Innovation and environmental policy: Clean vs. dirty technical change

We study a two sector endogenous growth model with environmental quality with two goods and two factors of production, one clean and one dirty. Technological change creates clean or dirty innovations. We compare the laissez-faire equilibrium and the social optimum and study first- and second-best policies. Optimal policy encourages research toward clean technologies. In a second-best world, we claim that a portfolio that includes a tax on the polluting good combined with optimal innovation subsidy policies is less costly than increasing the price of the polluting good alone. Moreover, a discriminating innovation subsidy policy is preferable to a non-discriminating one.

Os jornalistas e a produção noticiosa na imprensa regional: desafios na criação de uma “agenda dos cidadãos”

ORGANIZAÇÕES E TRABALHO, n.º37-38, 2012, pp. 89-103

InnovationCity Ruhr: a prime example for social and technological innovation

The project “InnovationCity Ruhr” deals with the reconstruction of the city of Bottrop with regard to energy saving measures. The aim is to make the city more environmental friendly in order to create a model for other industrial cities. Until the conclusion of the project in the year 2020, it is planned to change the surface of Bottrop in several positive ways. This paper focuses on the description of the project to give the reader an example of what exactly is done within the scope of InnovationCity Ruhr. Besides that, the link to the subject of sociology shall be given in order to show that the project is a prime example for social innovation.

Managing innovation complexity: About the co-existence of innovation types

The purpose of this study is to contribute to the changing innovation management literature by providing an overview of different innovation types and organizational complexity factors. Aiming at a better understanding of effective innovation management, innovation and complexity are related to the formulation of an innovation strategy and interaction between different innovation types is further explored. The chosen approach in this study is to review the existing literature on different innovation types and organizational complexity factors in order to design a survey which allows for statistical measurement of their interactions and relationships to innovation strategy formulation. The findings demonstrate interaction between individual innovation types. Additionally, organizational complexity factors and different innovation types are significantly related to innovation strategy formulation. In particular, more closed innovation and incremental innovation positively influence the likelihood of innovation strategy formulation. Organizational complexity factors have an overall negative influence on innovation strategy formulation. In order to define best practices for innovation management and to guide managerial decision making, organizations need to be aware of the co-existence of different innovation types and formulate an innovation strategy to more closely align their innovation objectives.

Support in decision-making under uncertainty: a project risk assessment tool development and supplementary advances

A foremost dispute that persists on the contemporary world’s agenda is change. The on-going social/technological/economic changes create a competitive and challenging environment for companies to endure. To benefit from these changes, world economies partially depend on emerging Small and Medium Enterprises (SMEs) and their adaptability skills, and subsequently the development of an integrated capability to innovate has become the prime strategy for most of SMEs to subsist and grow. However, innovation and change are always somewhat bonded to an inherent risk development, which subsequently brings on the necessity of a revision of risk management approaches in innovative processes, whose importance SMEs tend to disregard. Additionally, little efforts have been made to improve and create empirical models, metrics and tools to assist SMEs managing latent risks in their innovative projects. This work seeks to present and discuss a solution to support SMEs in engaging on systematic risk management practices, which consists on an integrated risk assessment and response support web-based tool - Spotrisk® - designed for SMEs. On the other hand, an inherent subjectivity is linked with risk management and identification processes, due to uncertainty trait of its nature, for each individual perceives situations according to his own idiosyncrasy, which brings complications in normalizing risk profiles and procedures. This essay aims to bring insights concerning the support in decision-making processes under uncertainty, by addressing issues related with the risk behavior character among individuals. To address such issues, subjects of neuroscience or psychology are explored and models to identify such character are proposed, as well as models to improve presented tool. This work attempts to go beyond the restrictive aim of endeavoring on technical improvement dissertation, and in embraces an exploratory conceptualization concerning micro, small and medium businesses’ traits regarding risk characters and project risk assessment tools.

Do social factors matter for innovation, and do they influence innovation in Aeronautics Industry?

Based on the report for the course on “Social Factors of Innovation” of the PhD Program on Technology Assessment, supervised by Prof. António Brandão Moniz, Monte de Caparica, University NOVA Lisbon, Faculty of Sciences and Technology, July 2013

Board independence and innovation

Legislation introduced in the U.S. in 2002/2003 significantly changed board composition of public firms by imposing a 50% independent directors’ ratio. Research on the effect of independent directors is not consensual, implying that this exogenous shock is a unique opportunity to study their importance. This study answers the question of whether or not independent directors can effectively mitigate agency conflicts between shareholders and the management, having a positive impact on the choice of successful R&D projects. We find that an increase of board independence has a positive impact on patent counts. Hence, the results support that independent directors truly spur innovation and risk taking.

Overcoming the “European Paradox”: The role of Regional Innovation Systems (RIS) in translating R&D investments into economic and employment growth

The emergence of the so-called “European Paradox” shows that R&D investment is not maximally effective and that increasing the scale of public R&D expenditures is not sufficient to generate employment and sustained economic growth. Increasing Governmental R&D Investment is far from being a “panacea” for stagnant growth. It is worth noting that Government R&D Investment does not have a statistically significant impact on employment, indicating the need to assess the trade-offs of policies that could lead to significant increases in government expenditure. Surprisingly, Governmental R&D Employment does not contribute to “mass-market” employment, despite its quite important role in reducing Youth-Unemployment. Despite the negative side-effects of Governmental R&D Employment on both GVA and GDP, University R&D Employment appears to have a quite important role in reducing Unemployment, especially Youth-Unemployment, while it also does not have a downside in terms of economic growth. Technological Capacity enhancement is the most effective instrument for reducing Unemployment and is a policy without any downside regarding sustainable economical development. In terms of wider policy implications, the results reinforce the idea that European Commission Research and Innovation policies must be restructured, shifting from a transnational framework to a more localised, measurable and operational approach.

Responsible research and innovation: a global perspective

Based on the paper presented at the Doctorate Conference on Technologogy Assessment in July 2013 at the University Nova Lisboa, Caparica campus

Measuring impact with the social return on investment: the case of the social innovation hub

There is a growing interest in social impact assessment across the private, the public and the nonprofit sector. However, there is still limited academic research produced in this area, particularly in what concerns to the application of the Social Return of Investment (SROI) methodology. The goal of this Work Project is to give an overview of the social impact measurement literature and apply the Social Return on Investment, a flagship methodology to measure impact, to the specific case of the Social Innovation Hub (SIH). The findings suggest that each 1€ invested on the SIH generates 1,21€ in terms of social value. While this value seems very appealing to use, there are some risks in monetizing impact in such way, mainly due to the lack of reliable data available for benchmarking purposes.

Responsible research and innovation: a global perspective

Based on the paper presented at the Doctorate Conference on Technologogy Assessment in July 2013 at the University Nova Lisboa, Caparica campus

Lag-user method: Using laggards to leverage user innovation

Laggards are the last users to adopt a product. Prior literature on user-led innovation ignores laggards’ impact on innovation. In this paper, we develop the Lag-User Method, through which laggards can generate new ideas. Through six studies with 62 teams in three countries, we apply the method to different technologies and services and present our findings to executives to get managerial insights. Findings reveal that laggards who generate new ideas (lag-users) have different perceptions of user-friendly products and different unfulfilled needs. They prefer simple products. We propose that by involving lag-users in NPD, firms can improve the effectiveness of NPD.

Decisions of technology innovation: the role of indicators

This work presents research conducted to understand the role of indicators in decisions of technology innovation. A gap was detected in the literature of innovation and technology assessment about the use and influence of indicators in this type of decision. It was important to address this gap because indicators are often frequent elements of innovation and technology assessment studies. The research was designed to determine the extent of the use and influence of indicators in decisions of technology innovation, to characterize the role of indicators in these decisions, and to understand how indicators are used in these decisions. The latter involved the test of four possible explanatory factors: the type and phase of decision, and the context and process of construction of evidence. Furthermore, it focused on three Portuguese innovation groups: public researchers, business R&D&I leaders and policymakers. The research used a combination of methods to collect quantitative and qualitative information, such as surveys, case studies and social network analysis. This research concluded that the use of indicators is different from their influence in decisions of technology innovation. In fact, there is a high use of indicators in these decisions, but lower and differentiated differences in their influence in each innovation group. This suggests that political-behavioural methods are also involved in the decisions to different degrees. The main social influences in the decisions came mostly from hierarchies, knowledge-based contacts and users. Furthermore, the research established that indicators played mostly symbolic roles in decisions of policymakers and business R&D&I leaders, although their role with researchers was more differentiated. Indicators were also described as helpful instruments to conduct a reasonable interpretation of data and to balance options in innovation and technology assessments studies, in particular when contextualised, described in detail and with discussion upon the options made. Results suggest that there are four main explanatory factors for the role of indicators in these decisions: First, the type of decision appears to be a factor to consider when explaining the role of indicators. In fact, each type of decision had different influences on the way indicators are used, and each type of decision used different types of indicators. Results for policy-making were particularly different from decisions of acquisition and development of products/technology. Second, the phase of the decision can help to understand the role indicators play in these decisions. Results distinguished between two phases detected in all decisions – before and after the decision – as well as two other phases that can be used to complement the decision process and where indicators can be involved. Third, the context of decision is an important factor to consider when explaining the way indicators are taken into consideration in policy decisions. In fact, the role of indicators can be influenced by the particular context of the decision maker, in which all types of evidence can be selected or downplayed. More importantly, the use of persuasive analytical evidence appears to be related with the dispute existent in the policy context. Fourth and last, the process of construction of evidence is a factor to consider when explaining the way indicators are involved in these decisions. In fact, indicators and other evidence were brought to the decision processes according to their availability and capacity to support the different arguments and interests of the actors and stakeholders. In one case, an indicator lost much persuasion strength with the controversies that it went through during the decision process. Therefore, it can be argued that the use of indicators is high but not very influential; their role is mostly symbolic to policymakers and business decisions, but varies among researchers. The role of indicators in these decisions depends on the type and phase of the decision and the context and process of construction of evidence. The latter two are related to the particular context of each decision maker, the existence of elements of dispute and controversies that influence the way indicators are introduced in the decision-making process.