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The purpose of this study is to investigate how incumbent firms’ marketing deterrence strategies, price-cuts and quality improvement, influence potential entrants’ (PEs) entry timing into incumbents’ markets and examine the moderating role of incumbents’ market-level resources and capabilities (R&Cs).

To test the hypotheses, an accelerated failure time model is applied to a rich data set of entry threats between 1997 and 2019 in the US airline industry.

The findings show that while quality improvements delay PEs’ entry, price-cuts expedite it. Furthermore, PEs are more likely to be deterred by price-cuts when incumbents possess high market-level R&Cs. However, such R&Cs do not moderate the link between incumbents’ quality improvement and PEs’ entry timing.

Market entry in this research is conceptualized and defined as a large resource deployment into a market and operationalized as a binary variable. However, PEs might rather choose a minor resource deployment instead to establish a foothold in new markets. It would be fruitful for future research to examine various levels of participation in a new market and examine how the incumbents’ marketing deterrence strategies affect PEs’ entry timing. Doing so would provide us with a deeper understanding of the difference between actual/full market entry and micro/minor market entry.

This research examines the impact of incumbents’ marketing deterrence strategies in a contingency framework and highlights the crucial role of R&Cs in implementing such deterrence strategies. Doing so provides actionable insights to managers who craft strategies to protect their markets against PEs.

Previous research illustrates that incumbent firms commonly respond to competitors’ entry threats by cutting prices and improving quality. While antecedents of these deterrence strategies have been extensively investigated, the consequences have yet to be empirically examined.

The aim of this research is to propose a quantitative approach to evaluating the quality of services provided, helping organizations to make strategic decisions by better understanding the characteristics that satisfy consumers.

The approach was based on the integration of the Kano model with SERVQUAL, adapted by the satisfaction equations of Albuquerque et al. (2022) and fuzzy systems theory. Through this, it was possible to infer which attributes influence customer satisfaction, identifying the ranges of satisfaction and, with the help of fuzzy, reducing the imprecision of customer perceptions.

A total of 42% of the attributes were classified as unidimensional, with attribute 11 (Reliability) and attribute 9 (Courtesy) having the highest satisfaction values. Attractive attributes accounted for 38% of the sample, with attribute 29 (Variety of products) and attribute 7 (Location) having the greatest impact on satisfaction. On the other hand, attribute 30 (Order Delay) and attribute 31 (Waiting for payment) caused more dissatisfaction among consumers (ranges −0.6, −0.71, respectively). In addition, Variety of products was the most satisfactory, while Order Delay generated the most dissatisfaction among users.

The originality of this research lies in its contribution to organizations in relation to the services offered by investigating a gap in the studies that use the Kano model, integrated with SERVQUAL, which do not include reverse attributes in their equations and analyses. With the help of fuzzy sets, the subjectivity of the individual can be translated into data for greater clarity of information.