Structural Equation Modeling for Analyzing the Relationships among Packaging, Perceived Quality, Customer Satisfaction, and Business Competitiveness in Food Products
Dian Handayani (a*), Fitriana Era Madani (b), Dania Siregar (a)

a) Study Program of Statistics, Universitas Negeri Jakarta (INDONESIA)
*dianh[at]unj.ac.id
b)Research Division, SWA Media Group (INDONESIA)

Abstract

Customer satisfaction is one of the important things which should be taken into account by food manufacturer to win the business competition. There are some factors which can contribute to customer satisfaction. This study aims to analyze the relationships between packaging, perceived quality, customer satisfaction, and business competitiveness in food products by using structural equation modelling. The categories of food products which are specified in this study are instant noodles in cup packaging, wafer cookies and malkist biscuits. Based on the Top Brand Index (TBI) 2021, Pop Mie, Tango Wafer and Roma Malkist Crackers have the largest TBI from categories of instant noodles in cup packaging, wafer cookies and malkist cookies respectively. We specify the criteria for our sample respondents are those who have purchased at least twice for Pop Mie, Tango Wafer and Roma Malkist Crackers. The sample respondents are from Jakarta, Bogor, Depok, Tangerang and Bekasi. Data collection was carried out by administering online questionnaire during June 2021. The results indicate that perceived quality has a significant direct effect on customer satisfaction and has a significant indirect effect on business competitiveness. Product packaging has significant direct effect to customer satisfaction, but it is not significant as indirect effect to business competitiveness (&#945-=0.05).The variability of customer satisfaction which can be explained by perceived quality and product packaging is 88%. Meanwhile, the variability of business competitiveness that can be explained by customer satisfaction is 64%.

Keywords: diagonally weighted least square- direct effect- indicator variable-indirect effect- latent variable

Topic: Statistics