Time as a strategic variable: business hours in the gasoline market

ABSTRACT

A popular argument in policy discussions on the liberalization of business hours proceeds on the assumption that business hours are strategic complements: if some firms open longer hours, competitors will be forced to extend their opening hours too. We provide first empirical evidence on the impact of competition and the form of strategic interaction in business hours between firms by using detailed information on business hours as well as the location of retail gasoline stations in Austria. Our findings reject the presumption of business hours being strategic complements. Firms tend to have longer opening hours in a more competitive environment.

KEYWORDS:

• Opening hours
• spatial differentiation
• strategic interaction
• gasoline stations

JEL CLASSIFICATION:

• D22
• L13

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes

¹ Ferris (1990) investigates consumers’ utility maximizing behaviour under a time constraint and shows that longer opening hours exert a positive effect on consumers’ willingness to pay for products sold at these stores. Additional arguments for a positive effect of opening hours on willingness to pay can be advanced when explicitly considering the effects of uncertainty. When consumers are uncertain about when they want to shop, for example opening hours might incorporate a real option value by creating flexibility in the eyes of consumers’ (Shy and Stenbacka (2008), 1194). Similarly, consumers may be uncertain about the precise timing of opening hours of a store. Thus, stores with long opening hours (or the reputation of it) might be preferred by consumers (Kosfeld (2002)).

² Aoki (2003) observes that the form of the second-stage competition in the product market is important. The author compares price and quantity competition in the second stage and concludes: ‘Product market competition matters because qualities are locally strategic complements with Bertrand competition but are locally strategic substitutes with Cournot competition in the relevant range’ (p. 654).

³ Modeling closing rather than opening hours has the advantage that classical Tobit approaches characterized by truncation from the left can be easily used. This has no far-reaching impact on the research question, but it should be taken into account in the interpretation of the results.

⁴ Following Finlay and Magnusson (2009), we apply the conditional likelihood ratio (CLR) test, the Lagrange multiplier test (LM), as well as the Anderson–Rubin (AR) test. The range of confidence intervals includes zero in all tests. We further observe that the confidence intervals derived from weak-instrument robust tests are not wider than the Wald confidence interval, indicating that instruments are strong and that point estimates are not biased. The online Appendix also reports results from the first-stage regression as well as test results for potential violation of the over-identification restrictions.

⁵ We have carried out a number of estimation experiments using different neighbourhood and market definitions. The parameter estimate for is insignificant in all models. To allow for differences between the decision to open full-time (zero closing hours) and the choice of the desired number of closing hours, we re-estimate the model using Heckman’s two-step estimator. This approach involves estimation of a IV-probit model for selection, followed by the insertion of a correction factor – the inverse Mills ratio, calculated from the probit model – into the second (linear) model estimated over all stations with . In none of the two equations was the parameter estimate for the impact of neighbouring stations’ business hours significantly different from zero. Finally, we also estimate a SAR-Tobit as well as a spatial Durbin-Tobit model in the reduced form of Equation (1) via maximum likelihood, as proposed by Le Sage and Pace (2009). Again, the presumption of strategic complementarity is clearly rejected; the parameter estimate for is not significantly different from zero. Detailed results for all econometric models are available in the online Appendix.

⁶ Note, however, that the empirical literature on the effects of market structure on product quality is not conclusive. Crespi and Marette (2009), for example observed a negative (positive) correlation between competition (concentration) and product quality indicators for 2244 products in over 80 manufacturing industries in the United States.

Additional information

Funding

This work was supported by the Austrian National Bank (OeNB) Anniversary Fund [grant number 16016].