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This study aims to adopt a holistic approach to understand cruise revenue management (RM) practices that cover ticket and onboard revenues, through a cross-disciplinary literature review and practitioner interviews. An integrated cruise RM framework was developed and served as a blueprint for future cruise studies and practices.

A multi-stage approach was adopted, including a systematic literature review, two-waves of interviews with 26 cruise industry practitioners and the development of a holistic RM framework.

This study clarifies cruise RM functions across product planning, delivery stages and identifies ticket and onboard RM components. These are incorporated into the integrated framework, with weather and itinerary/ route attractiveness as additional considerations. Interviews revealed that there is no difference in the RM cycle before and during the COVID-19 pandemic, although strategies and tactics may vary in response to the market situation.

Suggestions are made regarding product and service bundling and ways for ticket and onboard revenue teams to work together to optimize total revenue. Future research directions are also provided under the categories of RM applications and concepts, ticket core activities, onboard core activities and overall issues.

To the best of the authors’ knowledge, this is the first paper to conduct a cross-disciplinary systematic literature review of cruise RM without imposing publication dates or specific databases and the first to develop an integrated cruise “total” RM framework that includes ticket and onboard revenues.

The purpose of the study is to ascertain whether sport organizations which outsource ticket sales force management outperform sports organizations which manage their ticket sales force internally, relative to ticket revenue and attendance.

Thirteen years of ticket revenue and football attendance data were collected for National Collegiate Athletic Association (NCAA) Football bowl subdivision (FBS) Division I Athletics Departments (n = 126), as well as data on whether the organization employed an external (outsourced), internal or no ticket sales force. The number of salespeople employed was also captured. Within-subjects, fixed effects regression models, which included several control variables such as number of home contests, prior season attendance, team success and population, were run to assess the relationship between sales force type and both ticket revenue and attendance, for one year, two years and three years after sales force establishment.

All models were significant. While both internally managed ticket sales forces and those managed by outsourced firms saw significant increases in ticket revenue (compared to not employing a sales force), internally managed departments outperformed third parties. In addition, departments utilizing outsourcing companies reported lower attendance for the first two years after outsourcing, but attendance differences were negligible by the third year of outsourcing.

The results of the study provide data to help sport managers determine whether outsourcing sales functions within an organization will lead to greater ticket revenue and/or attendance.

While several sport management studies have examined the decision-making process of outsourcing organizational functions, no prior studies have examined the financial implications of doing so.

Pricing studies have largely focused on sellers' pricing strategies and price determinants. To expand earlier work on sellers' pricing decisions, this study considers time as a major factor driving sellers' ticket prices in the secondary market. Specifically, because most secondary market transactions occur in the last moments before a game, this study considers how resellers adjust ticket prices within a few days prior to a game day including an actual game day.

To examine the impact of time on secondary market ticket prices for Major League Baseball (MLB), ticket prices were collected from StubHub (one of the largest secondary ticket markets) four times per game: from 3 days to 1 day prior to a game day and on the actual game day. Additionally, 10 control variables were obtained from previous research on price determinants (N = 19,155). A multiple regression model was created based on the extant literature regarding secondary market ticket prices.

Results indicate the number of days before a game negatively influenced ticket prices: resellers decreased ticket prices consistently during the last few days prior to a game's first inning. Specifically, secondary market ticket prices decreased relatively dramatically on an actual game day. Time had no significant effects on ticket prices 2 days prior to a game day. In addition to the role of time, league affiliation and the number of all-star players were identified as key price determinants in the secondary market. Moreover, changes in weather forecasts and the home team starting pitcher's ERA played significant roles in price changes.

Despite containing a relatively high number of data observations compared with prior pricing studies, this study's findings were limited to certain teams. Additionally, as only MLB secondary market ticket pricing was considered, different outcomes and implications may apply in other major sport ticket markets (e.g. NBA, NFL, NHL and MLS) featuring distinct league structures, policies and demand.

This study offers practical guidance for sellers' pricing decisions. Most secondary ticket market sellers lowered their ticket prices relatively dramatically on an actual game day. Reducing ticket prices prior to a game day can lead to greater chances to avoid unsold tickets that compromise revenue management. This study's results also afford professional sport organizations and secondary ticket market consumers a clearer understanding of the factors resellers consider when setting ticket prices.

Although previous studies have uncovered essential elements influencing ticket prices and consumer demand in the secondary ticket market, little work has examined how time affects sellers' pricing decisions within a few days prior to a game day. Little is known about the elements that significantly influence sellers’ decisions to adjust (i.e. increase or decrease) ticket prices in the secondary market as well. This topic deserves ongoing attention, as new outcomes can supplement previous studies' findings due to changing market environments.

The past several years have seen dramatic increases in oil prices, which have adversely impacted airlines, with the average price of jet fuel increasing from $1.34 per gallon between 1995 and 2005 to $2.81 per gallon between 2006 and 2009. As a partial response to these increases in costs, many airlines have introduced fees for services that were previously provided to their customers free of charge. One such charge is a fee on checked baggage, which most airlines introduced in 2008. These charges have been successful in increasing airline revenues, so successful that many airlines have increased their fees multiple times over the past two years. Baggage fees have also enabled airlines to avoid dramatic increases in their airfares, which may result in significantly fewer customers, as these additional fees generate revenues, but since they are not collected when passengers book their tickets, the cost of air travel on these airlines appears lower than it actually is. The most notable exception to this pattern of charging baggage fees is Southwest Airlines, which has launched a “Bags Fly Free” advertising campaign in an attempt to differentiate their product from that of fee charging airlines. In this chapter, we use a spatial autoregressive model to analyze what impact the increase in fuel costs, and the introduction of baggage fees have had on ticket prices. Our results suggest that increases in jet fuel prices are passed along to travelers in the form of higher ticket prices but that baggage fees actually reduce ticket prices, as airlines may substitute baggage fee revenue for ticket revenue to become more competitive on their airfare. We also find that Southwest Airlines has increased their ticket prices on routes in which they compete with fee charging firms, leveraging their “Bags Fly Free” product differentiation to increase their revenues.

This paper aims to consider spatial effects in the analysis of the relationship of revenue and service quality. When firms’ customers are located in spatially dispersed areas, it can be difficult to manage service quality on a geographically small scale because the relative importance of service quality might vary spatially. Moreover, standard approaches discussed so far in the marketing science literature usually neglect spatial effects, such as spatial dependencies (e.g. spatial autocorrelation) and spatial drift (spatial non-stationarity).

The authors propose a comprehensive but intelligible approach based on spatial econometric methods that cover spatial dependencies and spatial drift simultaneously. In particular, they incorporate the spatial expansion method (spatial drift) into spatial econometric models (e.g. spatial lag model).

Using real company data on seasonal ticket revenue (dependent variable) and service quality (independent variables) of a regional public transport service provider, the authors find that the elasticity for the length of the public transport network is between 0.2 and 0.5, whereas the elasticity for the headway is between −0.2 and 0.6, for example. The authors control for several socio-economic, socio-demographic and land-use variables.

Based on the empirical findings, the authors show that addressing spatial effects of service data can improve management’s ability to implement programs aimed at enhancing seasonal ticket revenue. Therefore, they derive a spatial revenue response function that enables managers to identify small-scale areas that are most efficient in terms of increasing revenue by service improvement.

The paper addresses the need to account for spatial effects in revenue response functions of public transport companies.

Ticket sales are an essential source of income for football clubs and federations. Analyzing the determinants of fans' willingness-to-pay for tickets is therefore an important exercise. By knowing the match- and fan-related characteristics that influence how much a fan wants to pay for a ticket, as well as to what extent, football clubs and federations can modify their ticket offering and targeting in order to optimize this revenue stream.

Using a detailed discrete choice experiment, based on McFadden's random utility theory, this paper formulates a Bayesian hierarchical multinomial logit model. Such models are very common in the discrete choice modeling literature. The analysis identifies to what extent match and personal attributes influence fans' willingness-to-pay for games of the Belgian men's and women's football national teams.

The results show that the strength of the opponent, the type of competition, the location of the seats in the stadium, the day and kick-off time of the match and the ticket price exert an influence on the choice of the respondent. Fans are attracted most by competitive games against strong opponents. They prefer to sit along the sideline, and they have clear preferences for specific kick-off days and times. The authors also find substantial variation between socio-demographic groups, defined in terms of factors such as age, gender and family composition.

The authors use the results to estimate the willingness-to-pay for match tickets for different socio-demographic groups. Their findings are useful for football clubs and federations interested in optimizing the prices of their match tickets.

To the best of the authors' knowledge, no stated preference methods, such as discrete choice analysis, have been used to analyze the willingness-to-pay of sports fans. The advantage of discrete choice analysis is that options and variations in tickets that are not yet available in practice can be studied, allowing football organizations to increase revenues from new ticketing instruments.

The purpose of this paper is to analyse the effects of first-mover advantage (FMA) on revenue generation capacity (RGC) of US college football programmes during the 2008 global financial crisis.

The study used archival data analysed quantitatively using non-parametric regression in the form of binary logistic regression. The study was then framed and interpreted by the resource-dependence theory.

FMA was positively and statistically associated with donations, branding, media rights and ticket revenues, but not win–loss records. The binary logistic regression model was correctly classified at 82.1 per cent of the variance and indicated that branding and ticket revenues were mostly associated with FMA.

The study was delimited to public college football programmes in the USA during the 2008 global financial crisis.

The findings indicated that despite the 2008 global financial crisis, FMA was positively associated with RGC but not win–loss records.

The study was pioneering in evaluating the effects of FMA as a source of competitive advantage in college football programmes during the challenging time of the 2008 global financial crisis.

Direct marketing is seeing growing acceptance among non‐profit services as a means to reach audiences, raise revenues, and foster long‐term relationships with customers. However, academic research has lagged in investigating the influences on the extent to which these organizations implement direct marketing, and subsequent effects on performance outcomes associated with such marketing activities. This research investigates the case of non‐profit arts organizations. The results show that organizational formalization, external integration, total marketing effort, and managerial self‐confidence influence the direct marketing techniques implemented by the firm. The model also shows that sales and fund‐raising revenues are driven primarily by total marketing effort, while the percentage of total revenue derived from season‐ticket subscriptions is driven by the breadth and uniqueness of the direct marketing techniques implemented by the organization.

This paper seeks to integrate stakeholder theory with the entrepreneurial orientation literature to explore relationships between distinct entrepreneurial behaviors and support from stakeholders with divergent interests.

A longitudinal study in the non‐profit professional theatre industry examines how relationships between entrepreneurial orientation and stakeholder support evolve over time. A series of regression analyses examine how support from diverse stakeholders influences entrepreneurial behaviors and, subsequently, how those entrepreneurial behaviors influence future stakeholder support.

The findings support a multi‐dimensional conceptualization of entrepreneurial orientation, point to tensions inherent in satisfying multiple stakeholder demands, and illustrate that different stakeholders support entrepreneurial behaviors in unique and sometimes unexpected ways. The findings offer insight into the complex balancing act that entrepreneurial managers must execute to generate support from distinct stakeholder markets.

This research provides researchers and managers with unique insights into the evolutionary nature of the relationships between distinct entrepreneurial behaviors and external stakeholder support.