What is he best known for?
The fields of study he is best known for:
- Management
- Marketing
- Psychology
Andy Neely spends much of his time researching Performance measurement, Marketing, Process management, Operations management and Process.
The concepts of his Performance measurement study are interwoven with issues in Systems design, Performance management and Balanced scorecard.
Andy Neely combines subjects such as Empirical evidence and Industrial organization with his study of Marketing.
His study in the field of Manufacturing firms also crosses realms of Sample.
His studies deal with areas such as Operations research, Stakeholder, State, Service and Engineering design process as well as Process management.
His Operations management research focuses on subjects like Risk analysis, which are linked to Measure.
His most cited work include:
- Performance measurement system design: A literature review and research agenda (2676 citations)
- State-of-the-art in product-service systems (1342 citations)
- Networking and innovation: a systematic review of the evidence (1142 citations)
What are the main themes of his work throughout his whole career to date?
His scientific interests lie mostly in Marketing, Performance measurement, Process management, Knowledge management and Industrial organization.
His study in Service, Service product management and Business model is done as part of Marketing.
His research in the fields of Service provider and Service delivery framework overlaps with other disciplines such as Alliance.
His Performance measurement research is multidisciplinary, incorporating perspectives in Systems design, Performance management and Balanced scorecard.
His biological study spans a wide range of topics, including Process and Operations management.
His Industrial organization study incorporates themes from Productivity, Value chain and Revenue.
He most often published in these fields:
- Marketing (27.82%)
- Performance measurement (21.05%)
- Process management (19.17%)
What were the highlights of his more recent work (between 2015-2021)?
- Marketing (27.82%)
- Industrial organization (20.30%)
- Business model (10.15%)
In recent papers he was focusing on the following fields of study:
The scientist’s investigation covers issues in Marketing, Industrial organization, Business model, Knowledge management and Artificial intelligence.
His Marketing research includes elements of Financial performance, Resource dependence theory and Big data.
The concepts of his Industrial organization study are interwoven with issues in Customer needs and Co-creation.
His Business model study combines topics from a wide range of disciplines, such as Data-driven and Business value.
His studies deal with areas such as Professional services and Scale as well as Knowledge management.
He usually deals with Process and limits it to topics linked to Performance measurement and Conceptual framework.
Between 2015 and 2021, his most popular works were:
- Only the Brave: Product Innovation, Service Business Model Innovation, and Their Impact on Performance (176 citations)
- Capturing value from big data – a taxonomy of data-driven business models used by start-up firms (119 citations)
- Distributed manufacturing: scope, challenges and opportunities (112 citations)
In his most recent research, the most cited papers focused on:
- Management
- Marketing
- Psychology
His primary areas of investigation include Marketing, Business model, Artificial intelligence, Uncertainty quantification and Artificial neural network.
His study in Customer experience and Product innovation falls within the category of Marketing.
His work deals with themes such as Contingency and Business ecosystem, which intersect with Business model.
His study on Benchmark and Deep learning is often connected to Function and Likelihood principle as part of broader study in Artificial intelligence.
His Uncertainty quantification research incorporates themes from Gradient descent, Prediction interval and Bayesian inference.
His Artificial neural network research integrates issues from Variance and Bayesian probability.
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