Profiling Green Consumers with Data Mining

Concern about the environment has led to a new segment of consumers called green consumers. Because not all the consumers are equally green, using target marketing for persuading them to buy green product is essential. The first step in target marketing strategy is to segment the market and then develop profiles of the resulting market segments. This study aims to identify distinct green market segments based on demographic, psychographic, and behavioral variables and also investigate the relationship between each variable and green consumer behavior. This study uses self-organizing maps (SOM) to segment and then develop profiles of Iranian green consumers. Based on the results, four market segments have been identified and were named intense greens, potential greens, egoist browns, and intense browns based on profiles of consumers in each segment. The results of this study also indicate that the level of education and income together with egoistic value and environmental unfriendly habits correlate negatively with the greenness (intent and intense of green behaviors) of Iranian consumers and the age of consumers together with environmental attitude and knowledge, biospheric and altruistic values, and religiosity correlate positively

Importance-Performance Analysis of Service Attributes based on Customers Segmentation with a Data Mining Approach: a Study in the Mobile Telecommunication Market in Yazd Province

In customer relationship management (CRM) systems, importance and performance of the attributes that define a service is very important. Importance-Performance analysis is an effective tool for prioritizing service attributes based on customer needs and expectations and also for identifying strengths and weaknesses of organization in the market. In this study with the purpose of increasing reliability and accuracy of results, customers are segmented based on their demographic characteristics and perception of service attributes performance and then individual IPA matrixes are developed for each segment. Self-Organizing Maps (SOM) has been used for segmentation and a feed forward neural network has been used to estimate the importance of attributes. Research findings show that mobile subscribers in Yazd province can be categorized in three segments. Individual IPA matrixes have been provided for each of these segments. Based on these results, recommendations are offered to companies providing mobile phone services

Investigating the effect of green innovation dimensions on firm performance: the study in tile and ceramic industry in Yazd province

The modern world causes increased pollution and environmental problems and governments and organization‘s concerns about the environment and finally creates a concept as green innovation. This paper aims to evaluate the effect of green innovation dimensions on firm performance, with environmental performance as mediator. The firms in tile and ceramic industry in Yazd province are the target population of this study. This study proposes to evaluate green innovation practices with a particular focus on the managerial, process, product and technology innovation aspects. Structural equation modeling based on PLS method have been used to test the hypothesis. Results showed that green innovation dimensions including green process and technological innovation have significant effect directly on firm performance and also indirectly through the mediator role of environmental performance. Also, green management and product innovation effect only indirectly on firm performance