Driving Factors behind the Purchase of Paint Products : A Case of Indian Paint Shop Presented by: Bala Yogesh S Academic Mentor: Dr. Suresh M OBJECTIVE Identified Factors For Paint Buying Behavior Initial Reachability matrix . The customers who visit the dealer shops are • Product Variance (F1) F1 F2 F3 F4 F5 F6 F7 F8 F9 F10 predominantly painters and a few direct consumers. • Service Quality (F2) F1 1 0 0 0 1 1 1 1 0 0 . This paper primarily focus upon identifying the key • Perceived Quality (F3) F2 0 1 0 0 1 0 0 0 1 1 factors that will influence paint buying behavior in a • Perceived Value(F4) F3 0 0 1 1 1 0 0 0 0 0 dealer shop. • Brand Image(F5) F4 0 1 0 1 1 0 0 0 0 0 . In this paper a conceptual model has been developed • Compatible Price (F6) F5 0 0 1 0 1 0 1 0 0 0 using interpretative structural modelling(ISM) • Store Environment (F7) F6 0 0 1 1 0 1 0 0 0 1 approach. This study results indicates product variance • Product Reliability (F8) F7 0 1 0 0 0 0 1 0 1 0 is the key influencing factor, followed by compatible • Customer Value (F9) F8 0 0 1 1 1 0 0 1 0 1 price and product reliability for the purchase decision • Customer Loyalty (F10) F9 0 0 0 0 0 0 0 0 1 1 of paint products by customer. F10 0 0 0 0 0 0 0 0 0 1 Paint Industry WORKING MODEL Final Reachability Matrix Drivin F1 F2 F3 F4 F5 F6 F7 F8 F9 F10 g Power F1 1 1 1 1 1 1 1 1 1 1 10 Identification of Factors F2 0 1 1 1 1 0 1 0 1 1 7 from literature review F3 0 1 1 1 1 0 1 0 1 1 7 F4 0 1 1 1 1 0 1 0 1 1 7 F5 0 1 1 1 1 0 1 0 1 1 7 F6 0 1 1 1 1 1 1 0 1 1 8 F7 0 1 1 1 1 0 1 0 1 1 7 Application of ISM F8 0 1 1 1 1 0 1 1 1 1 8 approach F9 0 0 0 0 0 0 0 0 1 1 2 F10 0 0 0 0 0 0 0 0 0 1 1 . The market size of the paint industry in India is Dependen estimated to be around 350 billion. It is predicted that 1 8 8 8 8 2 8 2 9 10 64 ce Power there will be 9-10% growth in the paint industry over Classification of the next 5 years. factors into Level partition . Most of the paint purchasing happens only at dealer Autonomous, key, shops. It is difficult to convert this into online or e- dependent and Factors Level commerce sector because for a particular shade having independent F10 I thousand colors, that influence purchasing experience. F9 II . The consumers and painters visit the shop individually F2, F3,F4,F5,F7 III or together for the purchase of the paint. Thus, it F6, F8 IV makes a challenging task for the dealers to satisfy their need. RESEARCH METHODOLOGY F1 V LITERATURE REVIEW RESULTS AND OBSERVATIONS Respondents • Questionnair • Number of Digraph e • Dealers and Respondents Store = 50 Interpretive Employees Customer Buying Structural Data Sample Behavior Collection size Modelling (ISM) • Interpretive • Companies have structural now started modeling is used analyzing the ISM ALGORITHM for identifying and buying behavior of summarizing their customers. relationship • Customer among specific Iterations & Satisfaction Index Level variables, which Final Partition is used to measure Reachability define a problem Matrix the level of Initial or issue satisfaction each Reachability Matrix customer attains Self- structured Micmac analysis interaction matrix 10 F1 self-structured interaction matrix 9 Fac F1 F2 F3 F4 F5 F6 F7 F8 F9 F10 F6, RESEARCH QUESTION 8 tors F8 F1 1 O O O V V V V O O F2,F3, • What are the deciding parameters for 1 O A V O A O V V F4, F2 7 purchasing paint in a dealer shop ? F3 1 V X A O A O O F5,F7 1 V A O A O O • How are they interdependent with each F4 6 1 O V A O O other ? F5 DRIVING POWER 5 • What is the level of prominence of each F6 1 O O O V 4 factors ? F7 1 O V O 3 F8 1 O V 2 F9 F9 1 V 1 F10 F10 1 1 2 3 4 5 6 7 8 9 10 DEPENDENT POWER Poster template by ResearchPosters.co.za.