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Weekly Reads – Jan 15

Posted on January 15, 2021

Evaluating impact from research: A methodological framework – proposes a typology of research impact evaluation methods. They identify the following designs: experimental and statistical methods, systems analysis, textual, oral and arts-based methods, indicator-based approaches, evidence synthesis approaches.

Appraising research policy instrument mixes: a multicriteria mapping study in six European countries of diagnostic innovation to manage
antimicrobial resistance
– before I started my postdoc, I wrote a grant for a pharmaceutical research consortium to address AMR. This study is interesting just to check out what their method called multicriteria mapping is. As for the content, it is interesting as it explores policymakers’ preferences and uncertainties with various policy interventions against AMR. The policy options they explore were categorized in the following:

  • incentivizing diagnostic firms with financial rewards
  • funding R&D
  • coordinating stakeholders to make it easier to bring new tests to market
  • the government provisioning resources to lead R&D and testing themselves
  • incentivizing healthcare providers to use tests more appropriately
  • establishing IP regimes to support the development of tests based on demand

Deep Learning applications for COVID-19 – explores how deep learning is used in COVID. They categorize the application to four main areas: computer vision (ie. to analyze medical images and robotics), life sciences (ie. for drug repurposing and protein structure prediction), epidemiology (ie. for forecasting and contact tracing) and natural language processing (ie. literature mining).

Psychological factors influencing technology adoption: A case study from the oil and gas industry – introduces the Psychological Technology Adoption Framework (P-TAF) which categorizes various factors that facilitate or hinder adoption: personality (innovativeness, risk aversion), motivation (personal incentives, fear of technology failure), attitude (technology attitudes, trust), cognitive (risk perception, technical knowledge, certainty perception, previous experiences), social (social influence, subjective norms) and organizational (leadership, collaboration culture, technology adoption culture).

Legitimation of a heterogeneous market category through covert prototype differentiation – introduces the idea of covert prototype differentiation where entrepreneurs communicate how the category that they are in is united while at the same time creating prototype variants that attract entrants to their own camp.

About This Site

I am Angelo, an assistant professor in innovation management at ESADE Business School. In this blog, I share my learning adventures.

Recent Posts

  • Vibe Coding
  • Trying AI research paper assistants
  • Using LLMs for Problem Solving
  • Managing Data
  • Prototypes

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