Market Research Design on Modeling Propensity to Purchase and Market Potential: Using GIS and Data Mining as the Tools

2006 ◽  
Author(s):  
Lihua Zhao ◽  
Jennifer Harris
Keyword(s):  
Data Mining ◽  
Research Design ◽  
Market Research ◽  
Market Potential

scholarly journals The Good Practice in Marketing Microinsurance Product : Evidence from Indonesia

2017 ◽  
Vol 2 (No. 1 Apr 2017) ◽  
pp. 73-88
Author(s):  
Rofikoh Rokhim ◽  
Ruri Eka Fauziah Nasution ◽  
Melia Retno Astrini
Keyword(s):  
Central Asia ◽  
Consumer Protection ◽  
Low Income ◽  
Market Research ◽  
Good Practice ◽  
Market Potential ◽  
Corporate Values ◽  
Large Market ◽  
Low Income Consumers

The purpose of this study is to investigate the good practice of the microinsurance industry in Indonesia, using a case study of three microinsurance providers, namely Allianz, Prudential, and Asuransi Central Asia (ACA). In addition, this study also aims to analyze the challenges, of the microinsurance industry in Indonesia. Results from this study reveal that despite the large market potential for microinsurance in Indonesia, there are challenges that should be addressed, to boost the growth of the microinsurance industry in Indonesia. To respond to this challenge, attention should be focused on consumer protection, and consumer appeal aspects. From the three microinsurance providers discussed in this study, viable approaches to implement when competing in the microinsurance market in Indonesia, including market research to understand the behavior of low-income consumers, the extensive distribution of partners, consumer education practices, and corporate values that demonstrate the dedication of the company, to serve low-income consumers.

Market Research 2.0

2011 ◽  
pp. 169-186
Author(s):  
Lisa M. Given ◽  
Dinesh Rathi
Keyword(s):  
Web 2.0 ◽  
Research Design ◽  
Quantitative Research ◽  
Market Research ◽  
Qualitative And Quantitative ◽  
Legal Implications

This chapter examines the possibilities of conducting market research in Web 2.0 environments, with a focus on implications for small to medium-sized companies. The chapter discusses how companies can undertake market research using Web 2.0 platforms, explores how these tools can facilitate successful and appropriate market research design, and examines the characteristics of qualitative and quantitative “Research 2.0” techniques appropriate to a Web 2.0 environment. The chapter also presents examples of companies that are using these tools successfully for market research and discusses advantages and barriers in adopting these tools, including privacy, ethics, and legal implications of this type of research.

scholarly journals Market research and cost analysis of production of fried shallot as local superior product in Semau Island, East Nusa Tenggara, Indonesia

Food Research ◽  
2019 ◽  
Vol 4 (2) ◽  
pp. 343-348
Author(s):  
D. Tulipa ◽  
D. Rachmawati ◽  
L. Ellitan ◽  
I. Srianta
Keyword(s):  
Chemical Analysis ◽  
Cost Analysis ◽  
Purchase Intention ◽  
Market Research ◽  
Food Product ◽  
Appropriate Technology ◽  
Market Potential ◽  
Agricultural Commodities ◽  
Local Society ◽  
Market Test

The purpose of this research was to perform a market research and cost analysis of the fried shallots production. Food product development based on the local agricultural commodities with appropriate technology to the local society in Semau island is an important effort to improve socio-economic development. Shallot is one of the main agricultural commodities in Semau Island. Based on several criteria such as the applied technology, human resources, market potential, and economic contribution, fried shallot has potential as a Local Superior Product from Semau. In this research, fried shallot was developed at laboratory scale and subjected to the chemical analysis, market test and feasibility analysis on the economic aspect. The processing steps of fried shallot include peeling, slicing, mixing, frying and packaging. The results of the chemical analysis showed that moisture and fat contents of the product were comparable to the commercial fried shallot. In the market test, the purchase intention of the product was high enough. Cost analysis showed that the contribution margin ratio was 107%. Based on the technical and economic evaluation, the production of fried shallot was feasible to be implemented on Semau island.

scholarly journals Data Mining the Kids: Surveillance and Market Research Strategies in Children's Online Games

2006 ◽  
Vol 30 (4) ◽  
Author(s):  
Grace Chung ◽  
Sara M. Grimes
Keyword(s):  
Data Mining ◽  
Market Research ◽  
Personal Information ◽  
Marketing Research ◽  
Research Strategies ◽  
Policy Initiatives ◽  
Current Trends ◽  
Aggregate Information ◽  
Privacy Issues ◽  
Review Current

Abstract: This paper explores privacy issues in relation to the growing prominence of marketing research and data mining in websites for children. Whereas increasing protection is given to individuals’ personal information, little attention is paid to information that is aggregated, electronically scanned, and sorted — despite the fact that aggregate information is often highly valued by the marketing industry. The authors review current trends in Internet market research, data mining techniques, policy initiatives, and the contents of some of the most highly frequented children’s game sites. The paper demonstrates how common data mining practices constitute a threat to children’s emerging rights online. Résumé : Cet article explore la question de la vie privée des enfants et la proéminence croissante de la recherche marketing et le « data mining » dans le développement et gestion des sites Web pour enfants. De plus en plus, l’incorporation des technologies «data mining» dans les sites Web résultent en un fusionnement de contenu et commerce, ce qui élève un nombre de questions concernant les droits des enfants et les responsabilités des chercheurs. Les auteurs concluent que les droits naissants des enfants en ligne sont à risque dans ce contexte commercial de l’Internet.

The Study on Cross-Industry Standard Process for Data Mining in E-Marketing

2011 ◽  
Vol 66-68 ◽  
pp. 2298-2303
Author(s):  
Juan Wang
Keyword(s):  
Data Mining ◽  
Marketing Strategy ◽  
Research Methods ◽  
Process Model ◽  
Market Research ◽  
Standard Process ◽  
Customer Needs ◽  
Standard Data ◽  
Industry Standard ◽  
Traditional Market

According to the standard data mining process, CRISP-DM, one can directly collect data that are essential and useful for the mining results. It also offers practical help to those KD researchers both from industry and academia. In this paper, a KD procedure and method of E-marketing is discussed thoroughly, and a simple operating and easy understanding process model is presented to marketing people with little data mining background. In addition, the traditional market research methods are highly subjective; it is difficult to support the objective marketing decisions. While the KDDM process model can be effective in helping market analyst find the distribution and propensity of customers, thus to predict customer needs, determine the marketing strategy and ultimately to develop effective marketing plans.

Perspectives on Data Mining

2010 ◽  
Vol 52 (1) ◽  
pp. 11-19 ◽  
Author(s):  
Niall M. Adams
Keyword(s):  
Data Mining ◽  
Data Analysis ◽  
Market Research ◽  
Commercial Software ◽  
Software Packages

As a data analysis technology, data mining has matured to the extent that there are now a number of sophisticated commercial software packages available. The purpose of this article is to explore what data mining has become, its relationship to statistics and its relevance in market research.

scholarly journals Genotype-phenotype association mining in bipolar disorder: market research meets complex genetics

2017 ◽  
Author(s):  
René Breuer ◽  
Manuel Mattheisen ◽  
Josef Frank ◽  
Bertram Krumm ◽  
Jens Treutlein ◽  
...  
Keyword(s):  
Data Mining ◽  
Bipolar Disorder ◽  
Market Research ◽  
Association Studies ◽  
Genetic Research ◽  
Gene Discovery ◽  
Genome Wide Association Studies ◽  
Complex Disorders ◽  
Complex Genetics ◽  
Genome Wide

AbstractDisentangling the etiology of common, complex diseases is a major challenge in genetic research. For bipolar disorder (BD), several genome-wide association studies (GWAS) have been performed. Similar to other complex disorders, major breakthroughs in explaining the high heritability of BD through GWAS have remained elusive. To overcome this dilemma, genetic research into BD, has embraced a variety of strategies such as the formation of large consortia to increase sample size and sequencing approaches. Here we advocate a complementary approach making use of already existing GWAS data: applying a data mining procedure to identify yet undetected genotype-phenotype relationships. We adapted association rule mining, a data mining technique traditionally used in retail market research, to identify frequent and characteristic genotype patterns showing strong associations to phenotype clusters. We applied this strategy to three independent GWAS datasets from 2,835 phenotypically characterized patients with BD. In a discovery step, 20,882 candidate association rules were extracted. Two of these - one associated with eating disorder and the other with anxiety - remained significant in an independent dataset after robust correction for multiple testing, showing considerable effect sizes (odds ratio ~ 3.4 and 3.0, respectively). Our approach may help detect novel specific genotype-phenotype relationships in BD typically not explored by analyses like GWAS. While we adapted the data mining tool within the context of BD gene discovery, it may facilitate identifying highly specific genotype-phenotype relationships in subsets of genome-wide data sets of other complex phenotype with similar epidemiological properties and challenges to gene discovery efforts.

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