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The role of a relatively small cadre of high-tech startup firms in driving innovation and economic growth has been well known and amply celebrated in recent history. At the same time, it is well recognized that, while the overall contribution of startups is crucial, the high-risk and high-reward strategy followed by these startups leads to signific...
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... particular, after the first selection of 214 startups from these databases according to the availability of enough information, an expert-based analysis supported by the use of the SHELL methodology has been conducted, assigning each startup failure to one or more subcategories to standardize the reasons for failure. Figure 3 reports the distribution of the 214 startups considered for the study (a preliminary classification has been done to assign startups to a sector). In particular, the sector showing the highest number of postmortem reports on the two databases analyzed is Social Media, with the 12.3%. ...
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... Based on the discussed above, our study adopts a dimensional approach through the analysis of a database of 353 post-mortem reports of failed startups drawn from the CB Insights Tech Market Intelligence Platform for the period from 2014 to August 2020 with a sequential injection of reports each year. We stress that we do not have the primacy in using this database for this purpose as it was employed twice in a similar analysis by the corporation itself in 2014 [37], and then later by Cantamessa et al. (2018) [38]. For this purpose, we consider this paper an extension that takes into account the large size of this database, and attemps to address the issue with a deeper approach and a larger number of failure factors. ...
... Based on the discussed above, our study adopts a dimensional approach through the analysis of a database of 353 post-mortem reports of failed startups drawn from the CB Insights Tech Market Intelligence Platform for the period from 2014 to August 2020 with a sequential injection of reports each year. We stress that we do not have the primacy in using this database for this purpose as it was employed twice in a similar analysis by the corporation itself in 2014 [37], and then later by Cantamessa et al. (2018) [38]. For this purpose, we consider this paper an extension that takes into account the large size of this database, and attemps to address the issue with a deeper approach and a larger number of failure factors. ...
... That study adopted a holistic approach in dealing with the failure phenomenon based on 20 failure factors. The study by Cantamessa et al. [38] followed subsequently when the database had 166 reports, and the factors were classified within five dimensions (business model, consumer/user, product, organization, and environment), totaling 26 failure factors. ...
Failure as a phenomenon is roughly inseparable from the startups subject in previous literature, causing a debate among scholars about the diagnostic of the reasons of this pathology, due to the large failure rates of startups that impose risks of ruling out the positive impact and added value they allow. Our paper attempts to contribute to this debate by analysing a database of 353 startups post-mortem reports from the CB Insights Tech Market Intelligence Platform using 65 failure factors based on 245 factors used in 13 prior studies. Results indicate that failure factors related to product/market misfit, lack of capital, great power of competition, law and regulation problems, and bad business model appear as the most important factors that lead startups to fail. Furthermore, findings emphasize that failure factors related to product/market misfit and the lack of capital appear actively in the early stages of the startup lifecycle, to decline gradually in the later stages leaving room for factors related to great power of competition and law and regulation problems, with relative stability of financial problems through the lifecycle of the startup.
... One of the most critical phenomena in modern economics is the potential impact of startups on innovation, economic growth, and employment rates at the regional, national and industrial levels (Sedláček & Sterk, 2017). While startups' collective contributions are critical, the high-risk strategies they pursue lead to startups' high failure rates, up to 90% in some industries (Arora et al., 2018;Cantamessa et al., 2018;Marmer et al., 2011), so improving organizational performance is vital to these businesses. This study examines one critical organizational phenomenon -organizational silence -in Iranian startups. ...
Addressing the lack of research and knowledge about organizational silence in the nascent but promising Iranian startup ecosystem, this study examines the relationship between personality factors and organizational silence in Iranian startups. Data were collected using Vakola and Bouradas Organizational Silence Questionnaire and NEO Personality Inventory filled by 532 startup employees in Iran, then analyzed by Pearson and multivariate regression tests. Hypotheses were tested through SPSS. Data analysis demonstrated that personality factors predict 17.0% of the variance of organizational silence, and there is a significant relationship between each personality factor with organizational silence in startups. The strongest and weakest correlations with organizational silence were observed for openness to experiences and conscientiousness, respectively. The study is cross-sectional, so its results cannot be casually inferred; longitudinal studies are needed to obtain more comprehensive information. Access to qualified respondents was challenging because of startup managers’ overall conservativeness spirit and tendency to withhold information about their employees. This study has implications for startup managers and decision-makers. Since it has examined a destructive organizational phenomenon in the specific context of startups, this knowledge will help managers recognize and resolve organizational silence. This study has filled the research gap by examining the organizational silence in Iranian startups for the first time and has implications for theoretical development in this novel context; furthermore, it helps startup managers to deal with organizational silence more effectively.
... The third factor is the business model, this factor acts as a success factor as a basic concept in establishing a startup (Nalintippayawong et al., 2018). However, according to Cantamessa et al. (2018) and Bednár & Tarišková (2018) if the wrong business model is run, it will fail the startup. The fourth factor is funding, according to Cantamessa et al. (2018) and CB Insight (2021), funding has a very big influence on startup success, have no funds means failure. ...
... However, according to Cantamessa et al. (2018) and Bednár & Tarišková (2018) if the wrong business model is run, it will fail the startup. The fourth factor is funding, according to Cantamessa et al. (2018) and CB Insight (2021), funding has a very big influence on startup success, have no funds means failure. ...
... The fifth factor is the product, at the startup pioneering stage according to Cantamessa et al. (2018) and Bednár & Tarišková (2018) the product must be released in the right time (not too early or too late), if the product is released at the wrong time it will bring failure to the startup. The sixth factor is competitors, the strengths and advantages in the pioneering process can be known through competitors. ...
Background and Purpose : Successful digital startups can generate income for the country and improve people’s lives. However, for prospective founders who will launch their startups, the success factor in pioneering digital startups remains unknown. The purpose of this study is to identify key success factors for digital startups in pioneering stages.
Methodology: Thematic analysis is a method for identifying success factors in pioneering stage digital startups. The data will be collected from the interviews of ten startup founders.
Results: The findings show that fifteen critical factors are success factors in the digital startup pioneering stage, namely; problems, business ideas, teams, business models, capital or funding, products, incubators, validation, competitors, marketing, mastery of technology, market analysis, founders and co-founders, partners, and passion. These findings are expected to be ground-breaking for anyone interested in launching a digital startup.
Conclusion: The first conclusion that we can draw is that there are fifteen important factors that can be claimed and used as success factors in the classification of the digital startup pioneering stage. The second conclusion, based on the findings of the ten founders’ analyses, is that problem factors and team factors are two of the fifteen most dominant and influential digital startup success factors. Problem factor is critical for detecting problems encountered by many people and can motivate digital startup founders to develop solutions to these problems. While team factor is important because with a team, all problems raised are quickly and easily resolved, and all work is handled productively and collaboratively.
... This model has been iteratively tested in various parts of the world (Lussier, 1995;Marom and Lussier, 2014). Other research adapts methodologies to analyze airline crashes to a framework to analyze post-mortem reports of startups (Cantamessa et al., 2018). In a systematic literature review of 74 papers focusing on new ventures' failure, four main categories of causes for failure were identified, being resources (human and financial capital), strategic/managerial decisions, product-related aspects, and contextual/environmental-related issues (Pisoni et al., 2020). ...
... The questionnaire of this survey has been constructed based on existing literature on successful and failed startups (Cantamessa et al., 2018;Chhatwani et al., 2022;Marom and Lussier, 2014;Pisoni et al., 2020;Rizos et al., 2016;Skawińska and Zalewski, 2020), on recent research on circular companies in Flanders (Borms et al., 2023), and on the input of partner organizations that were willing to reach out to startups within their network. Draft versions were iteratively tested in the period July-September 2021. ...
... Regarding barriers to implement circular strategies, we based our questions on an extensive EU-wide research among businesses, governments, academia, and NGOs (Kirchherr et al., 2018), and on a paper that adapted a model to analyze aircraft crashes into a framework to analyze post-mortem reports of startups (Cantamessa et al., 2018). The list of potential enablers to implement circular strategies is based on a participatory study that included policy and industry perspectives to construct a working agenda for a circular manufacturing industry in Flanders (Versluys et al., 2021). ...
Circular economy practices contribute to achieving sustainability and alleviating the consequences of value chain disruptions and surging prices of energy and raw materials. While startups are increasingly recognized as a powerful engine for innovation processes needed to support this transition, empirical studies on the selection and implementation of circular strategies among startups remains scarce. In this paper, we report findings from the first academic survey on circular startups (N = 165) that allows for multivariate statistical analyses, considering both personal and company characteristics, and perspectives of the entrepreneurs involved. This survey includes startups with varying degrees of implementation levels of a set of 10 circular strategies at different startup lifecycle stages. Our results suggest that younger startup entrepreneurs tend to focus on inner circle strategies, while older startup entrepreneurs rather engage in outer circle strategies or no circular strategies at all. Female startup entrepreneurs are found to be less inclined to combine multiple circular strategies, and business-to-business and business-to-government market segments tend to be frontrunners for circular business models. Circular startups mostly acknowledge sustainability and circularity as a comparative advantage, and startup entrepreneurs with a migrant background seem to be more optimistic to start a profitable circular business. Our results suggest that there is no such thing as ‘the’ circular economy startup, so we recommend policy makers to develop tailor-made solutions to support startups implementing different circular strategies.
... Start-up risk was determined using the SHELL (Software, Hardware, Environment, Live-ware, and People) method by Cantamessa et al. (2018). In this approach, the relationship between the model's quadruple components and the start-up's organizational dimension is crucial. ...
... and "the CB Insights platform" containing data of 214 start-ups for which failure reports were available. It should be noted that the reasons for the failure of new businesses are based on the founders' perspectives (Cantamessa et al. 2018). Marco van Gelderen et al. (2005) tracked 517 individuals who started a new business during a three-year period to examine the causes of start-up success and failure. ...
... Risk Factors (Cantamessa et al. 2018) Product-Business model-Organization-Customer/user-Environment (Bednár and Tarišková 2017) Lack of money for further development-No need for a product/service in the market-No investors-Cost Issues-Not the right team-Under development business-Lack of enthusiasm-Ignoring customer's opinions-Great power of competition-Unattractive product-Pivot in the wrong-Burnout syndrome (Akhavan et al. 2021) Technology skills-Business skills-Manager commitment-Changes in customer needs-Dependence on suppliers-Budget management-Development time until exploitation-Industry life cycle-Quality-Exchange rate-Fixed capital-Network capital (Bamford and Douthett 2013) Risks to profit margin-Risks to sales generation-Risks to operational financing-Risk reduction and venture capitalists (Proksch et al. 2016) Agency risk-Liquidity or financial risks-Technology risk-Market risk-Human resources risks-Failure risk-Internationalization risk-Macro risk (Keizer and Vos 2003) Commercial viability risks-Competitor risks-Consumer acceptance and marketing risks-Public acceptance risks-Intellectual property risks-Manufacturing technology risks-Project management risks-Product family and brand positioning risks -Product technology risks-Screening and appraisal risks -Supply chain and sourcing risks -Trade customer risks (Cbinsights 2016) Failure to pivot-Burnout-Did not use the network-Legal challenges-No financing/investor interest-Failed geographical expansion-Lack of passion-Pivot gone bad-Disharmony among team/investors-Lose focus-Product mistimed-Ignore customers-Poor marketing-User un-friendly product-Product without a business mode-Pricing/cost issues-Get outcompeted-Not the right team-Ran out of cash-No market need (Gonçalves et al. 2014) Financial (liquidity, profitability, debt coverage/payback and activity)-Human capital (schooling, industry experience, management experience, success on previous projects, business plan)-Industry Level (industry growth, entry rate, industry concentration) ...
As historical data are typically unavailable for a start-up, risk assessment is always complex and challenging. Traditional methods are incapable of capturing all facets of this complexity; therefore, more sophisticated tools are necessary. Using an expert-elicited Bayesian networks (BNs) methodology, this paper aims to provide a method for combining diverse sources of information, such as historical data, expert knowledge, and the unique characteristics of each start-up, to estimate the default rate at various stages of the life cycle. The proposed method not only reduces the cognitive error of expert opinion for a new start-up but also considers the learning feature of BNs and the effect of lifespan when updating default estimations. In addition, the model considers the impact of investors’ risk appetite. Furthermore, the model can rank the most effective risk factors at various stages. The receiver operating characteristic (ROC) curve was utilized to assess the model’s explanatory power. Moreover, three distinct case studies were used to demonstrate the model’s capabilities.
... The questionnaire of this survey has been constructed based on existing literature on successful and failed startups (Cantamessa et al., 2018;Chhatwani et al., 2022;Marom & Lussier, 2014;Pisoni et al., 2021;Rizos et al., 2016;Skawińska & Zalewski, 2020), on earlier research on circular companies in Flanders (Borms et al., 2023), and on the input of partner organisations (Annex B) that were willing to reach out to startups within their network. The questionnaire provided separate answer pathways for startups that did not establish their company yet, for startups that are active, and for enterprises that stopped their activities. ...
Aside from potential environmental benefits, the implementation of circular economy principles in businesses can have merits for the labour market. The current unemployment in several regions of Europe and the qualitative mismatch between supply and demand could be countered by reskilling the labour force to adjust supply and demand to one another for increased reuse, repair, or recycling, among others. This study uses survey data to sketch the current and future landscape of startups’ skills in Flanders (Belgium) and analyses the relationship between circular strategies and different types of skills. The results show that design to lower material use increases the need for transport and logistics skills, digitalisation increases the need for R&D and IT skills, and the recuperation of waste requires technical knowledge. Furthermore, gender, age, and experience of the entrepreneur influence the needed skills. The paper probed for policy recommendations for the uptake of circular strategies and recommendations for future research. The most asked policy measures by the respondents are innovation and collaboration support (subsidies), fiscal measures that support circular goods and services, and public procurement for circular goods and services. This research is of relevance for several stakeholders, such as startup ecosystems, sector organisations, policy makers in innovation policy and labour market policy, and educational institutions.
... Several studies consider that startups have a strong innovative orientation (Colombelli et al., 2016;Vnoucková, 2018). However, startups also have several associated uncertainties, limited financial resources, and a high failure rate (Cantamessa et al., 2018). One of the conditions considered fundamental for developing innovation is that the company sacrifices some of its short-term results for long-term ones. ...
This study explores the role of talent in the processes of innovation, intrapreneurship, and internationalisation of startups. For this purpose, an empirical study was conducted with 226 Portuguese startups, and the impact of these components was analysed using the structural equation model. The findings indicate that talent attraction, development, and retention practices have a positive impact on innovation. However, the same correlation was not verified for intrapreneurship practices. Furthermore, both innovation and intrapreneurship are two determining elements in startups' internationalisation activities. This study offers pertinent contributions to the establishment of policies to support the internationalisation processes of startups, in which talent management emerges as a determining factor for its sustainable growth.
... While this type of internal tension has always been identifiable, the noted rise of 'startup culture' (Koskinen 2020) has further reinforced the need for an organisation to function in a wholly integrated manner. Recent examples Introduction 3 of business failures that were bursting with vision but had no operations (Cantamessa et al. 2018) are obvious early casualties in terms of longevity. Startups that are not able to develop a strategic direction are generally short-term propositions or invariably end up suffering from the negative influences of the founder effect (Fleising 2002). ...
... An important area of study in the eld of entrepreneurship is the factors that in uence the success or failure of new companies (Cantamessa, Gatteschi, Perboli, & Rosano, 2018). Startup rms are usually studied from nancial performance and using quantitative methods in analysis. ...
... From a handsome monthly salary to no salary has added considerable stress on these folks. 10. The most important and signi cant aspect that was extracted from the interviews was that the decision learning feedback loop for an entrepreneur was either missing or faulty. ...
Entrepreneurship is usually considered as a chaotic process paved with uncertainties. Without a method to the madness, entrepreneurship can become detrimental to the well-being of the entrepreneur. Early stage of a start-up refers to all important activities that help identify a potential business from an idea. This discovery process is characterised by stress and uncertainty which makes data driven decision making particularly challenging. Unlike mature phases (post launch and product-market fit phase) where data is available in plenty, early phase decision making depends on either limited data or generating one’s own data. Uncertainty gives rise to biases in the decision making. The two most negatively impacting biases are confirmation bias and self-serving bias. In a combination, they affect the way an entrepreneur in the early phase interprets both data and the consequences of his/her decision. Through a qualitative interview-based study involving 30 entrepreneurs in the early phase and 10 entrepreneurs in the mature stage, this study focuses on recognising the presence of these biases and proposes a habit-based process for grooming early-stage entrepreneurs. The scientific principles underlying the proposed framework have been detailed out and pragmatic solutions for improving early phase decision making have been derived.
... However, there are so many startups that fail due to several factors including market needs, internal conflicts, weak teamwork and inefficient funding. For example, the space infrastructure for activities is relatively expensive, and the existing infrastructure is inadequate, especially the appropriate functions with the activity needs and characteristics of creative startups (Cantamessa et al., 2018). For that we need a space that can accommodate and develop the creativity of creative startups that is comfortable, tailored to the needs and supports a collaborative atmosphere. ...
The rise of information and technology requires all businesses and nonprofits to digitize. The co-working facility in Bandung's Batununggal District does the same. Batununggal co-working facility intends to promote locals' creativity and host start-up actors. This community service targets MSME actors and inhabitants in Bandung's Batununggal subdistrict, those who have established a business and those who will establish a business. Workshops on digital technologies, digital ads, and AR-based social media content offer business actors insight and competence. Participants also received training on enterprise resource planning to help manage and integrate corporate operations in Batununggal, Bandung. This series of community service activities increased participants' insight into digital-based promotional strategies and the use of digital tools and digital ads for their products; increased participants' insight and competence in managing and integrating business using the ERP system; trained participants to use AR technology on social media, especially Instagram, to promote their products.
