scholarly journals Measuring network effects in mobile telecommunications markets with stated-preference valuation methods

Author(s):  
Mikoaj Czajkowski ◽  
Maciej Sobolewski
2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Lukasz Grzybowski ◽  
Julienne Liang ◽  
Christine Zulehner

Abstract In this paper, we analyze how fixed-mobile (quadruple-play) bundling impacts the decision of consumers to churn telecommunications services. We use a database from an European operator of fixed and mobile telecommunications services which includes information about 9.6 million fixed broadband subscribers and 14.2 million mobile subscribers between March 2014 and February 2015. These data is combined with socio-demographic characteristics from each municipality in this country. We find that consumers who bundle fixed and mobile services from the same provider are less likely to churn. Without fixed-mobile bundling the annual churn of fixed broadband consumers would increase from 8.4 to 9.2%. Furthermore, the consumer churn in the mobile market would increase from 11.5 to 13.1%. We conclude that in the current competitive environment in the country considered, bundling has a moderate impact on consumer retention on both fixed and mobile networks.


Author(s):  
Tim Haab ◽  
Lynne Lewis ◽  
John Whitehead

The contingent valuation method (CVM) is a stated preference approach to the valuation of non-market goods. It has a 50+-year history beginning with a clever suggestion to simply ask people for their consumer surplus. The first study was conducted in the 1960s and over 10,000 studies have been conducted to date. The CVM is used to estimate the use and non-use values of changes in the environment. It is one of the more flexible valuation methods, having been applied in a large number of contexts and policies. The CVM requires construction of a hypothetical scenario that makes clear what will be received in exchange for payment. The scenario must be realistic and consequential. Economists prefer revealed preference methods for environmental valuation due to their reliance on actual behavior data. In unguarded moments, economists are quick to condemn stated preference methods due to their reliance on hypothetical behavior data. Stated preference methods should be seen as approaches to providing estimates of the value of certain changes in the allocation of environmental and natural resources for which no other method can be used. The CVM has a tortured history, having suffered slings and arrows from industry-funded critics following the Exxon Valdez and British Petroleum (BP)–Deepwater Horizon oil spills. The critics have harped on studies that fail certain tests of hypothetical bias and scope, among others. Nonetheless, CVM proponents have found that it produces similar value estimates to those estimated from revealed preference methods such as the travel cost and hedonic methods. The CVM has produced willingness to pay (WTP) estimates that exhibit internal validity. CVM research teams must have a range of capabilities. A CVM study involves survey design so that the elicited WTP estimates have face validity. Questionnaire development and data collection are skills that must be mastered. Welfare economic theory is used to guide empirical tests of theory such as the scope test. Limited dependent variable econometric methods are often used with panel data to test value models and develop estimates of WTP. The popularity of the CVM is on the wane; indeed, another name for this article could be “the rise and fall of CVM,” not because the CVM is any less useful than other valuation methods. It is because the best practice in the CVM is merging with discrete choice experiments, and researchers seem to prefer to call their approach discrete choice experiments. Nevertheless, the problems that plague discrete choice experiments are the same as those that plague contingent valuation. Discrete choice experiment–contingent valuation–stated preference researchers should continue down the same familiar path of methods development.


2021 ◽  
pp. 102230
Author(s):  
David Bardey ◽  
Danilo Aristizábal ◽  
José Santiago Gómez ◽  
Bibiana Sáenz

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