How hotel managers decide to discount room rates: A conjoint analysis

Abstract Hoteliers face a paradox in managing the differences between actual and expected demand in their daily operations. While making adjustments in pricing, management takes control of identifying a problem, collecting/interpreting information, and finally making a choice whether or not to discount. The role management plays in influencing the pattern of shifting demand in relation to room rates needs to be addressed. The purpose of this study was to explore how discount choices are made by hotel managers and to investigate the role of human judgment based on contextual factors in the decision-making process. A conjoint analysis was used to examine the discount decision-making process. Findings suggest that time (i.e. booking window) is perceived as the critical determining factor that leads managers to make discount choices associated with poor performance.

[1]  Seyhmus Baloglu,et al.  Hotel Guests’ Preferences for Green Guest Room Attributes* , 2011 .

[2]  Amy M. Gregory,et al.  Pricing strategies for resort fees: consumer preferences favor simplicity , 2015 .

[3]  Peter Jones,et al.  Operations management research in the hospitality industry. , 1998 .

[4]  M. Olsen,et al.  Strategic Management in the Hospitality Industry , 1992 .

[5]  Wayne D. Hoyer,et al.  Customers’ reactions to price increases: Do customer satisfaction and perceived motive fairness matter? , 2005 .

[6]  Darren Lee-Ross,et al.  Yield management in hospitality SMEs , 1997 .

[7]  Jordan J. Louviere,et al.  Analyzing Decision Making: Metric Conjoint Analysis , 1988 .

[8]  Walter J. Relihan.  The Yield-Management Approach to Hotel-Room Pricing , 1989 .

[9]  Donald T. Campbell,et al.  Relabeling Internal and External Validity for Applied Social Scientists. , 1986 .

[10]  Sara Luciani.  Implementing yield management in small and medium sized hotels: an investigation of obstacles and success factors in Florence hotels , 1998 .

[11]  C. Nachtsheim.  Orthogonal Fractional Factorial Designs , 1985 .

[12]  B. D. Guillet,et al.  Measuring spa-goers’ preferences: A conjoint analysis approach , 2014 .

[13]  George A. Akerlof,et al.  Identity and the Economics of Organizations , 2005 .

[14]  P. Kotler,et al.  Marketing for Hospitality and Tourism , 1995 .

[15]  Eli Cohen,et al.  Hotel Revenue-management Forecasting , 2004 .

[16]  Paul E. Green,et al.  Conjoint Analysis in Marketing: New Developments with Implications for Research and Practice , 1990 .

[17]  D. Hensher,et al.  Stated Choice Methods: Analysis and Applications , 2000 .

[18]  Kathleen M. Eisenhardt,et al.  Managing organizational decline: Lessons from Atari , 1986 .

[19]  R. Law,et al.  Can setting hotel rate restrictions help balance the interest of hotels and customers , 2014 .

[20]  Dennis Reynolds,et al.  What is professional attire today? A conjoint analysis of personal presentation attributes , 2012 .

[21]  Linda Canina,et al.  Competitive Sets for Lodging Properties , 2011 .

[22]  P Jones.  Yield management in UK hotels: a systems analysis , 1999, J. Oper. Res. Soc..

[23]  B. Orme.  Getting Started with Conjoint Analysis: Strategies for Product Design and Pricing Research , 2005 .

[24]  Sally F. Goldfarb,et al.  A large hybrid electro-optical array , 1980 .

[25]  J. F. Silva,et al.  The visually impaired and consumption in restaurants , 2012 .

[26]  B. D. Guillet,et al.  Chinese Leisure Travelers' Preferences of Rate Fences in the Airline Industry , 2013 .

[27]  Margaret A. Peteraf.  The cornerstones of competitive advantage: A resource‐based view , 1993 .

[28]  Dennis Reynolds,et al.  Understanding perceptions of professional attributes using conjoint analysis , 2011 .

[29]  R. Law,et al.  Rate Fences in Hotel Revenue Management and Their Applications to Chinese Leisure Travelers , 2014 .

[30]  Pricing of experience products under consumer heterogeneity. , 2013 .

[31]  Paul P. Wang,et al.  Intelligent system to support judgmental business forecasting: the case of estimating hotel room demand , 2000, IEEE Trans. Fuzzy Syst..

[32]  Mark J. Zbaracki,et al.  Pricing process as a capability: a resource-based perspective , 2003 .

[33]  Paul A. Phillips,et al.  Hotel performance and competitive advantage: a contingency approach , 1999 .

[34]  Khaldoon Nusair,et al.  Effect of price discount frames and levels on consumers' perceptions in low-end service industries. , 2010 .

[35]  S. Winter,et al.  An evolutionary theory of economic change , 1983 .

[36]  Raquel Olivas,et al.  Consumer preferences for wine applying best‐worst scaling: a Spanish case study , 2012 .

[37]  Ian Mitchell,et al.  The meaning and management of yield in hotels , 1995 .

[38]  S. Kimes.  Hotel Revenue Management in an Economic Downturn: Results from an International Study , 2009 .

[39]  G. Piccoli,et al.  Customer Relationship Management—A Driver for Change in the Structure of the U.S. Lodging Industry: , 2003 .

[40]  A. Murray.  Top management group heterogeneity and firm performance , 1989 .

[41]  Robertico R. Croes,et al.  Does Discounting Work in the Lodging Industry? , 2012 .

[42]  Mark P. Sharfman,et al.  Does Decision Process Matter? A Study Of Strategic Decision-making Effectiveness , 1996 .

[43]  R. Cross,et al.  Discounting in the Hotel Industry , 2002 .

[44]  Jochen Wirtz,et al.  Has Revenue Management become Acceptable? , 2003 .

[45]  Sheryl E. Kimes,et al.  The Basics of Yield Management , 1989 .

[46]  A. Kalnins.  The U.S. Lodging Industry , 2016 .

[47]  J. Hair.  Multivariate data analysis , 1972 .

[48]  Richard L. Priem.  Top management team group factors, consensus, and firm performance , 1990 .

[49]  Beverly B. Tyler,et al.  Strategic decision models: Integrating different perspectives , 1991 .

[50]  R. Cross,et al.  Revenue Management's Renaissance , 2009 .

[51]  Dennis Reynolds,et al.  Perceptions of technical skills required for successful management in the hospitality industry—An exploratory study using conjoint analysis , 2014 .