59]. Similarly, digital technology that offers communication, collaboration, and/or computing capabilities to support innovation digital infrastructures requires new personnel with different roles (customers, investors, partners, etc.) in all stages of entrepreneurial process, from opportunity exploration to venture launch [59].
\nFurthermore, “digital infrastructures (digital technology tools and systems that offer communication, collaboration, and/or computing capabilities to support innovation and entrepreneurship) infuse a level of fluidity or variability into entrepreneurial processes, allowing them to unfold in a nonlinear fashion across time and space” (Nambisan, 2017, p. 6), making less stable boundaries in both entrepreneurial outcomes and processes. This, in turn, leads to changes in behaviors and actions among digital entrepreneurs. Indeed, digital firm’s success tends to step away from the exploiting of a certain opportunity, or the execution of a detailed value proposition, as it needs to follow a continuously evolving value proposition, namely actions that leverage the potential of a continuous re-scoping of business model [27].
\nThe continuous changes associated with the implementation of digital technologies also support a transformation in the figure of the entrepreneur and his orientation to primarily seek economic performance. On one side, in fact, the most important aspect of the firm, especially if in the initial stages of life, becomes the validity of the business idea that it intends to develop and the consistency with the skills already possessed. The goal is to ensure the future competitiveness of venture or its attractiveness toward larger companies that might decide to buy it. On the other side, the focus of the decision-making process could depend on the pool of employees, probably coetaneous of the entrepreneur but with more digital skills, who are able to identify and collect market opportunities and transforming in business [26].
\nIn the meantime, less importance of funding sources is expected in favor of the role of connections. In fact, unreleased opportunities to resort to financing with methods such as crowdfunding or crowdsourcing or obtaining support from customers and suppliers are arising. In this way, the traditional funding gaps for new businesses, particularly in technology sectors, normally looking for small amounts of finance, can also be easily filled [43].
\nOn closer inspection, these changes are intrinsic conditions and functionalities belonging to the entrepreneurship ecosystem approach. In ecosystems, the goal of profit is fundamentally subordinated to the desire for self-realization or experimentation with innovative ideas of aspiring entrepreneurs (the pleasure of discovery), while the presence of networks of stakeholders along the productive process and the supply chain is believed crucial. Likewise, a continuous rotation of employees who pushed by personal objectives of income, job satisfaction, or self-efficacy tends to offer their competencies to other neighboring companies or to create their own startup, is judged spontaneous.
\nThese behaviors improve not only the processes of dissemination of knowledge and innovative ideas within the ecosystem but also their propagation speed. This high fluidity of people and resources within the ecosystem is considered a strategic lever for its success [28]. But fluidity is also a key feature of digital technologies which often have low access barriers and are cheap to adopt and exploit.
\nIn addition, re-programmability and re-combinability of digital artifacts and platforms, on their own and in conjunction with other factors, enable the introduction of new functionalities in different market contexts, thereby refashioning existing pathways or opening new chances to create value, i.e., rendering existing market offerings less bounded from already existing opportunities. Digital firms could not feasibly operate without the Internet-enabled digital platforms (shared, common set of services and architecture that serves to host complementary offerings, including digital artifacts), which meet producers and consumers and facilitate the exchange of goods, services, or social currency, also enabling value creation for all through the digital landscape [25]. The difficulty to establish boundaries for digital platforms is therefore confirmed. In addition, the interaction of digital artifact properties with other contextual features resulting from the challenges linked to digital technologies (e.g., new legislative regulations, new pricing mechanisms, etc) also can radically change the definition of value in a market, proposing new further functionalities or business opportunities [59].
\nOn these premises, ecosystems could assure a fundamental contribution facilitating the developmental pathway for digital startups. Indeed, an ecosystem guarantees the passage of the traditional business environment to one no longer linked to individual or company factors but to a network of specialized partners with a wide availability of knowledge and open innovations.
\nDue to the presence of research centers disseminating knowledge, universities forming graduates in technical disciplines, and consultants, it is highly probable that these specific environments are linked to regional or urban areas. Not by chance, some authors (e.g., [33, 60]) put cities as the key organizing unit for innovation, entrepreneurship, and economic growth and argue about how digital startups and scale ups may take in place in cities and, sometime, require them as preferential ecosystem that help lever their development [58, 60].
\nEven the ecosystem tendency to the concentration of activities is coherent with the nature of digital companies. Their location choices do not depend on factors such as proximity to the market or availability of tangible inputs or from the availability of large physical space difficult to find in an urban area. As digital companies include online retailers but exclude retailers which have a physical presence on the ‘high street’ and are linked to the generation and diffusion of knowledge, as well as to the presence of specific support services or specialized human capital and venture capital, they should give priority to the agglomerations of competencies typical of urban context with the presence of universities and research centers [8, 61].
\nBelonging to an ecosystem presents another advantage for digital companies. In the ecosystem, the innovative and creative processes are no longer centered on the individuals or on the ventures, but looks at the entire regional context meant as fertile environment from which economic opportunities can arise. Therefore, the innovative and entrepreneurial critical processes become linked to the entire external environment, considered as a place of aggregation of individuals, companies, individual talents, institutions and support services [28]. This feature is consistent with the needs of digital entrepreneurship, where the most important productive factors are the availability of specialized personnel, of venture capitalists, and knowledge generation sources. To be placed in an ecosystem also could help all the memberships companies to obtain legislative rules that ensure, for example, the ownership of the innovations introduced and the cyber security of client companies, in doing so encouraging the adoption of the same technologies [62].
\nAnyway, to grow, digital startups must incorporate quickly new management functions, from operations to marketing, evolving from an unstructured chaotic day-to-day to an evolving structure, mature, and dynamic organization. Consequently, they have to bring out the need of new competencies, especially of digital nature. They have to be able to possess, manage, dominate, and develop digital technologies and the inherent knowledge. These competencies enclose hard skills (from the ability to use computer programs and packages to the use of specific machines and tools for production such as social, mobile, analytics, cloud, artificial intelligence, robotics, Internet of Things, and cybersecurity) and soft skills (linked to relationships and behaviors of people enabling the effective use of new digital tools such as problem solving, knowledge networking, the new media literacy, etc.) [63]. Consistent with the ecosystem features reminded in the previous sections, even from this last perspective, the ecosystem approach seems the more suitable for digital startups and their growth.
\nThe diffusion of digital technologies with their still undefined boundaries announces a new era in entrepreneurship, where traditional ways and forms of pursuing entrepreneurial opportunities will be increasingly reshaped. A new horizon of business opportunities only waits for being discovered and then managed profitably [27, 48, 57].
\nRelevant changes also are involving the basilar criteria of management and organization of companies and the ways to compete globally. From these modifications, new criteria to start a business and pathways for its development and growth descend: the emergence of digital entrepreneurship [25, 62].
\nFor policy makers, the main challenge is to assure both that the domestic ventures are able to collect digital business opportunities successfully and to provide benefits for the whole territorial context, along a development route stable and persistent in terms of net employment, income, and cross fertilization. A flourishing entrepreneurship research stream believes that a chance to reach the above objectives lies in the ability to implement specific business environments called ecosystems. These are targeted on selective measure supporting the emerging of ventures with innovative business models but also their development and growth ([24]; Napier and Hansens, 2011). While, according to empirical evidence, policies only focused in favoring the firms birth rate may not be the best solution to the problems of employment and growth of many Western countries.
\nAnyway to support scale ups and high growth firms in general is a hard task that must be carried out by specialized personnel and with the appropriate skills. This is because there are not many cases of good practice to follow, but only a basic logic according to which all the domains (a favorable culture, enabling policies, availability of adequate financing, high-quality human capital, safety-friendly markets for products, institutional supports, etc.) that make up an ecosystem must be aligned and coordinated (holistic approach). Moreover, the ecosystem needs to involve, since the beginning, many stakeholders/actors (at least an interested large corporation, policy makers, local bankers, and venture capitalists, people acting on the local culture, local universities, etc.) [24, 54]. The more intense the cooperation among these key actors is, the more likely the ecosystem will be to succeed.
\nNevertheless, both domains and actors are characterized by proximity and include hundreds of variables interacting in highly complex and idiosyncratic ways. They should be able to converge toward a set of shared objectives according to a series of priorities [31] (SEP, 2018).
\nDespite the complexity to create an ecosystem, its features and functionalities seem well-suited with digital enterprises features, as they focus on the development of the intellectual capital, which has to sustain the growth of firms operating with a new disruptive technology [8, 56]. Indeed, the roots of a well-operating ecosystem lie in a specialized and motivated human capital, open to innovation and with a widespread entrepreneurial culture. It is also founded on a dynamic system of connections among all the stakeholders of a context who are interested into its development, the networking capital. Again, the ecosystem rests its strength on the quality of the firms enclosed in terms of values, managerial philosophy, organizational patterns, and informative systems; in other word, the organizational capital.
\nTo this aim, therefore, policy makers are called to sustain a great effort. Not by the chance, up to now a lot of attempts aiming at creating conducive environments failed. Moreover, there is an effective risk that the entrepreneurial ecosystem remains a tautological concept (Stam, 2015): entrepreneurial ecosystems produce successful entrepreneurship, but where there is a lot of successful entrepreneurship, there is apparently a good entrepreneurial ecosystem.
\nBeyond this theoretical-conceptual paper, aimed to connect the increasing sector of digital firms with a specific business environment, future surveys should focus their analyses at least on three directions. Firstly, a clear individuation of the needs and resources requested by digital firms and startups in the light of their own specificities; secondly, the detailed examination of the operative mechanisms of existing ecosystems precisely focused on digital technologies; and lastly, an investigations on the coherence among digital technologies with the local background of competencies and knowledge to individuate possible gaps to fill.
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