Organizational Learning Curves for Customer Dissatisfaction: Heterogeneity Across Airlines
AbstractIn the extensive literature on learning curves, scholars have ignored outcome measures of organizational performance evaluated by customers. We explore whether customer dissatisfaction follows a learning-curve pattern. Do organizations learn to reduce customer dissatisfaction? Customer dissatisfaction occurs when customers' ex ante expectations about a product or service exceed ex post perceptions about the product or service. Because customers can increase expectations over time, customer dissatisfaction may not decline even when the product or service improves. Consequently, it is an open question whether customer dissatisfaction follows a learning-curve pattern. Drawing from the literatures on learning curves and organizational learning, we hypothesize that customer dissatisfaction follows a U-shaped function of operating experience (Hypothesis 1), that focused airlines learn faster to reduce customer dissatisfaction than full-service airlines (Hypothesis 2), and that organizational learning curves for customer dissatisfaction are heterogeneous across airlines (Hypothesis 3). We test these hypotheses with quarterly data covering 1987 to 1998 on consumer complaints against the 10 largest U.S. airlines. We find strong support for Hypothesis 1 and Hypothesis 3. Hypothesis 2 is not supported in the sense that the average focused airline did not learn faster than the average full-service airline. However, we do find that the best focused airline learns faster than the best full-service airline. We explore this result by extending a knowledge-based view of managing productivity learning curves in factories to complaint learning curves in airlines.
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Bibliographic InfoArticle provided by INFORMS in its journal Management Science.
Volume (Year): 52 (2006)
Issue (Month): 3 (March)
learning curve; organizational learning; customer complaints; customer dissatisfaction; airlines;
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- Robert S. Huckman & Bradley R. Staats, 2008. "Variation in Experience and Team Familiarity: Addressing the Knowledge Acquisition-Application Problem," Harvard Business School Working Papers 09-035, Harvard Business School.
- Cheng, Kuangnen & Lee, Zu-Hsu & Shomali, Hamid, 2012. "Airline firm boundary and ticket distribution in electronic markets," International Journal of Production Economics, Elsevier, vol. 137(1), pages 137-144.
- Jonathan R. Clark & Robert S. Huckman & Bradley R. Staats, 2013. "Learning from Customers: Individual and Organizational Effects in Outsourced Radiological Services," NBER Working Papers 18723, National Bureau of Economic Research, Inc.
- Xiujian Chen & Shu Lin & W. Robert Reed, 2006.
"A Monte Carlo Evaluation of the Efficiency of the PCSE Estimator,"
Working Papers in Economics
06/14, University of Canterbury, Department of Economics and Finance.
- Xiujian Chen & Shu Lin & W. Robert Reed, 2010. "A Monte Carlo evaluation of the efficiency of the PCSE estimator," Applied Economics Letters, Taylor & Francis Journals, vol. 17(1), pages 7-10.
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