MODES OF INNOVATION & UNCERTAINTIES IN THE CAPITAL GOODS INDUSTRY

Product innovation is a subtle process, frequently leading to shifts in the competitiveness of firms. Developing products in an environment undergoing technological change is given to frequent failure, even in well-established and sophisticated organizations. In order to tackle competitiveness and to deal with innovation uncertainty, firms develop diverse innovation processes. Two modes of innovation are suggested in recent literature: 1) Science, Technology and Innovation (STI) mode, which is based on the production and use of codified scientific and technical knowledge; and 2) Doing, Using and Interacting (DUI) mode, which relies on informal processes of learning and experience-based know-how. In this paper we analyse product innovation at firm level. We perform an exploratory analysis in four leading equipment and machinery producers from the Aveiro region, in Portugal. Doing so, we explore the main features of the capital goods’ industry with implications for innovation, and analyse the dominant uncertainties associated to the innovation process. and modes of innovation. Key findings include the complete absence of DUI mode in the cases studied, and even a low learning characteristic in one company. The paper concludes by considering the implications for firms’ competitiveness and for innovation policy.modes of innovation, uncertainties, R&D, capital goods, SME

A Review and Characterization of Progressive Visual Analytics

Progressive Visual Analytics (PVA) has gained increasing attention over the past years. It brings the user into the loop during otherwise long-running and non-transparent computations by producing intermediate partial results. These partial results can be shown to the user for early and continuous interaction with the emerging end result even while it is still being computed. Yet as clear-cut as this fundamental idea seems, the existing body of literature puts forth various interpretations and instantiations that have created a research domain of competing terms, various definitions, as well as long lists of practical requirements and design guidelines spread across different scientific communities. This makes it more and more difficult to get a succinct understanding of PVA’s principal concepts, let alone an overview of this increasingly diverging field. The review and discussion of PVA presented in this paper address these issues and provide (1) a literature collection on this topic, (2) a conceptual characterization of PVA, as well as (3) a consolidated set of practical recommendations for implementing and using PVA-based visual analytics solutions

Use of Network Analysis Technique for Prioritizing Project Portfolio: A Case Study

Network analysis is widely used in the context of exploring social phenomena that involve disciplines such as economics, marketing and psychology. This work proposes the use of network analysis from an optics perspective as a strategic analytical intelligence tool, where it discusses its use as a support tool when prioritizing project portfolios. The research was defined through a case study carried out in a Brazilian bank, in which a specific scenario of the need to prioritize demands within the existing portfolio was considered, covering the period from 2018 to the first quarter of 2019. To study these scenarios, 2-mode networks were analyzed to visualize the context and measures of centrality degree, proximity and intermediation were also used to provide analytical intelligence in identifying the best options for negotiation and prioritization. It was concluded, through the information provided by the use of network analysis, that complex scenarios and difficulties for prioritization can be predictively diagnosed, as well as the centrality measures allow the identification of the best options for prioritization and selection and the view of the impacted areas to be involved in the negotiation. The use of network analysis technique as a support tool for decision making in the prioritization of projects portfolio is very promising and becomes potential as a new efficient option to be considered, evaluating its ability to provide analytical intelligence and insights predictive of the prioritization scenarios

Aeronautical Engineering. A continuing bibliography with indexes, supplement 156

This bibliography lists 288 reports, articles and other documents introduced into the NASA scientific and technical information system in December 1982

DATA ANALYTICS FOR CRISIS MANAGEMENT: A CASE STUDY OF SHARING ECONOMY SERVICES IN THE COVID-19 PANDEMIC

This dissertation study aims to analyze the role of data-driven decision-making in sharing economy during the COVID-19 pandemic as a crisis management tool. In the twenty-first century, when applying analytical tools has become an essential component of business decision-making, including operations on crisis management, data analytics is an emerging field. To carry out corporate strategies, data-driven decision-making is seen as a crucial component of business operations. Data analytics can be applied to benefit-cost evaluations, strategy planning, client engagement, and service quality. Data forecasting can also be used to keep an eye on business operations and foresee potential risks. Risk Management and planning are essential for allocating the necessary resources with minimal cost and time and to be ready for a crisis. Hidden market trends and customer preferences can help companies make knowledgeable business decisions during crises and recessions. Each company should manage operations and response during emergencies, a path to recovery, and prepare for future similar events with appropriate data management tools. Sharing economy is part of social commerce, that brings together individuals who have underused assets and who want to rent those assets short-term. COVID-19 has emphasized the need for digital transformation. Since the pandemic began, the sharing economy has been facing challenges, while market demand dropped significantly. Shelter-in-Place and Stay-at-Home orders changed the way of offering such sharing services. Stricter safety procedures and the need for a strong balance sheet are the key take points to surviving during this difficult health crisis. Predictive analytics and peer-reviewed articles are used to assess the pandemic\u27s effects. The approaches chosen to assess the research objectives and the research questions are the predictive financial performance of Uber & Airbnb, bibliographic coupling, and keyword occurrence analyses of peer-reviewed works about the influence of data analytics on the sharing economy. The VOSViewer Bibliometric software program is utilized for computing bibliometric analysis, RapidMiner Predictive Data Analytics for computing data analytics, and LucidChart for visualizing data

Data Analytics for Crisis Management: A Case Study of Sharing Economy Services in the COVID-19 Pandemic

This dissertation study aims to analyze the role of data-driven decision-making in sharing economy during the COVID-19 pandemic as a crisis management tool. In the twenty-first century, when applying analytical tools has become an essential component of business decision-making, including operations on crisis management, data analytics is an emerging field. To carry out corporate strategies, data-driven decision-making is seen as a crucial component of business operations. Data analytics can be applied to benefit-cost evaluations, strategy planning, client engagement, and service quality. Data forecasting can also be used to keep an eye on business operations and foresee potential risks. Risk Management and planning are essential for allocating the necessary resources with minimal cost and time and to be ready for a crisis. Hidden market trends and customer preferences can help companies make knowledgeable business decisions during crises and recessions. Each company should manage operations and response during emergencies, a path to recovery, and prepare for future similar events with appropriate data management tools. Sharing economy is part of social commerce, that brings together individuals who have underused assets and who want to rent those assets short-term. COVID-19 has emphasized the need for digital transformation. Since the pandemic began, the sharing economy has been facing challenges, while market demand dropped significantly. Shelter-in-Place and Stay-at-Home orders changed the way of offering such sharing services. Stricter safety procedures and the need for a strong balance sheet are the key take points to surviving during this difficult health crisis. Predictive analytics and peer-reviewed articles are used to assess the pandemic\u27s effects. The approaches chosen to assess the research objectives and the research questions are the predictive financial performance of Uber & Airbnb, bibliographic coupling, and keyword occurrence analyses of peer-reviewed works about the influence of data analytics on the sharing economy. The VOSViewer Bibliometric software program is utilized for computing bibliometric analysis, RapidMiner Predictive Data Analytics for computing data analytics, and LucidChart for visualizing data