What is he best known for?
The fields of study he is best known for:
- Marketing
- Finance
- Microeconomics
His primary areas of investigation include Marketing, Microeconomics, Customer lifetime value, Econometrics and Customer profitability.
His Marketing research is multidisciplinary, incorporating elements of Advertising and Knowledge management.
His Advertising research incorporates themes from Service provider and Emotional contagion.
In the subject of general Microeconomics, his work in Willingness to pay is often linked to Business forecasting, thereby combining diverse domains of study.
His work in Econometrics covers topics such as Flat rate which are related to areas like Consumer behaviour and Marketing strategy.
His study focuses on the intersection of Customer profitability and fields such as Customer intelligence with connections in the field of Customer to customer.
His most cited work include:
- The Impact of New Media on Customer Relationships (885 citations)
- Measuring Consumers' Willingness to Pay at the Point of Purchase (446 citations)
- Seeding Strategies for Viral Marketing: An Empirical Comparison (395 citations)
What are the main themes of his work throughout his whole career to date?
Bernd Skiera mainly investigates Marketing, Microeconomics, Profit, Advertising and Industrial organization.
His study in the field of Digital marketing and Service provider also crosses realms of Empirical research and Customer to customer.
His study looks at the relationship between Customer to customer and fields such as Customer profitability, as well as how they intersect with chemical problems.
His Microeconomics study incorporates themes from Flat rate and Consumer behaviour.
His Online advertising study combines topics in areas such as Search engine optimization, Marketing science, Decision support system and Bidding.
His Willingness to pay study typically links adjacent topics like Econometrics.
He most often published in these fields:
- Marketing (31.19%)
- Microeconomics (18.81%)
- Profit (10.40%)
What were the highlights of his more recent work (between 2014-2021)?
- Marketing (31.19%)
- Advertising (10.89%)
- Microeconomics (18.81%)
In recent papers he was focusing on the following fields of study:
Bernd Skiera focuses on Marketing, Advertising, Microeconomics, Business economics and Consumption.
Bernd Skiera applies his multidisciplinary studies on Marketing and Customer equity in his research.
His Advertising research is multidisciplinary, relying on both Enterprise value, Display advertising and Search advertising.
The various areas that he examines in his Business economics study include Service provider, Popularity and Externality.
His Online advertising research incorporates elements of Business model, Common value auction, Transaction cost and Critical success factor.
His research integrates issues of Auction theory, Scale and Consumer behaviour in his study of Transaction cost.
Between 2014 and 2021, his most popular works were:
- Visualizing Asymmetric Competition Among More Than 1,000 Products Using Big Search Data (29 citations)
- How customer referral programs turn social capital into economic capital (28 citations)
- What makes deal-of-the-day promotions really effective? The interplay of discount and time constraint with product type (25 citations)
In his most recent research, the most cited papers focused on:
- Marketing
- Finance
- Microeconomics
His primary areas of study are Empirical research, Marketing, Microeconomics, Product and Female students.
Empirical research is connected with Payment, Consumption, Advance payment, Mental accounting and Actuarial science in his study.
His Marketing research incorporates themes from Common value auction and Transaction cost.
Microeconomics is connected with Product type, Time constraint, Price promotion, Conventional wisdom and Conceptual framework in his research.
His studies deal with areas such as Social media optimization and Social media marketing as well as Product.
Female students is integrated with Class, Perception, Social psychology, Contrast and Social network analysis in his study.
This overview was generated by a machine learning system which analysed the scientist’s
body of work. If you have any feedback, you can
contact us
here.
