Topic
Perceptual mapping
About: Perceptual mapping is a research topic. Over the lifetime, 390 publications have been published within this topic receiving 8930 citations.
Papers published on a yearly basis
Papers
TL;DR: The authors surveys economic choice theory, stressing developments that permit use of data from psychometric and conjoint experiments to produce market demand forecasts, and a new method for estimating multinomial probits is described.
Abstract: This paper surveys economic choice theory, stressing developments that permit use of data from psychometric and conjoint experiments to produce market demand forecasts. Alternatives to the widely used multinomial logit model are summarized, and a new method for estimating multinomial probits is described. An integration of choice models with attitudinal scaling and perceptual mapping, within a latent variable system, is described. Estimation of such systems under either “random effects” or “fixed effects” descriptions of heterogeneity across individuals is discussed. Issues in the use of choice models to describe responses from conjoint experiments are presented. New regression diagnostic tests for the consistency of multinomial logit representations are discussed.
1,424 citations
TL;DR: This paper identifies the key dimensions of customer service voiced by hotel visitors use a data mining approach, latent dirichlet analysis (LDA), which uncovers 19 controllable dimensions that are key for hotels to manage their interactions with visitors.
851 citations
TL;DR: In this paper, a text-mining approach and semantic network analysis tools are used to generate market-structure perceptual maps and meaningful insights from online user-generated content without interviewing a single consumer.
Abstract: Web 2.0 provides gathering places for Internet users in blogs, forums, and chat rooms. These gathering places leave footprints in the form of colossal amounts of data regarding consumers' thoughts, beliefs, experiences, and even interactions. In this paper, we propose an approach for firms to explore online user-generated content and “listen” to what customers write about their and their competitors' products. Our objective is to convert the user-generated content to market structures and competitive landscape insights. The difficulty in obtaining such market-structure insights from online user-generated content is that consumers' postings are often not easy to syndicate. To address these issues, we employ a text-mining approach and combine it with semantic network analysis tools. We demonstrate this approach using two cases---sedan cars and diabetes drugs---generating market-structure perceptual maps and meaningful insights without interviewing a single consumer. We compare a market structure based on user-generated content data with a market structure derived from more traditional sales and survey-based data to establish validity and highlight meaningful differences.
657 citations
TL;DR: This paper proposes an approach for firms to explore online user-generated content and “listen” to what customers write about their and their competitors' products and demonstrates this approach using two cases---sedan cars and diabetes drugs---generating market-structure perceptual maps and meaningful insights without interviewing a single consumer.
Abstract: Web 2.0 provides gathering places for internet users in blogs, forums, and chat rooms. These gathering places leave footprints in the form of colossal amounts of data regarding consumers’ thoughts, beliefs, experiences, and even interactions. In this paper, we propose an approach for firms to explore online user-generated content and “listen” to what customers write about their and the competitors’ products. Our objective is to convert the user-generated content to market structures and competitive landscape insights. The difficulty in obtaining such market-structure insights from online user-generated content is that consumers’ postings are often not easy to syndicate. To address these issues, we employ a text-mining approach and combine it with semantic network analysis tools. We demonstrate this approach using two cases - sedan cars and diabetes drugs, generating market-structure perceptual maps and meaningful insights without interviewing a single consumer. We demonstrate the validity of the approach by comparing a market structure based on user-generated content data with market structure derived from more traditional sales and survey-based data.
607 citations
TL;DR: This article applied a latent class modeling approach to segment web shoppers, based on their purchase behavior across several product categories, and then profile the segments along the twin dimensions of demographics and benefits sought.
336 citations
Related Topics (5)
Performance Metrics
| Year | Papers |
|---|---|
| 2025 | 1 |
| 2024 | 1 |
| 2023 | 7 |
| 2022 | 7 |
| 2021 | 10 |
| 2020 | 12 |