Technology revenue management system for customer groups in hotels

Abstract

This paper discusses revenue management; a technique that focuses on decision making that will maximize profit from the sale of perishable inventory units. New technologies management plays an important role in the development of revenue management techniques. Each new advance in technology management leads to more sophisticated revenue business capabilities. Today decision support revenue management systems and technologies management are crucial factors for the success of businesses in service industries. This paper addresses the specific case of customer groups in hotels.The paper introduces a new decision support system that sets the revenue maximization criteria for a hotel. The system includes a set of forecasting demand methods for customers. It addresses a general case considering individual guests and customer groups. The system also incorporates deterministic and stochastic mathematical programming models that help to make the best decisions. The actual revenue depends upon which reservation system the hotel uses. A simulation engine makes a comparison between different heuristics of room inventory control: the results include performance indexes such as occupancy rate, efficiency rate, and yield; it compares results and chooses one of them. The system proves its suitability for actual cases by testing against actual data and thus becomes an innovative and efficient tool in the management of hotels' reservation systems.

Hotel Revenue Management – A Critical Literature Review

“…Overbooking is a widely analyzed tool (Talluri & van Ryzin, 2005;Chiang et al, 2007;Lan, Ball & Karaesmen, 2007), also in the framework of the hotel industry (Badinelli, 2000;Bitran & Mondschein, 1995;Guadix, Cortes, Onieva & Munuzuri, 2010;Ivanov, 2006Ivanov, , 2007Koide & Ishii, 2005;Netessine & Shumsky, 2002;Pullman & Rogers, 2010;Tranter et al, 2008). Th e huge scholarly interest in management of overbookings is entirely justifi ed because of the criticism overbooking policies receive, especially in its legal terms and ethical considerations elaborated in further in the article.…”

“…Th is is result of the notion that hotel RM is an integrated system that has to provide solutions to RM problems for price levels, price fences, booking conditions and overbookings simultaneously through optimal room-rate allocation (room distribution) (Baker, Murthy & Jayaraman, 2002;Bitran & Gilbert, 1996;Bitran & Mondschein, 1995;El Gayar, Saleh, Atiya El-Shishiny, Zakhary & Habib, 2011;Guadix et al, 2010;Harewood, 2006). Furthermore, the optimal level of overbookings is infl uenced by room rate (see the model of Netessine & Shumsky, 2002;and Ivanov, 2006) which shows the interconnectedness of pricing and non-pricing tools.…”

“…Th e processing of large databases is impossible without appropriate RM software (Guadix et al, 2010) and hotels that employ it gain strategic advantage over those that rely on intuitive RM decisions only (cf. Emeksiz, Gursoy & Icoz, 2006).…”

Development of a Prototype Software for a Corporate Customer Relationship Management in the Postal Service

“…따라서 데이터를 바탕으 로 한 고객의 이해를 위해서 고객 데이터의 수집, 전달, 사용 및 통합을 위한 기술적 구현이 요구되며, 이를 통해 고객과의 관 계를 구축한 다음 그 고객을 꾸준히 유지함으로써, 궁극적으 로 재무적 산출로 나타나는 것이다 (Minami and Dawson, 2008). 기존의 많은 고객관계관리 연구는 크게 기술(technology), 비 즈니스 프로세스(business process), 인적 자원(human resource)의 세 가지 영역으로 구분되며, 각 영역의 내용은 다음의 <Table 1>과 같다 (Kim et al, 2010 (Ahearne et al, 2007;Anderson et al, 2007;Berry et al, 2010;Kim et al, 2009;Minami and Dawson, 2008), 금융업 (Haenlein et al, 2007;Kim et al, 2010;Peppard, 2000), 전자상거래 (Chan et al, 2007;Lee and Park, 2009;Mahdavi et al, 2008;Mahdavi et al, 2011), 관광업 (Daghfous and Barkhi, 2009;Guadix et al, 2010;Ozgener and Iraz, 2006 …”

Competitive revenue management for fixing quota and price of hotel commodities under uncertainty

“…The service industry has been a popular area of RM research for many researchers over the last two decades, and, in particular, researchers have applied RM in capacity-constrained service industries. For Example, Orkin (1988), Kimes (1989a), Brotherton and Mooney (1992), Weatherford and Kimes (2001), and Harewood (2006) have used the concepts of revenue management in the hospitality sector, Kimes (1989b) in healthcare, Goulding and Leask (1997) and Heo and Lee (2009) in theme parks, Hoseason and Johns (1998) in cruise lines, Noone and Mattila (2009), Guadix et al (2010) in hotel industry, Kasilingam (1997), Kuyumcu and Garcia-Diaz (2000), Gorin and Belobaba (2004), Luo and Peng (2007), Lindenmeier and Tscheulin (2008) in airline industry, Bharill and Rangaraj (2008) in railways, and Tsai and Hung (2009) in Internet retailing. Although extensive literature is available on applications of RM practices in various service industries, the literature is scanty, however, in the field of RM under uncertainty for fixing of quota and price of hotel commodities, where it is difficult to handle RM under stochastic market conditions i.e., uncertain customer demand, customer preferences, and commodity price.…”