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Start-up development with three strategic goals.
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The paper deals with conditions for the formation of technology start-up projects in the Slovak Republic. It summarizes current and upcoming legislative conditions for entrepreneurship and compares the conditions of startups developing in the EU and the USA, also their support within H2020 and in SR within the RIS III, as well. On the real examples...
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... A four-year period was selected based on the literature and practical considerations. According to the literature, the valley of death for newly created firms often occurs during three to five years after foundation (Gbadegeshin et al., 2022;Janáková, 2015;Laitinen, 2016). Only small and micro companies (those with total assets of up to 10 million euros) are included. ...
This study aims to determine whether financial performance is persistent in serial entrepreneurship and, if so, whether good performance is more persistent than bad. It is novel as studies focusing on financial performance in successive firms ran by serial entrepreneurs are scarce. The paper creates a multi-theoretical framework from which four hypotheses are drawn. These focus on the persistence of firm size, export intensity, financial risk level, and payment defaults in serial entrepreneurship, all of which have been rarely utilized in such research. The validation of hypotheses is conducted by using ordinary least squares regression with a sample of 1599 Estonian serial entrepreneurs, being further divided into those with earlier good or bad performance. The dependent and independent variables, supplemented by various controls, portray the four performance measures in serial entrepreneurs' new and old firms. The regression analyses show that financial performance persists in serial entrepreneurship in general. Good performance is more persistent than bad, indicating inter-firm transfer of financial success. In most cases, bad performance is not persistent at all, indicating that some serial entrepreneurs repeat their earlier poor results, while others improve their future performance.
... We observe the minimum debt ratio for Slovakia at 13.8%. The lower ratio is plausible due to the challenging landscape for new ventures in the country (Janáková, 2015). From the financials of the start-ups, we observe three types of debt financing. ...
In the blue economy start-ups play a critical role as they bring innovation, technology, and new business models, driving sustainable growth and development. However, blue start-ups also experience financing constraints and in this research, we evaluate the factors that drive their gearing ratio. Using a comprehensive sample of firms across twenty-seven EU member states between 2013 and 2020, we find a negative link between debt ratio and climatic and ocean disruptions. We also report a positive relationship between asset tangibility and gearing, while regulations have a negative influence on the choice of debt as the preferred mode of financing. Our findings also suggest that blue startups with more private equity, have a lower variation in their capital mix. Finally, the fundamentals play a favorable role to motivate the use of debt financing. These findings have important implications for blue start-ups and the related ecosystem.
... High-tech startups are typically characterized by being knowledge-intensive and innovative-driven, and producing and selling high-value-added products and services. They can promote the breakthrough or substantial improvement in relevant technology, services, or industry [8], but these types of entrepreneurships have the most difficulty succeeding [9]. They are the main target organizations of current government policy incentives. ...
In the context of digital transformation and the rapid development of artificial intelligence, corporate innovation has become increasingly important in leading industrial development and improving national competitiveness. In 2015, China launched a “mass entrepreneurship and innovation program”; in response to the policy, many makerspaces have been established, resulting in clusters of high-tech startups. High-tech startups are the pioneers in innovation development. However, there is still a lack of empirical evidence for whether these firms’ innovative activities, capabilities, and performance can be effectively stimulated by public policy. Drawing from the institutional theory and resource-based view, this paper develops a model of policy perception on innovation response. Using a sample of 500 startups located in the three representative makerspaces in China, this work verifies the effectiveness of innovation and entrepreneurship incentives on startups’ innovative activities, capabilities, and performance, and successfully identifies the mediating role of policy adaptation in the policy perception-innovative responses’ link and the moderating role of makerspace support.
... Accuracy described by ROC, precision and recall. [7] Investigating conditions of developing a technology start-up using current and future conditions. ...
In recent years, our data storage and processing abilities have been enhanced significantly. Machine learning (ML) has become able to capture and analyze huge data without human interference. In this context, the ML techniques will also be used for measuring, predicting, and recommending the consequences of start-up success. Therefore, first, we studied some essential contributions which employ the ML models for business success. Next, a system architecture has been demonstrated that will be able to predict the success of a start-up and also recommend the key insights. Further, we proposed and implemented a start-up success prediction model. In this modeling, we initially used four supervised learning algorithms, namely support vector machine (SVM), k-nearest neighbor (KNN), Naïve Bayes, and logistic regression. In addition, two unsupervised algorithms such as k-means and fuzzy c-means (FCM) are implemented. During experiments, we have found these models are able to provide only 58% of classification accuracy. Therefore, we have proposed to use convolutional neural network (CNN) for training and prediction. In this context, we have crafted three variants of CNN models for experimental study. According to obtained results, we found the first model provides only 48% classification accuracy, the second model provides (69%) accuracy, and the third model provides higher accuracy (74%). Thus, we found promising to work with the CNN and Crunchbase datasets. Therefore, in near future, we proposed to design a CNN model with the feature engineering processes.
... 1. These papers [11][12][13][14][15][16][17][18][19][20][21][22] all use a literature review across diverse sources. ...
... 2. These papers [11][12][13]16,18,19,[21][22][23][24][25][26] use general CSFs and thus not context-based ones. ...
Current research in the field of critical success factors of start-ups refers to general factors with which important information about the start-up is lost. Start-ups are too individual for a generalistic assessment, so a novel approach is presented in this paper that allows the context of start-ups to be included in the assessment of critical success factors. This results in the context-based critical success factor, which is defined for the first time in this paper.
... Despite many successful businesses, a majority of small technology startups self-destructs within two years from their creation [10,11]. Many research studies also focused on determining the relative performance of different methods and factors involved in startups success [12,13]. These models that are developed to analyze the startup success factors are interest in knowledge for the entrepreneurs in the pre-startups. ...
Small and Medium-Scale Enterprises have been recognized by the government due to their significant role in the country’s economy. The risk of capital investment is high in the enterprises and various factors need to be properly analyzed for the prediction of success of an enterprise. Machine learning techniques can be adopted to predict the success of startups that helps the entrepreneur to make a decision accordingly. In this paper, a details analysis has been carried out on the existing methodologies on startup success prediction to analyze the benefits and limitations. Fewer researches has been carried out in the startup success prediction and achieves the considerable prediction performance. Major limitation has been found among startup success prediction model that use irrelevant features. Some researchers have used social media datasets like Twitter data to increase the performance of the developed method. From existing methods, it has been observed that Random Forest classifiers have been out performed than Logistic Regression method.
... The Slovak business environment for start-ups is, according to Janakova (2015) and the KPMG study (2016) supported by many Slovak ministries (of finance, of economics, of education, R&D and sports) and agencies (SBA -Slovak Business Agency, SIEA -Slovak Innovation and Energy Agency, CVTI -Scientific and Technical Information Centre, venture capital companies such as Neulogy Ventures, business angels and crowdfunding platforms. ...
Creative regions contribute to a higher standard of living, are attractive to start-ups, create new jobs, reduce brain drain and attract applicants for university education. The paper aims to compare selected indicators of implementation of start-ups and creative potential in the regions of Slovakia at NUTS 3 level and to quantify their mutual relationship. Benchmarking of 8 Slovak NUTS 3 level regions is based on 2 comparisons, namely: 6 indicators of start-ups implementation (frequency of start-ups, creation of radical innovations, employment in fast-growing companies, venture capital awareness, crowdfunding awareness and possibilities of counselling in the implementation of start-ups) and 6 indicators of creative potential (openness and diversity, human capital, cultural environment, technologies, institutional environment and creative outputs). Numerical values of these indicators are obtained from secondary research studies-e. g. modified Slovak Creative Index, Regional Innovation Scoreboard, Slovak Start-up Report and websites of innovation incubators and crowdfunding platforms. To obtain the true values of these criteria, the analysis of secondary data-desk research and the method of pairwise comparison with 91 respondents (students of Slovak universities of economic orientation with Slovak or Ukrainian nationality) was used to determine the real significance (weights) of the criteria. According to pairwise comparison, the most important indicator of start-up implementation is possibilities of counselling and the most important indicator of creative potential is creative outputs. Consequently, the relationship between the two comparisons is quantified. The global benchmark based on the implementation of start-ups is the Bratislava region, as well as in the case with creative potential. There is a strong correlation (85.5 %) between the scores of the compared regions. The final ranking of the 5 regions out of 8 in both comparisons is also the same. The theoretical contribution is extending of the issue of benchmarking from traditional understanding (products, services, processes) to spatial understanding (region). The main practical contribution of the paper is to identify the weaknesses of each of the compared regions through benchmarking. Its implementation can be the basis for the development of regional strategies and the introduction of new study programs at universities.
... The use of these platforms is particularly important at the regional level (bottom-up), as they can help to identify key regional (and national) players, as well as encourage transparency and trust within and beyond the networks. This could be important for fostering a strong relationship between bio-based industries and society [45][46][47][48][49][50]. ...
Over the last decade, the bioeconomy has become increasingly important and visible in international policy agendas, with several strategies being recently developed. The implementation of bio-based technologies mostly takes place on a regional scale. Therefore, from a regional perspective, a key question revolves around what main challenges are associated with technological developments that could catalyze the implementation of sustainable bioeconomy regions. In this study, a cross-cutting analysis was carried out to determine these challenges. First, interviews were conducted with industry practitioners and scientists working in the bioeconomy field. These interviews were supplemented with a literature review to determine the status quo of bioeconomy strategies and their implementation, particularly on a regional level. A multidisciplinary workshop was then organized to identify the most relevant challenges in the short- and mid-term associated with establishing bioeconomy regions. The results show that there is a three-pronged challenge in innovative technological development from a regional perspective: (1) Resources: The establishment of sustainable regional feedstock strategies and supplies for supporting the bio-industrial sector; (2) collaborators: The establishment of a regional “critical mass” by fostering supply chain clusters and networks; and (3) neighbors: Understanding the local dynamics of societal trends and preferences and social acceptance of bio-technologies and their representative bio-based products.
... An information network, professional services, technical support, and availability of capital in the right quantities and at the right time help the business sustain itself. Failure to obtain positive cash flows and achieve break-even point in time result in failure of ventures (Janáková, 2015). ...
After the start-up boom in emerging markets like India, today when we analyse the scaling-up of start-ups, increasingly there is a trend of selling up successful start-ups after scaling them up. Even significantly large non-public start-ups also fall prey of this phenomena. For this paper, interviews were conducted with 20 owners of such start-ups to find out what were the motivations to scale-up and sell their ventures and not going for a sustainable enterprise. Was it a emerging market phenomenon, or it was a low risk model of wealth creation for the individual or were there some other reasons?
... The positive impact of EO on firm performance reflects the possible change it might bring to the start-up firms. The predictors of Start-up Success are mainly related to the efforts carried out to ensure a firm to be financially stable and resilient within the first five years (Janáková, 2015). Some authors even labeled it as the preparation for 'valley of death.' ...
... Despite the extensive review on EO and performance relationship in many countries, the gender impacts on EO practices are rare and inadequate (Fellnhofer et al., 2016;Priya & Sreeranganadhan, 2017). Also, scarcity of previous research to relate EO and Start-up Success portrayed that the understanding of these two ideas is limited (Janáková, 2015). These loopholes open-up a new gap to be filled with more studies, especially within the local context. ...
This paper examines the extent to which gender influences on the practice of Entrepreneurial Orien-tation (EO) on Start-up Success. This study was conducted among Spin-off and Symbiosis Com-pany (SSC) from all sectors in Peninsular Malaysia. Despite the remarkable research on EO and Start-up firms, there is a missing link on how gender provides different perspectives of EO practic-es among SSC, especially in Malaysia. A total of 120 SSC was chosen and the results show that EO was statistically related to Start-up Success and unveiled the magnitude of change that gender possesses in improving the relationship between EO practice and Start-up Success. The major implication of this study presents the unique contribution of gender in motivating SSC owners to engage in EO. Also, the difference of gender perceptions in business provides a variety of untapped opportunities in terms of entrepreneurial-related practices as different gender perceived different needs and capabilities. Future research is suggested to explore this phenomenon more extensively and develop a comprehensive model for the gender analysis. In brief, the discussion in this paper would help to strengthen the body of knowledge on Entrepreneurship and act as a future reference on SSC, EO, and Start-up Success.
