South Africa (SA) is classified as a middle-income emerging market, with the most resource-rich economy in Sub-Saharan Africa (SAccess, 2012). Its Research and Development (R&D) journey is characterised by a history of imbalances and oppression. Since the introduction of SA’s National R&D Strategy, recorded government R&D spending has been on the rise. However, the success rate for public-funded R&D projects has neither been satisfactory nor readily exposed for all to see. Factors considered critical for project success are largely contextual and tend to differ per project and industry. There appears to be no general consensus among scholars and authors on the common factors deemed critical in influencing the success of public-funded R&D projects. In SA, such factors still remain a mystery for further exploration. This research study sought to develop a model that will assist in achieving two key objectives, namely to identify the Critical Success Factors (CSF) of public-funded R&D projects in SA, as well as to exhume possible interrelationships between the identified critical success factors. This paper argues for a systemic and structure-based holistic approach and adopts Warfield’s Interactive Management (IM) in its endeavour to identify those factors that are deemed critical in the successful implementation of public-funded R&D projects in SA. The methodology comprises three key phases: a planning phase; a workshop phase; as well as a follow-up phase. The planning phase is a foundational phase that lays the basis and a plan for the ensuing two phases. The workshop, also known as the conversation phase, could be conceptualised as a process for building patterned interactions among the participants. It is in this phase that a relationship model, in the form of a diagraph, is constructed. The follow-up phase is the last phase and involves the implementation of the results to prove validity of solutions proposed in the workshop phase. However, since this last phase falls outside the scope of this paper, it has been excluded. Through the application of the IM methodology, a total of 35 identified CSFs were reduced to 23 key to formulate the CSF relationship model using the Interpretive Structural Model (ISM). Based on the model results, the study is concluded by identifying “Product market viability” and “Executive management support” as the two primary success factors that are most significant and have the greatest leverage to influence other factors towards the successful completion of public-funded R&D projects in SA.

This research investigates the association between board diversity and firms’ innovation in Canada over the period of 2001 to 2015. Previous research revealed that board diversity has conflicting effects on the firm innovation depending on the country, and there is no such study conducted in Canada. Moreover, only few proxies for the board diversity have been used to study the subject in the literature. Thus, this study introduces new factors of board diversity and add to the literature by assessing the topic in Canadian firms. We found that firms with more women on the board when women members are more than one fourth of the board members can increase the number of patents. Also, while more education diversity results in more patent numbers, more diversity in the number of years that board members have served the board results in less patent numbers for the firms, it is noteworthy that there is no significant association between the deviation in the number of years that board members have served the company and the innovation of the firm.

The thesis brings together three independent essays on the economics of innovation. I analyse the impact of competition on firm-level innovation (chapter 1) and the impact of different types of innovation on firm performance (chapter 2) looking at the top business R&D spenders of the world. I, then, switch my focus on researchers and analyse the determinants of brain drain in Europe (chapter 3).The first chapter is co-authored by Anabela Santos (European Commission) and Michele Cincera (ULB) and aims at assessing the impact of competition on firm-level innovation. The sample is composed of the world top corporate R&D spenders listed in the EU 2017 industrial R&D Scoreboard, and the analysis covers the years spanning from 2007 to 2016. We use an industry-year indicator, the inverse of the Lerner Index, as the indicator of competition for these firms that are leading in innovation efforts in the industries they are operating at the worldwide. R&D expenditures are used as the proxy for innovation. Model is estimated using two-stage least squares, to control for potential endogeneity of the competition indicator. Results confirm the existence of an inverted-U shaped relationship between competition and innovation. Further analysis is undertaken splitting the overall firm sample into services and manufacturing sectors according to technology and knowledge intensities and into the country of headquarters. We validate the inverted-U shaped relationship between competition and innovation for the firms in medium-high- and high-tech manufacturing sectors whereas we do not observe this impact for the firms operating in medium-low- and low-tech manufacturing sectors nor in services sectors. We also find differences in innovation behaviour of firms headquartered in the EU, US, Japan and China. While the inverted-U shaped relationship is highly pronounced for the Chinese firms, we find the U shaped impact of competition on the innovation of the EU and Japanese firms.The second chapter brings together firm-level R&D spending information with patent information, and aims at investigating the impact of different types of patented inventions on firm output growth performance controlling for R&D spending and other firm financials. The firm sample is sourced from the EU 2014 Industrial R&D Scoreboard that brings together the leading private sector R&D investors of the world. The analysis covers the years from 2005 to 2010. I consider forward-looking patent value indicators of breakthrough and general innovation using 7-year citation window, and backward-looking patent value indicators of originality and radicalness in innovation activities. Firm performance is estimated through a Cobb-Douglas production function. I allow for non-linearity in the relationship between innovation strategy and firm performance, and investigate sectoral heterogeneity looking at the impact in health industries and ICT producers. Models are estimated using two-stage least squares and generalised method of moments to control for potential endogeneity of innovation indicators. The findings confirm certain non-linearities and sectoral heterogeneities in the relationships between the different types of innovation and firm performance. ICT producers are growing with breakthrough innovations, generality and novelty in innovation process supporting the general-purpose technology feature of ICT. I, however, do not find a positive impact of technological breakthroughs nor a specific trend of generality and novelty in innovation process on productivity of pharmaceutical and biotechnology firms in the sample.The third chapter is co-authored by Christophe Colassin (ULB) and Michele Cincera (ULB) and aims at analysing the determinants of brain drain in Europe where there exists unbalances and polarisation between the States in terms of attractiveness for researchers despite the common policies and practices put in place by the European Union. The information about the mobility outflows are sourced from Centre for Science and Technology Studies and concern the year 2019. In order to analyse the macroeconomic determinants of mobility of researchers, the chapter brings together information from various data sources that attribute country-level values to the potential determinants of mobility outflows. We use a gravity model framework to detect quantitatively the pull and push factors of researchers' mobility including the 28 EU Member states in the time of analysis, and 3 additional Schengen countries, Norway, Iceland and Switzerland. In addition to the cultural and geographic proximity, we find that a country’s researcher base, entrepreneurial opportunities, knowledge intensity, public R&D spending and international collaborations increase the mobility of researchers within Europe whereas non-academic placements of researchers and the perception of virtual mobility as an alternative decrease the mobility. Researchers from countries with attractive research systems, more innovative private sector and more female researchers are found to be more mobile, whereas, the ones with higher GDP growth rates are less. We find that satisfaction with the recruitment process and the salary levels are decreasing factors for the mobility outflows. Finally, while fixed-term contracts in academia are found to be a factor that decreases the attractiveness; satisfaction with recruitment process, existence of the top R&D spending enterprises in the economy, and the freedom of academic exchange and dissemination are the factors that increases the attractiveness of a country for mobility inflows. / Doctorat en Sciences économiques et de gestion / info:eu-repo/semantics/nonPublished

Background: In current business world, big data and Artificial Intelligence (AI) implementation in daily business has become a mega-trend in different organization functions across various industries. The questions of what impacts against management and leadership can be expected with AI application, and how to make the most of AI application to achieve innovation success have become extremely interesting for business leaders, especially in R&D department which is considered to be innovation locomotive of a company. Objectives: Existing studies on implementation of AI application in research and development (R&D) department is rather scarce although there is a strong relevance for AI to be brought into R&D for achieving successful innovation. This study tries to fill this gap in literature aiming to explore the impacts of AI application on management and leadership, and also how AI can be used for achieving innovation success in R&D department. Method: The research methodology chosen for this study is a single and holistic case study on the organisation Thermo Fisher Scientific as we considered our research question to be unexplored and rare. We have used multiple sources of data including both primary data from multiple interviews and secondary data in the form of publicly available data. For the analysis of the data, we have used the grounded theory approach with 9 interviews for a phenomenological study. Results: A theoretical dynamic model was created for explaining the mechanism of AI influences in R&D by using grounded theory based on empirical interview data analysis. Interesting findings shed light on importance of implementation of AI application in R&D. The results disclose that AI application in R&D can lead to higher efficiencies in processes, decision making, costs and stimulate innovation, while a shift of leadership elements and organizational structure changes can be expected.

Like many fossil fuel dependant countries, South Africa faces the dual problem of responding to an increasing demand for coal production to satisfy rising energy requirements, while at the same time responding to the call to reduce greenhouse gas emissions. The exploration of renewable energy sources as an alternative to fossil fuels has therefore become an increasingly pressing concern in South Africa. South Africa has significant renewable energy potential which can simultaneously address both energy needs and the environmental concerns arising from greenhouse gas emissions. A tax incentive regime is a popular governmental policy instrument that has the potential to advance technologies and stimulate markets by encouraging research and development as well as the implementation of renewable energy technologies. It is therefore important to determine how the tax incentives currently available in South Africa for research and development and the implementation of renewable energy technologies, compare with those adopted internationally. China was identified as a country that offers generous fiscal incentives to encourage research and development and the implementation of technology such as renewable energy technologies. The objective of this study was to determine how the income tax incentives for research and development and the implementation of renewable energy technologies currently available in South Africa compare with the income tax incentives available in China for the same purpose. This was achieved by means of a head-to-head comparison of the impact that the two tax regimes would have in a hypothetical case study / Dissertation (MCom)--University of Pretoria, 2013. / am2014 / Taxation / Unrestricted

Coupled with the issue of promoting energy efficiency in South Africa is the need to focus on the source of energy production. The country's excessive burning of coal resources has been linked to the global warming crisis. To address this energy crisis, taxpayers can be encouraged to play an important role in moving the country towards a position of energy stability by conserving energy or decreasing their energy consumption, or contributing towards the research and development of energy-efficient processes as well as cleaner forms of energy. This study analyses the energy-related tax incentives that are currently legislated and available to South African taxpayers and discusses the feasibility of taking advantage of these incentives. The study may provide guidance to taxpayers that have decided to invest in renewable energy sources and will discuss some of the advantages and perceived challenges facing the renewable energy industry. This study also provides a worked example that illustrates a detailed calculation of the energy tax saving incentive set out in section 12L of the Income Tax Act, No. 58 of 1962. A case study guides taxpayers though the practical process of applying for and calculating their energy-saving tax deduction. The case study may be used as a point of reference for taxpayers planning to implement the section 12L energy efficiency tax incentive for the first time and may highlight complexities and concerns they should consider. / Mini Dissertation (MCom)--University of Pretoria, 2016. / Taxation / MCom / Unrestricted

Innovation efficiency is a key factor influencing the position of high-tech industries in the global value chain. Through stochastic frontier analysis, innovation efficiency of China's high-tech industry from 2000 to 2016 was estimated and analyzed. Through five random frontier analysis models, innovation efficiency of new product sales revenue and number of patent applications are analyzed. Results show that the overall level of innovation efficiency in China's high-tech industry is not high. Government subsidies for innovation have a positive impact on the R&D results of new product income from China’s high-tech industry, but have a negative impact on the number of patent applications. Scale of enterprise, degree of openness of enterprise, quality of the labor force and export delivery have a positive impact on innovation efficiency of China's high-tech industry. R&D capital stock and R&D human capital stock have a positive effect on high-tech industry innovation. In high-tech industry's transition from patents to new products, there will be a low conversion rate. Results of economic analysis can help the government to make the basis for management decisions. Conclusion of innovation performance analysis provides practical normative guidance for these high-tech industries.

R&amp;D organizations of today must constantly seek ways to becomemore efficient in order to stay competitive. To accomplish thismany organizations turn to process management approaches suchas lean product development. But how does the use of processmanagement influence the creativity of the people in theorganization? How will they manage both the creative search andexploration of future opportunities and the efficient exploitation ofcurrent offerings simultaneously? Previous research has shown thatcompanies often fail in this quest and that exploration is at risk ofbeing neglected in favour of exploitation where the feedback andreturn on invested work are more immediate.This thesis sets out to study how the combination of exploration interms of creativity, and exploitation in terms of processmanagement, plays out at Scania, a developer and manufacturer ofheavy trucks. The research builds on data collected by means of aquestionnaire study where a large part of the R&amp;D organizationparticipated. The results reveal surprisingly positive relationshipsbetween process management and creativity. Firstly, the existenceof clear routines showed a positive relationship with several aspectsof ideation. The results, however, stress the importance of havingdynamic routines where the organization is open to changing theexisting routines when needed. Secondly, strong demands ondelivery precision was positively related to the creation of novelideas in the industrialization process. Thirdly, the use of continuousimprovement efforts was positively related to aspects of creativity.These results indicate that routinization can benefit creativity andthat mangers should encourage the mapping and continuousimprovement of routines. Furthermore, goals for innovationinfluence how much time is spent on exploratory activities.Managers with innovation aspirations should therefore make clearto the organization that innovation is an important part of theoperations. Finally, managers and employees should formulatespecific product innovation goals and demand high deliveryprecision also for deliverables of exploratory nature. / <p>QC 20121130</p>

By using dynamic panel data model, this thesi selects the samples of large and medium indstrial enterprises in 2002 to 2011, empirically analyzin the impact of government scientific and technological subsidies on R&amp;D investment of enterprises.

Historical research on initial public offerings (IPOs) presents strong evidence of underpricing. This study investigates if there is a relationship between underpricing of IPOs and pre-IPO research and development (R&amp;D) activities within a company. According to the literature, R&amp;D activities have characteristics of information asymmetry and uncertainty, which can increase underpricing. This study’s sample consists of 231 Swedish companies listed on Nasdaq Stockholm and Nasdaq First North between January 2010 and December 2020. Sweden has a strong association with innovation activities such as R&amp;D, and the country’s IPO market has snowballed in recent years, making it a suitable context for the study. To investigate the relationship between underpricing and R&amp;D activities, the study uses an OLS regression. The findings indicate that R&amp;D positively affects underpricing, which is in line with previous studies on other markets. In addition, the study finds evidence of Firm Size, Offer Size, Shares Offered, VCPE backed, and Firm Leverage related to underpricing.