The Employment in Innovative Enterprises in Europe

In this article we evaluate the determinants of the Employment in Innovative Enterprises in Europe. We use data from the European Innovation Scoreboard of the European Commission for 36 countries in the period 2000-2019 with Panel Data with Fixed Effects, Panel Data with Random Effects, Dynamic Panel, WLS and Pooled OLS. We found that the “Employment in Innovative Enterprises in Europe” is positively associated with “Broadband Penetration in Europe”, “Foreign Controlled Enterprises Share of Value Added”, “Innovation Index”, “Medium and High-Tech Product Exports” and negatively associated to “Basic School Entrepreneurial Education and Training”, “International Co-Publications”, and “Marketing or Organizational Innovators”. Secondly, we perform a cluster analysis with the k-Means algorithm optimized with the Silhouette Coefficient and we found the presence of four different clusters. Finally, we perform a comparison among eight different machine learning algorithms to predict the level of “Employment in Innovative Enterprises” in Europe and we found that the Linear Regression is the best predictor.

The Corporate Innovation in Europe

In this article we investigate the political and industrial determinants of firm investment in Research and Development. We use data from the European Innovation Scoreboard of the European Commission for 36 countries in the period 2000-2019. We found that firm investments in Research and Development are positively associated with “Linkages”, “Innovation Index”, “International Co-publications”, “Medium and high-tech product exports”, “Non-R&D innovation expenditure”, “Turnover share large enterprises”, “Human Resources”, “Intellectual Assets”. Firm investments in Research and Development are negatively associated to “Foreign doctorate students”, “Knowledge-intensive services exports”, “Private co-funding of public R&D expenditures”, “Basic-school entrepreneurial education and training (SD)”, “New doctorate graduates”, “Trademark applications”, “Tertiary education” “Design applications”, “Lifelong Learning”, “Foreign-controlled enterprises – share of value added (SD)”, “Total Entrepreneurial Activity (TEA) (SD)”.

Is It Digital Entrepreneurship? Designing a New Sport through Audience Ethnography

In designing a brand-new sport, do basic tenets of digital entrepreneurship such as ‘solve a user problem’ apply? How is it possible to understand who the potential audience might be for a product and experience that does not yet exist in a Culture Industry such as sports? The paper examines the beginnings of an Australian startup with an early-stage product in the sports and entertainment industry and its use of digital ethnography to investigate key audience segments. The process of audience development occurred alongside the prototyping and testing of a high-tech product that is central to the sport. As the product underwent iterations of development and release, audience interaction with the product was tracked through social media. Discourse analysis of audience engagement with the product on Facebook was conducted to inform a series of user personas that indicated a heavy male bias in the future audience. In exploring the intersection of sports, Cultural Industries and digital entrepreneurship, the paper concludes with observations of how this case challenges each of those notions through the process of ‘starting up’.

The mechanisms of the impact of high-tech product export trade on regional carbon performance

Export trade is a driving force of economic development, but it is also an important source of increasing carbon dioxide emissions. Against the background of suggestions of conflicts between economic development and environmental health, the proportion of high-tech products in the export trade of various countries has been rising, leading governments and scholars to focus on identifying the appropriate export structure for countries. While there is some knowledge on how high-tech product exports affect carbon dioxide emissions, the mechanisms involved in that link have not been adequately addressed in previous studies. This study is based on China’s inter-provincial panel data from 2006 to 2017, and uses the fixed effects model stepwise regression method and the bootstrap method to systematically investigate the mediating effects of industrial structure supererogation, low-carbon technological innovation and human capital accumulation, operating in the impact of high-tech product export trade on regional carbon performance. The research results show that high-tech product exports can help improve regional carbon performance. The mediating variables, industrial structure supererogation, low-carbon technological innovation and human capital accumulation, separately have positive and partially mediating effects on the link between high-tech products export trade and regional carbon performance. After considering the alternative indicator of regional carbon performance and the replacement of test method, the results of this study are still robust. The research results are instructive for an understanding of the relationship between high-tech product export trade and regional carbon performance. They highlight the important role of high-tech product exports in improving regional carbon performance, and have significance in promoting China’s green and low-carbon transition.

Multicriterial model of increasing the efficiency of high-tech production commercialization tools

The paper deals with a multi-criteria model for improving the efficiency of tools for commercialization of high-tech products, based on the application of the expert assessments method. The defined vertical classification of multistage commercialization efficiency calculation of the economic organizations activity is developed on basis of classification of the efficiency estimation optimum criteria of the commercialization tools derived from the high-tech commercialization production mechanism. These evaluation criteria are found functional and are an actual assessment of the economic activity effects, immanent to the nature of the economic organization, namely commercialization, for national economy as a whole and on the economic condition of the studied economic organization in particular. Special attention is paid to the econometric interpretation of the evaluation of effects and criteria for further efficiency improvement, such as determining the optimal system of equations which are substantial to the elaborated model. Despite numerous domestic developments, determining the most optimal criteria for assessing the effectiveness of commercialization of high-tech products remains a promising task. It should be noted that the development of an effective model for improving the effectiveness of tools is derived from certain criteria for evaluating the effectiveness and tools of the commercialization mechanism. Both of these components need further refinement and improvement. The application of a multi-criteria model for efficiency tools improvement is based on the expert assessments method, which is key anti-crisis approach in conditions of uncertainty, when classical prediction modeling of economic processes based only on quantitative assessments is insufficient to accurately assess the impact of purely quantitative assessments. All-in-all, the commercialization of a high-tech product in modern times of the system of international entrepreneurship also counts indirect aspects of the economic activities of organizations, such as environmental, social and marketing activities, etc.

Brand loyalty as mediator of brand image-repurchase intention relationship of premium-priced, high-tech product in Indonesia

This research aims to examine whether there is a mediating role of brand loyalty in the relationship between brand image and repurchase intention of premium-priced, high-tech product in Indonesia. We chose Apple brand in this research through a preliminary study involving 50 respondents. From the self-administered survey, we concluded Apple were perceived as the premium-priced, high-tech product. After the preliminary study, we collected 210 users of Apple products to participate in our research. Hypotheses testing were done using linear regression in IBM SPSS Statistics version 24 and Hayes’ Macro Process version 3.3 model 4. Research findings show that all hypotheses were supported by the data, brand image significantly and positively influences repurchase intention and brand loyalty mediates the influence of brand image on repurchase intention. Research implications are discussed further in this article.