Role of social pressure as a key contributor of materialism and related status consumption

“At resale stores I have seen brand new clothes with original price tag still hanging from the sleeve. Some children have so many toys that they stay frustrated, not knowing which one to pick up for their next amusement. Presumably sensible adults trade in perfectly good cars just to have something shinier and newer. Didn’t us once live productive normal lives, without all these gadgets” [Cunningham (2005)]. During late eighties, nearly forty four percent of the participants, who took part in a consumer survey conducted in the US, responded positively to the question “My closets are filled with still 2 unopened items” [Faber and O’Guinn (1988)]. Reading such excerpts does not greatly surprise us anymore; as such reports have become common now. For many people shopping has moved beyond something that caters to their needs and wants and has become a hobby [Cunningham (2005)], an activity that they engage in to satisfy their hedonistic or pleasure-seeking goals [Ramnathan and Menon(2006), O’Cass and McEween (2004), Faber and O’Guinn (1989)]. Others look at their new possession as something that fills a void in their lives [Belk (1985), Diener et al. (1993)].

Design of a Knowledge-Based Geographic Information System

A GIS has been designed with limited Functionalities; but with a novel approach in Aits design. The spatial data model adopted in the design of KBGIS is the unlinked vector model. Each map entity is encoded separately in vector fonn, without referencing any of its neighbouring entities. Spatial relations, in other words, are not encoded. This approach is adequate for routine analysis of geographic data represented on a planar map, and their display (Pages 105-106). Even though spatial relations are not encoded explicitly, they can be extracted through the specially designed queries. This work was undertaken as an experiment to study the feasibility of developing a GIS using a knowledge base in place of a relational database. The source of input spatial data was accurate sheet maps that were manually digitised. Each identifiable geographic primitive was represented as a distinct object, with its spatial properties and attributes defined. Composite spatial objects, made up of primitive objects, were formulated, based on production rules defining such compositions. The facts and rules were then organised into a production system, using OPS5