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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.

Food choices profoundly affect one's dietary, nutritional and health outcomes. Using alcoholic beverages as a case study, the authors assess the potential of genetic data in predicting consumers' food choices combined with conventional socio-demographic data.

A discrete choice experiment was conducted to elicit the underlying preferences of 484 participants from seven provinces in China. By linking three types of data (—data from the choice experiment, socio-demographic information and individual genotyping data) of the participants, the authors employed four machine learning-based classification (MLC) models to assess the performance of genetic information in predicting individuals' food choices.

The authors found that the XGBoost algorithm incorporating both genetic and socio-demographic data achieves the highest prediction accuracy (77.36%), significantly outperforming those using only socio-demographic data (permutation test p-value = 0.033). Polygenic scores of several behavioral traits (e.g. depression and height) and genetic variants associated with bitter taste perceptions (e.g. TAS2R5 rs2227264 and TAS2R38 rs713598) offer contributions comparable to that of standard socio-demographic factors (e.g. gender, age and income).

This study is among the first in the economic literature to empirically demonstrate genetic factors' important role in predicting consumer behavior. The findings contribute fresh insights to the realm of random utility theory and warrant further consumer behavior studies integrating genetic data to facilitate developments in precision nutrition and precision marketing.

Infection and cross-contamination have been massive concerns in the medical field. This study aims to investigate consumers’ awareness and their choices of endoscopes, which may deter them from the cross-contamination problem.

A discrete choice experiment survey was administered to 166 respondents in Penang, Malaysia. Participants were asked to make hypothetical choices and estimate their preference for endoscopes. The multinomial logit model was used to estimate the assumptions based on the stated preference data collected.

Only two-fifths of respondents are aware of their rights regarding endoscope selection. The findings are consistent with utility theory, where choices are made to maximise personal satisfaction. If given the choice, consumers preferred the single-use endoscope over the reusable or the doctor’s preferred endoscope. Price, insurance coverage and personal income are significant determinants of the consumer’s choice of endoscopes.

This study only investigates subjects living in Penang. Other possible important attributes to endoscope choices, such as environmental and device availability may be considered in future study.

The findings may create awareness among consumers about their rights when choosing medical devices. It may also improve health-care institutions’ (users’) and device manufacturers’ (industry players’) understanding of consumer needs and demands from socioeconomic perspectives.

The research offers insights into consumer rights and awareness of health-care services. Ultimately leading to better policy to protect consumers’ rights and safety.

This study contributes to the rare literature on consumer rights toward medical devices, in particular, the consumer’s awareness of the choice of endoscopes.

This study aims to investigate low-carbon footprint travel choices, considering both destination attributes and climate change perceptions, and examine the impacts of nudging (a communication tool to alter individuals’ choices in a predictable way) on tourists’ preferences for carbon mitigation in destinations.

A discrete choice experiment questionnaire was administered to a sample of 958 Hong Kong respondents. Hybrid choice modeling was used to examine the respondents’ preferences for destination attributes and to explain preference heterogeneity using tourists’ climate change perceptions. The respondents’ willingness to pay for the destination attributes was also calculated to measure the monetary value of the attributes.

Destination type, carbon emissions and travel cost had significant effects on tourists’ choices of destination. Nudging increased tourists’ preference for low-carbon footprint choices. Tourists with higher climate change perceptions were more likely than others to select low-carbon destinations with carbon offset projects.

The findings of this study provide an impetus for destination management organizations to support local carbon offset projects, implement policies that mitigate carbon emissions and develop sustainable tourism to fulfill tourists’ demand for low-carbon footprint travel choices. Based on the findings, policymakers could promote sustainable tourism by publishing relevant climate change information on social media.

This study addressed a gap in the literature on tourist travel choice by considering carbon emission-related attributes and climate change perceptions and by confirming the role of nudging in increasing the choice of low-carbon destinations.

Images and caption descriptions serve as important visual stimuli that influence consumer preferences; therefore, the current study focuses on property images and captions illustrated on the home pages of accommodation-sharing platforms. Specifically, this study investigates the relative importance of hue, brightness and saturation of a property image and caption description styles on potential consumers’ preferences.

A mixed-method approach was used, and a total of 293 valid responses were collected through a discrete choice experiment approach. Interviews were conducted for additional analyses to explore the detailed explanations.

The utility model demonstrated that the image’s saturation was the most critical attribute perceived by the respondents, followed by caption description style, hue and brightness.

This is one of the first studies to investigate the display of attributes on a digital accommodation platform by exploring potential customers’ stated preferences. This study focuses explicitly on images and captions illustrated on the home page of an accommodation booking platform. Detailed image investigation is also a new research area in sharing economy-related research.

Storytelling through virtual reality (VR) combines the strengths of cutting-edge technology with traditional informational campaigns. As a tool for climate change mitigation, VR has been shown to educate individuals and stimulate both emotional and cognitive responses that promote pro-environmental behavior. This paper aims to investigate whether these benefits extend to the field of green investing through an experiment conducted with a sample of small business entrepreneurs.

The experimental design involved making choices between bonds varying in maturity dates, annual interest and environmental classification (regular versus green). To identify potential impacts of the immersive experience on investment decisions, these choices were made both before and after exposure to VR videos illustrating the devastating effects of climate change. A multiple price list was employed to elicit subjects' risk preferences, enabling the joint estimation of the treatment effect and the risk and time preference parameters.

The findings indicate that, when risk and time preference parameters are controlled for, a VR experience can nudge toward green investment choices. This effect is more profound among those who already exhibit a greater propensity to opt for green investments.

Previous research shows that negative emotions, such as guilt, affect pro-environmental intentions, as well as actions, while message vividness through immersive experiences is effective in nudging greener behavior. Since analogous results in the framework of financial investments are not currently available, this paper seeks to test whether VR videos depicting the adverse effects of climate change can generate negative emotions associated with experiencing these effects and make them salient in subsequent investment decisions made by small business entrepreneurs.

This study aims to progress scholarly understanding of the staycation phenomenon by examining customer segments and documenting local customers’ attribute preferences.

A stated choice experiment is used to examine customer preferences for staycation package attributes. Latent class discrete choice modeling is deployed to classify customers into market segments based on their preferences. The profile of each segment is enhanced by documenting customer characteristics and consumption styles.

Six prominent market segments are identified using a combination of sociodemographics, consumption styles and staycation attribute preferences. The findings draw on consumer experiences during the COVID-19 pandemic to generate theoretical insights into preferred staycation packages. Empirically, the estimation results from the research framework and choice experimental method demonstrate that staycation market segments exhibit distinct preference structures.

Practitioners and policymakers can incorporate the findings of this study in designing and/or assessing staycation packages. This can ensure differentiated products for defined segments that resonate within local communities through positive word of mouth, thus offering prospective spillovers to visiting friends and relatives.

This is a pioneering study on preference heterogeneity from the customer perspective, with a focus on staycation markets. The findings can encourage and assist hotel sector leaders to capitalize on local market developments to achieve a more resilient hospitality business model.

Using a generic cheese as an anchor product, in this study consumers' preferences for different EU quality schemes have been investigated. Specifically, the study aims to understand whether “Protected Designation of Origin” (PDO), “Organic” and “Mountain Product” labels are independent or if there are some synergies existing between them, questioning – at the same time – whether this alleged exchange of value plays a positive or negative role in terms of consumers' willingness to pay.

A discrete choice experiment (DCE) was conducted on 600 Italian consumers performing a random parameter logit model. The respondents were representative of the Italian population in terms of age, gender and geographical distribution. Consumers' preferences for the presence of “Organic” and “Mountain product” labels were assessed in the DCE, together with the effect of price, for both PDO and generic cheeses.

Consumers are willing to pay a premium in price for “Organic” and “Mountain Product” per se, for cheese with and without the PDO denomination. Considering the interaction effects, results showed that the combined use of “Organic” and “Mountain Product” labels do not decrease consumers' intention to buy. However, when applied on a PDO product, these attributes generate a lower consumers' willingness to pay in comparison with the generic ones, highlighting a possible overlapping between them.

Despite the abundant literature on EU quality schemes in many food categories, this study represents one of the first attempts to measure the interaction effect between different EU quality schemes.

This study aims to examine decision factors for global sourcing, differentiated into transcontinental and continental sourcing to obtain insight into locational aspects of sourcing decisions and global trends. This study analyzed various country perceptions to reveal their influence on sourcing decisions. The country of origin (COO) theory explains why certain country perceptions and images influence purchasing experts in their selection of suppliers.

This study used a two-study approach. In Study 1, the authors conducted discrete choice card experiments with 71 purchasing experts located in Europe and the USA to examine the importance of essential decision factors for global sourcing. Given the clear evidence that location is a factor in sourcing decisions, in Study 2 the authors investigated purchasers’ perceptions and images of countries, adding country ranking experiments on various perceived characteristics such as quality, price and technology.

Study 1 provides evidence that the purchasers’ personal relationship with the supplier plays a decisive role in the supplier selection process. While product quality and location impact sourcing decisions, the attraction of the buying company and cultural barriers are less significant. Interestingly, however, these factors seem as important as price to respondents. This implies that a strong relationship with suppliers and good quality products are essential aspects of a reliable and robust supply chain in the post-COVID-19 era. Examining the locational aspect in detail, Study 2 linked the choice card experiments with country ranking experiments. In this study, the authors found that purchasing experts consider that transcontinental countries such as Japan and China offer significant advantages in terms of price and technology. China has enhanced its quality, which is recognizable in the country ranking experiments. Therefore, decisions on global sourcing are not just based on such high-impact factors as price and availability; country perceptions are also influential. Additionally, the significance of the locational aspect could be linked to certain country images of transcontinental suppliers, as the COO theory describes.

The new approach divides global sourcing into transcontinental and European sourcing to evaluate special decision factors and link these factors to the locational aspect of sourcing decisions. To deepen the clear evidence for the locational aspect and investigate the possible influence of country perceptions, the authors applied the COO theory. This approach enabled authors to show the strong influence of country perception on purchasing departments, which is represented by the locational effect. Hence, the success of transcontinental countries relies not only on factors such as their availability but also on the purchasers’ positive perceptions of these countries in terms of technology and price.

The authors propose a dairy bundle, integrating strategies to jointly maximise producer revenue and consumer utility according to the latter's preferences.

An algorithm based on a nested logit model identifies the bundle maximising producer revenue based on factors affecting consumer purchase behaviour. The data are drawn from a mall-intercept survey administered in Iran, with consumers stating a hypothetical choice among a comprehensive set of dairy products.

Demographic characteristics and marketing mix elements significantly affect consumers' preferences. An algorithm based on the estimated dissimilarity parameter determines the best bundle of dairy products, simultaneously obtaining the highest utility and the highest expected revenue.

Consumer preference and maximum producer or retail seller income are considered simultaneously. The bundling promotion strategy is widely used for food offerings and fresh foods and can be extended to other products.

我們擬根據消費者偏好，提出一個整合了多個策略的捆綁包，以使生產製作者得到最高的收入和最佳的消費者效用。

研究人員根據巢式Logit 模型的演算法確認了一個捆綁包，以使生產製作者能得到最高的收入，而這均建基於會影響消費者購買行為的各個因素。有關的數據取自於伊朗的商場內進行的攔截調查，而回應的消費者須假想他們從一整套乳製品中選擇他們會購買的產品。

研究結果顯示，人口特徵和市場營銷組合元素均會顯著地影響消費者的偏好，一個基於估算的相異性參數而建立的演算法可確認最佳的乳製品捆綁包，這演算法同時也可取得最佳的裨益和最高的預期收入。

於本研究中，研究人員同時考慮消費者的偏好和生產製作者或零售賣家的最高收入。捆綁式的促銷策略在食物供品和新鮮食品方面被廣泛使用，這策略可擴展至其他產品。

乳製品捆綁包、消費者偏好、最佳化演算法、巢式Logit 模型.