Prioritising the preference of factors affecting the mobile network selection: A combination of factor analysis and best worst method

Abstract

The last two decades have witnessed enormous growth in wireless communication all over the world. The customers are the key concern of the marketers in this sector and marketers are trying their best to reach afar the expectations of the customers which makes them ready to serve customers 24*7. Customers in today's modern world have now become more informed with multiple options available due to which it has become a cumbrous job for marketers to retain or gain customers in the telecom sector. By gaining insights into preferences and expectations of customers regarding mobile network services can aid marketers to survive in this competitive sector. The study was conducted in two phases. In the First Phase, data were collected from 308 employees working in retail outlets operating in Punjab and Chandigarh who are directly dealing with customers. Factor analysis was conducted to explore the factors which according to them are significant for customers. In the second phase, the best‐worst multi‐criteria decision‐making technique was applied on a sample of 262 customers to prioritized or rank the factors based on significance for preference toward telecom service provider selection according to customers. Results of the study depicted Network/Signal coverage and price as the highest‐ranked and prioritized factor for consumers while preferring telecom service operators. While Brand image emerged as the least important factor. Data were collected in the area of Punjab and Chandigarh only. The study was conducted at a one‐time point due to which changes in the perception of the customers have not been considered. So, these are the limitations of the study. The research study is highly useful for telecom companies to target the highly prioritized factors of preference which will assist them in surviving and gaining an advantage over competitors. Previous researches have explored the factors preferences toward mobile telecom service provider and modeled their relationships. But the present study has employed the multi‐criteria decision‐making technique to add value to the existing knowledge base.