Recursos Humanos com formação de qualidade e boa capacitação se constituem no capital intelectual da indústria que busca a capacitação tecnológica e maior competitividade, tanto a nível nacional, quanto a mundial. Na permanente busca de alternativas para o preenchimento desta lacuna de pessoal qualificado, a Lei de Informática (LI – Lei nº 8.248/91) traz sua contribuição por meio da obrigação de aplicação em formação ou capacitação profissional como uma das atividades de Pesquisa e Desenvolvimento (P&D) estabelecidas no regramento legal da Lei. Os projetos de P&D da LI de formação ou capacitação profissional contribuem para a produção de capital intelectual, ou seja, capital humano capacitado, que vem de encontro a suprir em parte a falta de profissionais qualificados. A LI determina que as empresas de desenvolvimento ou produção de bens e serviços de informática e automação invistam em atividades de P&D em Tecnologia da informação (TI) e que possam pleitear os benefícios da Lei, que consistem em isenção do Imposto sobre Produtos Industrializados (IPI). Esta tese tem como objetivo analisar os projetos de P&D de Formação ou Capacitação Profissional, de níveis médio e superior, desenvolvidos pelas Instituições de Ensino e Pesquisa (IEPs) e executados com recursos da LI. Para atingir este objetivo, foi realizada uma análise qualitativa destes projetos e também uma análise quantitativa da Plataforma de Dados da SEPIN. Foram analisados 199 projetos de uma média de 18 empresas incentivadas, executados por uma média de 25 IEPs, no período de 2011-2014. A principal conclusão deste estudo é a confirmação do resultado da LI como instrumento de fomento da capacitação tecnológica e do estímulo da competitividade, por meio do incentivo às atividades de Pesquisa e Desenvolvimento (P&D) em Tecnologia da Informação (TI). Estas atividades englobam Formação ou Capacitação Profissional, que foi o foco deste trabalho. / Human resources with high quality and good professional training are the industry's intellectual capital, that seeks technological capacity and more competitiveness, both nationally and globally. In the ongoing search for alternatives to fill this qualified personnel gap, the Informatics Law (IL - Law nº. 8.248 / 1991) brings its contribution through the law requirement application in formal or professional training as one of the Research and Development (R & D) activities established by this law. The R & D projects developed on the scope of the IL, involving training or professional training, contributed to the production of intellectual capital, what is the trained human resources, which addresses the market’s lack of qualified professionals. The IL determines that development or production companies of Information Technology (IT) and automation invest in R & D in IT, may claim the benefits of the law, consisting of tax reduction. This thesis analyzes the R & D projects of formal or professional training, at both secondary and superior level, developed by the Education and Research institutions and executed with financial resources from the IL. To achieve this goal, this author carried out a qualitative analysis of these projects and also a quantitative analysis of the SEPIN Data Base Platform. The author analyzed 199 projects, involving 18 IL beneficiary companies (average), executed by an average of 25 certificated Teaching and Research Institutions, during the period 2011-2014. The main finding of this study is the confirmation of the results expected from the IL as an instrument for fostering technological capacity and a stimulus of competence via incentives of P&D activities in IT. These activities include formal professional training in IT, which was the focus of this study.

This thesis analyzes what effects human capital, R&D and ICT-goods trade have on innovation. Positive outcomes from innovation are an increased level of productivity, which increases incentives for greater innovative activity. Throughout this thesis patent-applications will be used as a proxy for innovation, which is in accordance with previous literature. The main scope of this paper will focus on econometric panel-data to determine which indicators have a significant effect on national-wide patent-applications and basic policy making in accordance with the findings. The scope of the study will include 27 European Union countries. The methodology used concerning panel-data is fixed effects. However, due to the amount of missing data the econometric estimation, we will focus on imputation of the missing values. According to various tests that determine what kind of model fits the underlying dataset, we can conclude that this study requires the use of a Multiple Imputation technique. Our result shows that investments towards R&D have the biggest impact on innovations. / Denna uppsats har som mål att undersöka och analysera vilka effekter humankapital, forskning och utveckling och IKT-varor har på innovation. Positiva följder av innovation är en ökad produktivitetsnivå, vilket ökar incitamenten för att fortsätta med innovationer. I denna uppsats kommer patentansökningar att användas som en proxy för innovation. Detta är även något som tidigare studier har gjort. För att undersöka och identifiera de faktorer som har en påverkan på innovationer kommer en panelregression med fixed effects att genomföras. De länder som ingår i studien är 27 EU-medlemsländer. Vår databas saknar en stor mängd värden vilket försvårar analysen vid en panelregression. För att komma runt detta problem kommer en multipel imputation av värden att genomföras. Resultatet visar att statliga investeringar i forskning och utveckling har störst påverkan på innovationer.

Information Technology (IT) has become a vital tool for most industrial businesses and Scania CV AB is no exception. As the importance of IT generally has increased, the usage and number of applications has grown as well. Applications are substantial assets for an organization that is heavily supported by IT. Consequently, a way of managing applications efficiently and sustaining the costs of applications rather low ? doing more with less ? is required. In addition it is also important, from a business perspective, that applications as part of IT are aligned with business strategies and goals. Application Portfolio Management (APM) is a practice and a business-centric activity aimed to allocate IT resources to support business objectives and strategies; it helps determining the impact of applications and the relative importance of each application in the portfolio to the business. APM attempts to justify and measure the financial benefits of each application relative to the costs of the applications? maintenance and operations. Performing APM successfully is nevertheless a complicated issue, and something that many businesses are challenged with on a daily basis. New applications are constantly and regularly added, downloaded, purchased or selfdeveloped ? too often without any further control. In order to regain the control of the software that automates the business, and ensuring that the applications adds value and reliability to the company, Scania CV AB requires a rigorous and comprehensive method for an APM approach. In this master thesis together with Camilla Palomeques?s thesis1, such a method is provided. These two theses also offer a suggestion on how to proceed with the APM effort at Scania CV AB.

This study seeks to review the topic of how deep tech innovation is raised in Sweden and more particularly, the finance-related constraints of this ecosystem. The study proceeds from the idea of mapping out the available, and subsequently more suitable financing alternatives for novel deep tech ventures. A more specific focus lies within understanding what factors are influencing investment decisions amongst such actors.  Thereon, there is an attempt to ground a theory revolving around what kind of features in the deep tech start-up, are critical in order to overcome the identified financial challenges. Theoretically, it is explained how the inherent uncertainty of new innovative ventures in general, and those of deep tech character in particular, entails additional financing constraints that deter investors. This results in an s.c "Valley of Death", normally transpiring as a firm aspires to transition from a research-driven development business to a market-driven commercial business. The findings in this study can be considered to confirm this phenomenon as transpiring in Sweden, whereupon it is also seen as a reasonable opinion that the respective problem can be maneuvered. The main arguments in terms of success factors in this respect is; (i) the ability to match with investors with a solid understanding of the particular industry of operations, as wells as for deep tech in general, (ii) the ability to acquire a diverse team with solid industry experience and contacts, (iii) the ability to demonstrate market proximity, (iv) the ability to demonstrate a potential that can justify the intensified uncertainty, as well as a credible plan to reach it, (v) and abilities to argue positively for impacts in sustainable aspects. Furthermore, a few suggestions for further research in relation to the topic and problematization have been identified; alternative choices for fiscal policies, deep tech opportunities in the shadow of s.c impact investing, eventual opportunities in addressing public markets, and eventual constraints in the external dichotomy between public and private sector financing.

(in English) This thesis deals with the issue of information support of science and research development in Italy through information systems and library networks. The introductory chapter deals with several questions concerning the Italian academic environment and its relation to research and coordination of information. The second chapter introduces the current situation of Italian libraries, the library structures, legislation elements and mainly focuses on the institutions managing the libraries. The third chapter is devoted to science and research in Italy. The thesis also describes the current situation comparing it to other European countries. The emphasis is on major research institutions, support organizations and ministries. Followed by the explanation of funding and assessment of research institutions. The fourth chapter deals with the support of research in the area of Tuscany. The three largest universities of this region are analyzed - University of Florence, Pisa and Siena. After a description of these institutions, the thesis looks closely at their library networks, research activities and support. The conclusion summarizes the information obtained and answers the questions formulated in the introduction of this thesis.

In the 21st century, managing outsourced research and development (R&D) processes is critical to an organization's success. Guided by the logistic outsourcing theory developed by de Boer, Gaytan, and Arroyo, the purpose of this single case study was to explore strategies and processes organizational leaders used to manage outsourced R&D to maintain market competitiveness. Semistructured interviews were conducted with 5 purposefully selected business leaders who were responsible for outsourcing R&D in a single Fortune 500 corporation in the Mid-Atlantic region of the United States. Company records were also gathered as data. Yin's 5-step process for a case study and key words in context analysis were used to analyze the data. Findings included 3 main themes: (a) the outsourcing decision-making process with internal and external constraints, (b) the effectiveness of managing outsourcing services and processes, and (c) the influence of outsourcing on business effectiveness and new products. Findings also indicated no practical system to measure effectiveness of outsourced R&D services on market competitiveness. The lack of measurement effectiveness was due to a lack of processes in place to measure R&D performance and no practical approach to measure impact of R&D on market competitiveness. Findings offered insight into strategies used by business leaders to manage outsourced R&D processes. Findings may also have implications for positive social change such as impacting communities through employment, generating government revenues through taxes, and creating a positive impact on job creation in the industries that promote R&D outsourcing.

ABSTRACT The large-scale integration of PV solar energy onto the electricity grid remains a major challenge because of the intermittency issues which affect the grid reliability. In this thesis, we investigate the impact of grid integration issues upon the optimal energy R&D portfolio for climate change under damage uncertainty. We especially look at how the following two contrasting assumptions about solar intermittency issues will impact the composition of the optimal energy R&D technology portfolio for climate change. The first assumption, which we term “costly solar storage”, implies that grid integration will have costs; the second assumption, which we term “free solar storage”, implies that grid integration will have no costs. To achieve this task, we first present a two-stage stochastic programming model for energy R&D portfolio for climate change and the solution methods used to solve it. We will refer to this model as the budget constraint model (BCM model). Then, we will introduce a relaxation of the BCM model by including the R&D budget as a cost in the objective function. We will call this the overall optimal model (OOM model). In order to represent the impacts of technical change, we will use the Mini-Climate Assessment Model (MiniCAM) to generate marginal abatement cost curves (MAC), which represent the cost of reducing an additional ton of CO2. Two sets of MAC curves based on the two assumptions are generated and used in our models to estimate the impacts of grid issues on the optimal R&D portfolios for climate change. The results of our analysis using the BCM model show that the composition of the optimal portfolio remains almost the same under the two grid assumptions. However, the results of the OOM model show some significant differences between the two assumptions, with considerably more solar R&D investment when intermittency issues are neglected. Our estimates of the costs of the grid range between 2.5 billion and 21 billion dollars.

The German government's "Industry 4.0" paradigm transforms technology application across domains using real-time data and connectivity. The telecom sector's reliance on digital, software-driven infrastructure for real-time data and connectivity is paramount. Data science and Artificial Intelligence (AI) are crucial, enhancing telecom networks' reliability, cutting costs, and improving service. This technology drives efficiency and innovation, shaping 33% of the market. As AI matures, discussions revolve around potential human replacement, especially in innovation management. Early AI investments yield cost-effective innovation but may not entirely replace human discretion. The exact AI implementation varies, aligning with organizational goals. This research investigates the challenges of implementing AI in the dynamic telecom industry's R&D departments, particularly in Sweden and Finland. The research employs a case-study approach, utilizing semi-structured interviews and document analysis. Thematic analysis of the qualitative data reveals key challenges, including "Lack of Understanding and Awareness," "Recruitment and Skills Gap," "Data Security and Privacy Concerns," and "Infrastructure and Funding Limitations." These findings contribute to a comprehensive understanding of AI adoption challenges in the telecom sector, offering valuable insights for future research and industry practice. Ethical considerations and credibility measures were employed to ensure the rigor and validity of the research, emphasizing the importance of impartiality and multiple perspectives in qualitative research. A thematic analysis was conducted focusing on the "People," "Position," "Process," and "Technology" themes. "Position" categorizes organizations and individuals into AI-beginners, AI-followers, and AI-leaders, showing the diverse stages of AI adoption. "People" emphasizes upskilling, culture, and employee receptiveness. "Process" delves into integration challenges, data quality, ethics, and communication. "Technology" highlights data and budget challenges, infrastructure, and scalability. The findings reveal the telecom industry's transformative AI journey and the importance of balancing technological advancements, cultural shifts, skill development, and ethical considerations for successful AI implementation. While the research followed a rigorous qualitative approach, transparency is crucial for evaluating its credibility and acknowledging potential biases and limitations. The telecom industry's future success in harnessing AI's potential relies on understanding and addressing these multifaceted challenges. This research categorizes organizations and individuals into three distinct AI adoption stages: AI-beginners, AI-followers, and AI-leaders. This framework illuminates the diverse positions within the AI adoption spectrum and emphasizes the critical role of leadership, resource allocation, and skills development. Moreover, this research underscores the significance of human factors, integration processes, and technological considerations in successful AI adoption. Practical implications encompass strategic planning, resource allocation, leadership development, cross-functional collaboration, change management, ethical considerations, and talent acquisition. While offering valuable insights, the research acknowledges limitations in sample size, subjectivity, temporal relevance, and contextual completeness. This research also explores the potential future research directions in the domain of AI adoption in the telecom industry. Drawing from the insights gathered through interviews, several promising avenues for future investigations are outlined. These include longitudinal studies to track the evolution of AI adoption, cross-industry comparisons to identify best practices, quantitative analyses of AI's impact on key performance indicators, examinations of regulatory and ethical frameworks, in-depth studies of AI-related skill development, investigations into AI's impact on employment, and explorations of cultural transformations necessary for successful AI adoption. These avenues offer opportunities to advance our understanding of AI adoption dynamics and their implications for the telecom sector.

This thesis carries out empirical investigations of the possible impacts of institutions relating to different aspects of innovation, namely incremental innovation activities, collaborative research and development (R&D) activities and radical innovation outcomes. It comprises three studies. The first empirical study focuses on examining the impact of financial constraints and intellectual property rights (IPR) protection on incremental innovation. Using firm-level data from transition countries and employing a two-step probit model with endogenous regressors, this study provides evidence that both financing constraints and strong IPR protection are negatively associated with the incremental innovation activities of firms. Results also confirm that financing constraints faced by firms are significantly influenced by the overall levels of development of financial institutions within a country. The second empirical study looks at the effects of contracting institutions and intellectual property institutions on firms’ collaborative research and development (R&D) activities in developing and transition countries. By employing the Cragg double-hurdle model, this study finds that efficient contract enforcement has a positive effect on the likelihood of firms engaging in R&D partnership and the intensity of firms' expenditures on collaborative R&D. On the other hand, the decision of firms to participate in R&D partnerships and their level of expenditure on collaborative R&D are adversely affected by the strength of IPR protection. The third empirical study investigates the influences of a set of institutions on producing new-to-the-world technologies, as measured by patents. This study is conducted by using a large panel dataset of 98 developed and developing countries over a period of 23 years. Building on the idea production framework, the unconditional quantile regression (UQR) estimates of this study show that along with key research inputs (i.e., existing knowledge stock and resources devoted to R&D), the strength of IPR protection, quality of governance and functioning of financial institutions are also significant determinants of the patent output of a country. The UQR methodology also demonstrates that the effects of institutions on patent production are heterogeneous throughout the various quantiles of patent output distribution. This thesis, therefore, offers an example of how the new institutional economics (NIE) theory is applicable in analysing innovation performances. The findings of this thesis propose useful policy directions that can assist policymakers and managers in accelerating innovation and technological development. / Ministry of Public Administration, the Government of the People’s Republic of Bangladesh

Information technology (IT) investments have increased over the last half-century without clear justification in academic or practice-based literatures. One area that has not been adequately addressed in the past literature is the role of IT investments in mitigating firm financial vulnerability. This dissertation specifically attempts to understand the marginal effects of IT investments on financial vulnerability as defined by firm risk and R&D depreciation. Two research questions are pursued to help explain the role IT investments play in firm financial vulnerability: 1) What is the relationship between IT investments and R&D depreciation? and 2) What is the relationship between IT investments and firm risk? For this, I draw testable from the Real Options Theory. In addition, I develop measures of firm risk and the Depreciation of Business R&D capital. I source the data from three archival sources: Compustat, The Center for Research in Security Prices (CRSP), and the Ci Technology Database (CiTDB). This dissertation uses panel regression models using fixed effects to control the unobservable time invariant firm heterogeneity. To alleviate potential endogeneity and sampling biases, I use generalized method of moments models. The results suggest the relationships between IT investments and both firm risk and depreciation, namely that IT investments increase firm risk and decrease R&D depreciation.